Quantifying treatment benefit for individuals: using means and accounting for competing risks

Music City Center 

Background: Personalized estimates of treatment benefit allow for informed decision making.
Methods: Using the addition of ADT to RT in prostate cancer as an example, we calculate and compare measures of treatment benefit using differences in probability vs differences in mean times. We utilize a novel data integration approach to calculate the absolute risk of PCSM (cancer mortality) and MFS (mets free survival) within 15 years using patient level covariates for both cancer outcomes and competing mortality risk. We calculate Mean MFS times unrestricted and restricted to 15 years. We calculated each of these measures for individual patients in a contemporary cohort of >1000 patients enrolled in a statewide quality consortium.
Results: The 15-year risk of PCSM for a stage IIC patient treated with RT+ADT varies from 7% to 15% at the 10th vs 90th percentile of competing mortality risk. For men in the same UIR risk group, ADT reduced the risk of mets at 10 years by an average of 4%, but the 10th and 90th percentiles were 1% and 14%, respectively.
Conclusions: Accounting for individual competing risk levels is important when estimating treatment benefit.

Data Integration

Survival Analysis

Competing risks

Treatment efficacy

Personalized medicine 

Biopharmaceutical Section