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Factors Used To Select Adjuvant Therapy—Overview

Gary M. Clark , Ph.D.

The terms “prognostic factors” and “predictive factors” have been used in many different contexts. Some factors may be patient-specific (for example, race, age, socioeconomic, environmental); others may be disease-specific (for example, biomarkers measured on tumor specimens, serum, bone marrow, etc.). These factors have several potential clinical uses, including identifying patients at high risk for a specific disease or for diagnosing that disease, estimating prognosis for patients diagnosed with a specific disease who receive no therapy or standard therapy, predicting response to a particular therapy, monitoring response to therapy during a treatment course, or identifying targets of opportunity for new therapies.

For this presentation, I will focus on prognostic biomarkers that might be used to estimate prognosis for patients diagnosed with a specific disease who receive no therapy or standard therapy, and on predictive biomarkers for predicting response to a particular therapy. Evaluation of prognostic biomarkers requires a single group of patients, preferably untreated. Evaluation of predictive biomarkers requires two groups of patients, preferably randomized to treatment or no treatment. Evidence of predictability is obtained by computing a statistical test for an interaction between treatment and biomarker status.

The clinical endpoints for evaluating prognostic or predictive biomarkers may be overall survival, disease-specific survival, disease-free survival, progression-free survival, event-free survival, tumor response as determined by tumor shrinkage, or modulation of another biomarker. Efficacy may be expressed as absolute benefit or relative benefit. Relative benefit for a survival endpoint is often expressed as the relative risk (risk of dying in the experimental group divided by the risk of dying in the control group), or the relative odds ratio (odds of surviving vs. dying in the experimental group divided by the odds of surviving vs. dying in the control group). The hazard ratio obtained from statistical regression models is often used to approximate the relative risk.

Only recently have criteria been proposed for determining the clinical utility of biomarkers. The American Society of Clinical Oncology (ASCO Expert Panel, 1996) used very conservative criteria to develop practice guidelines for using biomarkers. Partly in response to the lack of consensus about these criteria, a tumor marker utility grading system (TMUGS) was developed to differentiate levels of evidence among published studies (Hayes, Bast, Desch, et al., 1996). The College of American Pathologists used a modification of this system to develop its consensus statements about prognostic factors in breast, colon, and prostate cancer (Fitzgibbons, Page, Weaver, et al., 1999).

Study designs to evaluate biomarkers for different clinical uses vary with respect to the types of subjects and/or tissues to be studied, the endpoints that need to be measured, and the number of subjects and/or tissues that need to be accrued. However, the basic methodological principles for good study designs are common to all clinical uses (Altman, Lyman, 1998). All study designs should be based on clearly stated hypotheses. Assays should be reproducible and should be performed without knowledge of the clinical data and patient outcome. Results for individual factors should be analyzed using multivariate techniques that incorporate standard biomarkers that are already in clinical use. All results should be validated in subsequent studies before they are incorporated into clinical practice.

Very few new prognostic or predictive factors have been validated and endorsed for clinical use during the past several years. Part of the reason is a lack of adherence to proposed guidelines for the design, conduct, analysis, and reporting of results from prognostic factor studies. It is time to translate the principles of good study design and analysis that have been developed for clinical trials to the evaluation of new biomarkers.

References

Altman DG, Lyman GH. Methodological challenges in the evaluation of prognostic factors in breast cancer. Breast Cancer Res Treat 1998;52:289-303. Abstract.

American Society of Clinical Oncology (ASCO) Expert Panel. Clinical practice guidelines for the use of tumor markers in breast and colorectal cancer: report of the American Society of Clinical Oncology Expert Panel. J Clin Oncol 1996;14:2843-77. Abstract.

Fitzgibbons PL, Page DL, Weaver D, Thor AD, Allred DC, Clark GM, et al. Prognostic factors in breast cancer: College of American Pathologists Consensus Statement 1999. Arch Pathol Lab Med 2000;124:966-78. Abstract.

Hayes DF, Bast RC, Desch CE, Fritsche H Jr, Kemeny NE, Jessup JM, et al. Tumor marker utility grading system: a framework to evaluate clinical utility of tumor markers. J Natl Cancer Inst 1996;88:1456-66. Abstract.