Development and validation of prediction model for incident overactive bladder: The Nagahama study

Abstract

[Objectives] We aimed to develop models to predict new-onset overactive bladder in 5 years using a large prospective cohort of the general population. [Methods] This is a secondary analysis of a longitudinal cohort study in Japan. The baseline characteristics were measured between 2008 and 2010, with follow-ups every 5 years. We included subjects without overactive bladder at baseline and with follow-up data 5 years later. Overactive bladder was assessed using the overactive bladder symptom score. Baseline characteristics (demographics, health behaviors, comorbidities, and overactive bladder symptom scores) and blood test data were included as predictors. We developed two competing prediction models for each sex based on logistic regression with penalized likelihood (LASSO). We chose the best model separately for men and women after evaluating models' performance in terms of discrimination and calibration using an internal validation via 200 bootstrap resamples and a temporal validation. [Results] We analyzed 7218 participants (male: 2238, female: 4980). The median age was 60 and 55 years, and the number of new-onset overactive bladder was 223 (10.0%) and 288 (5.8%) per 5 years in males and females, respectively. The in-sample estimates for C-statistic, calibration intercept, and slope for the best performing models were 0.77 (95% confidence interval 0.74–0.80), 0.28 and 1.15 for males, and 0.77 (95% confidence interval 0.74–0.80), 0.20 and 1.08 for females. Internal and temporal validation gave broadly similar estimates of performance, indicating low optimism. [Conclusion] We developed risk prediction models for new-onset overactive bladder among men and women with good predictive ability.