Improved Long-Term Model Predicts Prostate Cancer Mortality More Accurately,  suggests research

Dr. Shravani Dali

Improved Long-Term Model Predicts Prostate Cancer Mortality More Accurately, suggests research

Written By : Dr. Shravani Dali Published On 2026-01-23T23:00:47+05:30 | Updated On 23 Jan 2026 11:01 PM IST

A newly developed long-term prediction model demonstrated greater accuracy in estimating prostate cancer–specific mortality compared with existing risk assessment tools. Unlike traditional models, it incorporates the competing risk of death from other causes, which contributes significantly to its improved predictive performance. The findings, published in Annals of Internal Medicine, suggest this model may better support long-term prognostication and clinical decision-making in prostate cancer care.

Despite the scale of prostate-specific antigen (PSA) testing for prostate cancer (PCa) screening, prediction models do not predict time-to-event end points or adjust for patient life expectancy. A study was done to develop, externally validate, and compare to existing tools a novel prognostic model for risk for prostate cancer–specific mortality (PCSM) after a prostate-specific antigen test. Prognostic model development in the PCa screening group of the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial; external validation in a Veterans Affairs (VA) population of patients undergoing prostate-specific antigen testing. Prostate, Lung, Colorectal and Ovarian patients were enrolled from 1993 to 2001, and VA patients underwent prostate-specific antigen testing from 2002 to 2006. Survival follow-up was updated through 2022 in both cohorts. Male patients aged 55 to 74 years in the Prostate, Lung, Colorectal and Ovarian PCa screening group (n = 33 339) and the VA Healthcare System (n = 174 787). The model’s predicted outcome is prostate cancer–specific mortality at a specified time point; predictors included prostate-specific antigen level, family history of PCa, and race. Predictors of other-cause mortality included age; body mass index; smoking status; and presence of hypertension, diabetes, or stroke.

Results: In the model development cohort, the area under the receiver operating characteristic curve (AUC) at 29.5 years from screening was 0.666 compared with 0.643 for a previously validated prostate biopsy risk model (Prostate Biopsy Collaborative Group [PBCG]) (P < 0.001). In the external validation cohort, the AUC at 20 years from screening was 0.776 for the Prostate, Lung, Colorectal and Ovarian model versus 0.749 for the PBCG model (P = 0.031). The model may not be generalizable to more contemporary prostate-specific antigen screening practices given the periods studied. This prostate cancer–specific mortality prognostic model was developed from long-term clinical trial data, was externally validated in a large national cohort, and may be used to improve interpretation of prostate-specific antigen results.

Reference:

Patrick Lewicki, Ralph Jiang, Archana Radhakrishnan, et al. Predicting Long-Term Risk for Prostate Cancer Mortality Following a Prostate-Specific Antigen Screening Test: Prognostic Model Development and External Validation. Ann Intern Med. [Epub 13 January 2026]. doi:10.7326/ANNALS-25-02036

Keywords:

Improved, Long-Term, Model, Predicts, Prostate, Cancer, Mortality, More, Accurately, Patrick Lewicki, Ralph Jiang, Archana Radhakrishnan

ImprovedLong-TermModelPredictsProstateCancerMortalityMoreAccurately

Source : Annals of Internal Medicine.

Dr. Shravani Dali

Dr. Shravani Dali has completed her BDS from Pravara institute of medical sciences, loni. Following which she extensively worked in the healthcare sector for 2+ years. She has been actively involved in writing blogs in field of health and wellness. Currently she is pursuing her Masters of public health-health administration from Tata institute of social sciences. She can be contacted at editorial@medicaldialogues.in.