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Did FDA Reverse Course on Convalescent Plasma Therapy for COVID-19?

Reporter: Stephen J. Williams, PhD

 

Starting with a timeline of recent announcements by the FDA on convalescent plasma therapy

April 16, 2020

FDA STATEMENT

Coronavirus (COVID-19) Update: FDA Encourages Recovered Patients to Donate Plasma for Development of Blood-Related Therapies

 

As part of the all-of-America approach to fighting the COVID-19 pandemic, the U.S. Food and Drug Administration has been working with partners across the U.S. government, academia and industry to expedite the development and availability of critical medical products to treat this novel virus. Today, we are providing an update on one potential treatment called convalescent plasma and encouraging those who have recovered from COVID-19 to donate plasma to help others fight this disease.

Convalescent plasma is an antibody-rich product made from blood donated by people who have recovered from the disease caused by the virus. Prior experience with respiratory viruses and limited data that have emerged from China suggest that convalescent plasma has the potential to lessen the severity or shorten the length of illness caused by COVID-19. It is important that we evaluate this potential therapy in the context of clinical trials, through expanded access, as well as facilitate emergency access for individual patients, as appropriate.

The response to the agency’s recently announced national efforts to facilitate the development of and access to convalescent plasma has been tremendous. More than 1,040 sites and 950 physician investigators nationwide have signed on to participate in the Mayo Clinic-led expanded access protocol. A number of clinical trials are also taking place to evaluate the safety and efficacy of convalescent plasma and the FDA has granted numerous single patient emergency investigational new drug (eIND) applications as well.

Source: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-encourages-recovered-patients-donate-plasma-development-blood

August 23, 2020

 

Recommendations for Investigational COVID-19 Convalescent Plasma

 

  • FDA issues guidelines on clinical trials and obtaining emergency enrollment concerning convalescent plasma

FDA has issued guidance to provide recommendations to health care providers and investigators on the administration and study of investigational convalescent plasma collected from individuals who have recovered from COVID-19 (COVID-19 convalescent plasma) during the public health emergency.

The guidance provides recommendations on the following:

Because COVID-19 convalescent plasma has not yet been approved for use by FDA, it is regulated as an investigational product.  A health care provider must participate in one of the pathways described below.  FDA does not collect COVID-19 convalescent plasma or provide COVID-19 convalescent plasma.  Health care providers or acute care facilities should instead obtain COVID-19 convalescent plasma from an FDA-registered blood establishment.

Excerpts from the guidance document are provided below.

Background

The Food and Drug Administration (FDA or Agency) plays a critical role in protecting the United States (U.S.) from threats including emerging infectious diseases, such as the Coronavirus Disease 2019 (COVID-19) pandemic.  FDA is committed to providing timely guidance to support response efforts to this pandemic.

One investigational treatment being explored for COVID-19 is the use of convalescent plasma collected from individuals who have recovered from COVID-19.  Convalescent plasma that contains antibodies to severe acute respiratory syndrome coronavirus 2 or SARS-CoV-2 (the virus that causes COVID-19) is being studied for administration to patients with COVID-19. Use of convalescent plasma has been studied in outbreaks of other respiratory infections, including the 2003 SARS-CoV-1 epidemic, the 2009-2010 H1N1 influenza virus pandemic, and the 2012 MERS-CoV epidemic.

Although promising, convalescent plasma has not yet been shown to be safe and effective as a treatment for COVID-19. Therefore, it is important to study the safety and efficacy of COVID-19 convalescent plasma in clinical trials.

Pathways for Use of Investigational COVID-19 Convalescent Plasma

The following pathways are available for administering or studying the use of COVID-19 convalescent plasma:

  1. Clinical Trials

Investigators wishing to study the use of convalescent plasma in a clinical trial should submit requests to FDA for investigational use under the traditional IND regulatory pathway (21 CFR Part 312). CBER’s Office of Blood Research and Review is committed to engaging with sponsors and reviewing such requests expeditiously. During the COVID-19 pandemic, INDs may be submitted via email to CBERDCC_eMailSub@fda.hhs.gov.

  1. Expanded Access

An IND application for expanded access is an alternative for use of COVID-19 convalescent plasma for patients with serious or immediately life-threatening COVID-19 disease who are not eligible or who are unable to participate in randomized clinical trials (21 CFR 312.305). FDA has worked with multiple federal partners and academia to open an expanded access protocol to facilitate access to COVID-19 convalescent plasma across the nation. Access to this investigational product may be available through participation of acute care facilities in an investigational expanded access protocol under an IND that is already in place.

Currently, the following protocol is in place: National Expanded Access Treatment Protocol

  1. Single Patient Emergency IND

Although participation in clinical trials or an expanded access program are ways for patients to obtain access to convalescent plasma, for various reasons these may not be readily available to all patients in potential need. Therefore, given the public health emergency that the COVID-19 pandemic presents, and while clinical trials are being conducted and a national expanded access protocol is available, FDA also is facilitating access to COVID-19 convalescent plasma for use in patients with serious or immediately life-threatening COVID-19 infections through the process of the patient’s physician requesting a single patient emergency IND (eIND) for the individual patient under 21 CFR 312.310. This process allows the use of an investigational drug for the treatment of an individual patient by a licensed physician upon FDA authorization, if the applicable regulatory criteria are met.  Note, in such case, a licensed physician seeking to administer COVID-19 convalescent plasma to an individual patient must request the eIND (see 21 CFR 312.310(b)).

To Obtain a Single Patient Emergency IND  

The requesting physician may contact FDA by completing Form FDA 3926 (https://www.fda.gov/media/98616/download) and submitting the form by email to CBER_eIND_Covid-19@FDA.HHS.gov.

FACT SHEET FOR PATIENTS AND PARENTS/CAREGIVERS EMERGENCY USE AUTHORIZATION (EUA) OF COVID-19 CONVALESCENT PLASMA FOR TREATMENT OF COVID-19 IN HOSPITALIZED PATIENTS

  • FDA issues fact sheet for patients on donating plasma

August 23, 2020

 

FDA Issues Emergency Use Authorization for Convalescent Plasma as Potential Promising COVID–19 Treatment, Another Achievement in Administration’s Fight Against Pandemic

 

Today, the U.S. Food and Drug Administration issued an emergency use authorization (EUA) for investigational convalescent plasma for the treatment of COVID-19 in hospitalized patients as part of the agency’s ongoing efforts to fight COVID-19. Based on scientific evidence available, the FDA concluded, as outlined in its decision memorandum, this product may be effective in treating COVID-19 and that the known and potential benefits of the product outweigh the known and potential risks of the product.

Today’s action follows the FDA’s extensive review of the science and data generated over the past several months stemming from efforts to facilitate emergency access to convalescent plasma for patients as clinical trials to definitively demonstrate safety and efficacy remain ongoing.

The EUA authorizes the distribution of COVID-19 convalescent plasma in the U.S. and its administration by health care providers, as appropriate, to treat suspected or laboratory-confirmed COVID-19 in hospitalized patients with COVID-19.

Alex Azar, Health and Human Services Secretary:
“The FDA’s emergency authorization for convalescent plasma is a milestone achievement in President Trump’s efforts to save lives from COVID-19,” said Secretary Azar. “The Trump Administration recognized the potential of convalescent plasma early on. Months ago, the FDA, BARDA, and private partners began work on making this product available across the country while continuing to evaluate data through clinical trials. Our work on convalescent plasma has delivered broader access to the product than is available in any other country and reached more than 70,000 American patients so far. We are deeply grateful to Americans who have already donated and encourage individuals who have recovered from COVID-19 to consider donating convalescent plasma.”

Stephen M. Hahn, M.D., FDA Commissioner:
“I am committed to releasing safe and potentially helpful treatments for COVID-19 as quickly as possible in order to save lives. We’re encouraged by the early promising data that we’ve seen about convalescent plasma. The data from studies conducted this year shows that plasma from patients who’ve recovered from COVID-19 has the potential to help treat those who are suffering from the effects of getting this terrible virus,” said Dr. Hahn. “At the same time, we will continue to work with researchers to continue randomized clinical trials to study the safety and effectiveness of convalescent plasma in treating patients infected with the novel coronavirus.”

Scientific Evidence on Convalescent Plasma

Based on an evaluation of the EUA criteria and the totality of the available scientific evidence, the FDA’s Center for Biologics Evaluation and Research determined that the statutory criteria for issuing an EUA criteria were met.

The FDA determined that it is reasonable to believe that COVID-19 convalescent plasma may be effective in lessening the severity or shortening the length of COVID-19 illness in some hospitalized patients. The agency also determined that the known and potential benefits of the product, when used to treat COVID-19, outweigh the known and potential risks of the product and that that there are no adequate, approved, and available alternative treatments.

 

August 24, 2020

Donate COVID-19 Plasma

 

  • FDA posts video and blog about how to donate plasms if you had been infected with COVID

 

https://youtu.be/PlX15rWdBbY

 

 

Please go to https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/donate-covid-19-plasma

to read more from FDA

 

 

August 25, 2020

 

CLINICAL MEMORANDUM From: , OBRR/DBCD/CRS To: , OBRR Through: , OBRR/DBCD , OBRR/DBCD , OBRR/DBCD/CRS Re: EUA 26382: Emergency Use Authorization (EUA) Request (original request 8/12/20; amended request 8/23/20) Product: COVID-19 Convalescent Plasma Items reviewed: EUA request Fact Sheet for Health Care Providers Fact Sheet for Recipients Sponsor: Robert Kadlec, M.D. Assistant Secretary for Preparedness and Response (ASPR) Office of Assistant Secretary for Preparedness and Response (ASPR) U.S. Department of Health and Human Services (HHS) EXECUTIVE SUMMARY COVID-19 Convalescent Plasma (CCP), an unapproved biological product, is proposed for use under an Emergency Use Authorization (EUA) under section 564 of the Federal Food, Drug, and Cosmetic Act (the Act),(21 USC 360bbb-3) as a passive immune therapy for the treatment of hospitalized patients with COVID-19, a serious or life-threatening disease. There currently is no adequate, approved, and available alternative to CCP for treating COVID-19. The sponsor has pointed to four lines of evidence to support that CCP may be effective in the treatment of hospitalized patients with COVID-19: 1) History of convalescent plasma for respiratory coronaviruses; 2) Evidence of preclinical safety and efficacy in animal models; 3) Published studies of the safety and efficacy of CCP; and 4) Data on safety and efficacy from the National Expanded Access Treatment Protocol (EAP) sponsored by the Mayo Clinic. Considering the totality of the scientific evidence presented in the EUA, I conclude that current data for the use of CCP in adult hospitalized patients with COVID-19 supports the conclusion that CCP meets the “may be effective” criterion for issuance of an EUA from section 564(c)(2)(A) of the Act. It is reasonable to conclude that the known and potential benefits of CCP outweigh the known and potential risks of CCP for the proposed EUA. Current data suggest the largest clinical benefit is associated with high-titer units of CCP administered early course of the disease.

Source: https://www.fda.gov/media/141480/download

 

And Today August 26, 2020

  • A letter, from Senator Warren, to Commissioner Hahn from Senate Committee asking for documentation for any communication between FDA and White House

August 25, 2020 Dr. Stephen M. Hahn, M.D. Commissioner of Food and Drugs U.S. Food and Drug Administration 10903 New Hampshire Avenue Silver Spring, MD 20993 Dear Commissioner Hahn: We write regarding the U.S. Food and Drug Administration’s (FDA) troubling decision earlier this week to issue an Emergency Use Authorization (EUA) for convalescent plasma as a treatment for coronavirus disease 2019 (COVID-19).1 Reports suggests that the FDA granted the EUA amid intense political pressure from President Trump and other Administration officials, despite limited evidence of convalescent plasma’s effectiveness as a COVID-19 treatment.2 To help us better understand whether the issuance of the blood plasma EUA was motivated by politics, we request copies of any and all communications between FDA and White House officials regarding the blood plasma EUA.

Source: https://www.warren.senate.gov/imo/media/doc/2020.08.25%20Letter%20to%20FDA%20re%20Blood%20Plasma%20EUA.pdf

…….. which may have been a response to this article

FDA chief walks back comments on effectiveness of coronavirus plasma treatment

 

From CNBC: https://www.cnbc.com/2020/08/25/fda-chief-walks-back-comments-on-effectiveness-of-coronavirus-plasma-treatment.html

PUBLISHED TUE, AUG 25 202010:45 AM EDTUPDATED TUE, AUG 25 20204:12 PM EDT

Berkeley Lovelace Jr.@BERKELEYJR

Will Feuer@WILLFOIA

KEY POINTS

  • The authorization will allow health-care providers in the U.S. to use the plasma to treat hospitalized patients with Covid-19.
  • The FDA’s emergency use authorization came a day after President Trump accused the agency of delaying enrollment in clinical trials for vaccines or therapeutics.
  • The criticism from Trump and action from the FDA led some scientists to believe the authorization, which came on the eve of the GOP national convention, was politically motivated.

FDA Commissioner Dr. Stephen Hahn is walking back comments on the benefits of convalescent plasma, saying he could have done a better job of explaining the data on its effectiveness against the coronavirus after authorizing it for emergency use over the weekend.

Commisioners responses over Twitter

https://twitter.com/SteveFDA/status/1298071603675373569?s=20

https://twitter.com/SteveFDA/status/1298071619236245504?s=20

August 26, 2020

In an interview with Bloomberg’s , FDA Commissioner Hahn reiterates that his decision was based on hard evidence and scientific fact, not political pressure.  The whole interview is at the link below:

https://www.bloomberg.com/news/articles/2020-08-25/fda-s-hahn-vows-to-stick-to-the-science-amid-vaccine-pressure?sref=yLCixKPR

Some key points:

  • Dr. Hahn corrected his initial statement about 35% of people would be cured by convalescent plasma. In the interview he stated:

I was trying to do what I do with patients, because patients often understand things in absolute terms versus relative terms. And I should’ve been more careful, there’s no question about it. What I was trying to get to is that if you look at a hundred patients who receive high titre, and a hundred patients who received low titre, the difference between those two particular subset of patients who had these specific criteria was a 35% reduction in mortality. So I frankly did not do a good job of explaining that.

  • FDA colleagues had frank discussion after the statement was made.  He is not asking for other people in HHS to retract their statements, only is concerned that FDA has correct information for physicians and patients
  • Hahn is worried that people will not enroll due to chance they may be given placebo
  • He gave no opinion when asked if FDA should be an independent agency

 

For more articles on COVID19 please go to our Coronavirus Portal at

https://pharmaceuticalintelligence.com/coronavirus-portal/

 

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Online Event: Vaccine matters: Can we cure coronavirus? An AAAS Webinar on COVID19: 8/12/2020

Reporter: Stephen J. Williams. PhD

Source: Online Event

Top on the world’s want list right now is a coronavirus vaccine. There is plenty of speculation about how and when this might become a reality, but clear answers are scarce.Science/AAAS, the world’s leading scientific organization and publisher of the Science family of journals, brings together experts in the field of coronavirus vaccine research to answer the public’s most pressing questions: What vaccines are being developed? When are we likely to get them? Are they safe? And most importantly, will they work?

link: https://view6.workcast.net/AuditoriumAuthenticator.aspx?cpak=1836435787247718&pak=8073702641735492

Presenters

Presenter
Speaker: Sarah Gilbert, Ph.D.

University of Oxford
Oxford, UK
View Bio

Presenter
Speaker: Kizzmekia Corbett, Ph.D.

National Institute of Allergy and Infectious Diseases, NIH
Bethesda, MD
View Bio

Presenter
Speaker: Kathryn M. Edwards, M.D.

Vanderbilt Vaccine Research Program
Nashville, TN
View Bio

Presenter
Speaker: Jon Cohen

Science/AAAS
San Diego, CA
View Bio

Presenter
Moderator: Sean Sanders, Ph.D.

Science/AAAS
Washington, DC
View Moderator Bio

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Recent Grim COVID-19 Statistics in U.S. and Explanation from Dr. John Campbell: Why We Need to be More Proactive

Reporter: Stephen J. Williams, Ph.D.

In case you have not been following the excellent daily YouTube sessions on COVID-19 by Dr. John Campbell I am posting his latest video on how grim the statistics have become and the importance of using proactive measures (like consistent use of facial masks, proper social distancing) instead of relying on reactive measures (e.g. lockdowns after infection spikes).  In addition, below the video are some notes from his presentation and some links to sites discussed within the video.

 

Notes from the video:

  • approaching 5 million confirmed cases in US however is probably an underestimation
  • 160,00 deaths as of 8/08/2020

From the University of Washington Institute for Health Metrics and Evaluation in Seattle WA

  • 295,000 US COVID-19 related deaths estimated by December 1, 2020
  • however if 95% of people in US consistently and properly wear masks could save 66,000 lives
  • however this will mean a remaining 228,271 deaths which is a depressing statistic
  • Dr. John Campbell agrees with Dr. Christopher Murray, director of the Institute for Health Metrics that “people’s inconsistent use of these measures (face masks, social distancing) is a serious problem”
  • States with increasing transmission like Colorado, Idaho, Kansas, Kentucky, Mississippi, Missouri, Ohio, Oklahoma, Oregon, and Virginia are suggested to have a lockdown when death rate reaches 8 deaths per million population however it seems we should be also focusing on population densities rather than geographic states
  • Dr. Campbell and Dr. Murray stress more proactive measures than reactive ones like lockdowns
  • if mask usage were to increase to 95% usage reimposition to shutdown could be delayed 6 to 8 weeks

 

New IHME COVID-19 Forecasts See Nearly 300,000 Deaths by December 1

SEATTLE (August 6, 2020) – America’s COVID-19 death toll is expected to reach nearly 300,000 by December 1; however, consistent mask-wearing beginning today could save about 70,000 lives, according to new data from the Institute for Health Metrics and Evaluation (IHME) at the University of Washington’s School of Medicine.The US forecast totals 295,011 deaths by December. As of today, when, thus far, 158,000 have died, IHME is projecting approximately 137,000 more deaths. However, starting today, if 95% of the people in the US were to wear masks when leaving their homes, that total number would decrease to 228,271 deaths, a drop of 49%. And more than 66,000 lives would be saved.Masks and other protective measures against transmission of the virus are essential to staying COVID-free, but people’s inconsistent use of those measures is a serious problem, said IHME Director Dr. Christopher Murray.

“We’re seeing a rollercoaster in the United States,” Murray said. “It appears that people are wearing masks and socially distancing more frequently as infections increase, then after a while as infections drop, people let their guard down and stop taking these measures to protect themselves and others – which, of course, leads to more infections. And the potentially deadly cycle starts over again.”

Murray noted that there appear to be fewer transmissions of the virus in Arizona, California, Florida, and Texas, but deaths are rising and will continue to rise for the next week or two. The drop in infections appears to be driven by the combination of local mandates for mask use, bar and restaurant closures, and more responsible behavior by the public.

“The public’s behavior had a direct correlation to the transmission of the virus and, in turn, the numbers of deaths,” Murray said. “Such efforts to act more cautiously and responsibly will be an important aspect of COVID-19 forecasting and the up-and-down patterns in individual states throughout the coming months and into next year.”

Murray said that based on cases, hospitalizations, and deaths, several states are seeing increases in the transmission of COVID-19, including Colorado, Idaho, Kansas, Kentucky, Mississippi, Missouri, Ohio, Oklahoma, Oregon, and Virginia.

“These states may experience increasing cases for several weeks and then may see a response toward more responsible behavior,” Murray said.

In addition, since July 15, several states have added mask mandates. IHME’s statistical analysis suggests that mandates with no penalties increase mask wearing by 8 percentage points. But mandates with penalties increase mask wearing by 15 percentage points.

“These efforts, along with media coverage and public information efforts by state and local health agencies and others, have led to an increase in the US rate of mask wearing by about 5 percentage points since mid-July,” Murray said. Mask-wearing increases have been larger in states with larger epidemics, he said.

IHME’s model assumes that states will reimpose a series of mandates, including non-essential business closures and stay-at-home orders, when the daily death rate reaches 8 per million. This threshold is based on data regarding when states and/or communities imposed mandates in March and April, and implies that many states will have to reimpose mandates.

As a result, the model suggests which states will need to reimpose mandates and when:

  • August – Arizona, Florida, Mississippi, and South Carolina
  • September – Georgia and Texas
  • October – Colorado, Kansas, Louisiana, Missouri, Nevada, North Carolina, and Oregon.
  • November – Alabama, Arkansas, California, Iowa, New Mexico, Oklahoma, Utah, Washington, and Wisconsin.

However, if mask use is increased to 95%, the re-imposition of stricter mandates could be delayed 6 to 8 weeks on average.

Source: http://www.healthdata.org/news-release/new-ihme-covid-19-forecasts-see-nearly-300000-deaths-december-1

 

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Is SARS-COV2 Hijacking the Complement and Coagulation Systems?

Reporter: Stephen J. Williams, PhD

In a recent Nature Medicine paper “Immune complement and coagulation dysfunction in adverse outcomes of SARS-CoV-2 infection” Ramlall et al. demonstrate, in a retrospective study, that a significant number of patients presenting SARS-CoV2 complications had prior incidences of macular degeneration and coagulation disorders and these previous indications are risk factors for COVID-related complications.

 

Abstract

Understanding the pathophysiology of SARS-CoV-2 infection is critical for therapeutic and public health strategies. Viral–host interactions can guide discovery of disease regulators, and protein structure function analysis points to several immune pathways, including complement and coagulation, as targets of coronaviruses. To determine whether conditions associated with dysregulated complement or coagulation systems impact disease, we performed a retrospective observational study and found that history of macular degeneration (a proxy for complement-activation disorders) and history of coagulation disorders (thrombocytopenia, thrombosis and hemorrhage) are risk factors for SARS-CoV-2-associated morbidity and mortality—effects that are independent of age, sex or history of smoking. Transcriptional profiling of nasopharyngeal swabs demonstrated that in addition to type-I interferon and interleukin-6-dependent inflammatory responses, infection results in robust engagement of the complement and coagulation pathways. Finally, in a candidate-driven genetic association study of severe SARS-CoV-2 disease, we identified putative complement and coagulation-associated loci including missense, eQTL and sQTL variants of critical complement and coagulation regulators. In addition to providing evidence that complement function modulates SARS-CoV-2 infection outcome, the data point to putative transcriptional genetic markers of susceptibility. The results highlight the value of using a multimodal analytical approach to reveal determinants and predictors of immunity, susceptibility and clinical outcome associated with infection.

Introduction

As part of a separate study, the authors mapped over 140 cellular proteins that are structurally mimicked by coronaviruses (CoVs) and identified complement and coagulation pathways as targets of this strategy across all CoV strains4. The complement system is a critical defense against pathogens, including viruses5 and when dysregulated (by germline variants or acquired through age-related effects or excessive tissue damage) can contribute to pathologies mediated by inflammation5,6,7.

“So, virally encoded structural mimics of complement and coagulation factors may contribute to CoV-associated immune-mediated pathology and indicate sensitivities in antiviral defenses.”

 

Methods and Results

  • Between 1 February 2020 and 25 April 2020, 11,116 patients presented to New York-Presbyterian/Columbia University Irving Medical Center with suspected SARS-CoV-2 infection, of which 6,398 tested positive
  • Electronic health records (EHRs) were used to define sex, age and smoking history status as well as histories of macular degeneration, coagulatory disorders (thrombocytopenia, thrombosis and hemorrhage), hypertension, type 2 diabetes (T2D), coronary artery disease (CAD) and obesity (see Methods). A Python algorithm was used to analyze all confounders.
  • identified 88 patients with history of macular degeneration, 4 with complement deficiency disorders and 1,179 with coagulatory disorders).
  • observed a 35% mortality rate among patients that were put on mechanical ventilation and that 31% of deceased patients had been on mechanical respiration.
  • patients with AMD (a proxy for complement activation disorders) and coagulation disorders (thrombocytopenia, thrombosis and hemorrhage) were at significantly increased risk of adverse clinical outcomes (including mechanical respiration and death) following SARS-CoV-2 infection
  • 650 NP swabs from control and SARS-CoV-2-infected patients who presented to Weill-Cornell Medical Center were evaluated by RNA-Seq. Gene set enrichment analysis (GSEA) of Hallmark gene sets found that SARS-CoV-2 infection (as defined by presence of SARS-CoV-2 RNA and stratified into ‘positive’, ‘low’, ‘medium’ or ‘high’ based on viral load; induces genes related to pathways with known immune modulatory functions (Fig. 2a). Moreover, among the most enriched gene sets, SARS-CoV-2 infection induces robust activation of the complement cascade (false discovery rate (FDR) P < 0.001), with increasing enrichment and significance with viral load (FDR P < 0.0001).
  • KEGG Pathway Analysis revealed KEGG_Complement_and_Coagulation_Cascades’, ‘GO_Coagulation’ and ‘Reactome_initial_triggering_of_complement’ to be significantly enriched in expression profiles of SARS-CoV-2-infected samples
  • conducted a candidate-driven study to evaluate whether genetic variation within a 60-Kb window around 102 genes with known roles in regulating complement or coagulation cascades (2,888 genetic variants fulfill this criteria of the 805,426 profiled in the UK Biobank) is associated with poor SARS-CoV-2 clinical outcome
  • identified 11 loci representing seven genes with study-wide significance. A variant of coagulation factor III (F3), variant rs72729504, was found to be associated with increased risk of adverse clinical outcome associated with SARS-CoV-2 infection. The analysis also identified that four variants previously reported to be associated with AMD (rs45574833, rs61821114, rs61821041 and rs12064775)15predispose carriers to hospitalization following SARS-CoV-2 infection

As authors state:

“Among the implications, the data warrant heightened public health awareness for the most vulnerable individuals and further investigation into an existing menu of complement and coagulation targeting therapies that were recently shown to be beneficial in a small cohort of patients with SARS-CoV-2 infection.” 26,27.

 

References

Ramlall, V., Thangaraj, P.M., Meydan, C. et al. Immune complement and coagulation dysfunction in adverse outcomes of SARS-CoV-2 infection. Nat Med (2020). https://doi.org/10.1038/s41591-020-1021-2

 

4.

Lasso, G., Honig, B. & Shapira, S. D. A sweep of earth’s virome reveals host-guided viral protein structural mimicry; with implications for human disease. Preprint at bioRxiv https://doi.org/10.1101/2020.06.18.159467 (2020).

 

SUMMARY

Viruses deploy an array of genetically encoded strategies to coopt host machinery and support viral replicative cycles. Molecular mimicry, manifested by structural similarity between viral and endogenous host proteins, allow viruses to harness or disrupt cellular functions including nucleic acid metabolism and modulation of immune responses. Here, we use protein structure similarity to scan for virally encoded structure mimics across thousands of catalogued viruses and hosts spanning broad ecological niches and taxonomic range, including bacteria, plants and fungi, invertebrates and vertebrates. Our survey identified over 6,000,000 instances of structural mimicry, the vast majority of which (>70%) cannot be discerned through protein sequence. The results point to molecular mimicry as a pervasive strategy employed by viruses and indicate that the protein structure space used by a given virus is dictated by the host proteome. Interrogation of proteins mimicked by human-infecting viruses points to broad diversification of cellular pathways targeted via structural mimicry, identifies biological processes that may underly autoimmune disorders, and reveals virally encoded mimics that may be leveraged to engineer synthetic metabolic circuits or may serve as targets for therapeutics. Moreover, the manner and degree to which viruses exploit molecular mimicry varies by genome size and nucleic acid type, with ssRNA viruses circumventing limitations of their small genomes by mimicking human proteins to a greater extent than their large dsDNA counterparts. Finally, we identified over 140 cellular proteins that are mimicked by CoV, providing clues about cellular processes driving the pathogenesis of the ongoing COVID-19 pandemic.

 

26.

Risitano, A. M. Complement as a target in COVID-19?. Nat. Rev. Immunol. 20, 343–344 (2020).

 

27.

Mastaglio, S. et al. The first case of COVID-19 treated with the complement C3 inhibitor AMY-101. Clin. Immunol. 215, 108450 (2020).

 

28.

Polubriaginof, F. C. G. et al. Challenges with quality of race and ethnicity data in observational databases. J. Am. Med. Inf. Assoc. 26, 730–736 (2019).

 

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The Inequality and Health Disparity seen with the COVID-19 Pandemic Is Similar to Past Pandemics

Curator: Stephen J. Williams, PhD

2019-nCoV-CDC-23311

It has become very evident, at least in during this pandemic within the United States, that African Americans and poorer communities have been disproportionately affected by the SARS-CoV2 outbreak . However, there are many other diseases such as diabetes, heart disease, and cancer in which these specific health disparities are evident as well :

Diversity and Health Disparity Issues Need to be Addressed for GWAS and Precision Medicine Studies

Personalized Medicine, Omics, and Health Disparities in Cancer:  Can Personalized Medicine Help Reduce the Disparity Problem?

Disease like cancer have been shown to have wide disparities based on socioeconomic status, with higher incidence rates seen in poorer and less educated sub-populations, not just here but underdeveloped countries as well (see Opinion Articles from the Lancet: COVID-19 and Cancer Care in China and Africa) and graphics below)

 

 

 

 

 

 

 

 

 

 

In an article in Science by Lizzie Wade, these disparities separated on socioeconomic status, have occurred in many other pandemics throughout history, and is not unique to the current COVID19 outbreak.  The article, entitled “An Unequal Blow”, reveal how

in past pandemics, people on the margins suffered the most.

Source: https://science.sciencemag.org/content/368/6492/700.summary

Health Disparities during the Black Death Bubonic Plague Pandemic in the 14th Century (1347-1351)

During the mid 14th century, all of Europe was affected by a plague induced by the bacterium Yersinia pestis, and killed anywhere between 30 – 60% of the European population.  According to reports by the time the Black Death had reached London by January 1349 there had already been horrendous reports coming out of Florence Italy where the deadly disease ravished the population there in the summer of 1348 (more than half of the city’s population died). And by mid 1349 the Black Death had killed more than half of Londoners.  It appeared that no one was safe from the deadly pandemic, affecting the rich, the poor, the young, the old.

However, after careful and meticulous archaeological and historical analysis in England and other sites, revealed a distinct social and economic inequalities that predominated and most likely guided the pandemics course throughout Europe.   According to Dr. Gwen Robbins Schug, a bio-archaeologist at Appalachian State University,

Bio-archaeology and other social sciences have repeatedly demonstrated that these kinds of crises play out along the preexisting fault lines of each society.  The people at greatest risk were often those already marginalized- the poor and minorities who faced discrimination in ways that damaged their health or limited their access to medical care even in pandemic times.

At the start of the Black Death, Europe had already gone under a climactic change with erratic weather.  As a result, a Great Famine struck Europe between 1315-17.  Wages fell and more people fell into poverty while the wealthiest expanded their riches, leading to an increased gap in wealth and social disparity.  In fact according to recordkeeping most of Englanders were living below the poverty line.

Author Lizzie Wade also interviewed Dr. Sharon, DeWitte, a biological anthropologist at University of South Carolina, who looks at skeletal remains of Black Death victims to get evidence on their health status, like evidence of malnutrition, osteoporosis, etc.   And it appears that most of the victims may have had preexisting health conditions indicative of poorer status.  And other evidence show that wealthy landowners had a lower mortality rate than poorer inner city dwellers.

1918 Spanish Flu

Socioeconomic and demographic studies have shown that both Native American Indians and African Americans on the lower end of the socioeconomic status were disproportionately affected by the 1918 Spanish flu pandemic.  According to census records, the poorest had a 50% higher mortality rate than wealthy areas in the city of Oslo.  In the US, minors and factory workers died at the highest rates.  In the US African Americans had already had bouts with preexisting issues like tuberculosis and may have contributed to the higher mortality.  In addition Jim Crow laws in the South, responsible for widespread discrimination, also impacted the ability of African Americans to seek proper medical care.

From the Atlantic

Source: https://www.theatlantic.com/politics/archive/2016/05/americas-health-segregation-problem/483219/

America’s Health Segregation Problem

Has the country done enough to overcome its Jim Crow health care history?

VANN R. NEWKIRK II

MAY 18, 2016

Like other forms of segregation, health-care segregation was originally a function of explicitly racist black codes and Jim Crow laws. Many hospitals, clinics, and doctor’s offices were totally segregated by race, and many more maintained separate wings or staff that could never intermingle under threat of law. The deficit of trained black medical professionals (itself caused by a number of factors including education segregation) meant that no matter where black people received health-care services, they would find their care to be subpar compared to that of whites. While there were some deaths that were directly attributable to being denied emergency service, most of the damage was done in establishing the same cumulative health disparities that plague black people today as a societal fate. The descendants of enslaved people lived much more dangerous and unhealthy lives than white counterparts, on disease-ridden and degraded environments. Within the confines of a segregated health-care system, these factors became poor health outcomes that shaped black America as if they were its genetic material.

 

https://twitter.com/time4equity/status/1175080469425266688?s=20

 

R.A.HahnaB.I.TrumanbD.R.Williamsc.Civil rights as determinants of public health and racial and ethnic health equity: Health care, education, employment, and housing in the United States.

SSM – Population Health: Volume 4, April 2018, Pages 17-24

Highlights

  • Civil rights are characterized as social determinants of health.
  • Four domains in civil rights history since 1950 are explored in—health care, education, employment, and housing.
  • Health care, education, employment show substantial benefits when civil rights are enforced.
  • Housing shows an overall failure to enforce existing civil rights and persistent discrimination.
  • Civil rights and their enforcement may be considered a powerful arena for public health theorizing, research, policy, and action.

 

For more articles on COVID-19 Please go to our Coronovirus Portal

https://pharmaceuticalintelligence.com/coronavirus-portal/

 

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National Public Radio interview with Dr. Anthony Fauci on his optimism on a COVID-19 vaccine by early 2021

Reporter: Stephen J. Williams, PhD

Below I am giving a link to an important interview by NPR’s Judy Woodruff with Dr. Anthony Fauci on his thoughts regarding the recent spikes in cases, the potential for a COVID-19 vaccine by next year, and promising therapeutics in the pipeline.  The interview link is given below however I will summarize a few of the highlights of the interview.

 

Some notes on the interview

Judy Woodruff began her report with some up to date news regarding the recent spike and that Miami Florida has just ordered the additional use of facemasks.  She asked Dr. Anthony Fauci, head of the National Institute of Allergy and Infectious Diseases (NIAD), about if the measures currently in use are enough to bring this spike down.  Dr. Fauci said that we need to reboot our efforts, mainly because people are not doing three things which could have prevented this spike mainly

  1. universal wearing of masks
  2. distancing properly from each other
  3. close the bars and pubs (see Wisconsin bars packed after ruling)

It hasn’t been a uniform personal effort

Dr. Fauci on testing

We have to use the tests we have out there efficiently and effectively And we have to get them out to the right people who can do the proper identification, isolation, and do proper contract tracing and need to test more widely in a surveillance way to get a feel of the extent and penetrance of this community spread.  there needs to be support and money for these testing labs

We have a problem and we need to admit and own it but we need to do the things we know are effective to turn this thing around.

On Vaccines

“May be later this year”

His response to Merck’s CEO Ken Frazer who said officials are giving false hop if they say ‘end of year’ but Dr. Fauci disagrees.  He says a year end goal is not outlandish.

What we have been doing is putting certain things in line with each other in an unprecedented way.

Dr. Fauci went on to say that, in the past yes, it took a long time, even years to develop a vaccine but now they have been able to go from sequence of virus to a vaccine development program in days, which is unheard of.  Sixty two days later we have gone into phase 1 trials. the speed at which this is occurring is so much faster.  He says that generally it would take a couple of years to get a neutralizing antibody but we are already there.  Another candidate will be undergoing phase 3 trials by end of this month (July 2020).

He is “cautiously optimistic” that we will have one or more vaccines to give to patients by end of year because given the amount of cases it will be able to get a handle on safety and efficacy by late fall.

Now he says the game changer is that the government is working with companies to ramp up the production of doses of the candidate vaccines so when we find which one works we will have ample doses on hand.  He is worried about the anti vaccine movement derailing vaccine testing and vaccinations but says if we keep on informing the public we can combat this.

Going back to school

Dr. Fauci is concerned for the safety of the vulnerable in schools, including students and staff.  He wants the US to get down to a reasonable baseline of cases but in the US that baseline after the first wave was still significantly higher than in most countries, where the baseline was more like tens of cases not hundreds of cases.

For more information on COVID-19 Please go to our Coronavirus Portal at

https://pharmaceuticalintelligence.com/coronavirus-portal/

 

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Placenta lacks molecules required for COVID-19 infection

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

The pandemic of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected more than 10 million people, including pregnant women. To date, no consistent evidence for the vertical transmission of SARS-CoV-2 has been found. The placenta serves as the lungs, gut, kidneys, and liver of the fetus. This fetal organ also has major endocrine actions that modulate maternal physiology and, importantly, together with the extraplacental chorioamniotic membranes shield the fetus against microbes from hematogenous dissemination and from invading the amniotic cavity.

 

Most pathogens that cause hematogenous infections in the mother are not able to reach the fetus, which is largely due to the potent protective mechanisms provided by placental cells (i.e. trophoblast cells: syncytiotrophoblasts and cytotrophoblasts). Yet, some of these pathogens such as Toxoplasma gondii, Rubella virus, herpesvirus (HSV), cytomegalovirus (CMV), and Zika virus (ZIKV), among others, are capable of crossing the placenta and infecting the fetus, causing congenital disease.

 

The placental membranes that contain the fetus and amniotic fluid lack the messenger RNA (mRNA) molecule required to manufacture the ACE2 receptor, the main cell surface receptor used by the SARS-CoV-2 virus to cause infection. These placental tissues also lack mRNA needed to make an enzyme, called TMPRSS2, that SARS-CoV-2 uses to enter a cell. Both the receptor and enzyme are present in only miniscule amounts in the placenta, suggesting a possible explanation for why SARS-CoV-2 has only rarely been found in fetuses or newborns of women infected with the virus, according to the study authors.

 

The single-cell transcriptomic analysis presented by the researchers provides evidence that SARS-CoV-2 is unlikely to infect the placenta and fetus since its canonical receptor and protease, ACE2 and TRMPSS2, are only minimally expressed by the human placenta throughout pregnancy. In addition, it was shown that the SARS-CoV-2 receptors are not expressed by the chorioamniotic membranes in the third trimester. However, viral receptors utilized by CMV, ZIKV, and others are highly expressed by the human placental tissues.

 

Transcript levels do not always correlate with protein expression, but the data of the present study indicates a low likelihood of placental infection and vertical transmission of SARS-CoV-2. However, it is still possible that the expression of these proteins is much higher in individuals with pregnancy complications related with the renin-angiotensin-aldosterone system, which can alter the expression of ACE2. The cellular receptors and mechanisms that could be exploited by SARS-CoV-2 are still under investigation.

 

References:

 

https://www.nih.gov/news-events/news-releases/placenta-lacks-major-molecules-used-sars-cov-2-virus-cause-infection

 

https://pubmed.ncbi.nlm.nih.gov/32662421/

 

https://pubmed.ncbi.nlm.nih.gov/32217113/

 

https://pubmed.ncbi.nlm.nih.gov/32161408/

 

https://pubmed.ncbi.nlm.nih.gov/32335053/

 

https://pubmed.ncbi.nlm.nih.gov/32298273/

 

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From Cell Press:  New Insights on the D614G Strain of COVID: Will a New Mutated Strain Delay Vaccine Development?

Reporter: Stephen J. Williams, PhD

Two recent articles in Cell Press, both peer reviewed, discuss the emergence and potential dominance of a new mutated strain of COVID-19, in which the spike protein harbors a D614G mutation.

In the first article “Making Sense of Mutation: What D614G means for the COVID-19 pandemic Remains Unclear”[1] , authors Drs. Nathan Grubaugh, William Hanage, and Angela Rasmussen discuss the recent findings by Korber et al. 2020 [2] which describe the potential increases in infectivity and mortality of this new mutant compared to the parent strain of SARS-CoV2.  For completeness sake I will post this article as to not defer from their interpretations of this important paper by Korber and to offer some counter opinion to some articles which have surfaced this morning in the news.

Making sense of mutation: what D614G means for the COVID-19 pandemic remains unclear

 

Nathan D. Grubaugh1 *, William P. Hanage2 *, Angela L. Rasmussen3 * 1Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA 2Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA 3Center for Infection and Immunity, Columbia Mailman School of Public Health, New York, NY 10032, USA Correspondence: grubaughlab@gmail.com

 

Abstract: Korber et al. (2020) found that a SARS-CoV-2 variant in the spike protein, D614G, rapidly became dominant around the world. While clinical and in vitro data suggest that D614G changes the virus phenotype, the impact of the mutation on transmission, disease, and vaccine and therapeutic development are largely unknown.

Introduction: Following the emergence of SARS-CoV-2 in China in late 2019, and the rapid expansion of the COVID19 pandemic in 2020, questions about viral evolution have come tumbling after. Did SARS-CoV-2 evolve to become better adapted to humans? More infectious or transmissible? More deadly? Virus mutations can rise in frequency due to natural selection, random genetic drift, or features of recent epidemiology. As these forces can work in tandem, it’s often hard to differentiate when a virus mutation becomes common through fitness or by chance. It is even harder to determine if a single mutation will change the outcome of an infection, or a pandemic. The new study by Korber et al. (2020) sits at the heart of this debate. They present compelling data that an amino acid change in the virus’ spike protein, D614G, emerged early during the pandemic, and viruses containing G614 are now dominant in many places around the world. The crucial questions are whether this is the result of natural selection, and what it means for the COVID-19 pandemic. For viruses like SARS-CoV-2 transmission really is everything – if they don’t get into another host their lineage ends. Korber et al. (2020) hypothesized that the rapid spread of G614 was because it is more infectious than D614. In support of their hypothesis, the authors provided evidence that clinical samples from G614 infections have a higher levels of viral RNA, and produced higher titers in pseudoviruses from in vitro experiments; results that now seem to be corroborated by others [e.g. (Hu et al., 2020; Wagner et al., 2020)]. Still, these data do not prove that G614 is more infectious or transmissible than viruses containing D614. And because of that, many questions remain on the potential impacts, if any, that D614G has on the COVID-19 pandemic.

The authors note that this new G614 variant has become the predominant form over the whole world however in China the predominant form is still the D614 form.  As they state

“over the period that G614 became the global majority variant, the number of introductions from China where D614 was still dominant were declining, while those from Europe climbed. This alone might explain the apparent success of G614.”

Grubaugh et al. feel there is not enough evidence that infection with this new variant will lead to higher mortality.  Both Korber et al. and the Seattle study (Wagner et al) did not find that the higher viral load of this variant led to a difference in hospitalizations so apparently each variant might be equally as morbid.

In addition, Grubaugh et al. believe this variant would not have much affect on vaccine development as, even though the mutation lies within the spike protein, D614G is not in the receptor binding domain of the spike protein.  Korber suggest that there may be changes in glycosylation however these experiments will need to be performed.  In addition, antibodies from either D614 or G614 variant infected patients could cross neutralize.

 

Conclusions: While there has already been much breathless commentary on what this mutation means for the COVID19 pandemic, the global expansion of G614 whether through natural selection or chance means that this variant now is the pandemic. As a result its properties matter. It is clear from the in vitro and clinical data that G614 has a distinct phenotype, but whether this is the result of bonafide adaptation to human ACE2, whether it increases transmissibility, or will have a notable effect, is not clear. The work by Korber et al. (2020) provides an early base for more extensive epidemiological, in vivo experimental, and diverse clinical investigations to fill in the many critical gaps in how D614G impacts the pandemic.

The link to the Korber Cell paper is here: https://www.cell.com/cell/fulltext/S0092-8674(20)30820-5

Tracking changes in SARS-CoV-2 Spike: evidence that D614G increases infectivity of the COVID-19 virus

DOI: https://doi.org/10.1016/j.cell.2020.06.043

Keypoints

  • The consistent increase of G614 at regional levels may indicate a fitness advantage

 

  • G614 is associated with lower RT PCR Ct’s, suggestive of higher viral loads in patients

 

  • The G614 variant grows to higher titers as pseudotyped virions

Summary

A SARS-CoV-2 variant carrying the Spike protein amino acid change D614G has become the most prevalent form in the global pandemic. Dynamic tracking of variant frequencies revealed a recurrent pattern of G614 increase at multiple geographic levels: national, regional and municipal. The shift occurred even in local epidemics where the original D614 form was well established prior to the introduction of the G614 variant. The consistency of this pattern was highly statistically significant, suggesting that the G614 variant may have a fitness advantage. We found that the G614 variant grows to higher titer as pseudotyped virions. In infected individuals G614 is associated with lower RT-PCR cycle thresholds, suggestive of higher upper respiratory tract viral loads, although not with increased disease severity. These findings illuminate changes important for a mechanistic understanding of the virus, and support continuing surveillance of Spike mutations to aid in the development of immunological interventions.

 

References

  1. Grubaugh, N.D., Hanage, W.P., Rasmussen, A.L., Making sense of mutation: what D614G means for the COVID-19 pandemic remains unclear, Cell (2020), doi: https:// doi.org/10.1016/j.cell.2020.06.040.
  2. Korber, B., Fischer, W.M., Gnanakaran, S., Yoon, H., Theiler, J., Abfalterer, W., Hengartner, N., Giorgi, E.E., Bhattacharya, T., Foley, B., et al. (2020). Tracking changes in SARS-CoV-2 Spike: evidence that D614G increases infectivity of the COVID-19 virus. Cell 182.
  3. Endo, A., Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group, Abbott, S., Kucharski, A.J., and Funk, S. (2020). Estimating the overdispersion in COVID-19 transmission using outbreak sizes outside China. Wellcome Open Res 5, 67.
  4. Hu, J., He, C.-L., Gao, Q.-Z., Zhang, G.-J., Cao, X.-X., Long, Q.-X., Deng, H.-J., Huang, L.-Y., Chen, J., Wang, K., et al. (2020). The D614G mutation of SARS-CoV-2 spike protein enhances viral infectivity and decreases neutralization sensitivity to individual convalescent sera. bioRxiv 2020.06.20.161323.
  5. Wagner, C., Roychoudhury, P., Hadfield, J., Hodcroft, E.B., Lee, J., Moncla, L.H., Müller, N.F., Behrens, C., Huang, M.-L., Mathias, P., et al. (2020). Comparing viral load and clinical outcomes in Washington State across D614G mutation in spike protein of SARS-CoV-2. Https://github.com/blab/ncov-D614G.

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The Castleman Disease Research Network publishes Phase 1 Results of Drug Repurposing Database for COVID-19

Reporter: Stephen J. Williams, PhD.

 

From CNN at https://www.cnn.com/2020/06/27/health/coronavirus-treatment-fajgenbaum-drug-review-scn-wellness/index.html

Updated 8:17 AM ET, Sat June 27, 2020

(CNN)Every morning, Dr. David Fajgenbaum takes three life-saving pills. He wakes up his 21-month-old daughter Amelia to help feed her. He usually grabs some Greek yogurt to eat quickly before sitting down in his home office. Then he spends most of the next 14 hours leading dozens of fellow researchers and volunteers in a systematic review of all the drugs that physicians and researchers have used so far to treat Covid-19. His team has already pored over more than 8,000 papers on how to treat coronavirus patients.

The 35-year-old associate professor at the University of Pennsylvania Perelman School of Medicine leads the school’s Center for Cytokine Storm Treatment & Laboratory. For the last few years, he has dedicated his life to studying Castleman disease, a rare condition that nearly claimed his life. Against epic odds, he found a drug that saved his own life six years ago, by creating a collaborative method for organizing medical research that could be applicable to thousands of human diseases. But after seeing how the same types of flares of immune-signaling cells, called cytokine storms, kill both Castleman and Covid-19 patients alike, his lab has devoted nearly all of its resources to aiding doctors fighting the pandemic.

A global repository for Covid-19 treatment data

Researchers working with his lab have reviewed published data on more than 150 drugs doctors around the world have to treat nearly 50,000 patients diagnosed with Covid-19. They’ve made their analysis public in a database called the Covid-19 Registry of Off-label & New Agents (or CORONA for short).
It’s a central repository of all available data in scientific journals on all the therapies used so far to curb the pandemic. This information can help doctors treat patients and tell researchers how to build clinical trials.The team’s process resembles that of the coordination Fajgenbaum used as a medical student to discover that he could repurpose Sirolimus, an immunosuppressant drug approved for kidney transplant patients, to prevent his body from producing deadly flares of immune-signaling cells called cytokines.The 13 members of Fajgenbaum’s lab recruited dozens of other scientific colleagues to join their coronavirus effort. And what this group is finding has ramifications for scientists globally.
This effort by Dr. Fajgenbaum’s lab and the resultant collaborative effort shows the power and speed at which a coordinated open science effort can achieve goals. Below is the description of the phased efforts planned and completed from the CORONA website.

CORONA (COvid19 Registry of Off-label & New Agents)

Drug Repurposing for COVID-19

Our overarching vision:  A world where data on all treatments that have been used against COVID19 are maintained in a central repository and analyzed so that physicians currently treating COVID19 patients know what treatments are most likely to help their patients and so that clinical trials can be appropriately prioritized.

 

Phase 1: COMPLETED

Our team reviewed 2500+ papers & extracted data on over 9,000 COVID19 patients. We found 115 repurposed drugs that have been used to treat COVID19 patients and analyzed data on which ones seem most promising for clinical trials. This data is open source and can be used by physicians to treat patients and prioritize drugs for trials. The CDCN will keep this database updated as a resource for this global fight. Repurposed drugs give us the best chance to help COVID19 as quickly as possible! As disease hunters who have identified and repurposed drugs for Castleman disease, we’re applying our ChasingMyCure approach to COVID19.

Read our systematic literature review published in Infectious Diseases and Therapy at the following link: Treatments Administered to the First 9152 Reported Cases of COVID-19: A Systematic Review

From Fajgenbaum, D.C., Khor, J.S., Gorzewski, A. et al. Treatments Administered to the First 9152 Reported Cases of COVID-19: A Systematic Review. Infect Dis Ther (2020). https://doi.org/10.1007/s40121-020-00303-8

The following is the Abstract and link to the metastudy.  This study was a systematic review of literature with strict inclusion criteria.  Data was curated from these published studies and a total of 9152 patients were evaluated for treatment regimens for COVID19 complications and clinical response was curated for therapies in these curated studies.  Main insights from this study were as follows:

Key Summary Points

Why carry out this study?
  • Data on drugs that have been used to treat COVID-19 worldwide are currently spread throughout disparate publications.
  • We performed a systematic review of the literature to identify drugs that have been tried in COVID-19 patients and to explore clinically meaningful response time.
What was learned from the study?
  • We identified 115 uniquely referenced treatments administered to COVID-19 patients. Antivirals were the most frequently administered class; combination lopinavir/ritonavir was the most frequently used treatment.
  • This study presents the latest status of off-label and experimental treatments for COVID-19. Studies such as this are important for all diseases, especially those that do not currently have definitive evidence from randomized controlled trials or approved therapies.

Treatments Administered to the First 9152 Reported Cases of COVID-19: A Systematic Review

Abstract

The emergence of SARS-CoV-2/2019 novel coronavirus (COVID-19) has created a global pandemic with no approved treatments or vaccines. Many treatments have already been administered to COVID-19 patients but have not been systematically evaluated. We performed a systematic literature review to identify all treatments reported to be administered to COVID-19 patients and to assess time to clinically meaningful response for treatments with sufficient data. We searched PubMed, BioRxiv, MedRxiv, and ChinaXiv for articles reporting treatments for COVID-19 patients published between 1 December 2019 and 27 March 2020. Data were analyzed descriptively. Of the 2706 articles identified, 155 studies met the inclusion criteria, comprising 9152 patients. The cohort was 45.4% female and 98.3% hospitalized, and mean (SD) age was 44.4 years (SD 21.0). The most frequently administered drug classes were antivirals, antibiotics, and corticosteroids, and of the 115 reported drugs, the most frequently administered was combination lopinavir/ritonavir, which was associated with a time to clinically meaningful response (complete symptom resolution or hospital discharge) of 11.7 (1.09) days. There were insufficient data to compare across treatments. Many treatments have been administered to the first 9152 reported cases of COVID-19. These data serve as the basis for an open-source registry of all reported treatments given to COVID-19 patients at www.CDCN.org/CORONA. Further work is needed to prioritize drugs for investigation in well-controlled clinical trials and treatment protocols.

Read the Press Release from PennMedicine at the following link: PennMedicine Press Release

Phase 2: Continue to update CORONA

Our team continues to work diligently to maintain an updated listing of all treatments reported to be used in COVID19 patients from papers in PubMed. We are also re-analyzing publicly available COVID19 single cell transcriptomic data alongside our iMCD data to search for novel insights and therapeutic targets.

You can visit the following link to access a database viewer built and managed by Matt Chadsey, owner of Nonlinear Ventures.

If you are a physician treating COVID19 patients, please visit the FDA’s CURE ID app to report de-identified information about drugs you’ve used to treat COVID19 in just a couple minutes.

For more information on COVID19 on this Open Access Journal please see our Coronavirus Portal at

https://pharmaceuticalintelligence.com/coronavirus-portal/

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National Cancer Institute Director Neil Sharpless says mortality from delays in cancer screenings due to COVID19 pandemic could result in tens of thousands of extra deaths in next decade

Reporter: Stephen J Williams, PhD

UPDATED: 08/14/2023

A Cross Sectional Study Reveals What Oncologists Had Feared: Cancer Screenings During Pandemic Has Decreased, leading to Decreased Early Detection

As discussed in many articles here on COVID-19 and cancer, during the pandemic many oncologists were worried that people slowed getting their cancer screenings due to health risks due to the COVID-19 outbreak.  Governmental agencies went as far to project upticks in future cancer rates, as preventative screening rates were down due to closed hospitals, shuttered services, or patient trepidation during the height of the pandemic.  As many oncologists voiced, a decrease in cancer screenings might lead to missing out on the early stages of the disease, when most treatable. Now, reported in a Lancet cross-sectional analysis by investigators at ACS and University of Texas Southwest (1), we have the first indication of the effects of this decrease in preventative screening, namely decreased early detection and diagnosis.

The authors used data from the US National Cancer Database, a nationwide hospital-based cancer registry, to perform a cross sectional nationwide assessment of the prevalence of new cancer diagnosis before, during, and after the height of the pandemic (March 1 2020 to December 31, 2020).  Newly diagnosed cases of first primary malignant cancer between Jan1, 2018 to Dec 31, 2020 were identified and monthly and annual counts and stage distributions were caluculated andpresented as adjusted odds ratios (aORs).  They also used the period from 2018 to Jan 2020 as a baseline or prepandemic level of newly diagnosed cancer.

Results of this analysis identified 2,404,050 adults with newly diagnosed cancer during study period 2018 to 2020.  The monthly number of new cancer diagnoses (all stages) decreased significantly after the start of the COVID-19 pandemic in March 2020.  However new cancer diagnosis returned to pre-pandemic levels by end of 2020.  The decrease in diagnosis was largest for stage I diseases however the odds of being diagnosed with late stage IV disease were higher in 2020 than in 2019.  When the authors stratified the cohorts based on sociodemographic groups, interestingly those most affected (with lowest diagnosis rates during the pandemic) were those living in socioeconomic deprived areas, hispanics, asian americans, pacific Islanders, and uninsured individuals.

The authors’ interpretations are a warning: Substantial cancer underdiagnosis and decreases in the proportion of early stage diagnoses occurred during 2020 in the USA, particularly among medically underserved individuals. Monitoring the long-term effects of the pandemic on morbidity, survival, and mortality is warranted.

 

 

Evidence before this study

We searched PubMed using the terms “COVID”, “pandemic”, and “cancer” for studies published in English between

March 1, 2020, and Nov 30, 2022. Health care was disrupted during the emergence of the COVID-19 pandemic. In the USA, rapid decreases in screening were reported for nearly all types of cancer screening services after the declaration of the COVID-19 national emergency. Decreased screening, and delayed and forgone routine check-ups or health-care visits, can lead to underdiagnosis of cancer, especially for early stage disease for which treatment is most effective. Several studies have identified reduced use of diagnostic procedures and decreases in the number of newly diagnosed patients during 2020 in the USA. However, these studies were done in selected populations, in specific geographical areas, or for only a single cancer type, limiting understanding of the COVID-19 pandemic on cancer burden nationally.

Added value of this study

Using a recently released nationwide cancer registry dataset, we comprehensively evaluated changes in cancer diagnoses and stage distribution during the first year of the COVID-19 pandemic by cancer type and key sociodemographic factors in the USA.

Implications of all the available evidence

Along with existing evidence, our findings should help to inform future policy and cancer care delivery interventions to improve access to care for underserved populations. Research is warranted to monitor the long-term effects of the underdiagnosis of early stage cancer identified in this study on morbidity, mortality, and disparities in health outcomes.

Results

The main results from the paper are summarized below:

 

Between 2020 and 2019, annual stage I diagnoses decreased by 17·2% (95% CI 16·8–17·6), and annual stage IV diagnoses decreased 9·8% (9·2–10·5). Notably, by race and ethnicity, the largest percentage reduction in stage I diagnoses was among Hispanic individuals and Asian American and Pacific Islander individuals, and the largest percentage reduction in stage IV diagnoses was among non-Hispanic Black and non-Hispanic White individuals. Diagnoses of lung cancer, colorectal cancer, melanoma, and non-Hodgkin lymphoma had the largest percentage reduction among both stage I (>18%) and stage IV (>10%) diagnoses; cancers of the prostate, cervix, liver, oesophagus, stomach, and thyroid also had large percentage reductions in stage I diagnoses (>20).

After adjusting for sociodemographic and clinical factors, the stage distribution of new diagnoses changed in 2020 compared with 2019 (table 3). Specifically, the aOR for being diagnosed with stage I disease versus stage II–IV disease in 2020 compared with 2019 was 0·946 (95% CI 0·939–0·952), and the aOR for being diagnosed with stage IV disease versus stage I–III disease in 2020 compared with 2019 was 1·074 (1·066–1·083).

These results also confirmed results seen in other studies coming from Europe (2,3, 4).

References

  1. Han X, Yang NN, Nogueira L, Jiang C, Wagle NS, Zhao J, Shi KS, Fan Q, Schafer E, Yabroff KR, Jemal A. Changes in cancer diagnoses and stage distribution during the first year of the COVID-19 pandemic in the USA: a cross-sectional nationwide assessment. Lancet Oncol. 2023 Aug;24(8):855-867. doi: 10.1016/S1470-2045(23)00293-0. PMID: 37541271.
  2. Kuzuu K, Misawa N, Ashikari K, et al. Gastrointestinal cancer stage at diagnosis before and during the COVID-19 pandemic in Japan. JAMA Netw Open 2021; 4: e2126334. DOI: 10.1001/jamanetworkopen.2021.26334
  3. Linck PA, Garnier C, Depetiteville MP, et al. Impact of the COVID-19 lockdown in France on the diagnosis and staging of breast cancers in a tertiary cancer centre. Eur Radiol 2022; 32: 1644–51. DOI: 10.1007/s00330-021-08264-3
  4. Mynard N, Saxena A, Mavracick A, et al. Lung cancer stage shift as a result of COVID-19 lockdowns in New York City, a brief report. Clin Lung Cancer 2022; 23: e238–42.  DOI: 10.1016/j.cllc.2021.08.010

 

 

UPDATED: 10/11/2021

Source: https://cancerletter.com/articles/20200619_1/

NCI Director’s Report

Sharpless: COVID-19 expected to increase mortality by at least 10,000 deaths from breast and colorectal cancers over 10 years

By Matthew Bin Han Ong

This story is part of The Cancer Letter’s ongoing coverage of COVID-19’s impact on oncology. A full list of our coverage, as well as the latest meeting cancellations, is available here.

The COVID-19 pandemic will likely cause at least 10,000 excess deaths from breast cancer and colorectal cancer over the next 10 years in the United States.

Scenarios run by NCI and affiliated modeling groups predict that delays in screening for and diagnosis of breast and colorectal cancers will lead to a 1% increase in deaths through 2030. This translates into 10,000 additional deaths, on top of the expected one million deaths resulting from these two cancers.

“For both these cancer types, we believe the pandemic will influence cancer deaths for at least a decade,” NCI Director Ned Sharpless said in a virtual joint meeting of the Board of Scientific Advisors and the National Cancer Advisory Board June 15. “I find this worrisome as cancer mortality is common. Even a 1% increase every decade is a lot of cancer suffering.

“And this analysis, frankly, is pretty conservative. We do not consider cancers other than those of breast and colon, but there is every reason to believe the pandemic will affect other types of cancer, too. We did not account for the additional non-lethal morbidity from upstaging, but this could also be significant and burdensome.”

An editorial by Sharpless on this subject appears in the journal Science.

The early analyses, conducted by the institute’s Cancer Intervention and Surveillance Modeling Network, focused on breast and colorectal cancers, because these are common, with relatively high screening rates.

CISNET modelers created four scenarios to assess long-term increases in cancer mortality rates for these two diseases:

  1. The pandemic has no effect on cancer mortality
  1. Delayed screening—with 75% reduction in mammography and, colorectal screening and adenoma surveillance for six months
  1. Delayed diagnosis—with one-third of people delaying follow-up after a positive screening or diagnostic mammogram, positive FIT or clinical symptoms for six months during a six-month period
  1. Combination of scenarios two and three

Treatment scenarios after diagnosis were not included in the model. These would be: delays in treatment, cancellation of treatment, or modified treatment.

“What we did is show the impact of the number of excess deaths per year for 10 years for each year starting in 2020 for scenario four versus scenario one,” Eric “Rocky” Feuer, chief of the NCI’s Statistical Research and Applications Branch in the Surveillance Research Program, said to The Cancer Letter.

Feuer is the overall project scientist for CISNET, a collaborative group of investigators who use simulation modeling to guide public health research and priorities.

“The results for breast cancer were somewhat larger than for colorectal,” Feuer said. “And that’s because breast cancer has a longer preclinical natural history relative to colorectal cancer.”

Modelers in oncology are creating a global modeling consortium, COVID-19 and Cancer Taskforce, to “support decision-making in cancer control both during and after the crisis.” The consortium is supported by the Union for International Cancer Control, The International Agency for Research on Cancer, The International Cancer Screening Network, the Canadian Partnership Against Cancer, and Cancer Council NSW, Australia.

A spike in cancer mortality rates threatens to reverse or slow down—at least in the medium term—the steady trend of reduction of cancer deaths. On Jan. 8, the American Cancer Society published its annual estimates of new cancer cases and deaths, declaring that the latest data—from 2016 to 2017—show the “largest ever single-year drop in overall cancer mortality of 2.2%.” Experts say that innovation in lung cancer treatment and the success of smoking cessation programs are driving the sharp decrease (The Cancer LetterFeb. 7, 2020).

The pandemic is expected to have broader impact, including increases in mortality rates for other cancer types. Also, variations in severity of COVID-19 in different regions in the U.S. will influence mortality metrics.

“There’s some other cancers that might have delays in screening—for example cervical, prostate, and lung cancer, although lung cancer screening rates are still quite low and prostate cancer screening should only be conducted on those who determine that the benefits outweigh the harms,” Feuer said. “So, those are the major screening cancers, but impacts of delays in treatment, canceling treatment or alternative treatments—could impact a larger range of cancer sites.

“This model assumes a moderate disruption which resolves after six months, and doesn’t consider non-lethal morbidities associated with the delay. One thing I think probably is occurring is regional variation in these impacts,” Feuer said. “If you’re living in New York City where things were ground zero for some of the worst impact early on, probably delays were larger than other areas of the country. But now, as we’re seeing upticks in other areas of the country, there may be in impact in these areas as well”

How can health care providers mitigate some of these harms? For example, for people who delayed screening and diagnosis, are providers able to perform triage, so that those at highest risk are prioritized?

“From a strictly cancer control point of view, let’s get those people who delayed screening, or followup to a positive test, or treatment back on schedule as soon as possible,” Feuer said. “But it’s not a simple calculus, because in every situation, we have to weigh the harms and benefits. As we come out of the pandemic, it tips more and more to, ‘Let’s get back to business with respect to cancer control.’

“Telemedicine doesn’t completely substitute for seeing patients in person, but at least people could get the advice they need, and then are triaged through their health care providers to indicate if they really should prioritize coming in. That helps the individual and the health care provider  weigh the harms and benefits, and try to strategize about what’s best for any individual.”

If the pandemic continues to disrupt routine care, cancer-related mortality rates would rise beyond the predictions in this model.

“I think this analysis begins to help us understand the costs with regard to cancer outcomes of the pandemic,” Sharpless said. “Let’s all agree we will do everything in our power to minimize these adverse effects, to protect our patients from cancer suffering.”

UPDATED: 10/11/2021

Patients with Cancer Appear More Vulnerable to SARS-CoV-2: A Multicenter Study during the COVID-19 Outbreak

Source:

Mengyuan DaiDianbo LiuMiao LiuFuxiang ZhouGuiling LiZhen ChenZhian ZhangHua YouMeng WuQichao ZhengYong XiongHuihua XiongChun WangChangchun ChenFei XiongYan ZhangYaqin PengSiping GeBo ZhenTingting YuLing WangHua WangYu LiuYeshan ChenJunhua MeiXiaojia GaoZhuyan LiLijuan GanCan HeZhen LiYuying ShiYuwen QiJing YangDaniel G. TenenLi ChaiLorelei A. MucciMauricio Santillana and Hongbing Cai. Patients with Cancer Appear More Vulnerable to SARS-CoV-2: A Multicenter Study during the COVID-19 Outbreak

Abstract

The novel COVID-19 outbreak has affected more than 200 countries and territories as of March 2020. Given that patients with cancer are generally more vulnerable to infections, systematic analysis of diverse cohorts of patients with cancer affected by COVID-19 is needed. We performed a multicenter study including 105 patients with cancer and 536 age-matched noncancer patients confirmed with COVID-19. Our results showed COVID-19 patients with cancer had higher risks in all severe outcomes. Patients with hematologic cancer, lung cancer, or with metastatic cancer (stage IV) had the highest frequency of severe events. Patients with nonmetastatic cancer experienced similar frequencies of severe conditions to those observed in patients without cancer. Patients who received surgery had higher risks of having severe events, whereas patients who underwent only radiotherapy did not demonstrate significant differences in severe events when compared with patients without cancer. These findings indicate that patients with cancer appear more vulnerable to SARS-CoV-2 outbreak.

Significance: Because this is the first large cohort study on this topic, our report will provide much-needed information that will benefit patients with cancer globally. As such, we believe it is extremely important that our study be disseminated widely to alert clinicians and patients.

Introduction

A new acute respiratory syndrome coronavirus, named SARS-CoV-2 by the World Health Organization (WHO), has rapidly spread around the world since its first reported case in late December 2019 from Wuhan, China (1). As of March 2020, this virus has affected more than 200 countries and territories, infecting more than 800,000 individuals and causing more than 40,000 deaths (2).

With more than 18 million new cases per year globally, cancer affects a significant portion of the population. Individuals affected by cancer are more susceptible to infections due to coexisting chronic diseases, overall poor health status, and systemic immunosuppressive states caused by both cancer and anticancer treatments (3). As a consequence, patients with cancer who are infected by the SARS-CoV-2 coronavirus may experience more difficult outcomes than other populations. Until now, there is still no systematic evaluation of the effects that the SARS-CoV-2 coronavirus has of patients with cancer in a representative population. A recent study reported a higher risk of severe events in patients with cancer when compared with patients without cancer (4); however, the small sample size of SARS-CoV-2 patients with cancer used in the study limited how representative it was of the whole population and made it difficult to conduct more insightful analyses, such as comparing clinical characteristics of patients with different types of cancer, as well as anticancer treatments (5, 6).

Using patient information collected from 14 hospitals in Hubei Province, China, the epicenter of the 2019–2020 COVID-19 outbreak, we describe the clinical characteristics and outcomes [death, intensive care unit (ICU) admission, development of severe/critical symptoms, and utilization of invasive mechanical ventilation] of patients affected by the SARS-CoV-2 coronavirus for 105 hospitalized patients with cancer and 536 patients without cancer. We document our findings for different cancer types and stages, as well as different types of cancer treatments. We believe the information and insights provided in this study will help improve our understanding of the effects of SARS-CoV-2 in patients with cancer.

Results

Patients Characteristics

In total, 105 COVID-19 patients with cancer were enrolled in our study for the time period January 1, 2020, to February 24, 2020, from 14 hospitals in Wuhan, China. COVID-19 patients without cancer matched by the same hospital, hospitalization time, and age were randomly selected as our control group. Our patient population included 339 females and 302 males. Patients with cancer [median = 64.00, interquartile range (IQR) = 14.00], when compared with those without cancer (median = 63.50, IQR = 14.00) had similar age distributions (by design), experienced more in-hospital infections [20 (19.04%) of 105 patients vs. 8 (1.49%) of 536 patients;P < 0.01], and had more smoking history [36 (34.28%) of 105 patients vs. 46 (8.58%) of 536 patients; P < 0.01], but had no significant differences in sex, other baseline symptoms, and other comorbidities (Table 1). With respect to signs and symptoms upon admission, COVID-19 patients with cancer were similar to those without cancer except for a higher prevalence of chest distress [15 (14.29%) of 105 patients vs. 36 (6.16%) of 536 patients; P = 0.02].

Table 1.

Characteristics of COVID-19 patients with and without cancer

Clinical Outcomes

Compared with COVID-19 patients without cancer, patients with cancer had higher observed death rates [OR, 2.34; 95% confidence interval (CI), (1.15–4.77); P = 0.03], higher rates of ICU admission [OR, 2.84; 95% CI (1.59–5.08); P < 0.01], higher rates of having at least one severe or critical symptom [OR, 2.79; 95% CI, (1.74–4.41); P < 0.01], and higher chances of needing invasive mechanical ventilation (Fig. 1A). We also conducted survival analysis on occurrence of any severe condition which included death, ICU admission, having severe symptoms, and utilization of invasive mechanical ventilation (see cumulative incidence curves in Fig. 1B). In general, patients with cancer deteriorated more rapidly than those without cancer. These observations are consistent with logistic regression results (Supplementary Fig. S1), after adjusting for age, sex, smoking, and comorbidities including diabetes, hypertension, and chronic obstructive pulmonary disease (COPD). According to our multivariate logistic regression results, patients with cancer still had an excess OR of 2.17 (P = 0.06) for death (Supplementary Fig. S1A), 1.99 (P < 0.01) for experiencing any severe symptoms (Supplementary Fig. S1B), 3.13 (P < 0.01) for ICU admission (Supplementary Fig. S1C), and 2.71 (P = 0.04) for utilization of invasive mechanical ventilation (Supplementary Fig. S1D; Supplementary Table S1). The consistency of observed ORs between the multivariate regression model and unadjusted calculation reassures the association between cancer and severe events even in the presence of other factors such as age differences.

Figure 1.

Severe conditions in patients with and without cancer, and patients with different types, stages, and treatments of cancer. Severe conditions include death, ICU admission, having severe/critical symptoms, and usage of invasive mechanical ventilation. Incidence and survival analysis of severe conditions among COVID-19 patients with cancer and without cancer (A and B), among patients with different types of cancer (C and D), among patients with metastatic and nonmetastatic cancers (E and F), among patients with lung cancer, other cancers than lung with lung metastasis, and other cancers than lung without lung metastasis (G and H), and patients receiving different types of cancer treatments (I and J). P values indicate differences between cancer subgroups versus patients without cancer. For ACEGI, *, P < 0.05; **, P < 0.01. OR, 95% CI, and P values between different subgroups are listed in Supplementary Table S2. For BDFHJ, HR, 95% CI, and P values are listed in Supplementary Table S3.

Cancer Types

Information regarding potential risks of severe conditions in SARS-CoV-2 associated with each type of cancer was calculated. We compared different conditions among cancer types (Table 2). Lung cancer was the most frequent cancer type [22 (20.95%) of 105 patients], followed by gastrointestinal cancer [13 (12.38%) of 105 patients], breast cancer [11 (10.48%) of 105 patients], thyroid cancer [11 (10.48%) of 105 patients], and hematologic cancer [9 (8.57%) of 105 patients]. As shown in Fig. 1C and D and Supplementary Table S2, patients with hematologic cancer including leukemia, lymphoma, and myeloma have a relatively high death rate [3 (33.33%) of 9 patients], high ICU admission rate [4 (44.44%) of 9 patients], high risks of severe/critical symptoms [6 (66.67%) of 9 patients], and high chance of utilization of invasive mechanical ventilation [2 (22.22%) of 9 patients]. Patients with lung cancer had the second-highest risk levels, with death rate [4 (18.18%) of 22 patients], ICU admission rate [6 (27.27%) of 22 patients], risks of severe/critical symptoms [11 (50.00%) of 22 patients], and the chance of utilization of invasive mechanical ventilation [4 (18.18%) of 22 patients; Table 2].

Table 2.

Severe events in 105 patients with cancer for each type of cancer

Cancer Stage

We found that patients with metastatic cancer (stage IV) had even higher risks of death [OR, 5.58; 95% CI (1.71–18.23); P = 0.01], ICU admission [OR, 6.59; 95% CI (2.32–18.72); P < 0.01], having severe conditions [OR, 5.97; 95% CI (2.24–15.91); P < 0.01], and use of invasive mechanical ventilation [OR, 55.42; 95% CI (13.21–232.47); P < 0.01]. In contrast, patients with nonmetastatic cancer did not demonstrate statistically significant differences compared with patients without cancer, with all P > 0.05 (Fig. 1E and F; Supplementary Tables S2 and S3). In addition, when compared with patients without cancer, patients with lung cancer or other cancers with lung metastasis also showed higher risks of death, ICU admission rates, higher critical symptoms, and use of invasive mechanical ventilation, with all P values below 0.01, but other cancers without lung metastasis had no statistically significant differences (all P values > 0.05; Fig. 1G and H; Supplementary Table S3) when compared with patients without cancer.

Cancer Treatments

Among the 105 COVID-19 patients with cancer in our study, 13 (12.26%) had radiotherapy, 17 (14.15%) received chemotherapy, 8 (7.62%) received surgery, 4 (3.81%) had targeted therapy, and 6 (5.71%) had immunotherapy within 40 days before the onset of COVID-19 symptoms. All of the targeted therapeutic drugs were EGFR–tyrosine kinase inhibitors for treatment of lung cancer, and all of the immunotherapy drugs were PD-1 inhibitors for the treatment of lung cancer. A patient with cancer may have more than one type of therapy. Our observation suggested that patients who received immunotherapy tended to have high rates of death [2 (33.33%) of 6 patients] and high chances of developing critical symptoms [4 (66.67%) of 6 patients]. Patients who received surgery demonstrated higher rates of death [2 (25.00%) of 8 patients], higher chances of ICU admission [3 (37.50%) of 8 patients], higher chances of having severe or critical symptoms [5 (62.50%) of 8 patients], and higher use of invasive ventilation [2 (25.00%) of 8 patients] than other treatments excluding immunotherapy. However, patients with cancer who received radiotherapy did not show statistically significant differences in having any severe events when compared with patients without cancer, with all P values > 0.10 (Fig. 1I and J). Clinical details on the cancer diagnoses and cancer treatments are summarized in Supplementary Table S4.

Timeline of Severe Events

To evaluate the time-dependent evolution of the disease, we conducted the timeline of different events for COVID-19 patients with cancer (Fig. 2A) and COVID-19 patients without cancer (Fig. 2B) with death and other severe events marked in the figure. COVID-19 patients with cancer had a mean length of stay of 27.01 days (SD 9.52) and patients without cancer had a mean length of stay of 17.75 days (SD 8.64); the difference is significant (Wilcoxon test, P < 0.01). To better clarify the contributing factors that might influence outcomes, we also included logistic regression of COVID-19 patients with cancer adjusted by immunosuppression levels in Supplementary Table S5. However, no significant association between immunosuppression and severe outcomes was observed from the analysis (with all P > 0.05).

Figure 2.

Timeline of events for COVID-19 patients. A, Timeline of events in COVID-19 patients with cancer. B, Timeline of events in COVID-19 patients without cancer. For visualization purposes, patients without timeline information are excluded and only 105 COVID-19 patients without cancer are shown.

Discussion

The findings in this study suggest that patients with cancer infected with SARS-CoV-2 tend to have more severe outcomes when compared with patients without cancer. Patients with hematologic cancer, lung cancer, and cancers in metastatic stages demonstrated higher rates of severe events compared with patients without cancer. In addition, patients who underwent cancer surgery showed higher death rates and higher chances of having critical symptoms.

The SARS-CoV-2 virus has spread rapidly globally; thus, many countries have not been ready to handle the large volume of people affected by this outbreak due to a lack of knowledge about how this coronavirus affects the general population. To date, reports on the general population infected with SARS-CoV-2 suggest elderly males have a higher incidence and death rate (7, 8). Limited information is known about the outcome of patients with cancer who contract this highly communicable disease. Cancer is among the top causes of death. Asia, Europe, and North America have the highest incidence of cancer in the world (9), and at the moment of the writing of this study the SARS-CoV-2 virus is mainly spreading in these three areas (referred from https://www.cdc.gov/media/releases/2020/s0226-Covid-19-spread.htmlhttps://www.nytimes.com/2020/02/27/world/coronavirusnews.html). Although COVID-19 patients with cancer may share some epidemiologic features with the general population with this disease, they may also have additional clinical characteristics. Therefore, we conducted this study on patients with cancer with coexisting COVID-19 disease to evaluate the potential effect of COVID-19 on patients with cancer.

On the basis of our analysis, COVID-19 patients with cancer tend to have more severe outcomes when compared with the noncancer population. Although COVID-19 is reported to have a relatively low death rate of 2% to 3% in the general population (10), patients with cancer and COVID-19 not only have a nearly 3-fold increase in the death rate than that of COVID-19 patients without cancer, but also tend to have much higher severity of their illness. Altogether, these findings suggest that patients with cancer are a much more vulnerable population in the current COVID-19 outbreak. Our findings are consistent with those presented in a previous study based on 18 patients with cancer (4). Because of the limited number of patients with cancer in the previous study, the authors concluded that among patients with cancer, age is the only risk factor for the severity of the illness. On the basis of our data on 105 patients with cancer, we have discovered additional risk factors, including cancer types, cancer stage, and cancer treatments, which may contribute to the severity of the disease among patients with cancer.

Our data demonstrate that the severity of SARS-CoV-2 infection in patients is significantly affected by the types of tumors. From our analysis, patients with hematologic cancer have the highest severity and death rates among all patients with cancer, and lung cancer follows second. Patients with hematologic cancer in our study include patients with leukemia, myeloma, and lymphoma, who have a more compromised immune system than patients with solid tumors (11). These patients all had a rapidly deteriorating clinical course once infected with COVID-19. Because malignant or dysfunctional plasma cells, lymphocytes, or white blood cells in general in hematologic malignancies have decreased immunologic function (12–14), this could be the main reason why patients with hematologic cancer have very high severity and death rates. All patients with hematologic cancer are prone to the complications of serious infection (12–14), which can exacerbate the condition which could have worsened in patients with COVID-19. In our study, 55.56% of patients with hematologic cancer had severe immunosuppression, which may be the main reason for deteriorated outcomes. Although the small sample size limits representativity of the observation, we believe our finding can serve as an informative starting point for further investigation when a larger cohort from a wide range of healthcare providers becomes available. Among solid tumors, lung cancer is the highest risk category disease in patients with SARS-CoV-2 infection (Fig. 1C). Decreased lung function and severe infection in patients with lung cancer could contribute to the worse outcome in this subpopulation (15, 16).

In our analysis, we classified the SARS-CoV-2 infection–related high risk factors based on death, severe or critical illness, ICU admission, and the utilization of invasive mechanical ventilation. Using these parameters, we detected a multi-fold increase in risk in the cancer population, in contrast to the noncancer population. If there were primary or metastatic tumors in the lungs, patients were more prone to a deteriorated course in a short time. Intriguingly, when patients with cancer had only early-stage disease without metastasis, we did not observe any difference between the cancer and noncancer population in terms of COVID-19–related death rate or severity (Fig. 1E). The stage of cancer diagnosis seemed to play a significant role in the severity and death rate of COVID-19.

Patients with cancer received a wide range of treatments, and we also found that different types of treatments had different influences on severity and death when these patients contracted COVID-19. Recently, immunotherapy has assumed a very important role in treating tumors, which aids in treatment of cancer by blocking the immune escape of cancer cells. But in our study, in contrast to patients with cancer with other treatments, patients with immunotherapy had the highest death rate and the highest severity of illness, a very puzzling finding. According to pathologic studies on the patients with COVID-19, there were desquamation of pneumocytes and hyaline membrane formation, implying that these patients had acute respiratory distress syndrome (ARDS; ref. 17). ARDS induced by cytokine storm is reported to be the main reason for death of SARS-CoV-2–infected patients (18). It is possible that in this setting, immunotherapy induces the release of a large amount of cytokines, which can be toxic to normal cells, including lung epithelial cells (19–21), and therefore lead to a more severe illness. However, in this study the number of patients with immunotherapy was too small; further research with a large case population needs to be conducted in the future.

In addition, COVID-19 patients with cancer who are under active treatment or not under active treatment do not show differences in their outcomes, and there is a significant difference between COVID-19 patients with cancer but not with active treatment and patients without cancer (Supplementary Table S2). These results indicate that COVID-19 patients with both active treatment and just cancer history have a higher risk of developing severe events than noncancer COVID-19 patients. The possible reasons could be due to some known cancer-related complications, for example, anemia, hypoproteinaemia, or dyspnea in early phase of COVID-19 (22). We considered that cancer had a lifetime effect on patients and that cancer survivors always need routine follow-up after primary resection. Therefore, in clinical COVID-19 patient management, equivalent attention needs to be paid to those with cancer whether they are under active therapeutics or not during the outbreak of COVID-19.

This study has several limitations. Although the cohort of COVID-19 patients with cancer is one of the largest in Hubei province, China, the epicenter of the initial outbreak, a larger cohort from the whole country or even from multiple countries will be more representative. Large-scale national and international research collaboration will be necessary to achieve this. At the initial stage of the outbreak, data collection and research activities were not a priority of the hospitals. Therefore, it was not possible to record and collect some data that are potentially informative for our analysis in a timely manner. In addition, due to the urgency of clinical treatment, medical data used in this study were largely disconnected from the patients’ historical electronic medical records, which are mostly stored with a different healthcare provider than the medical center providing COVID-19 care. This left us with limited information about each patient.

Our study is the midsize cohort study on this topic and will provide much-needed information on risk factors of this population. We hope that our findings will help countries better protect patients with cancer affected by the ongoing COVID-19 pandemic.

Methods

Study Design and Patients

We conducted a multicenter study focusing on the clinical characteristics of confirmed cases of COVID-19 patients with cancer in 14 hospitals in Hubei province, China; all of the 14 hospitals served as government-designated hospitals for patients diagnosed with COVID-19. SARS-CoV-2–infected patients without cancer matched by the same hospital and hospitalization time were randomly selected as our control group. In addition, as age is one of the major predictors of severity of respiratory diseases like COVID-19 (4), we excluded from our analysis 117 younger COVID-19 patients without cancer so that median ages of patients with cancer (median = 64.0, IRQ = 14.00) and patients without cancers (median = 63.5, IQR = 14.00) would be comparable.

End Points and Assessments

There were four primary outcomes analyzed in this study: death, admission into the ICU, development of severe or critical symptoms, and utilization of invasive mechanical ventilation. The clinical definition of severe/critical symptoms follows the 5th edition of the 2019Novel Coronavirus Disease (COVID-19) Diagnostic Criteria published by the National Health Commission in China, including septic shock, ARDS, acute kidney injury, disseminated intravascular coagulation, and rhabdomyolysis.

Case Fatality Rate of Cancer Patients with COVID-19 in a New York Hospital System

Source:

Vikas MehtaSanjay GoelRafi KabarritiDaniel ColeMendel GoldfingerAna Acuna-VillaordunaKith PradhanRaja ThotaStan ReissmanJoseph A. SparanoBenjamin A. GartrellRichard V. SmithNitin OhriMadhur GargAndrew D. RacineShalom KalnickiRoman Perez-SolerBalazs Halmos and Amit Verma. Case Fatality Rate of Cancer Patients with COVID-19 in a New York Hospital System

Abstract

Patients with cancer are presumed to be at increased risk from COVID-19 infection–related fatality due to underlying malignancy, treatment-related immunosuppression, or increased comorbidities. A total of 218 COVID-19–positive patients from March 18, 2020, to April 8, 2020, with a malignant diagnosis were identified. A total of 61 (28%) patients with cancer died from COVID-19 with a case fatality rate (CFR) of 37% (20/54) for hematologic malignancies and 25% (41/164) for solid malignancies. Six of 11 (55%) patients with lung cancer died from COVID-19 disease. Increased mortality was significantly associated with older age, multiple comorbidities, need for ICU support, and elevated levels of D-dimer, lactate dehydrogenase, and lactate in multivariate analysis. Age-adjusted CFRs in patients with cancer compared with noncancer patients at our institution and New York City reported a significant increase in case fatality for patients with cancer. These data suggest the need for proactive strategies to reduce likelihood of infection and improve early identification in this vulnerable patient population.

Significance: COVID-19 in patients with cancer is associated with a significantly increased risk of case fatality, suggesting the need for proactive strategies to reduce likelihood of infection and improve early identification in this vulnerable patient population.

Introduction

The novel coronavirus COVID-19, or severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has spread rapidly throughout the world since its emergence in December 2019 (1). The virus has infected approximately 2.9 million people in more than 200 countries with more than 200,000 deaths at the time of writing (2). Most recently, the United States has become the epicenter of this pandemic, reporting an estimated 956,000 cases of COVID-19 infection, with the largest concentration in New York City (NYC) and its surrounding areas (approximately >203,000 cases or 35% of all U.S. infections; ref. 3).

Early data suggests that 14% to 19% of infected patients will develop significant sequelae with acute respiratory distress syndrome, septic shock, and/or multiorgan failure (1, 4, 5), and approximately 1% to 4% will die from the disease (2). Recent meta-analyses have demonstrated an almost 6-fold increase in the odds of mortality for patients with chronic obstructive pulmonary disease (COPD) and a 2.5-fold increase for those with diabetes, possibly due to the underlying pulmonary and immune dysfunction (6, 7). Given these findings, patients with cancer would ostensibly be at a higher risk of developing and succumbing to COVID-19 due to immunosuppression, increased coexisting medical conditions, and, in cases of lung malignancy, underlying pulmonary compromise. Patients with hematologic cancer, or those who are receiving active chemotherapy or immunotherapy, may be particularly susceptible because of increased immunosuppression and/or dysfunction.

According the NCI, there were approximately 15.5 million cancer survivors and an estimated 1,762,450 new cases of cancer diagnosed in the United States in 2019 (8). Early case series from China and Italy have suggested that patients with malignancy are more susceptible to severe infection and mortality from COVID-19 (9–12), a phenomenon that has been noted in other pandemics (13). Many of these descriptive studies have included small patient cohorts and have lacked cancer site–specific mortality data or information regarding active cancer treatment. As New York has emerged as the current epicenter of the pandemic, we sought to investigate the risk posed by COVID-19 to our cancer population with more granular data regarding cancer type and active treatment, and identify factors that placed patients with cancer at highest risk of fatality from COVID-19.

Results

Outcomes of 218 Cancer Patients with COVID-19 Show High Overall Mortality with Tumor-Specific Patterns

A total of 218 patients with cancer and COVID-19 were treated in Montefiore Health System (New York, NY) from March 18, 2020, to April 8, 2020. These included 164 (75%) patients with solid tumors and 54 (25%) with hematologic malignancies. This cohort included 127 (58%) males and 91 (42%) females. The cohort was predominantly composed of adult patients (215/218, 98.6%) with a median age of 69 years (range 10–92 years).

Sixty-one (28%) patients expired as a result of COVID-19disease at the time of analysis (Table 1). The mortality was 25% among all patients with solid tumors and was seen to occur at higher rates in patients with lung cancers (55%), gastrointestinal (GI) cancers [colorectal (38%), pancreatic (67%), upper GI (38%)], and gynecologic malignancies (38%). Genitourinary (15%) and breast (14%) cancers were associated with relatively lower mortality with COVID-19 infection.

Table 1.

Outcomes in patients with cancer and COVID-19

Hematologic malignancies were associated with higher rate of mortality with COVID-19 (37%). Myeloid malignancies [myelodysplastic syndromes (MDS)/acute myeloid leukemia (AML)/myeloproliferative neoplasm (MPN)] showed a trend for higher mortality compared with lymphoid neoplasms [non-Hodgkin lymphoma (NHL)/chronic lymphoid leukemia (CLL)/acute lymphoblastic leukemia (ALL)/multiple myeloma (MM)/Hodgkin lymphoma; Table 1]. Rates of ICU admission and ventilator use were slightly higher for hematologic malignancies than solid tumors (26% vs. 19% and 11% vs. 10%, respectively), but this did not achieve statistical significance.

Disease Characteristics of Cancer Patients with COVID-19 Demonstrate the Effect of Age, Comorbidities, and Laboratory Biomarkers on Mortality

Analysis of patient characteristics with mortality did not show any gender bias (Table 2). Older age was significantly associated with increased mortality, with median age of deceased cohort at 76 years when compared with 66 years for the nondeceased group (P = 0.0006; Cochran-Armitage test). No significant associations between race and mortality were seen.

Table 2.

Disease characteristics of patients with cancer with COVID-19 and association with mortality

COVID-19 disease severity, as evident from patients who needed ICU care and ventilator support, was significantly associated with increased mortality. Interestingly, active disease (<1 year) and advanced metastatic disease showed a trend for increased mortality, but the association did not achieve statistical significance (P = 0.09 and 0.06, respectively). Active chemotherapy and radiotherapy treatment were not associated with increased case fatality. Very few patients in this cohort were on immunotherapy, and this did not show any associations with mortality.

Analysis of comorbidities demonstrated increased risk of dying from COVID-19 in patients with cancer with concomitant heart disease [hypertension (HTN), coronary artery disease (CAD), and congestive heart failure (CHF)] and chronic lung disease (Table 2). Diabetes and chronic kidney disease were not associated with increased mortality in univariate analysis (Table 2).

We also analyzed laboratory values obtained prior to diagnosis of COVID-19 and during the time of nadir after COVID-19 positivity in our cancer cohort. Relative anemia pre–COVID-19 was associated with increased mortality, whereas pre-COVID platelet and lymphocyte counts were not (Table 3).Post–COVID-19 infection, lower hemoglobin levels, higher total white blood cell (WBC) counts, and higher absolute neutrophil counts were associated with increased mortality (Table 3). Analysis of other serologic biomarkers demonstrated that elevated D-dimer, lactate, and lactate dehydrogenase (LDH) in patients were significantly correlated with dying (Table 3).

Table 3.

Laboratory values of cancer patients with COVID-19 and association with mortality

Next, we conducted multivariate analyses and used variables that showed a significant association with mortality in univariate analysis (P < 0.05 in univariate was seen with age, ICU admission, hypertension, chronic lung disease, CAD, CHF, baseline hemoglobin, nadir hemoglobin, WBC counts, D-dimer, lactate, and LDH). Gender was forced in the model and we used a composite score of comorbidities from the sum of indicators for diabetes mellitus (DM), HTN, chronic lung disease, chronic kidney disease, CAD, and CHF capped at a maximum of 3. In the multivariate model (Supplementary Table S1), we observed that older age [age < 65; OR, 0.23; 95% confidence interval (CI), 0.07–0.6], higher composite comorbidity score (OR, 1.52; 95% CI, 1.02–2.33), ICU admission (OR, 4.83; 95% CI, 1.46–17.15), and elevated inflammatory markers (D-dimer, lactate, and LDH) were significantly associated with mortality after multivariate comparison in patients with cancer and COVID-19.

Interaction with the Healthcare Environment was a Prominent Source of Exposure for Patients with Cancer

A detailed analysis of deceased patients (N = 61; Supplementary Table S2) demonstrated that many were either nursing-home or shelter (n = 22) residents, and/or admitted as an inpatient or presented to the emergency room within the 30 days prior to their COVID-19 positive test (21/61). Altogether, 37/61 (61%) of the deceased cohort were exposed to the healthcare environment at the outset of the COVID-19 epidemic. Few of the patients in the cohort were on active oncologic therapy. The vast majority had a poor Eastern Cooperative Oncology Group performance status (ECOG PS; 51/61 with an ECOG PS of 2 or higher) and carried multiple comorbidities.

Patients with Cancer Demonstrate a Markedly Increased COVID-19 Mortality Rate Compared with Noncancer and All NYC COVID-19 Patients

An age- and sex-matched cohort of 1,090 patients at a 5:1 ratio of noncancer to cancer COVID-19 patients from the same time period and from the same hospital system was also obtained after propensity matching and used as control to estimate the increased risk posed to our cancer population (Table 4). We observed case fatality rates (CFR) were elevated in all age cohorts in patients with cancer and achieved statistical significance in the age groups 45–64 and in patients older than 75 years of age.

Table 4.

Comparison of cancer and COVID-19 mortality with all NYC cases (official NYC numbers up to 5 p.m., April 12, 2020) and a control group from the same healthcare facility

To also compare our CFRs with a larger dataset from the greater NYC region, we obtained official case numbers from New York State (current up to April 12, 2020; ref. 3). In all cohorts, the percentage of deceased patients was found to rise sharply with increasing age (Table 4). Strikingly, CFRs in cancer patients with COVID-19 were significantly, many-fold higher in all age groups when compared with all NYC cases (Table 4).

Discussion

To our knowledge, this is the first large report of COVID-19 CFRs among patients with cancer in the United States. The overall case fatality among COVID-19–infected patients with cancer in an academic center located within the current epicenter of the global pandemic exceeded 25%. In addition, striking tumor-specific discrepancies were seen, with marked increased susceptibility for those with hematologic malignancies and lung cancer. CFRs were 2 to 3 times the age-specific percentages seen in our noncancer population and the greater NYC area for all COVID-19 patients.

Our results seem to mirror the typical prognosis of the various cancer types. Among the most common malignancies within the U.S. population (lung, breast, prostate, and colorectal), there was 55% mortality among patients with lung cancer, 14% for breast cancer, 20% for prostate cancer, and 38% for colorectal cancer. This pattern reflects the overall known lethality of these cancers. The percent annual mortality (ratio of annual deaths/new diagnosis) is 59.3% for lung cancer, 15.2% for breast cancer, 17.4% for prostate cancer, and 36% for colorectal cancer (8). This suggests that COVID-19 infection amplifies the risk of death regardless of the cancer type.

Patients with hematologic malignancies demonstrate a higher mortality than those with solid tumors. These patients tend to be treated with more myelosuppressive therapy, and are often severely immunocompromised because of underlying disease. There is accumulating evidence that one major mechanism of injury may be a cytokine-storm syndrome secondary to hyperinflammation, which results in pulmonary damage. Patients with hematologic malignancy may potentially be more susceptible to cytokine-mediated inflammation due to perturbations in myeloid and lymphocyte cell compartments (14).

Many of the predictive risk factors for mortality in our cancer cohort were similar to published data among all COVID-19 patients. A recent meta-analysis highlighted the association of chronic diseases including hypertension (OR, 2.29), diabetes (OR, 2.47), COPD (OR, 5.97), cardiovascular disease (OR, 2.93), and cerebrovascular disease (OR, 3.89) with a risk for developing severe COVID-19 infection among all patients (15). In our cancer patient dataset, a large proportion of patients had at least one of these concurrent risk factors. In a univariate model, we observed significant associations of death from COVID-19 infection in patients with hypertension, chronic lung disease, coronary heart disease, and congestive heart failure. Serologic predictors in our dataset predictive for mortality included anemia at time of infection, and elevated LDH, D-dimer, and lactic acid, which correlate with available data from all COVID-19 patients.

Rapidly accumulating reports suggest that age and race may play a role in the severity of COVID-19 infection. In our cancer cohort, the median age of the patients succumbing to COVID-19 was 76 years, which was 10 years older than patients who have remained alive. The CDC has reported a disproportionate number of African Americans are affected by COVID-19 in the United States, accounting for 33% of all hospitalized patients while constituting only 13% of the U.S. population (15). However, the racial breakdown of our patients was proportional to the Bronx population as a whole, and race was not a significant predictor of mortality in our univariate or multivariate models. Our data might argue that the increased mortality noted in the larger NYC populations might also likely be driven by socioeconomic and health disparities in addition to underlying biological factors. Overall mortality with COVID-19 has been higher in the Bronx, which is a socioeconomically disadvantaged community with a mean per capita income of $19,721 (16, 17). Our patients with cancer were predominantly from the Bronx and potentially had increased mortality in part due to socioeconomic factors and comorbidities. Even after accounting for the increased mortality seen in COVID-19 in the Bronx, the many-fold magnitude increase in death rates within our cancer cohort can potentially be attributed to the vulnerability of oncology patients. This was evident in the comparison with a control group from the same hospital system that demonstrated a significant association of cancer with mortality in patients between 45 and 64 years of age and older than 75 years of age.

Interaction with the healthcare environment prior to widespread knowledge of the epidemic within NYC was a prominent source of exposure for our patients with cancer. Many of those who succumbed to COVID-19 infection were older and frail with significant impairment of pulmonary and/or immunologic function. These findings could be utilized to risk-stratify patients with cancer during this pandemic, or in future viral airborne outbreaks, and inform mitigation practices for high-risk individuals. These strategies could include early and aggressive social distancing, resource allocation toward more outpatient-based care and telemedicine, testing of asymptomatic high-risk patients, and institution of strict infection-control measures. Indeed, such strategies were implemented early in the pandemic at our center, possibly explaining the relatively low number of infected patients on active therapy.

There were several limitations to our study. Data regarding do not resuscitate or intubate orders were not included in the analysis and could have significantly affected the decision-making and mortality surrounding these patients. Although an attempt was made to control for those receiving active cancer treatment or with additional comorbidities, we could not fully account for the patients’ preexisting health conditions prior to COVID-19 infection. Differential treatment paradigms for COVID-19 infection and sequelae were not controlled for in our analysis. Because of the limited follow-up, the full clinical course of these patients may not be included. Future comparative studies to noncancer patients will be needed to fully ascertain the risk posed to oncology patients. Finally, though our data does include those who were tested and discharged within our health system, we cannot fully account for those who were tested in nonaffiliated outpatient settings, which may potentially bias our study to more severe cases. We also acknowledge that the mortality rate is highly dependent on the breadth of testing, and therefore understand that more widespread detection of viral infection would likely alter the results.

Our data suggest significant risk posed to patients with cancer infected with COVID-19, with an observed significant increase in mortality. The highest susceptibility appears to be in hematologic or lung malignancies, suggesting that proactive strategies to reduce likelihood of infection and improve early identification of COVID-19 positivity in the cancer patient population are clearly warranted. Overall, we hope and expect that our data from the current epicenter of the COVID-19 epidemic will help inform other healthcare systems, patients with cancer, and the public about the particular vulnerability of patients with cancer to this disease.

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