The medication-based Rx-Risk Comorbidity Index and risk of hip fracture - a nationwide NOREPOS cohort study.

BACKGROUND: Few previous studies have assessed overall morbidity at the individual level with respect to future risk of hip fracture. The aim of this register-based cohort study was to examine the association between morbidity measured by the medication-based Rx-Risk Comorbidity Index (Rx-Risk) and the risk of first hip fracture. METHODS: Individual-level data on medications dispensed from pharmacies (2005-2016) was retrieved from the Norwegian Prescription Database and used to calculate Rx-Risk for each calendar year. Information on first hip fractures (2006-2017) was obtained from a nationwide hip fracture database. Individuals ≥ 51 years who filled at least one prescription during the study period comprised the population at risk. Using Rx-Risk as a time-varying exposure variable, relative risk estimates were obtained by a negative binomial model. RESULTS: During 2006-2017, 94,104 individuals sustained a first hip fracture. A higher Rx-Risk was associated with increased risk of hip fracture within all categories of age and sex. Women with the highest Rx-Risk (> 25) had a relative risk of 6.1 (95% confidence interval (CI): 5.4, 6.8) compared to women with Rx-Risk ≤ 0, whereas the corresponding relative risk in women with Rx-Risk 1-5 was 1.4 (95% CI: 1.3, 1.4). Similar results were found in men. Women > 80 years with Rx-Risk 21-25 had the highest incidence rate (514 (95% CI: 462, 566) per 10, 000 person years). The relative increase in hip fracture risk with higher Rx-Risk was most pronounced in the youngest patients aged 51-65 years. CONCLUSIONS: Rx-Risk is a strong predictor of hip fracture in the general outpatient population and may be useful to identify individuals at risk in a clinical setting and in future studies.

Validation of the cardiovascular risk model NORRISK 2 in South Asians and people with diabetes.

OBJECTIVES: To evaluate the predictive ability of the previously published NORRISK 2 cardiovascular risk model in Norwegian-born and immigrants born in South Asia living in Norway, and to add information about diabetes and ethnicity in an updated model for South Asians and diabetics (NORRISK 2-SADia). Design. We included participants (30-74 years) born in Norway (n = 13,885) or South Asia (n = 1942) from health surveys conducted in Oslo 2000-2003. Cardiovascular disease (CVD) risk factor information including self-reported diabetes was linked with information on subsequent acute myocardial infarction (AMI) and acute cerebral stroke in hospital and mortality registry data throughout 2014 from the nationwide CVDNOR project. We developed an updated model using Cox regression with diabetes and South Asian ethnicity as additional predictors. We assessed model performance by Harrell's C and calibration plots. Results. The NORRISK 2 model underestimated the risk in South Asians in all quintiles of predicted risk. The mean predicted 13-year risk by the NORRISK 2 model was 3.9% (95% CI 3.7-4.2) versus observed 7.3% (95% CI 5.9-9.1) in South Asian men and 1.1% (95% CI 1.0-1.2) versus 2.7% (95% CI 1.7-4.2) observed risk in South Asian women. The mean predictions from the NORRISK 2-SADia model were 7.2% (95% CI 6.7-7.6) in South Asian men and 2.7% (95% CI 2.4-3.0) in South Asian women. Conclusions. The NORRISK 2-SADia model improved predictions of CVD substantially in South Asians, whose risks were underestimated by the NORRISK 2 model. The NORRISK 2-SADia model may facilitate more intense preventive measures in this high-risk population.

Performance of a Framingham cardiovascular risk model among Indians and Europeans in New Zealand and the role of body mass index and social deprivation.

Objectives: To evaluate a Framingham 5-year cardiovascular disease (CVD) risk score in Indians and Europeans in New Zealand, and determine whether body mass index (BMI) and socioeconomic deprivation were independent predictors of CVD risk. Methods: We included Indians and Europeans, aged 30-74 years without prior CVD undergoing risk assessment in New Zealand primary care during 2002-2015 (n=256 446). Risk profiles included standard Framingham predictors (age, sex, systolic blood pressure, total cholesterol/high-density lipoprotein ratio, smoking and diabetes) and were linked with national CVD hospitalisations and mortality datasets. Discrimination was measured by the area under the receiver operating characteristics curve (AUC) and calibration examined graphically. We used Cox regression to study the impact of BMI and deprivation on the risk of CVD with and without adjustment for the Framingham score. Results: During follow-up, 8105 and 1156 CVD events occurred in Europeans and Indians, respectively. Higher AUCs of 0.76 were found in Indian men (95% CI 0.74 to 0.78) and women (95% CI 0.73 to 0.78) compared with 0.74 (95% CI 0.73 to 0.74) in European men and 0.72 (95% CI 0.71 to 0.73) in European women. Framingham was best calibrated in Indian men, and overestimated risk in Indian women and in Europeans. BMI and deprivation were positively associated with CVD, also after adjustment for the Framingham risk score, although the BMI association was attenuated. Conclusions: The Framingham risk model performed reasonably well in Indian men, but overestimated risk in Indian women and in Europeans. BMI and socioeconomic deprivation could be useful predictors in addition to a Framingham score.