Use of archived specimens in evaluation of prognostic and predictive biomarkers.
The development of tumor biomarkers ready for clinical use is complex. We propose a refined system for biomarker study design, conduct, analysis, and evaluation that incorporates a hierarchal level of evidence scale for tumor marker studies, including those using archived specimens. Although fully prospective randomized clinical trials to evaluate the medical utility of a prognostic or predictive biomarker are the gold standard, such trials are costly, so we discuss more efficient indirect "prospective-retrospective" designs using archived specimens. In particular, we propose new guidelines that stipulate that 1) adequate amounts of archived tissue must be available from enough patients from a prospective trial (which for predictive factors should generally be a randomized design) for analyses to have adequate statistical power and for the patients included in the evaluation to be clearly representative of the patients in the trial; 2) the test should be analytically and preanalytically validated for use with archived tissue; 3) the plan for biomarker evaluation should be completely specified in writing before the performance of biomarker assays on archived tissue and should be focused on evaluation of a single completely defined classifier; and 4) the results from archived specimens should be validated using specimens from one or more similar, but separate, studies.
Simon
Richard M
RM
Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892-7434, USA. rsimon@nih.gov
Paik
Soonmyung
S
Hayes
Daniel F
DF
D000970:Antineoplastic Agents / Q000008:administration & dosage* / Q000494:pharmacology; D014408:Biomarkers, Tumor / Q000032:analysis*; D019317:Evidence-Based Medicine; D006801:Humans; D017410:Practice Guidelines as Topic; D011237:Predictive Value of Tests; D011379:Prognosis; D011446:Prospective Studies; D016032:Randomized Controlled Trials as Topic; D012107:Research Design; D012189:Retrospective Studies; D015983:Selection Bias; D014015:Tissue Banks
D000970:Antineoplastic Agents; D014408:Biomarkers, Tumor