Histopathological examination of surgical specimens for benign prostatic hyperplasia (BPH) can detect incidental prostate cancer (iPCa). The aim of our study was to develop a predictive model for iPCa diagnosis for patients for whom BPH surgery is being considered.
We conducted a retrospective analysis of medical files for patients who underwent BPH surgery in three academic centers between 2012 and 2022. Patients diagnosed with PCa before surgery were excluded. We calculated the global iPCa rate, and the clinically significant iPCa rate (grade group ≥2). Univariate and multivariable regression models were used to assess factors predictive of iPCa. The area under the receiver operating characteristic curve (AUC) was compared for each risk factor and for the global model. We used χ2 automated interaction detection (CHAID) for decision tree analysis.
We included 2452 patients in the analysis, of whom 247 (10.0%) had iPCa, which was clinically significant in 49/247 cases (20.2%). Multivariable analysis revealed that age and prostate-specific antigen density (PSAD) were independent predictive factors for iPCa diagnosis. The AUC for a model including age and PSAD was 0.65. CHAID analysis revealed that patients with PSAD >0.1 ng/ml/cm3 had an iPCa risk of 23.4% (χ2 = 52.6; p < 0.001). For those patients, age >72 yr increased the iPCa risk to 35.4% (χ2 = 11.1, p = 0.008). Our study is mainly limited by its retrospective design.
Age and PSAD were independent risk factors for iPCa diagnosis. The combination of age >72 yr and PSAD >0.1 ng/ml/cm3 was associated with an iPCa rate of 35.4%.
We performed a study to find predictors of prostate cancer for patients undergoing surgery for benign enlargement of the prostate. Our model can identify patients at risk, and diagnose their cancer before surgery. This could avoid unnecessary or harmful procedures.
European urology oncology. 2024 Sep 09 [Epub ahead of print]
Julien Anract, Clément Klein, Ugo Pinar, Morgan Rouprêt, Nicolas Barry Delongchamps, Grégoire Robert
Department of Urology, Hôpital Cochin, AP-HP, Université Paris Cité, Paris, France. Electronic address: ., Department of Urology, CHU de Bordeaux, Université de Bordeaux, Bordeaux, France., Department of Urology, Hôpital Pitié Salpêtrière, Sorbonne Université, Paris, France., GRC 5 Predictive Onco-Uro, Department of Urology, Hôpital Pitié Salpêtrière, Sorbonne University, Paris, France., Department of Urology, Hôpital Cochin, AP-HP, Université Paris Cité, Paris, France.