The Value of Claims-Based Nontraditional Risk Factors in Predicting Long-term Mortality After MitraClip Procedure

Background

We sought to identify nontraditional risk factors coded in administrative claims data and evaluate their ability to improve prediction of long-term mortality in patients undergoing percutaneous mitral valve repair.

Methods

Patients undergoing transcatheter mitral valve repair using MitraClip implantation between September 28, 2010, and September 30, 2015 were identified among Medicare fee-for-service beneficiaries. We used nested Cox regression models to identify claims codes predictive of long-term mortality. Four groups of variables were introduced sequentially: cardiac and noncardiac risk factors, presentation characteristics, and nontraditional risk factors.

Results

A total of 3782 patients from 280 clinical sites received treatment with MitraClip over the study period. During the follow-up period, 1114 (29.5%) patients died with a median follow-up time period of 13.6 (9.6 to 17.3) months. The discrimination of a model to predict long-term mortality including only cardiac risk factors was 0.58 (0.55 to 0.60). Model discrimination improved with the addition of noncardiac risk factors (c = 0.63, 0.61 to 0.65; integrated discrimination improvement IDI] = 0.038, P < 0.001), and with the subsequent addition of presentation characteristics (c = 0.67, 0.65 to 0.69; IDI = 0.033, P < 0.001 compared with the second model). Finally, the addition of nontraditional risk factors significantly improved model discrimination (c = 0.70, 0.68 to 0.72; IDI = 0.019, P < 0.001, compared with the third model).

Conclusions

Risk-prediction models, which include nontraditional risk factors as identified in claims data, can be used to predict long-term mortality risk more accurately in patients who have undergone MitraClip procedures.