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External validation of the OHTS-EGPS model for predicting the 5-year risk of open-angle glaucoma in ocular hypertensives

机译:OHTS-EGPS模型的外部验证,用于预测高眼压性青光眼的5年风险

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Aims: To independently evaluate and compare the performance of the Ocular Hypertension Treatment Study-European Glaucoma Prevention Study (OHTSEGPS) prediction equation for estimating the 5-year risk of open-angle glaucoma (OAG) in four cohorts of adults with ocular hypertension. Methods: Data from two randomised controlled trials and two observational studies were analysed individually to assess transferability of the prediction equation between different geographical locations and settings. To make best use of the data and to avoid bias, missing predictor values were imputed using multivariate imputation by chained equations. Using the OHTS-EGPS risk prediction equation, predicted risk was calculated for each patient in each cohort. We used the c-index, calibration plot and calibration slope to evaluate predictive ability of the equation. Results: Analyses were based on 393, 298, 188 and 159 patients for the Rotterdam, Moorfields, Dunfermline, and Nottingham cohorts, respectively. The discriminative ability was good, with c-indices between 0.69 and 0.83. In calibration analyses, the risk of OAG was generally overestimated, although for the Rotterdam cohort the calibration slope was close to 1 (1.09, 95% CI 0.72 to 1.46), the ideal value when there is perfect agreement between predicted and observed risks. Conclusions: The OHTS-EGPS risk prediction equation has predictive utility, but further validation in a population-based setting is needed.
机译:目的:为了独立评估和比较《高眼压症治疗研究》-《欧洲青光眼预防研究》(OHTSEGPS)预测方程的性能,以估算四组成年人高眼压性青光眼(OAG)的5年风险。方法:分别分析来自两项随机对照试验和两项观察性研究的数据,以评估预测方程在不同地理位置和环境之间的可转移性。为了充分利用数据并避免偏差,使用链式方程式的多元插补法来估算缺少的预测值。使用OHTS-EGPS风险预测方程,可以计算每个队列中每个患者的预测风险。我们使用c指数,校准图和校准斜率来评估方程的预测能力。结果:分别基于鹿特丹,Moorfields,Dunfermline和诺丁汉队列的393、298、188和159位患者进行分析。判别能力良好,C指数在0.69至0.83之间。在校准分析中,通常会高估OAG的风险,尽管对于鹿特丹队列而言,校准斜率接近1(1.09,95%CI 0.72至1.46),这是预测风险与观察风险之间完全吻合的理想值。结论:OHTS-EGPS风险预测方程具有预测效用,但需要在基于人群的环境中进行进一步验证。

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