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Understanding Bladder Cancer Screening Limits Through Comparative Modeling: The Maximum Clinical Incidence Reduction

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    Bladder cancer screening effectiveness is limited by a short detectable preclinical phase, according to three models. Findings suggest focusing on risk-targeted and repeated screening strategies for better bladder cancer detection.

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    Area of Science:

    • Oncology
    • Epidemiology
    • Health Economics

    Background:

    • Bladder cancer presents significant clinical and economic challenges.
    • Key natural history parameters for screening effectiveness, like preclinical reservoir size and sojourn time, are difficult to observe.
    • The Cancer Intervention and Surveillance Modeling Network (CISNET) uses standardized stress tests to compare microsimulation models and understand intervention impacts.

    Purpose of the Study:

    • To compare three independently developed bladder cancer microsimulation models using the CISNET Maximum Clinical Incidence Reduction (MCLIR) and Realistic Clinical Incidence Reduction (RCLIR) frameworks.
    • To assess the impact of one-time screening interventions on bladder cancer incidence reduction.
    • To understand how model differences influence predictions of screening effectiveness.

    Main Methods:

    • Applied the CISNET MCLIR/RCLIR protocol to three models (COBRAS, Kystis, SCOUT) calibrated to U.S. epidemiologic targets.
    • Simulated a 1950 U.S. birth cohort under no-screening, perfect screening (MCLIR), and realistic screening (RCLIR-1 and RCLIR-2) scenarios.
    • Analyzed age-specific clinical incidence, incidence-reduction curves, and cumulative reductions.

    Main Results:

    • Median preclinical sojourn times varied across models (2.1 to 3.3 years).
    • Peak incidence reductions under MCLIR ranged from 20% to 32% at age 65 for White men, with varying persistence.
    • Realistic screening (RCLIR) yielded smaller reductions, and most residual incidence was due to new lesion emergence.

    Conclusions:

    • Three bladder cancer microsimulation models suggest a short detectable preclinical phase, limiting one-time screening effectiveness.
    • Differences in model predictions are linked to variations in implied sojourn time and detectable reservoir size.
    • Findings support evaluating risk-targeted and repeated screening, and identify priorities for improving bladder cancer natural history inference.