Evaluating markers for the early detection of cancer: overview of study designs and methods.
BACKGROUND
The field of cancer biomarker development has been evolving rapidly. New developments both in the biologic and statistical realms are providing increasing opportunities for evaluation of markers for both early detection and diagnosis of cancer.


OBJECTIVE
To review the major conceptual and methodological issues in cancer biomarker evaluation, with an emphasis on recent developments in statistical methods together with practical recommendations.


METHODS
We organized this review by type of study: preliminary performance, retrospective performance, prospective performance and cancer screening evaluation.


RESULTS
For each type of study, we discuss methodologic issues, provide examples and discuss strengths and limitations.


CONCLUSIONS
Preliminary performance studies are useful for quickly winnowing down the number of candidate markers; however their results may not apply to the ultimate target population, asymptomatic subjects. If stored specimens from cohort studies with clinical cancer endpoints are available, retrospective studies provide a quick and valid way to evaluate performance of the markers or changes in the markers prior to the onset of clinical symptoms. Prospective studies have a restricted role because they require large sample sizes, and, if the endpoint is cancer on biopsy, there may be bias due to overdiagnosis. Cancer screening studies require very large sample sizes and long follow-up, but are necessary for evaluating the marker as a trigger of early intervention.
National Institutes of Health, Bethesda, MD, USA. sb16i@nih.gov
Stuart G
SG
Baker
Barnett S
BS
Kramer
Martin
M
McIntosh
Blossom H
BH
Patterson
Yu
Y
Shyr
Steven
S
Skates
D014408:Biomarkers, Tumor / Q000032:analysis; D015340:Epidemiologic Research Design; D006801:Humans; D008954:Models, Biological; D009369:Neoplasms / Q000175:diagnosis*; D011446:Prospective Studies; D012372:ROC Curve; D016032:Randomized Controlled Trials as Topic; D012107:Research Design; D018401:Sample Size; D015983:Selection Bias
D014408:Biomarkers, Tumor