Imminent opioid overdose risk prediction using classical and machine learning survival models following first recorded opioid-related diagnosis: a prospective cohort study from the All of Us research program.

Among 14,737 individuals, 560 overdoses occurred within 30 days (cumulative incidence 3.8%, 95% CI 3.5-4.1).

Test-set C-indices ranged from 0.708 to 0.745, with Weibull Accelerated Failure Time and Survival SVM performing best, although performance was similar across models.

Calibration was acceptable, with predicted risks closely aligned with observed 30-day risks across low and moderate risk strata, and high-risk groups demonstrated substantially lower overdose-free survival.