Nassif Michael E, Tang Yuanyuan, Cleland John G, Abraham William T, Linde Cecilia, Gold Michael R, Young James B, Daubert J Claude, Sherfesee Lou, Schaber Dan, Tang Anthony S L, Jones Philip G, Arnold Suzanne V, Spertus John A
From the Division of Cardiology, Saint Luke's Mid America Heart Institute, Kansas City, MO (M.E.N., Y.T., P.G.J., S.V.A., J.A.S.); Division of Bioinformatics, University of Missouri-Kansas City (M.E.N., P.G.J., S.V.A., J.A.S.); Division of Cardiology, National Heart and Lung Institute, Imperial College London, England, United Kingdom (Royal Brompton and Harefield Hospitals) (J.G.C.); Department of Cardiology, Castle Hill Hospital, University of Hull, Kingston upon Hull, United Kingdom (J.G.C.); Division of Cardiovascular Medicine (W.T.A.) and Davis Heart and Lung Research Institute (W.T.A.), Ohio State University, Columbus (W.T.A.); Department of Cardiology, Karolinska University Hospital, Stockholm, Sweden (C.L.); Division of Cardiology, Medical University of South Carolina, Charleston (M.R.G.); Division of Cardiology, Cleveland Clinic Lerner College of Medicine, OH (J.B.Y.); Departement de Cardiologie, CHU Rennes, France (J.C.D.); Medtronic, Inc, Minneapolis, MN (L.S., D.S.); and Division of Cardiology, Island Medical Program, University of British Columbia, Vancouver, Canada (A.S.L.T.).
Circ Heart Fail. 2017 Oct;10(10). doi: 10.1161/CIRCHEARTFAILURE.117.004111.
Clinical trials have established the average benefit of cardiac resynchronization therapy (CRT), but estimating benefit for individual patients remains difficult because of the heterogeneity in treatment response. Accordingly, we created a multivariable model to predict changes in quality of life (QoL) with and without CRT.
Patient-level data from 5 randomized trials comparing CRT with no CRT were used to create a prediction model of change in QoL at 3 months using a partial proportional odds model for no change, small, moderate, and large improvement, or deterioration of any magnitude. The C statistics for not worsening or obtaining at least a small, moderate, and large improvement were calculated. Among the 3614 patients, regardless of assigned treatment, 33.3% had a deterioration in QoL, 9.2% had no change, 9.2% had a small improvement, 13.5% had a moderate improvement, and the remaining 34.9% had a large improvement. Patients undergoing CRT were less likely to have a decrement in their QoL (28.2% versus 38.9%; <0.001) and more likely to have a large QoL improvement (38.7% versus 30.6%; <0.001). A partial proportional odds model identified baseline QoL, age, and an interaction of CRT with QRS duration as predictors of QoL benefits 3 months after randomization. C statistics of 0.65 for not worsening, 0.68 for at least a small improvement, 0.69 for at least a moderate improvement, and 0.73 for predicting a large improvement were observed.
There is marked heterogeneity of treatment benefit of CRT that can be predicted based on baseline QoL, age, and QRS duration.
临床试验已确定心脏再同步治疗(CRT)的平均获益,但由于治疗反应存在异质性,估计个体患者的获益仍然困难。因此,我们创建了一个多变量模型来预测接受和未接受CRT时生活质量(QoL)的变化。
来自5项比较CRT与非CRT的随机试验的患者水平数据用于创建一个预测模型,该模型使用部分比例优势模型来预测随机分组3个月时QoL无变化、小幅改善、中度改善、大幅改善或任何程度恶化的情况。计算未恶化或至少获得小幅、中度和大幅改善的C统计量。在3614例患者中,无论分配何种治疗,33.3%的患者QoL恶化,9.2%无变化,9.2%有小幅改善,13.5%有中度改善,其余34.9%有大幅改善。接受CRT的患者QoL下降的可能性较小(28.2%对38.9%;<0.001),且QoL大幅改善的可能性较大(38.7%对30.6%;<0.001)。一个部分比例优势模型确定基线QoL、年龄以及CRT与QRS时限的相互作用为随机分组3个月后QoL获益的预测因素。观察到未恶化的C统计量为0.65,至少有小幅改善的为0.68,至少有中度改善的为0.69,预测有大幅改善的为0.73。
CRT治疗获益存在显著异质性,可根据基线QoL、年龄和QRS时限进行预测。