Leaders in Pharmaceutical Business Intelligence (LPBI) Group

Biomarkers: Diagnosis and Management, Present and Future

Curator: Larry H Bernstein, MD, FCAP

Biomarkers of Cardiovascular Disease : Molecular Basis and Practical Considerations.RS Vasan .
Circulation. 2006;113:2335-2362. http://dx.doi.org/10.1161/CIRCULATIONAHA.104.482570

Biomarkers that are cost-effective in preventing late sequelae of CVD will likely survive.
Diagnostic markers will find use in point-of-care testing in emergency departments and by the bedside.
Biomarkers that perform well and cost-effectively in the testing of rapid “rule out” or “rule in”
strategies and those that help to triage patients into low- and high-risk treatment strategies will be integrated into clinical decision-making  protocols.

Biomarkers (including pharmacogenetic ones) that

• facilitate choice of the most appropriate drug,
• that enable titration of drug dose to avoid side effects, and
• that maximize therapeutic effects are likely to be attractive to clinicians.

Biomarker development must be associated with concurrent advances in physician training

• to use the array of biomarkers available so that clinicians can
• order tests appropriately and interpret them correctly.

Parallel advances must be made in medical information systems,

• in the quality control procedures within clinical laboratories, and in
• the interpretive reporting of biomarker tests.

The advent of genomic biomarkers has generated a number of ethical and regulatory issues that must be addressed concomitantly.

Ultimately, the evolution of CVD biomarkers will represent the coordinated and concerted effort of

• basic scientists,
• clinicians,
• technology experts,
• epidemiologists,
• statisticians,
• federal and industrial sponsors, and
• regulatory agencies within a cooperative framework

Biomarkers of acute coronary syndromes (adapted with permission from Naghavi et al.
[copyright 2003, American Heart Association] and Apple et al.). The arrows indicate the
sequence of events during an acute coronary syndrome. Biomarkers that may be elevated
at each phase of the disease are displayed. sCD40L indicates soluble CD40 ligand;
Fbg, fibrinogen; FFA, free fatty acid; ICAM, intercellular adhesion molecule; IL, interleukin; IMA, ischemia modified albumin; MMP, matrix metalloproteinases; MPO, myeloperoxidase; Myg, myoglobin; NT-proBNP, N-terminal proBNP; Ox-LDL, oxidized low-density lipoprotein; PAI-1, plasminogen activator inhibitor; PAPP-A, pregnancy-associated plasma protein-A; PlGF, placental growth factor; TF, tissue factor; TNF, tumor necrosis factor; TNI, troponin I; TNT, troponin T; VCAM, vascular cell adhesion molecule; and VWF, von Willebrand factor.

SOURCE:

Naghavi M, Libby P, Falk E, Casscells SW, Litovsky S, et al. From vulnerable plaque to
vulnerable patient: a call for new definitions and risk assessment strategies: part I. Circulation. 2003; 108:1664 –1672.  ‎  Naghavi M, Libby P, Falk E, Casscells SW, et al. From vulnerable plaque to vulnerable patient: a call for new definitions and risk assessment strategies: part II. Circulation. 2003; 108:1772–1778.  http://circ.ahajournals.org/content/108/15/1772.full

Apple FS, Wu AHB, Mair J, Ravkilde J, … Jaffe AS, on behalf of the Committee on Standardization of Markers of Cardiac Damage of the IFCC. Future biomarkers for detection of ischemia and risk stratification in acute coronary syndrome. Clin Chem. 2005; 51:810–824.
http://www.clinchem.org/content/51/9/1744.full

TABLE 1. Biomarkers: A Basic Glossary

Biological marker (biomarker): A characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic  processes, or pharmacological responses to a therapeutic intervention.

• Type 0 biomarker: A marker of the natural history of a disease and correlates
  longitudinally with known clinical indices.
• Type I biomarker: A marker that captures the effects of a therapeutic
  intervention in accordance with its mechanism of action.
• Risk factor: A risk factor is associated with a disease because it is in the causal pathway
• leading to the disease.
• Risk marker: A risk marker is associated with the disease (statistically) but need not be causally linked; it may be a measure of the disease process itself.
• Surrogate end point (type 2 biomarker): A marker that is intended to substitute for a clinical end point; a surrogate end point is expected to predict clinical benefit (or harm or lack of benefit or harm) on the basis of

1. epidemiological,
2. therapeutic,
3. pathophysiological,
4. or other scientific evidence.

• Clinical end point: A characteristic or variable that reflects how a patient feels, functions, or survives.
• Intermediate end point: A true clinical end point (a symptom or measure of function, such as symptoms of angina frequency or exercise tolerance) but not the ultimate end point of the disease, such as survival or the rate of other serious and irreversible morbid events.

Validation or method validation: A process for assessing performance characteristics

1. sensitivity,
2. specificity, and
3. reproducibility

• Clinical Validation: Theprocess linking a biomarker to disease biology or clinical outcome.

Evaluation of a Biomarker: A Process of Linking Biomarkers to Outcomes,

• often with a view to establish surrogate status.

SOURCE:

Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints:
preferred definitions and conceptual framework. Clin Pharmacol Ther. 2001; 69:89 –95.
http://dx.doi.org/10.1067/mcp.2001.113989.

Suitability a Biomarker for Classification or Prediction

Pivotal Evaluation of the Accuracy of a Biomarker Used for Classification or Prediction:
Standards for Study Design. MS Pepe, Z Feng, H Janes, PM Bossuyt, and JD Potter.
J Natl Cancer Inst 2008;100(20):1432-1438. http://dx.doi.org/10.1093/jnci/djn326

Research methods for biomarker evaluation lag behind those for evaluating therapeutic treatments. Al phased approach to development of biomarkers exists and guidelines are available for reporting study results, but guidelines for study design has not been delineated. Authors describe a nested case–control study design that involves prospective collection of specimens

• before outcome ascertainment from a study cohort that is relevant to the clinical application.

The biomarker is assayed in a blinded fashion on specimens from randomly selected

• case patients and control subjects in the study cohort.

Authored separately describe aspects of the design that relate to the

• clinical context,
• biomarker performance criteria,
• the biomarker test, and
• study size.

The design can be applied to studies of biomarkers intended for use in

• disease diagnosis,
• screening, or
• prognosis.

Common biases that pervade the biomarker research literature would

• be eliminated if these rigorous standards were followed.

Five phases of biomarker development: from discovery to delivery (adapted from
Pepe et al.) with permission from Oxford University Press).

1. Content validity refers to the degree to which the biomarker represents the
   biological phenomenon studied (eg, serum CRP represents systemic inflammation);
2. Construct validity refers to establishing that the biomarker is measuring the
   aspect of disease (some conceptual construct or theory) that we want to measure
   (eg, we want to measure plaque inflammation; therefore, we should establish
   whether serum CRP relates to atherogenesis and plaque inflammation); and
3. Criterion validity refers to the how well the biomarker identifies disease state when
   compared with a gold standard (measured in terms of sensitivity and specificity;
   eg, how well does CRP predict CVD?). RCT indicates randomized controlled trial.

SOURCE:

Pepe MS, Etzioni R, Feng Z, Potter JD, Thompson ML, et al. Phases of biomarker
development for early detection of cancer. J Natl Cancer Inst. 2001; 93:1054 –1061.
http://dx.doi.org/10.1093/jnci/djq335.

Advances in Clinical Genome Sequencing and Diagnostics

Points taken from –  Advances in Clinical Genome Sequencing and Diagnostics
Kevin Davies, PhD. founding editor of Bio-IT World and the journal Nature Genetics.

He is the author of three books that explore the impact of technology and genomics in medicine, most recently
“The $1,000 Genome” (Free Press, 2010). Kevin also serves as an advisor to Cambridge
Healthtech Associates and blogs at NGS Leaders.

Progress in clinical genome sequencing is being fueled by steady advances in existing platforms,
the arrival of new diagnostic platforms, and improvements in genome analysis software.
The adoption of clinical NGS is not trivial, and many questions still remain about setting standards,
ensuring analytic and clinical validity of the tests, and reimbursement.

 Landmark Guideline for Genomic Testing

Hank

Hank Pieniaszek

CSO and President at HPP Consulting & Sevices, Inc.

Excellent review for 2006! More time devoted to suitability of the biomarker bioanalytical validation (including specimen collection and handling, analyte stability, etc.) would have been an excellent addition. This process is commonly not considered and the biomarker results are taken as valid point estimates rather than point estimates with confidence limits. What about %IPA?