A permutation test for a weighted Kaplan-Meier estimator with application to the nutritional prevention of cancer trial.
The phenomenon of losing statistical significance with increasing follow-up can arise when a proportional hazard model is applied in a clinical trial where the impact of the intervention results in delaying a negative event such as cancer diagnosis, progression or death. Often parametric methods can be employed in such a setting, however, in studies where only a small percentage of subjects have an event, these methods are often inappropriate. We present an alternative method based on a weighted Kaplan-Meier estimator and a permutation test, and demonstrate its utility in the setting of the Nutritional Prevention of Cancer study where increasing follow-up resulted in loss of statistical significance for the ability of selenized yeast to prevent lung cancer.
Frankel
Paul H
PH
Department of Biostatistics, City of Hope National Medical Center, 1500 E. Duarte Rd., Duarte, CA 91010-3000, United States. pfrankel@coh.org
Reid
Mary E
ME
Marshall
James R
JR
D019540:Area Under Curve; D015982:Bias; D015179:Colorectal Neoplasms / Q000175:diagnosis / Q000401:mortality / Q000517:prevention & control; D019587:Dietary Supplements; D005500:Follow-Up Studies; D006801:Humans; D053208:Kaplan-Meier Estimate; D008175:Lung Neoplasms / Q000175:diagnosis / Q000401:mortality / Q000517:prevention & control; D008297:Male; D009369:Neoplasms / Q000175:diagnosis / Q000401:mortality / Q000517:prevention & control*; D016016:Proportional Hazards Models; D011471:Prostatic Neoplasms / Q000175:diagnosis / Q000401:mortality / Q000517:prevention & control; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D012643:Selenium / Q000008:administration & dosage*; D017211:Treatment Failure; D016896:Treatment Outcome; D015002:Yeast, Dried / Q000008:administration & dosage*
D012643:Selenium