Development and Validation of the Predicting Risk of Ischemic Stroke in Malignancy Estimation Tool

Background The risk of ischemic stroke is highest during the first year following a new diagnosis of cancer, but no tools exist to identify patients at highest risk. Methods Using linked clinical and administrative databases, we conducted a population‐based retrospective cohort study of adults in Ontario, Canada, with newly diagnosed cancer from 2010 to 2021. Patients were randomly selected for prediction model derivation (60%) or validation (40%). The final model predicting ischemic stroke within 1 year following cancer diagnosis was derived using multivariable Fine‐Gray regression with candidate predictors selected via backward elimination. Subdistribution‐adjusted hazard ratios and 95% CIs were calculated, where all‐cause mortality was treated as a competing event. Performance of the prediction model was assessed in the validation cohort based on the C statistic and calibration plots for discrimination and calibration, respectively. Results There were 698 566 eligible patients, with 418 911 in the derivation cohort and 279 576 in the validation cohort. The overall rate of stroke per 1000 person‐years was 6.7 (95% CI, 6.4–6.9). The final model included 22 predictors, including age, sex, demographic factors, cancer characteristics, and treatment characteristics. Discrimination was good, with a C statistic of 0.73. The model was well calibrated, with points following the desired 45‐degree line. Conclusions We derived and validated the PRIME (Predicting Risk of Ischemic Stroke in Malignancy Estimation) tool with good discrimination for ischemic stroke in patients with a new cancer diagnosis. The model was built into an online calculator ( https://study.ohri.ca/PRIME/ ) and has the potential to stratify patients with cancer based on their risk of stroke within a year following their diagnosis.