Treatment effect of high-dose statin therapy estimated by prediction model
Dorresteijn JA, Boekholdt SM, Van der Graaf Y, et al.
High-Dose Statin Therapy in Patients with Stable Coronary Artery Disease: Treating the Right Patients Based on Individualized Prediction of Treatment Effect
Circulation May 14, 2013, doi: 10.1161/CIRCULATIONAHA.112.000712
BackgroundIntensive lipid lowering results in reduction of vascular events in patients with coronary artery disease (CAD) [1-6]. Reluctance may exist about high-dose statin therapy for all patients with stable CAD, caused by concerns about side-effects, costs and need for closer follow-up. Patients most likely to benefit from high-dose statin therapy should be identified. Currently, guidelines recommend dose titration in patients whose LDL-cholesterol is not at target [7,8]. Meta-analyses however show that the reduction of vascular events by statin treatment is independent of pre-treatment LDL-C ; the absolute CV risk reduction by high-dose statin therapy is only proportional to the absolute baseline risk. The aim of this study was to develop and validate a model, based on multiple clinical patient characteristics, for prediction of treatment effect of high-dose versus usual-dose statin therapy in patients with stable CAD. Data from the Treating to New Targets (TNT, n=10,001) trial and the Incremental Decrease in End Points Through Aggressive Lipid Lowering (IDEAL, n=8,888) trial were analyzed [1,2]. Net benefit of strategies to select high-risk patients with stable CAD for high-dose statin therapy were compared.
- Based on data from the TNT, a Cox proportional hazards model was developed comprising 13 easy-to-measure clinical predictors: age, sex, smoking, diabetes mellitus, total cholesterol, HDL-C, systolic blood pressure, history of myocardial infarction, coronary artery bypass grafting, congestive heart failure or abdominal aortic aneurysm, glomerular filtration rate, and treatment status (i.e. atorvastatin 80mg or 10mg).
- The model C-statistic was 0.67 (95%CI 0.65-0.68) in the derivation sample (TNT), and 0.63 (95%CI 0.62-0.65) in the validation sample (IDEAL). The calibration plots of 5-year predicted versus observed event-free survival (i.e. 1-risk) in the derivation and validation sample show that model calibration was excellent. The p-values of the Gronnesby and Borgan tests were 0.65 in the derivation sample and 0.30 in the validation sample, thus confirming satisfactory goodness-of-fit.
- The median absolute reduction of 5-year risk of major cardiovascular events (MCVE) was 2.2% [IQR 1.6-3.1%; 5-year number needed to treat, NNT 45]. However, 41.9% of patients had <2% predicted treatment effect (5-year NNT>50) and 46.4% of patients had 2 to 4% predicted treatment effect (5-year NNT between 25 and 50). A total of 11.7% of patients had >4% predicted reduction of absolute 5-year MCVE risk (5-year NNT <25).
- If treatment of patients with <6% 5-year MCVE-risk with atorvastatin 80mg instead of usual-dose statin is acceptable, the strategy that leads to optimal net benefit is to simply prescribe atorvastatin 80 mg to all. The median treatment effect will then be 2.0% reduction of absolute MCVE risk (effective NNT=49). If a threshold between ~6% and ~23% is considered appropriate, more selective prediction-based treatment can reduce the treatment rate and average NNT.
ConclusionThe incremental treatment effect of high-dose statin therapy over usual-dose statin therapy in individual CAD-patients can be estimated by a prediction model, containing 13 easy-to-measure clinical predictors that are readily available in clinical practice. Predicted treatment effect can be used to guide treatment decisions in clinical practice, which may improve net benefit of therapy.
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