Counseling Men With Prostate Cancer: A Nomogram for Predicting the Presence of Small, Moderately Differentiated, Confined Tumors

TLDR

Men diagnosed with clinically localized prostate cancer face multiple treatment options, and widespread PSA testing has led to earlier detection of many small, low‑risk tumors. The study aimed to develop a statistical model that predicts the presence of small, moderately differentiated, organ‑confined prostate cancer using clinical variables and systematic biopsy data. The model was built using logistic regression on 409 patients’ data, incorporating serum PSA, clinical stage, Gleason grade, ultrasound volume, biopsy core involvement metrics, and defining indolent cancer as ≤0.5 cc without poorly differentiated elements. Nomograms incorporating pretreatment variables predicted indolent cancer with discrimination AUCs ranging from 0.64 to 0.79, showed good calibration, and may aid clinicians and patients in treatment decision‑making.

Abstract

Men diagnosed with clinically localized prostate cancer have a number of treatment options available, including watchful waiting, radical prostatectomy and radiation therapy. With the widespread use of serum prostate specific antigen (PSA) testing, prostate cancers are being diagnosed earlier in their natural history, with many tumors being small and of little health risk to the patient, at least in the short term. To better counsel men diagnosed with prostate cancer, we developed a statistical model that accurately predicts the presence of small moderately differentiated, confined cancer based on clinical variables (serum PSA, clinical stage, prostate biopsy Gleason grade and ultrasound volume) and variables derived from the analysis of systematic biopsies.The analysis included 409 patients diagnosed by systematic needle biopsy with clinical stages T1c or T2a N0 or NX and M0 or MX prostate cancer who were treated solely with radical prostatectomy at 1 of 2 institutions. Additional biopsy features included number and percentage of biopsy cores involved with cancer and high grade cancer, in addition to total length of biopsy cores involved. Indolent cancer was defined as pathologically organ confined cancer 0.5 cc or less in volume and without poorly differentiated elements. Logistic regression was used to construct several prediction models and the resulting nomograms.Overall 80 (20%) of the patients had indolent cancer. The nomogram predicted the presence of an indolent cancer with discrimination (area under the receiver operating characteristics curves) for various models ranging from 0.64 to 0.79. Calibration of the models appeared good.Nomograms incorporating pretreatment variables (clinical stage, Gleason grade, PSA and the amount of cancer in a systematic biopsy specimen) can predict the probability that a man with prostate cancer has an indolent tumor. These nomograms have good discriminatory ability and calibration, and may benefit the patient and clinician when the various treatment options for prostate cancer are being considered.