Multi-institutional Patient-level Comparison of Decipher Genomic Classifier and Artera Multimodal Artificial Intelligence (MMAI) in Prostate Cancer.
Abstract
Importance
The Decipher Prostate Genomic Classifier (GC) and ArteraAI Multimodal Artificial Intelligence (MMAI) platform are widely used prognostic tools for localized prostate cancer (PCa), yet no direct comparison has been performed within the same patient cohort.
Methods
We sought to evaluate the concordance and prognostic value of GC and MMAI across multi-institutional cohorts totaling 688 patients with localized and oligometastatic PCa. These included populations enriched for African American and East Asian patients. GC and MMAI scores were stratified into risk groups based on specimen type (biopsy or radical prostatectomy (RP)). The primary endpoint was distant metastasis-free survival (DMFS), measured from diagnosis to last follow-up or event.
Results
GC and MMAI scores were significantly correlated across multiple cohorts. In Moffitt RP, biopsy, and NCCS cohorts, both MMAI and GC were prognostic alone and after adjusting for clinical variables. Multivariable analysis including both biomarkers and clinical variables showed that MMAI was significant even accounting for GC in Moffitt RP, and borderline in Moffitt biopsy. Analysis of concordant/discordant cases showed that patients who were high-risk for both GC and MMAI did qualitatively worse. In pathway analysis, concordance with GC and MMAI was high for Moffitt RP and oligometastatic patients. Across both biopsy cohorts, while most biological pathways were concordant, there were consistent discordant signaling, metabolic, and DNA repair pathways.
Conclusions
In the first direct patient-level comparison of GC and MMAI in PCa, these biomarkers were found to demonstrate moderate correlation, and both biomarkers demonstrated prognostic value across diverse populations and disease states.