Exact tests using two correlated binomial variables in contemporary cancer clinical trials.
New therapy strategies for the treatment of cancer are rapidly emerging because of recent technology advances in genetics and molecular biology. Although newer targeted therapies can improve survival without measurable changes in tumor size, clinical trial conduct has remained nearly unchanged. When potentially efficacious therapies are tested, current clinical trial design and analysis methods may not be suitable for detecting therapeutic effects. We propose an exact method with respect to testing cytostatic cancer treatment using correlated bivariate binomial random variables to simultaneously assess two primary outcomes. The method is easy to implement. It does not increase the sample size over that of the univariate exact test and in most cases reduces the sample size required. Sample size calculations are provided for selected designs.
Yu
Jihnhee
J
Department of Biostatistics, University at Buffalo, State University of New York, Buffalo, NY, USA. jinheeyu@buffalo.edu
Kepner
James L
JL
Iyer
Renuka
R
D016010:Binomial Distribution; D002986:Clinical Trials as Topic / Q000379:methods*; D003627:Data Interpretation, Statistical; D006801:Humans; D009369:Neoplasms / Q000188:drug therapy* / Q000401:mortality*; D017063:Outcome Assessment, Health Care / Q000379:methods*; D015995:Prevalence; D011379:Prognosis; D016016:Proportional Hazards Models; D018570:Risk Assessment / Q000379:methods; D012307:Risk Factors; D018401:Sample Size; D013223:Statistics as Topic; D016019:Survival Analysis; D015996:Survival Rate