LAUSR

OBJECTIVE Developing clinical prediction models (CPMs) on data of sufficient sample size is critical to help minimise overfitting. Using prostate cancer as a clinical exemplar, we aimed to investigate to what extent existing CPMs adhere to recent formal sample size criteria, or historic rules-of-thumb of Events per Predictor Parameter (EPP)≥10. STUDY DESIGN AND SETTING A systematic review to identify CPMs related to prostate cancer, which provided enough information to calculate minimum sample size. We compared the reported sample size of each CPM against the traditional 10 EPP rule-of-thumb and formal sample size criteria. RESULTS 211 CPMs were included. Three of the studies justified the sample size used, mostly using EPP rules-of-thumb. Overall, 69% of the CPMs were derived on sample sizes that surpassed the traditional EPP≥10 rule-of-thumb, but only 48% surpassed recent formal sample size criteria. For most CPMs, the required sample size based on formal criteria was higher than the sample sizes to surpass 10 EPP. CONCLUSION Few of the CPMs included in this study justified their sample size, with most justifications being based on EPP. This study shows that, in real-world datasets, adhering to the classic EPP rules-of-thumb is insufficient to adhere to recent formal sample size criteria.