Validation of an artificial intelligence-based prognostic biomarker in patients with oligometastatic Castration-Sensitive prostate cancer.

BACKGROUND

There is a need for clinically actionable prognostic and predictive tools to guide the management of oligometastatic castration-sensitive prostate cancer (omCSPC).

METHODS

This is a multicenter retrospective study to assess the prognostic and predictive performance of a multimodal artificial intelligence biomarker (MMAI; the ArteraAI Prostate Test) in men with omCSPC (n = 222). The cohort also included 51 patients from the STOMP and ORIOLE phase 2 clinical trials which randomized patients to observation versus metastasis-directed therapy (MDT). MMAI scores were computed from digitized histopathology slides and clinical variables. Overall survival (OS) and time to castration-resistant prostate cancer (TTCRPC) were assessed for the entire cohort from time of diagnosis. Metastasis free survival (MFS) was assessed for the trial cohort from time of randomization.

RESULTS

In the overall cohort, patients with a high MMAI score had significantly worse OS (HR = 6.46, 95 % CI = 1.44-28.9; p = 0.01) and shorter TTCRPC (HR = 2.07, 95 % CI = 1.15-3.72; p = 0.015). In a multivariable Cox model, MMAI score remained the only variable significantly associated with OS (HR = 6.51, 95 % CI = 1.32-32.2; p = 0.02). In the subset of patients randomized in the STOMP and ORIOLE trials, high MMAI score corresponded to improved MFS with MDT (p = 0.039) compared to patients with a low score, with p = 0.04.

CONCLUSION

The ArteraAI MMAI biomarker is prognostic for OS and TTCRPC among patients with omCSPC and may predict for response to MDT. Further work is needed to validate the MMAI biomarker in a broader mCSPC cohort.