Prostate cancer remains one of the most common cancers in men and a major cause of cancer-related deaths. Advances in screening and treatment have improved survival rates, but a growing concern is the emergence of secondary primary malignancies (SPMs). These unrelated cancers affect 11–22% of prostate cancer survivors and often reduce life expectancy.
Addressing this challenge, researchers from Guangzhou Medical University and collaborators published a study in UroPrecision on March 27, 2025 (DOI: 10.1002/uro2.70017). The team developed a prognostic tool to predict survival outcomes in prostate cancer patients with SPMs and explored genetic links between prostate cancer and other cancers.
Using data from 6,363 patients in the U.S. Surveillance, Epidemiology, and End Results (SEER) program, the researchers created a visual nomogram—a survival prediction model that incorporates multiple risk factors.
These included age, marital status, tumor site, stage, PSA levels, and treatment history. Statistical modeling demonstrated that the nomogram outperformed traditional AJCC staging, with high predictive accuracy (AUC values of 0.84–0.87). To enhance clinical use, the team also developed a dynamic, web-based calculator for personalized survival estimates.
The study went further by applying two-sample Mendelian randomization (TSMR) to examine genetic associations between prostate cancer and 10 common SPMs. Results revealed a significant causal link between prostate cancer and urothelial carcinoma, particularly bladder and upper tract cancers.
“Our research addresses two critical gaps—clinical prediction and genetic causality—in prostate cancer patients who develop second malignancies,” said lead author Dr. Di Gu. “The nomogram provides physicians with a practical tool for risk assessment, while our genetic analysis highlights the importance of closer monitoring for urinary system cancers.”
The findings support precision oncology approaches that combine clinical data with genetic insights. By supplementing traditional staging, the model enables clinicians to tailor follow-up, treatment intensity, and supportive care. The genetic evidence also suggests that prostate cancer survivors may benefit from heightened surveillance for bladder and upper tract cancers.
Together, these advances mark an important step toward more personalized management of prostate cancer survivors at risk of secondary malignancies.
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