Analytical decision model for sample size and effectiveness projections for use in planning a population‐based randomized controlled trial of colorectal cancer screening

Abstract

Population-based randomized controlled trials (RCTs) often involve enormous costs and long-term follow-up to evaluate primary end points. Analytical decision-simulated model for sample size and effectiveness projections based on primary and surrogate end points are necessary before planning a population-based RCT. Based on the study design similar to two previous RCTs, transition rates were estimated using a five-state natural history model [normal, preclinical detection phase (PCDP) Dukes' A/B, PCDP Dukes' C/D, Clinical Dukes' A/B and Clinical Dukes' C/D]. The Markov cycle tree was assigned transition parameters, variables related to screening and survival rate that simulated results of 10-year follow-up in the absence of screening for a hypothetical cohort aged 45-74 years. The corresponding screened arm was to simulate the results after the introduction of population-based screening for colorectal cancer with fecal occult blood test with stop screen design. The natural course of mean sojourn time for five-state Markov model were estimated as 2.75 years for preclinical Dukes' A/B and 1.38 years for preclinical Dukes' C/D. The expected reductions in mortality and Dukes' C/D were 13% (95% confidence intervals: 7-19%) and 26% (95% confidence intervals: 20-32%), respectively, given a 70% acceptance rate and a 90% colonoscopy referral rate. Sample sizes required were 86,150 and 65,592 subjects for the primary end point and the surrogate end point, respectively, given an incidence rate up to 0.0020 per year. The sample sizes required for primary and surrogate end points and the projection of effectiveness of fecal occult blood test for colorectal cancer screening were developed. Both are very important to plan a population-based RCT.