How valid is a prescription-based multimorbidity index (Rx-risk) in predicting mortality in the Outcomes and Multimorbidity In Type 2 diabetes (OMIT) study? A nation-wide registry-based cohort study from Norway

Abstract

Objective The prescription-based Rx-risk index has previously been developed to measure multimorbidity. We aimed to adapt and evaluate the validity of the Rx-risk index in prediction of mortality among persons with type 2 diabetes.

Design Registry-based study.

Setting Adults with type 2 diabetes in Norway identified within the ‘Outcomes and Multimorbidity In Type 2 diabetes’ cohort, with linkage to prescriptions from the Norwegian Prescription Database and mortality from the Population Registry.

Participants We defined a calibration sample of 42 290 adults diagnosed with type 2 diabetes 1950–2013, and a temporal validation sample of 7085 adults diagnosed 2014–2016 to evaluate the index validity over time

Primary outcome measure All-cause mortality

Methods For the calibration sample, dispensed drug prescriptions in 2013 were used to define 44 morbidity categories. Weights were estimated using regression coefficients from a Cox regression model with 5 year mortality as the outcome and all morbidity categories, age and sex included as covariates. The Rx-risk index was computed as a weighted sum of morbidities. The validity of the index was evaluated using C-statistic and calibration plots.

Results In the calibration sample, mean (SD) age at start of follow-up and duration of diabetes was 63.8 (12.4) and 10.1 (7.0) years, respectively. The overall C-statistic was 0.82 and varied from 0.74 to 0.85 when stratifying on age groups, sex, level of education and country of origin. In the validation sample, mean (SD) age and duration of diabetes was 59.7 (13.0) and 2.0 (0.8) years, respectively. Despite younger age, shorter duration of diabetes and later time period, the C-index was high both in the total sample (0.84) and separately for men (0.83) and women (0.84).

Conclusions The Rx-risk index showed good discrimination and calibration in predicting mortality and thus presents a valid tool to assess multimorbidity among persons with type 2 diabetes.