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Appendix A
Table of Papers About Biomarker Qualification
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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.
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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.
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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.
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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.
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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.
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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?
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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.
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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.
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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.)
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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.
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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.
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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.
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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.
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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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