Feeds:
Posts
Comments

Posts Tagged ‘COVID-19’

Novel SARS-CoV-2 sybodies

Reporter: Irina Robu, PhD

Absolute Antibody Ltd., a leader of the market in recombinant antibody products announced a partnership with University of Zurich to offer synthetic nanobodies against the receptor binding domain (RBD) of SARS-CoV-2. Under the partnership, the original nanobodies and recently engineered formats are now accessible to the global research community for use as serological controls and in COVID-19 therapeutic development. The synthetic nanobodies hold a particular potential for the development of inhalable drugs, which could suggest a convenient treatment option for the COVID-19 pandemic.

The laboratory of Markus Seeger at University of Zurich designs a rapid in vitro selection platform to generate synthetic nanobodies, sybodies, against the receptor binding domain (RBD) of SARS-CoV-2. Within a two-week timeframe, the lab had recognized more than 60 unique anti-RBD sybodies from combinatorial display libraries. The sybodies are “designed to mimic the natural shape diversity of camelid nanobodies, consequently allowing for an optimal surface complementarity to the limited hydrophilic epitopes on membrane proteins. Due to their high thermal stabilities and low production costs, sybodies demonstrate a promise for diagnostic and therapeutic applications.

Sybodies are perfectly suited to trap intrinsically flexible membrane proteins and thereby facilitate structure determination by X-ray crystallography and cryo-EM. Additional research indicate that six of the sybodies bound SARS-CoV-2 spike protein with very high affinity, while five of those also inhibited ACE2, the host cell receptor to which SARS-CoV-2 binds to initiate the COVID-19 infection. Furthermore, two of the sybodies can at the same time bind the RBD, which could permit the construction of a polyvalent antiviral drug. The SARS-CoV-2 sybodies are therefore valuable tools for coronavirus research, diagnostics and therapeutic development.

Moreover, Absolute Antibody has used antibody engineering to fuse the nanobodies to Fc domains in different species, isotypes and subtypes. Absolute Antibody also offers supporting coronavirus research such as the production of gram quantities of human antibodies sequenced from recovering COVID-19 patients.

SOURCE

https://www.biocompare.com/Life-Science-News/562900-SARS-CoV-2-COVID-19-Research-News-Latest-Updates

 

Read Full Post »

Three Stages to COVID-19 Brain Damage

Reporter: Irina Robu, PhD

According to a review published by Majid Fotuhi, PhD in the Journal of Alzheimer’s Disease, the impact of COVID-19 on the nervous system can be classified in three stages. In stage 1, viral damage is limited to the epithelial cells of the nose and mouth; stage 2, blood clots that form in the lungs can travel to the brain and in stage 3, the virus crosses the blood brain barrier and invades the brain.

Dr. Fotuhi recognized that patients with COVID-19 should have a neurological evaluation and an MRI before leaving the hospital, to distinguish if there are any anomalies. It has become increasingly obvious that SARS-CoV-2 can cause neurologic manifestations, including anosmia, seizures, stroke, confusion, encephalopathy, and total paralysis, the authors write. As stated by authors of the review, the SARS-CoV-2 binds to angiotensin-converting enzyme 2 (ACE2) that facilitates the conversion of angiotensin II to angiotensin. Subsequently ACE2 binds to respiratory epithelial cells, and then to epithelial cells in blood vessels, SARS-CoV-2 triggers the formation of a “cytokine storm.” The cytokines, increase vascular permeability, edema and widespread inflammation which can cause small or large blood clots that affect multiple organs.

They concluded, that If SARS-CoV-2 crosses the blood–brain barrier, directly entering the brain, it can contribute to demyelination or neurodegeneration. Scientists have limited information published about it, so doctors/scientists are uncertain why a virus this small can cause so many neurological things.

SOURCE

https://www.medscape.com/viewarticle/933131

Read Full Post »

Does CSF Antibody Testing Confirm Coronavirus in the Brain?

Reporter: Irina Robu, PhD

It is still uncertain how COVID-19 invades the brain, but testing for antibodies in the cerebrospinal fluid may give some indication.  COVID-19 is typic Is characterized by respiratory illness and viral pneumonia with fever, cough, shortness of breath, and in severe cases, progression to acute respiratory distress syndrome. Recently, there have been a few investigations on what neurological complications can COVID-19 produce.

A case series of three patients attending an inner-city US hospital who had severe, laboratory-confirmed COVID-19 and encephalitis indicated that while only one had abnormal white blood cells or protein present in cerebral spinal fluid, all had evidence of immunoglobulin (IgM) antibodies. The cases include a 31-year-old woman with sickle cell disease who had a recent pulmonary embolus, a 34-year-old woman with sign of fever, shortness of breath and hypertension and a 64-year-old with hypertension. Dr. Benameur, from Emory University assessed cerebrospinal fluid inflammatory proteins and completed testing for SARS-CoV-2 using reverse transcription polymerase chain reaction (PCR).

The results show that two of the patients had normal white blood cell counts and protein levels. Yet, according to Dr. Benameur, even though the PCR in cerebral spinal fluid is negative, it doesn’t mean that the virus didn’t make it into the brain. The PCR test is good for some viruses, but it is not as reliable for this new coronavirus. Even though, all patients had encephalitis, the female patients also developed encephalomyelitis as indicated by inflammation in her brain and spinal cord.

Altogether, patients had symptoms affecting cortical and brainstem function at the peak of neurologic illness.

SOURCE

https://www.medscape.com/viewarticle/931964?src=mkm_covid_update_200608_mscpedit

 

Read Full Post »

The race for a COVID-19 vaccine: What’s ahead ?

Reporter: Irina Robu, PhD

Researchers are conducting over 100 coronavirus vaccines studies, as they race to produce the first serum to protect people from COVID-19. Its uncertain which one would be successful, but what is certain is that without the vaccine, life would not return to normal anywhere on the world.

Usually, a vaccine takes 20 to 15 years to develop, but Moderna Therapeutics, a U.S. pharmaceutical company will test their vaccine on tens of thousands of people which are in critical phase 3. Even though many vaccines are tested now, only ten candidates are currently in clinical trials. The process to develop a vaccine is complicated and requires time and money.

However, in order to develop a vaccine, a pathogen has to be identified. After several in vitro trials, the vaccine is tested in mice, then in a non-human primate model. After these preclinical studies show  promising results, then the next step is to into clinical trials i.e. human testing. The human testing, occurs in various steps. The first step, phase 1 clinical trial is usually a small trial with 20 to 100 patients. The goal of this step is to asses the toxicity of the vaccine. Once, the first step clinical trials are completed and the results show positive result on toxicity and safety, progress to phase 2 trials can be started. Phase 2 clinical trials include 200 to 400 patients. In this phase, immunogenicity of the vaccine it is tested as well as how long it is effective.  Then, the last step is phase 3 clinical trial which can include as many as 30,000 people. The last phase it assesses whether the vaccine works on a broader scale.

Once the vaccine is effective, companies have to increase production to develop more than 7 billion doses. But due to the large number of people requiring this vaccine, scientists have to look at how to increase the manufacturing capability and distribution. In order to produce them effectively, a portfolio of vaccines have to be used.

 SOURCE

https://scopeblog.stanford.edu/2020/06/25/the-race-for-a-covid-19-vaccine-whats-ahead/

 

 

 

Read Full Post »

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/

 

Read Full Post »

6/30/2020

Chasing change: Innovation and patent
activity during COVID-19

A report on the pandemic’s impact on the global
R&D community and innovation lifecycle

Reporters: Aviva Lev-Ari, Ph.D., RN & Gail S. Thornton, M.A.

Published by Clarivate Derwent

In just a few short months, COVID-19 swept through the world. While many aspects of everyday life have altered as the pandemic has gripped the globe, society at large has been and remains remarkably resilient.

To understand the impact of COVID-19 on the world’s innovators, we asked organizations from a cross-section of industries globally about how the pandemic has affected their organizations’ innovation strategies.

We are pleased to share the results with you in the report, “Chasing change: Innovation and patent activity during COVID-19.”

SOURCE:

https://clarivate.com/derwent/wp-content/uploads/sites/3/dlm_uploads/2020/06/DW507408683-COVID-19-Report_FINAL.pdf?utm_campaign=EM1_Report_Derwent_COVID_19_Survey_Apr_IPS_Global_2020_ClientsProspects

Other related article published in this Open Access Online Scientific Journal include the following:

Corticosteroid, Dexamethasone Improves Survival in COVID-19: Deaths reduction by 1/3 in ventilated patients and by 1/5 in other patients receiving oxygen only

Reporter: Aviva Lev-Ari, PhD, RN https://pharmaceuticalintelligence.com/2020/06/27/corticosteroid-dexamethasone-improves-survival-in-covid-19-deaths-reduction-by-1-3-in-ventilated-patients-and-by-1-5-in-other-patients-receiving-oxygen-only/

###

Read Full Post »

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/

Read Full Post »

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.

For more Articles on COVID-19 please see our Coronavirus Portal at

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

Read Full Post »

Updates on the Oxford, AstraZeneca COVID-19 Vaccine

Reporter: Stephen J. Williams, PhD

AstraZeneca’s CEO states that their COVID-19 vaccine, codeveloped with Oxford University, should provide protection for a year.

AstraZeneca’s potential coronavirus vaccine is likely to provide protection against contracting Covid-19 for about a year, the company’s chief executive told a Belgian radio station on Tuesday.

The British drugmaker has already begun human trials of the vaccine developed by the University of Oxford, with a phase I trial in Britain due to end soon and a phase III trial already begun, Pascal Soriot told broadcaster Bel RTL.

“We think that it will protect for about a year,” Soriot said.

AstraZeneca said on Saturday that it had signed contracts with France, Germany, Italy and the Netherlands to supply the European Union with up to 400 million doses of the potential vaccine.

It has also agreed deals with Britain and the United States.

“If all goes well, we will have the results of the clinical trials in August/September. We are manufacturing in parallel. We will be ready to deliver from October if all goes well,” Soriot said.

Source: https://www.cnbc.com/2020/06/16/astrazeneca-covid-19-vaccine-likely-to-protect-for-a-year-ceo-says.html

 

 

From In The Pipeline (Derek Lowe’s regular column in Science)

Criticism of the Oxford Coronavirus Vaccine

By Derek Lowe 18 May, 2020

This piece at Forbes by Bill Haseltine has set off a lot of comment – it’s a look at the Oxford group’s vaccine candidate as compared to the SinoVac candidate, and you may recall (background here) that these are the two teams that have separately reported that their vaccines appear to protect rhesus monkeys from infection after exposure to the coronavirus. Haseltine has some criticisms of the Oxford data, and as you will see from that link to his name, his opinions deserve to be taken seriously. So what’s going on? Update: here’s the take on this at BioCentury.

Looking at the preprint on the Oxford results, Haseltine has a problem with the claim that the monkeys were protected from infection by a dose of ChAdOx1 nCoV-19. The key data are in the preprint’s Figure 3. The Oxford team checked for viral RNA several different ways. One was using bronchoaveolar lavage (BAL fluid), a sampling technique that involves running a bronchoscope down into the lungs and washing out aveolar spaces – a pretty darn invasive assay, which is why you don’t hear about it all that much compared to the still-not-so-nonivasive nose swabs. BAL fluid of the virus-exposed unvaccinated animals showed coronavirus genomic RNA throughout the study, and viral subgenomic RNA (more indicative of active replication) at days 3 and 5 after exposure. Meanwhile, the vaccinated animals showed the genomic RNA in only two monkeys, and no subgenomic RNA at all.

So far, so good. But both vaccinated and unvaccinated monkeys showed the same amount of viral genomic RNA from nose swab samples (Figure 3c). That’s the test that’s used out in the human population, and that means that the vaccinated animals would still be declared as positive for the coronavirus after being exposed to it. And the other thing that Haseltine notes is that the amount (the “titer”, in the lingo) of neutralizing antibodies in the blood of the vaccinated animals does not appear to be that high. You’d like to be able to dilute the blood antibody samples down by hundreds of times or even a thousandfold and still see antiviral activity in an in vitro assay, but in the Oxford case the activity started disappearing at about fortyfold dilution (Figure 2b).

On the positive side, 2/3 of the unvaccinated animals showed clear evidence of viral pneumonia at autopsy, but none of the vaccinated ones did. The conclusion is that the vaccinated animals were indeed infected – the vaccine did not protect against that – but that the disease was definitely less severe. But these results mean that the virus might well still be transmissible from people who had been so vaccinated, even if the disease course itself was not as deadly. You’d want to do better than that, if you can. Haseltine’s take is “Time will tell if this is the best approach. I wouldn’t bet on it.

Haseltine compares these results to the SinoVac inactivated virus vaccine, and finds that that one looks better – at its highest dose, no viral RNA was recovered from the tissues of the vaccinated animals, for example. This sort of “sterilizing immunity” is what you’d want to aim for – it gives the virus nowhere to go in the human population if you can vaccinate enough people. But it’s worth noting that the SinoVac results were from three doses of their vaccine (versus one of the Oxford candidate), and the viral exposure challenge was about half as strong (total viral particles) as what the Oxford paper used. The Oxford group also inoculated their monkeys in both the upper and lower respiratory tract, while the SinoVac team used a single inoculation in the trachea. So I agree with that tweet linked from AndyBiotech; I don’t think that a head-to-head comparison is fair. But Haseltine’s point stands, that the results as we have them from the ChAdOx1 nCoV-19 vaccine did not actually protect monkeys from infection.

Source: https://blogs.sciencemag.org/pipeline/archives/2020/05/18/criticism-of-the-oxford-coronavirus-vaccine

 

Please see other Articles on COVID-19 on our Coronavirus Portal Including Late Breaking News at:

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

 

Read Full Post »

New Coronavirus Passive Vaccine Developed by Israeli Researchers

Reporter: Irina Robu, PhD

Researchers at Bar-Ilan University have identified short amino acid sequences that could help the development of a vaccine against COVID-19 virus. Of the 25 epitopes that were discovered to be 100% identical to SARS, seven are theoretically efficient vaccine candidates. Their research indicate that they could cover as much as 87% of the world population

Their study has identified a set of immunodominant epitopes from the SARS-CoV-2 proteome, which are capable of generating antibody and cell mediated immune responses. The epitopes, known as antigenic determinants, are the part of the antigen that binds to a specific antigen receptor on the surface of B cells or T cells and are able to provoke an immune response.

It is known that immune response occurs within an organism for the purpose of defending against foreign invaders such as viruses, bacteria, parasites and fungi. The immune responses that are based on specific immunodominant epitopes contain the generation of both antibody- and cell-mediated immunity against pathogens. Such immunity can facilitate fast and effective elimination of the pathogen. The end result is a passive vaccine capable of capable of activating both cellular and humoral immune responses in humans.

According to the team at Bar-Ilan University, the mapped coronavirus epitopes with those of the influenza virus. And they found that 85% of the sequence identity with experimentally detected epitopes of Severe Acute Respiratory Syndrome-related coronavirus (SARS-CoV).

Additional analysis indicated that the epitopes are non-allergic and non-toxic to humans and have very low risk for generating autoimmune responses. The team is looking to partner with companies to build vaccine constructs and test them in-vitro and on animal trials before starting any clinical trials.

SOURCE

https://www.jpost.com/health-science/israeli-researchers-on-road-to-new-covid-19-passive-vaccine-630988?utm_source=ActiveCampaign

Read Full Post »

« Newer Posts - Older Posts »