Understanding Bladder Cancer Screening Limits Through Comparative Modeling: The Maximum Clinical Incidence Reduction (MCLIR) Methodology

BackgroundBladder cancer imposes substantial clinical and economic burden, yet key natural-history quantities that determine the potential effectiveness of screening--such as the size of the screen-detectable preclinical reservoir and the preclinical sojourn time--are largely unobservable. The Cancer Intervention and Surveillance Modeling Network (CISNET) uses standardized stress tests to compare independently developed microsimulation models and to clarify how differences in model structure translate into differences in intervention impact. The Maximum Clinical Incidence Reduction (MCLIR) framework estimates the maximum achievable reduction in clinically detected incidence following a one-time, perfect screening intervention, while Realistic Clinical Incidence Reduction (RCLIR) relaxes the perfect-test and/or perfect-treatment assumptions. MethodsWe applied the CISNET MCLIR/RCLIR protocol to three independently developed bladder cancer microsimulation models (COBRAS, Kystis, and SCOUT), each calibrated to common U.S. epidemiologic targets. We simulated a U.S. birth cohort born in 1950 and compared: (1) no-screening baseline; (2) one-time perfect screening with universally curative treatment (MCLIR) at ages 60, 65, 70, and 75; and (3) one-time realistic screening with cystoscopy sensitivity of 80% and perfect treatment (RCLIR-1) or usual-care treatment effectiveness (RCLIR-2). Outcomes included age-specific clinical incidence and incidence-reduction curves relative to baseline, as well as cumulative reductions over follow-up. ResultsAcross models, median ages at first lesion emergence, clinical diagnosis, and onset of muscle-invasive disease were similar, but preclinical sojourn time differed meaningfully: COBRAS produced the shortest median sojourn time (2.1 years) compared with Kystis (3.3 years) and SCOUT (3.1 years). Under MCLIR, all models predicted an immediate drop in clinical incidence followed by attenuation toward zero as new lesions emerged after the screening age. Peak MCLIR at age 65 among White men ranged from 20% (COBRAS) to 21% (Kystis) and 32% (SCOUT), with reductions dissipating within [~]8 years in COBRAS and persisting [~]10 years in Kystis and SCOUT. In COBRAS and Kystis, incidence reductions later became negative, consistent with rebound emergence of new lesions among individuals whose first lesions were removed by screening. Under RCLIR-1, peak reductions were smaller and varied substantially across models (13%, 4%, and 37% for COBRAS, Kystis, and SCOUT, respectively). RCLIR-2 further reduced gains and produced more gradual decay, reflecting incomplete prevention under usual-care treatment. Across models, most residual post-screening incidence was attributable to new lesion emergence rather than missed detection or incomplete treatment. ConclusionsIn a standardized CISNET stress test, three bladder cancer microsimulation models imply a relatively short detectable preclinical phase, placing a modest upper bound on the effectiveness of one-time screening in the general population. Differences in MCLIR/RCLIR magnitude and persistence are explained by differences in implied sojourn time and detectable reservoir size. These findings motivate evaluation of risk-targeted and repeated early-detection strategies and highlight key empirical priorities for improving inference on bladder cancer natural history.