Development and Validation of a Model to Predict Absolute Vascular Risk Reduction by Moderate-Intensity Statin Therapy in Individual Patients With Type 2 Diabetes Mellitus

Abstract

Statin therapy is effective in preventing major cardiovascular events in patients with type 2 diabetes mellitus with an average relative risk reduction that is similar to the effect of statins in patients without type 2 diabetes mellitus.1 Based on this, guidelines recommend statin therapy for most patients with type 2 diabetes mellitus. 2,3 In clinical practice, decisionBackground-In this study, we aimed to translate the average relative effect of statin therapy from trial data to the individual patient with type 2 diabetes mellitus by developing and validating a model to predict individualized absolute risk reductions (ARR) of cardiovascular events. Methods and Results-Data of 2725 patients with type 2 diabetes mellitus from the Lipid Lowering Arm of the AngloScandinavian Cardiac Outcomes Trial (ASCOT-LLA) study (atorvastatin 10 mg versus placebo) were used for model derivation. The model was based on 8 clinical predictors including treatment allocation (statin/placebo). Ten-year individualized ARR on major cardiovascular events by statin therapy were calculated for each patient by subtracting the estimated on-treatment risk from the estimated off-treatment risk. Predicted 10-year ARR by statin therapy was <2% for 13% of the patients. About 30% had an ARR of >4% (median ARR, 3.2%; interquartile range, 2.5%-4.3%; 95% confidence interval for 3.2% ARR, -1.4% to 6.8%). Addition of treatment interactions did not improve model performance. Therefore, the wide distribution in ARR was a consequence of the underlying distribution in cardiovascular risk enrolled in these trials. External validation of the model was performed in data from the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT-LLT; pravastatin 40 mg versus usual care) and Collaborative Atorvastatin Diabetes Study (CARDS; atorvastatin 10 mg versus placebo) of 3878 and 2838 patients with type 2 diabetes mellitus, respectively. Model calibration was adequate in both external data sets, discrimination was moderate 0.64 [95% confidence interval,

Development of predictive risk models for major adverse cardiovascular events among patients with type 2 diabetes mellitus using health insurance claims data

“…The finding that age was one of the most important risk factor in predicting cardiovascular events is consistent with findings in previous studies that primarily focused on a diabetes population, such as the UKPDS risk engine [ 21 , 23 ] and studies that focused on a general population, such as the Framingham Heart Study [ 12 ]. However, a major difference between the models developed in the current study and previous ones is that the latter included risk factors derived from laboratory results and medical records [ 12 , 17 , 18 , 20 – 22 ], which are often not available to national quality of care organizations and payers. In contrast, the current study used only information that is readily available from medical claims data.…”

“…The ADVANCE model, developed in a population of diabetic patients at risk of cardiovascular events similar to the secondary prevention population in this study, also presented comparable C-statistics of 0.69-0.70 [ 22 ]. Moreover, several other multivariate risk models were published and reported C-statistics ranging between 0.64 and 0.70 [ 17 , 18 , 20 ]. A comprehensive external validation study would be needed to evaluate the performance of the different models on the same cohort of patients [ 42 ].…”

A Practical Statin Recommendation System Based on Real-World Data to Improve LDL-C Management in Secondary Prevention

“…In addition, some models have recently been developed to predict the prognosis of cardiovascular disease and the choice of drugs. The multivariate model developed by Kaasenbrood et al 15 could predict the treatment benefits of statins in patients with type 2 diabetes and translate the average treatment benefit of statins into individualized risk reduction, which is believed to be more helpful for clinical decision making. The ABCD-GENE score, 16 which combines genotyping and patient clinical characteristics (Age, Body Mass Index, Chronic Kidney Disease, and Diabetes Mellitus), was developed to guide the selection of P2Y12 inhibitors for patients with acute coronary syndromes.…”

Yield, NNS and prevalence of screening for DM and hypertension among pulmonary tuberculosis index cases and contacts through single time screening: A contact tracing-based study

“…The NNS was computed by dividing the NNT for risk factors by PrC. The NNT was computed through one divided by the ARR of the interested disease, which equals the risk off treatment minus the risk on treatment [31]. We obtained the estimates for ARR of DM [31] and hypertension [32] for our study from the previous studies.…”