Novel tool may help predict early PSA response to ARPIs in mHSPC

Investigators have developed a model that may be able to predict early favorable prostate-specific antigen (PSA) response (0.2 ng/mL or lower by 6 months) in patients with metastatic hormone sensitive prostate cancer (mHSPC) who are receiving treatment with androgen receptor pathway inhibitors (ARPI).^1,2

The findings were published in Nature Communications.

“Early decline in PSA to very low levels is one of the strongest predictors of long-term survival in metastatic prostate cancer,” explained lead author Soumyajit Roy, MBBS, MD, MSc, a radiation oncologist at University Hospitals (UH) Seidman Cancer Center, Cleveland, Ohio, in a news release on the findings.² “However, clinicians currently have to wait up to 6 months after starting therapy to see whether a patient achieves this favorable response. For patients who do not respond well, this delay may allow the cancer to progress and become more resistant to treatment.”

To that end, the investigators trained and validated a multiple logistic regression model, NADIR, to predict favorable early PSA response in these patients.

The study included retrospective data from patients in the ARPI cohorts of the LATITUDE (abiraterone [Zytiga]), TITAN (apalutamide [Erleada]), and ARASENS (darolutamide [Nubeqa]) trials. These patients were randomly allocated 60:40 to the training (n = 1030) or validation (n = 688) sets. The model was then externally validated using data from the enzalutamide (Xtandi) arm of the ENZAMET trial (n = 540).

In the external cohort, the locked model showed an area under the curve of 0.82 (95% CI, 0.78 to 0.85), and a Brier score of 0.16.

The investigators also assessed the proportion of patients who achieved a PSA response to 0.2 ng/mL or lower across the tertiles (upper, middle, and lower; all n = 180) of predicted probability of early PSA response by the NADIR model in the external validation cohort. Overall, the proportion of patients who achieved a favorable PSA response was 92% in the upper tertile (95% CI, 88 to 96), 74% in the middle tertile (95% CI, 68 to 81), and 39% in the lower tertile (95% CI, 32 to 47).

According to the authors, the next step is to prospectively validate the model in real-world clinical settings or within ongoing clinical trials. The investigators also plan to integrate additional biomarkers, such as genomic, molecular, or advanced imaging data, to further refine the model’s risk prediction.

If validated, this tool could play a role in guiding treatment decisions.

“The significance lies in shifting prostate cancer care from a reactive approach—waiting to see who fails therapy—to a proactive, personalized strategy,” concluded senior author Daniel E. Spratt, MD, Vincent K. Smith Chair of Radiation Oncology at the UH Seidman Cancer Center and Associate Chief Scientific Officer of UH CMC, in the news release.² “By identifying patients who are unlikely to achieve an early favorable PSA response, clinicians may be able to intervene sooner, consider treatment intensification, or prioritize enrollment in clinical trials.”

REFERENCES

1. Roy S, Sun Y, Hussain M, et al. Early favorable prostate-specific antigen response prediction in metastatic hormone sensitive prostate cancer. Nat Commun. 2025. doi:10.1038/s41467-025-67298-z

2. University Hospitals Seidman Cancer Center Researchers develop easy-to-use tool that can identify high- and low-risk metastatic prostate cancer patients earlier. News release. University Hospitals. January 7, 2026. Accessed January 14, 2026. https://news.uhhospitals.org/news-releases/articles/2026/01/uh-researchers-develop-tool-to-identify-risk-in-metastatic-prostate-cancer