Mehrdad Valipour, Davood Khalili, Masoud Solaymani-Dodaran, Seyed Abbas Motevalian, Mohammad Ebrahim Khamseh, Hamid Reza Baradaran
{"title":"伊朗国家糖尿病项目中确定的2型糖尿病患者的英国前瞻性糖尿病研究(UKPDS)风险引擎的外部验证","authors":"Mehrdad Valipour, Davood Khalili, Masoud Solaymani-Dodaran, Seyed Abbas Motevalian, Mohammad Ebrahim Khamseh, Hamid Reza Baradaran","doi":"10.1007/s40200-023-01224-2","DOIUrl":null,"url":null,"abstract":"Cardiovascular diseases are the first leading cause of mortality in the world. Practical guidelines recommend an accurate estimation of the risk of these events for effective treatment and care. The UK Prospective Diabetes Study (UKPDS) has a risk engine for predicting CHD risk in patients with type 2 diabetes, but in some countries, it has been shown that the risk of CHD is poorly estimated. Hence, we assessed the external validity of the UKPDS risk engine in patients with type 2 diabetes identified in the national diabetes program in Iran. The cohort included 853 patients with type 2diabetes identified between March 21, 2007, and March 20, 2018 in Lorestan province of Iran. Patients were followed for the incidence of CHD. The performance of the models was assessed in terms of discrimination and calibration. Discrimination was examined using the c-statistic and calibration was assessed with the Hosmer–Lemeshow χ2 statistic (HLχ2) test and a calibration plot was depicted to show the predicted risks versus observed ones. During 7464.5 person-years of follow-up 170 first Coronary heart disease occurred. The median follow-up was 8.6 years. The UKPDS risk engine showed moderate discrimination for CHD (c-statistic was 0.72 for 10-year risk) and the calibration of the UKPDS risk engine was poor (HLχ2 = 69.9, p < 0.001) and the UKPDS risk engine78% overestimated the risk of heart disease in patients with type 2 diabetes identified in the national diabetes program in Iran. This study shows that the ability of the UKPDS Risk Engine to discriminate patients who developed CHD events from those who did not; was moderate and the ability of the risk prediction model to accurately predict the absolute risk of CHD (calibration) was poor and it overestimated the CHD risk. To improve the prediction of CHD in patients with type 2 diabetes, this model should be updated in the Iranian diabetic population.","PeriodicalId":15604,"journal":{"name":"Journal of Diabetes & Metabolic Disorders","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"External validation of the UK prospective diabetes study (UKPDS) risk engine in patients with type 2 diabetes identified in the national diabetes program in Iran\",\"authors\":\"Mehrdad Valipour, Davood Khalili, Masoud Solaymani-Dodaran, Seyed Abbas Motevalian, Mohammad Ebrahim Khamseh, Hamid Reza Baradaran\",\"doi\":\"10.1007/s40200-023-01224-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cardiovascular diseases are the first leading cause of mortality in the world. Practical guidelines recommend an accurate estimation of the risk of these events for effective treatment and care. The UK Prospective Diabetes Study (UKPDS) has a risk engine for predicting CHD risk in patients with type 2 diabetes, but in some countries, it has been shown that the risk of CHD is poorly estimated. Hence, we assessed the external validity of the UKPDS risk engine in patients with type 2 diabetes identified in the national diabetes program in Iran. The cohort included 853 patients with type 2diabetes identified between March 21, 2007, and March 20, 2018 in Lorestan province of Iran. Patients were followed for the incidence of CHD. The performance of the models was assessed in terms of discrimination and calibration. Discrimination was examined using the c-statistic and calibration was assessed with the Hosmer–Lemeshow χ2 statistic (HLχ2) test and a calibration plot was depicted to show the predicted risks versus observed ones. During 7464.5 person-years of follow-up 170 first Coronary heart disease occurred. The median follow-up was 8.6 years. The UKPDS risk engine showed moderate discrimination for CHD (c-statistic was 0.72 for 10-year risk) and the calibration of the UKPDS risk engine was poor (HLχ2 = 69.9, p < 0.001) and the UKPDS risk engine78% overestimated the risk of heart disease in patients with type 2 diabetes identified in the national diabetes program in Iran. This study shows that the ability of the UKPDS Risk Engine to discriminate patients who developed CHD events from those who did not; was moderate and the ability of the risk prediction model to accurately predict the absolute risk of CHD (calibration) was poor and it overestimated the CHD risk. To improve the prediction of CHD in patients with type 2 diabetes, this model should be updated in the Iranian diabetic population.\",\"PeriodicalId\":15604,\"journal\":{\"name\":\"Journal of Diabetes & Metabolic Disorders\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Diabetes & Metabolic Disorders\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s40200-023-01224-2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Diabetes & Metabolic Disorders","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40200-023-01224-2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
心血管疾病是世界上导致死亡的第一大原因。实用指南建议准确估计这些事件的风险,以便进行有效的治疗和护理。英国前瞻性糖尿病研究(UKPDS)有一个预测2型糖尿病患者冠心病风险的风险引擎,但在一些国家,已经表明冠心病的风险估计不准确。因此,我们评估了UKPDS风险引擎在伊朗国家糖尿病计划中确定的2型糖尿病患者中的外部有效性。该队列包括2007年3月21日至2018年3月20日在伊朗洛雷斯坦省发现的853例2型糖尿病患者。随访患者冠心病发生率。从识别和校准两个方面对模型的性能进行了评估。使用c统计量检验差异,使用Hosmer-Lemeshow χ2 (HLχ2)检验评估校准,并绘制校准图以显示预测风险与观察风险。在7464.5人年的随访中,170例首次发生冠心病。中位随访时间为8.6年。UKPDS风险引擎对冠心病的区分程度中等(10年风险的c统计值为0.72),UKPDS风险引擎的校准较差(HLχ2 = 69.9, p < 0.001), UKPDS风险引擎高估了伊朗国家糖尿病计划中确定的2型糖尿病患者的心脏病风险78%。这项研究表明,UKPDS风险引擎能够区分发生冠心病事件的患者和没有发生冠心病事件的患者;风险预测模型准确预测冠心病绝对风险(校正)的能力较差,高估了冠心病风险。为了提高对2型糖尿病患者冠心病的预测,该模型应在伊朗糖尿病人群中进行更新。
External validation of the UK prospective diabetes study (UKPDS) risk engine in patients with type 2 diabetes identified in the national diabetes program in Iran
Cardiovascular diseases are the first leading cause of mortality in the world. Practical guidelines recommend an accurate estimation of the risk of these events for effective treatment and care. The UK Prospective Diabetes Study (UKPDS) has a risk engine for predicting CHD risk in patients with type 2 diabetes, but in some countries, it has been shown that the risk of CHD is poorly estimated. Hence, we assessed the external validity of the UKPDS risk engine in patients with type 2 diabetes identified in the national diabetes program in Iran. The cohort included 853 patients with type 2diabetes identified between March 21, 2007, and March 20, 2018 in Lorestan province of Iran. Patients were followed for the incidence of CHD. The performance of the models was assessed in terms of discrimination and calibration. Discrimination was examined using the c-statistic and calibration was assessed with the Hosmer–Lemeshow χ2 statistic (HLχ2) test and a calibration plot was depicted to show the predicted risks versus observed ones. During 7464.5 person-years of follow-up 170 first Coronary heart disease occurred. The median follow-up was 8.6 years. The UKPDS risk engine showed moderate discrimination for CHD (c-statistic was 0.72 for 10-year risk) and the calibration of the UKPDS risk engine was poor (HLχ2 = 69.9, p < 0.001) and the UKPDS risk engine78% overestimated the risk of heart disease in patients with type 2 diabetes identified in the national diabetes program in Iran. This study shows that the ability of the UKPDS Risk Engine to discriminate patients who developed CHD events from those who did not; was moderate and the ability of the risk prediction model to accurately predict the absolute risk of CHD (calibration) was poor and it overestimated the CHD risk. To improve the prediction of CHD in patients with type 2 diabetes, this model should be updated in the Iranian diabetic population.