Investigators have developed and validated a simple prediction model for other-cause mortality (OCM) among US patients with prostate cancer. These life expectancy estimates may outperform Social Security Administration (SSA) life tables, according to a recent report.
The other-cause comorbidity-adjusted mortality (OCCAM) model, which incorporates 8 predictors of OCM (age, education, marital status, diabetes, hypertension, stroke, body mass index, and smoking), provides more precise estimates of life expectancy. It can be used in accordance with National Comprehensive Cancer Network (NCCN) guidelines “and has high potential to improve quality of care when patient life expectancy is a factor,” a team led by Elizabeth C. Chase, PhD, of the University of Michigan in Ann Arbor, concluded in a paper published in BJU International.
NCCN guidelines generally recommend that men with prostate cancer who have a life expectancy of 10 years or more receive more aggressive treatment appropriate to their cancer stage, whereas men with a life expectancy less than 10 years receive less aggressive treatment. The NCCN recommends using SSA actuarial tables to predict life expectancy, but Dr Chase and colleagues pointed out that research suggests the SSA tables overestimate life expectancy of patients with distant disease and do not adjust for patient comorbidities, “which can have a notable effect on life expectancy.”
The investigators developed the model using data from a training cohort of 2420 participants in the National Health and Nutrition Examination Survey (NHANES), a nationally representative sample of the US non-institutionalized civilian population. They validated the model in a cohort of 8220 men in the Prostate, Lung, Colon, and Ovarian Cancer Screening Trial (PLCO) prostate cohort. In this validation cohort, the model had an area under the curve of 0.75 at 10 years for predicting OCM, the investigators reported.
Using the new model, Dr Chase’s team found substantial variation in life expectancy estimates in prostate cancer within age. They noted, for example, that the life expectancy of a 74-year-old man was 10 years based on SSA predictions, but ranged from 5 years to more than 15 years according to the new model.
“For younger men, SSA predictions were more optimistic because they failed to account for comorbidities that reduce life expectancy,” they wrote. “For older men, SSA predictions were pessimistic because they failed to recognize that elderly men can be very healthy.”
Using the NCCN threshold of a 10-year life expectancy for particular treatment recommendations, the discrepancies between the new model and SSA estimates would have changed NCCN treatment recommendations for nearly 15% of the men in the PLCO trial, Dr Chase’s team reported. The study demonstrated that 12% of men in the trial would have their NCCN-recommended treatment changed by an overly pessimistic prediction from SSA, whereas 2.4% of men in the trial would have their treatment amended by an overly optimistic prediction from SSA.
The new model “adds to the list of OCM prediction models for men with prostate cancer; however, it is unique in its high externally validated predictive performance, simplicity, and usability in diverse patients population,” the authors stated.
Chase EC, Bryant AK, Sun Y, et al. Development and validation of a life expectancy calculator for US patients with prostate cancer. BJU Int. Published online April 3, 2022. doi:10.1111/bju.15740
This article originally appeared on Renal and Urology News