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Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease (2010)

Chapter: Appendix A: Table of Papers About Biomarker Qualification

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Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
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Appendix A
Table of Papers About Biomarker Qualification

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
×

TABLE A-1 Historical Review of the Biomarker–Surrogate Endpoint Literature with Special Reference to the Nomenclature, Initial Reports, Systems of Classification, and Statistical Methods Developed for Their Evaluation

Year

Author

Focus

Field/Summary and Commentary

1963

Mainland

Nomenclature: Substituted variables

Statistics and Medicine In his Elementary Medical Statistics, he discusses substituting variables that are easy to observe for ones that are difficult to observe.

1966

Rushing

Nomenclature: First report of surrogate used in any context

Psychology, Ethics, Social Science, Law

The role of the hospital nurse as a mother surrogate. (Many publications followed in the 1960s and 1970s where surrogate was used in this context of a person’s role in the fields of psychology, ethics, social science, and law.)

1973

Rho et al.

Nomenclature: First report of biomarker

Biology

A search for porphyrin biomarkers in nonesuch shale and extraterrestrial samples. Biomarker here represents biological marker—origins of biological life.

1976

Schlenger

Nomenclature: First report of surrogate AND outcome

Epidemiology

Mortality and morbidity rates as surrogates for “health.”

1977

Karpetsky et al.

Nomenclature: Second report of biomarker

Oncology

Serum RNase level was found to be an indicator of renal function, and was not a biomarker either for the presence or extent of the plasma cell tumor. (Forty of 46 biomarker reports from 1977 to 1985 were in oncology.)

1978

Baker

Nomenclature: Third report of biomarker

Oncology

Preoperative assessment of the patient with breast cancer.

1980

Regelson

Nomenclature: First report of biomarker outside cancer in medicine

General Medicine

Biomarkers in aging: A beginning for a therapeutic approach in Transactions of the Association of Life Insurance Medical Directors of America.

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
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Year

Author

Focus

Field/Summary and Commentary

 

Webb and Lin

Nomenclature: First report of biomarker in title of publication

Oncology

Urinary fibronectin: Potential as a biomarker in prostatic cancer.

1982

Waalkes et al.

Biomarkers for clinical application

Oncology

Feasibility study in the development of 17 biological markers for ovarian cancer.

1983

Wood

Nomenclature: First report of surrogate AND endpoint, second report of surrogate AND outcome

Rheumatology

Nature of surrogate endpoints. Relationships considered at two levels: (1) ability of the attribute to act as a surrogate in detection of the underlying state (at a particular point in time); (2) potential of the surrogate to reveal changes in the underlying state as its course unfolds.

1986

Bigger

Second surrogate and endpoint, third surrogate and outcome

Cardiology

Electrophysiological testing to select patients with ventricular arrhythmias for drug trials and to determine anti-arrhythmic drug efficacy. (By the end of the decade, the use of biomarkers as surrogates in cardiology had a number of high-profile failures.)

 

Buccheri et al.

First report of biomarker as measure of tumor burden and predict outcome

Oncology

Clinical value of a multiple biomarker assay (CEA, TPA, b-HCG, LDH) in patients with bronchogenic carcinoma.

1987

Kalish et al.

Third surrogate and endpoint

Oncology

Surrogates as endpoints in bladder cancer trials. Data show that superficial disease endpoints do not predict surrogates for invasive disease endpoints.

 

Schulof et al.

Surrogates markers first used as response to therapy

HIV

Phase I/II trial of thymosin fraction 5 and thymosin alpha one in HTLV-III–seropositive subjects.

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
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Year

Author

Focus

Field/Summary and Commentary

 

Rosin et al.

Intermediate endpoints

Oncology

Promise of intermediate endpoints in quantitating the response of precancerous lesions to chemopreventive agents.

1989

The Cardiac Arrhythmia Suppression Trial (CAST) Investigators; Ruskin

First example of study to test surrogate; treatment of a biomarker successful, but patient outcome worse

Cardiology

CAST showed that successful suppression of the ventricular arrhythmia biomarker with antiarrhythmic therapy was associated with increased rather than decreased patient mortality.

 

Herson

First substantive discussion on surrogate endpoints in clinical trials

Methodology

An introduction to four invited papers on surrogate endpoints in clinical trials. These were pivotal papers. Trigger was an FDA criticism of new drug applications in cardiology and oncology because they used surrogate endpoints.

Ellenberg and Hamilton

All key issues discussed using examples from oncology

Methodology

Advantages and disadvantages of surrogate endpoints. Key points: Used when endpoints of interest are too difficult and/or expensive to measure; must be sufficiently well correlated with the endpoints of interest to justify substitution; initial choice often based on biologic rationale as primary endpoints are more acceptable in early drug development than later pivotal studies.

 

Wittes et al.

Many key issues discussed using examples from cardiology

Methodology

Key points: “True” endpoint is one with clinical importance to the patient, such as mortality or a major clinical outcome; surrogate is one biologically closer to the process of disease; surrogate is useful if easily measured and highly correlated with the true endpoint; surrogates can dramatically reduce sample size and trial duration.

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
×

Year

Author

Focus

Field/Summary and Commentary

 

Prentice

First report addressing the key statistical barrier to the use of surrogates

Statistics

Prentice defines a surrogate endpoint to be a “response variable for which a test of the null hypothesis of no relationship to the treatment groups under comparison is also a valid test of the corresponding null hypothesis based on the true endpoint.”

 

Beaudry and Spence

First report of surrogate outcome

Cardiology

Atherosclerosis severity index based on noninvasive ultrasound assessment to replace angiographic measurement of atherosclerosis (costly and invasive), which in turn replaced clinical endpoints (latter most expensive). (Example of developing a surrogate to replace another surrogate.)

 

Buchwald et al.

Empirical surrogate endpoint validation

Cardiology

RCT to demonstrate a reduction in overall mortality by lipid modification and to validate coronary arteriographic change as a surrogate for change in coronary heart disease risk.

1990

Machado et al.

Testing validity of surrogate therapeutics

HIV Medicine

Pros for surrogate endpoints: Ethical/practical reasons for hastening decision making about the efficacy of new treatments for HIV infection. Cons: Serious overestimates of clinical benefit if treatment had delayed toxicity or only transient beneficial effects; serious underestimates of clinical benefit when the treatment had no effect on the transition from healthy to the marker state.

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
×

Year

Author

Focus

Field/Summary and Commentary

 

Schatzkin et al.

Statistical validation strategy

Oncology

The intermediate endpoint is a valid cancer surrogate if the attributable proportion is near 1.0, but not if it is near 0 (usually the attributable proportion is neither 1.0 nor 0); in this case in an established exposure-cancer relationship, the exposure effect would vanish if adjusted for the intermediate endpoint.

 

Woosley

Further commentary on CAST results and implications for drug development

Cardiology

High-profile study that illustrated the dangers of surrogate therapeutics. (Further failures followed in other cardiology studies. Within a few years, surrogates rarely used in cardiology and large outcome trials with patient endpoints were the norm. Other fields in medicine did not have resources to conduct large, long studies and continued to argue for the use of surrogates in drug development.)

Lippman et al.

Schema

Oncology

Proposed three classes of biomarkers: genomic, proliferation, and differentiation markers. Biomarker validation studies should follow an evolutionary process. This leads to first generation (short-term trials in high-risk patients), second generation (dose and schedule trials), and third generation trials (long-term phase III trials to validate first generation candidate biomarkers).

1992

New drug, antibiotic, and biological drug product regulations; accelerated approval—FDA. Final Rulea

FDA “accelerated approval” regulation

General

Accelerate approval of new drugs and biological products for serious or life-threatening illnesses, with provisions for any necessary continued study of the drugs’ clinical benefits after approval.

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
×

Year

Author

Focus

Field/Summary and Commentary

 

Freedman et al.

Statistical validation

Statistics

Statistical validation of intermediate endpoints requires exposure or intervention effect, adjusted for the intermediate endpoint, to be reduced to zero. The estimating statistic—PTE—is explained by the intermediate/surrogate endpoint and its 95% confidence limits are determined.

 

Boissel et al.

Schema

Methodology

Three provisos for surrogate outcome evaluation. Proviso 1, the surrogate endpoint, should occur more frequently than corresponding clinical endpoint. Proviso 2, that relationship between the surrogate and clinical endpoint, is well established through relevant epidemiological studies. Proviso 3, that the estimate of the expected clinical benefit should be derivable from the estimate of the reduction on the surrogate endpoint, which can be obtained from randomized clinical trials data.

 

Freedman et al.

Schema

Methodology

A new validation criterion based on an analysis of the three-way relationship of exposure (E), marker (M), and disease (D). Provides the level of evidence required for using intermediate markers as endpoints for Phase II and Phase III trials. (These criteria were conceptual and qualitative only.)

 

Freedman and Schatzkin

Sample-size issues

Methodology

Different sample-size requirements for questions on surrogate endpoint validity: Does the intervention affect the intermediate endpoint? Is the intermediate endpoint associated with the main outcome? Is the intervention effect on the main outcome mediated by the intermediate endpoint?

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
×

Year

Author

Focus

Field/Summary and Commentary

1993

The Hypertension Optimal Treatment Study (the HOT Study)

Targeting biomarker

Cardiology

Dose–response relationship between surrogate target and clinical outcome.

 

Lin et al.

Application of Prentice

AIDS

CD4-lymphocyte count captures part of the relationship between zidovudine and time to a first critical event, but does not fulfill the Prentice criterion.

1994

Aickin

Surrogate endpoint biomarker

Oncology

If there is gold in the labeling index hills, are we digging in the right place? (Tool for cancer chemoprevention studies.)

1995

Temple

Schema

Methodology

“Feels function or survives” definition for surrogate endpoint.

 

Lee et al.

Review

Methodology

Surrogate biochemical markers: Precise measurement for strategic drug and biologics development.

Hughes et al.

Review

Statistics/HIV

Evaluating surrogate markers.

 

Scientific Advisory Committee on Surrogate Markers of HIV

Consensus

HIV Medicine

Consensus statement. Scientific advisory committee on surrogate markers of HIV.

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
×

Year

Author

Focus

Field/Summary and Commentary

1996

Fleming and DeMets

Review

Methodology

Surrogate endpoints in clinical trials. Are we being misled? Argues for use of surrogate endpoints in Phase II, but not Phase III pivotal trials. Failure of surrogate endpoints because: (1) surrogate is not in the causal pathway of the disease process; (2) of several causal pathways of the disease, the intervention affects only the pathway mediated through the surrogate; (3) surrogate is not in the pathway of the intervention’s effect or is insensitive to its effect; and (4) intervention has mechanisms of action independent of disease process.

 

Schatzkin et al.

Review

Methodology

Surrogate endpoints in cancer research: a critique.

1997

De Gruttola et al.

Schema

Methodology

Validating surrogate markers: Are we being naïve? The variety of proposed metrics for evaluating the degree to which this criterion is met are subject to misinterpretation because of the multiplicity of mechanisms by which drugs operate. Without detailed understanding of these mechanisms, metrics of “surrogacy” are not directly interpretable. Even when all of the mechanisms are understood, these metrics are associated with a high degree of uncertainty unless either treatment effects are large in moderate-sized studies or sample sizes are large in studies of moderately effective treatments.

 

Lin et al.

Statistics

Statistics

Estimating the proportion of a treatment effect explained by surrogate marker.

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
×

Year

Author

Focus

Field/Summary and Commentary

 

Mildvan et al.

Schema

Methodology

An approach to the validation of markers for use in AIDS clinical trials.

 

Rolan

Schema

Methodology

The contribution of clinical pharmacology surrogates and models to drug development. Proposes five dimensional properties of surrogates. These are validation (statistical), innovation, proximity to clinical outcome, specificity for an intervention, and practicality.

 

Topol et al.

Review

Methodology

Need clinical endpoints to establish safety and efficacy.

 

Daniels and Hughes

Schema

Statistical Method/HIV

Meta-analysis for the evaluation of potential surrogate markers.

 

Boissel et al.

Schema

Methodology

Clinical evaluation: From intermediate to surrogate criteria (French).

 

Colburn

Schema

Methodology

Selecting and validating biologic markers for drug development.

1998

Albert et al.

Review– consensus

Methodology/HIV

Statistical issues for HIV surrogate endpoints: Point/counterpoint.

 

Buyse and Molenberghs

Statistics

Statistics

Introduction of the relative effect (RE) and adjusted association (AA) for single-unit studies.

 

FDA and NIH

Review and abstracts

Methodology

Biomarkers and surrogate endpoints: Advancing clinical research and applications. (Abstracts.)

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
×

Year

Author

Focus

Field/Summary and Commentary

 

Hayes

Schema

Methodology

Tumor Marker Utility Grading System (TMUGS) proposed to evaluate the clinical utility of tumor markers and to establish an investigational agenda for evaluation of new tumor markers for risk assessment, screening, differential diagnosis, prognosis, monitoring clinical course, and use in clinical trials. Includes a TMUGS Worksheet that clarifies the precise characteristics of the marker in question and evaluates its clinical utility on a six-point scale (ranging from 0 to +++).

1999

Bucher et al.

Schema

Methodology

How to use and article measuring the effects of an intervention on surrogate endpoints.

2000

Buyse et al.

Statistics

Statistics

Validation of surrogate endpoints in meta-analysis of randomized experiments.

 

Buyse et al.

Statistics

Statistics

Statistical validation of surrogate endpoints.

 

Colburn

Schema

Methodology

Optimizing the use of biomarkers, surrogate endpoints, and clinical endpoints for efficient drug development.

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
×

Year

Author

Focus

Field/Summary and Commentary

 

Gail et al.

Statistics

Methodology

The strengths and weakness of meta-analytic assessment of surrogate endpoints: (1) which trials? (2) how many trials? (3) difficult to obtain individual-level data to estimate within study variance. (4) between-study variation can yield much less precise estimates of treatment effects on true-endpoint than estimates based on true-endpoint itself. (5) realistic models for distribution complicated. (6) difficulty modeling joint or marginal distributions of true-endpoint and surrogate. (7) which approach frequentist, empirical Bayes, and Bayesian for hierarchical systems. (8) how to use covariates. (9) unanticipated toxicity. Conclusion: Meta-analysis of surrogate endpoints may lead to less precise estimates of treatment effect on clinical endpoint than relying on clinical endpoint itself.

 

Begg and Leung

Statistics

Statistics

Provide conceptual alternatives to Prentice criterion for surrogate statistical validation.

 

Schatzkin

Review

Methodology

Intermediate markers as surrogate endpoints in cancer research.

 

Fleming

Review

Methodology

Brief review of practical and statistical issues.

2001

Li et al.

Statistics

Statistics

A method to assess the proportion of treatment effect explained by a surrogate endpoint—a general model and graphical setting.

 

Lesko and Atkinson

Schemas

Methodology

Biomarkers and surrogate endpoints in drug development and regulatory decision making.

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
×

Year

Author

Focus

Field/Summary and Commentary

 

Xu and Zeger

Statistics

Statistics

Evaluation of multiple surrogate endpoints.

 

Biomarkers

Definitions

Working Group

Schema

Methodology

Biomarkers and surrogate endpoints: preferred definitions and conceptual framework.

 

De Gruttola et al.

Schema

Methodology

Considerations and recommendations in evaluation of surrogate endpoints in clinical trials: Summary of NIH workshop.

2002

Wang and Taylor

Statistics

Statistics

A measure of the proportion of treatment effect explained by a surrogate marker.

 

Lathia

Review

Methodology

Biomarkers and surrogate endpoints: How and when might they impact drug development?

 

Molenberghs et al.

Statistics

Statistics

Statistical challenges in the evaluation of surrogate endpoints in randomized trials.

 

Wagner

Review

Methodology

Overview of biomarkers and surrogate endpoints in drug development.

 

Cowles

Statistics

Statistics

Bayesian estimation of the PTE captured by a surrogate marker.

 

Schatzkin and Gail

Review

Methodology

Promise and peril of surrogate endpoints in cancer research: Review of the logical issues as well as the problem of measurement error.

 

Frangakis and Rubin

Statistics

Statistics

Principal stratification in causal inference.

 

Henderson et al.

Statistics

Statistics

Longitudinal modeling.

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
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Year

Author

Focus

Field/Summary and Commentary

 

Lin et al.

Statistics

Statistics

Latent class models for joint analysis.

 

Taylor and Wang

Statistics

Statistics

Surrogate markers and joint models.

 

Hughes

Comment

Methodology

Imprecision in the estimates require modeling.

2003

Rolan et al.

Review

Methodology

Use of biomarkers from drug discovery through clinical practice. Mechanistic classification into six types of biomarkers.

 

Baker and Freedman

Statistics

Statistics

Method for analyzing data from a randomized trial with a missing binary outcome.

 

Baker and Kramer

Review

Methodology

A perfect correlate does not a surrogate make.

2004

FDA

Position paper

FDA’s Critical Path Document

Innovation or Stagnation: Challenge and Opportunity on the Critical Path to New Medical Products.

 

Berger

Statistics

Statistics

Does Prentice criterion validate surrogate endpoints?

 

Molenberghs et al.

Statistics

Methodology

Perspective of surrogate endpoints in controlled trials.

 

Alonso et al.

Statistics

Methodology

Role of statistics in surrogate endpoints.

 

Rubin

Statistics

Methodology

Direct versus indirect causal effects.

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
×

Year

Author

Focus

Field/Summary and Commentary

 

Baker et al.

Review

Drug Development

A general framework for describing various roles for biomarkers in cancer prevention research (early detection, surrogate endpoint, and cohort identification for primary prevention) and the phases in their evaluation.

2005

Fleming

Review

Methodology

Surrogate endpoints and FDA’s accelerated approval process.

 

Sargent et al.

Statistics

Oncology

Meta-analytic approach for surrogate validation.

 

Baker, 2006a

Statistics

Methodology

A simple meta-analytic approach for using a binary endpoint to predict the effect of intervention on true endpoint.

 

Korn et al.

Statistics

Methodology

Assessing surrogates as trial endpoints using mixed models.

2006

Weir and Walley

Statistics

Review

Statistical evaluation of biomarkers as surrogate endpoints: A literature review.

 

Baker, 2006b

Statistics

Review

Title: Surrogate endpoints: Wishful thinking or reality?

 

Finley Austin and Babiss

Review

Methodology

Where and how could biomarkers be used in 2016?

 

Qu and Case

Statistics

Statistics

Quantifying the indirect treatment effect via surrogate markers.

 

Desai et al.

Review

Cardiology

Blood pressure as an example of a biomarker that functions as a surrogate.

 

Hughes

Review

HIV Medicine

Initial treatment of HIV Infection: Randomized trials with clinical endpoints are still needed.

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
×

Year

Author

Focus

Field/Summary and Commentary

 

Johnson et al.

Statistics

Oncology Prediction bands used in a meta-analysis of RCTs to determine the surrogate threshold for response-rate and time to progression endpoints as predictors of mortality in metastatic colorectal cancer and non-small-cell lung cancer.

 

FDA

Regulatory initiatives

Update on Critical Path Initiative.

2007

Lassere et al., 2007b

Schema

Methodology Definitions and validation criteria for biomarkers and surrogate endpoints: Development and testing of quantitative hierarchical levels of evidence schema.

 

Lassere et al., 2007a

Statistics

Review Simulation studies of surrogate endpoint validation using single trial and multitrial statistical approaches.

 

Wagner et al.

Schema

Methodology Biomarker qualification, a graded, “fit-for-purpose” qualitative evidentiary process linking a biomarker with biology and clinical endpoints.

NOTES:

a 57 Federal Register 239 (1992) pp. 58942–58960. AA = adjusted association; AIDS = acquired immune deficiency syndrome; b-HCG = beta-human chorionic gonadotropin; CAST = The Cardiac Arrhythmia Suppression Trial; CEA = carcinoembryonic antigen; FDA = Food and Drug Administration; HIV = human immunodeficiency virus; HOT = The Hypertension Optimal Treatment Study; HTLV-III = human T-lymphotropic virus type III; LDH = lactate dehydrogenase; NIH = National Institutes of Health; PTE = proportion of treatment effect; RCT = randomized controlled trial; RE = relative effect; TPA = tissue plasminogen activator.

SOURCE: Lassere (2008). Reprinted with permission from SAGE publications, Copyright 2009 by SAGE Publications.

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
×

TABLE A-2 Continuation of Table A-1 for 2007-2009

Year

Author

Focus

Field/Summary and Commentary

2007

Alonso and Molenberghs

Statistics

Methodology

An information-based validation method for surrogate endpoints.

 

Pryseley et al.

Statistics

Methodology

The authors test and review a meta-analytic approach to biomarker qualification and support use of a recently proposed, more computationally efficient process in some circumstances.

 

Rasnake et al.

Regulatory

Nutrition

Discussion of emerging surrogate endpoints and the use of surrogate endpoints in the review of health claims at the FDA.

2008

Alonso and Molenberghs

Statistics

Methodology/Oncology

Evaluation of time to cancer recurrence as a surrogate endpoint for survival, as evaluated using a meta-analytic framework.

 

Altar et al.

Schema

Methodology

Provides an “evidence map” for grading available evidence and a process for biomarker qualification.

 

Burzykowski

Comment

Methodology

A concise summary of the topic of surrogate endpoint qualification.

 

Chakravarty and Sridhara

Regulatory

Oncology/Regulatory Issues

Discussion of use of progression-free survival as a trial endpoint.

 

Green et al.

Statistics

Methodology

Use of multiple methods, both statistical and clinically relevant qualitative methods, is proposed.

 

Joy and Hegele

Comment

Methodology

Discussion of the failure of the torcetrapib trials and the implications for CETP inhibition as a treatment target.

 

Krumholz and Lee

Comment

Methodology

Recent failures of surrogate endpoints in cardiology and endocrinology.

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
×

Year

Author

Focus

Field/Summary and Commentary

 

Lassere

Review, schema

Methodology

Systematic review of biomarker and surrogate endpoint validation criteria from 1950 to 2007; also provides criteria for ranking surrogate validity.

 

Osborne

Comment

Alzheimer’s/Regulatory

Comment on shifts in use of surrogate endpoints for Alzheimer’s disease drug development.

 

Psaty and Lumley

Comment

Cardiology

Further discussion of recent surrogate endpoint failures in lipid-altering drug clinical trials.

 

Wagner

Schema

Methodology

Comprehensive discussion of fit-for-purpose biomarker qualification for all stages of drug development.

2009

Hlatky et al.

Schema

Methodology/Cardiology

Title: Criteria for evaluation of novel markers of cardiovascular risk: A scientific statement from the American Heart Association.

 

Lathia et al.

Schema

Methodology

Successes and failures in use of surrogate endpoints for drug development; discussion of necessary criteria for surrogate endpoint qualification and use.

 

Prentice

Statistics

Methodology

Title: Surrogate and mediating endpoints: Current status and future directions.

 

Rigatto and Barrett

Review

Methodology

Statement of definitions, advantages, and disadvantages to biomarker and surrogate endpoint use for clinical trials.

Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
×

Year

Author

Focus

Field/Summary and Commentary

 

Shi and Sargent

Review

Methodology

Discussion of surrogate endpoints evaluation and the use of meta-analysis of multiple clinical trials for evaluation.

NOTES: CETP = cholesteryl ester transfer protein; FDA = Food and Drug Administration.

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Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
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Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
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Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
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Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
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Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
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Suggested Citation:"Appendix A: Table of Papers About Biomarker Qualification." Institute of Medicine. 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: The National Academies Press. doi: 10.17226/12869.
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Next: Appendix B: Recommendations from Related IOM Reports »
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Many people naturally assume that the claims made for foods and nutritional supplements have the same degree of scientific grounding as those for medication, but that is not always the case. The IOM recommends that the FDA adopt a consistent scientific framework for biomarker evaluation in order to achieve a rigorous and transparent process.

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