{"title":"基于中国老年患者血清沉默信息调节剂6水平预测模型的建立和验证:横断面描述性研究。","authors":"Yuzi You, Wei Liang, Yajie Zhao","doi":"10.2196/64374","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Serum levels of silent information regulator 6 (SIRT6), a key biomarker of aging, were identified as a predictor of coronary artery disease (CAD), but whether SIRT6 can distinguish severity of coronary artery lesions in older adult patients is unknown.</p><p><strong>Objectives: </strong>This study developed a nomogram to demonstrate the functionality of SIRT6 in assessing severity of coronary artery atherosclerosis.</p><p><strong>Methods: </strong>Patients aged 60 years and older with angina pectoris were screened for this single-center clinical study between October 1, 2022, and March 31, 2023. Serum specimens of eligible patients were collected for SIRT6 detection by enzyme-linked immunosorbent assay. Clinical data and putative predictors, including 29 physiological characteristics, biochemical parameters, carotid artery ultrasonographic results, and complete coronary angiography findings, were evaluated, with CAD diagnosis as the primary outcome. The nomogram was derived from the Extreme Gradient Boosting (XGBoost) model, with logistic regression for variable selection. Model performance was assessed by examining discrimination, calibration, and clinical use separately. A 10-fold cross-validation technique was used to compare all models. The models' performance was further evaluated on the internal validation set to ensure that the obtained results were not due to overoptimization.</p><p><strong>Results: </strong>Eligible patients (n=222) were divided into 2 cohorts: the development cohort (n=178) and the validation cohort (n=44). Serum SIRT6 levels were identified as both an independent risk factor and a predictor for CAD in older adults. The area under the receiver operating characteristic curve (AUROC) was 0.725 (95% CI 0.653-0.797). The optimal cutoff value of SIRT6 for predicting CAD was 546.384 pg/mL. Predictors included in this nomogram were serum SIRT6 levels, triglyceride glucose (TyG) index, and apolipoprotein B. The model achieved an AUROC of 0.956 (95% CI 0.928-0.983) in the development cohort. Similarly, in the internal validation cohort, the AUROC was 0.913 (95% CI 0.828-0.999). All models demonstrated satisfactory calibration, with predicted outcomes closely aligning with actual results.</p><p><strong>Conclusions: </strong>SIRT6 shows promise in predicting CAD, with enhanced predictive abilities when combined with the TyG index. In clinical settings, monitoring fluctuations in SIRT6 and TyG may offer valuable insights for early CAD detection. The nomogram for CAD outcome prediction in older adult patients with angina pectoris may aid in clinical trial design and personalized clinical decision-making, particularly in institutions where SIRT6 is being explored as a biomarker for aging or cardiovascular health.</p>","PeriodicalId":36245,"journal":{"name":"JMIR Aging","volume":"8 ","pages":"e64374"},"PeriodicalIF":5.0000,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11758378/pdf/","citationCount":"0","resultStr":"{\"title\":\"Development and Validation of a Predictive Model Based on Serum Silent Information Regulator 6 Levels in Chinese Older Adult Patients: Cross-Sectional Descriptive Study.\",\"authors\":\"Yuzi You, Wei Liang, Yajie Zhao\",\"doi\":\"10.2196/64374\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Serum levels of silent information regulator 6 (SIRT6), a key biomarker of aging, were identified as a predictor of coronary artery disease (CAD), but whether SIRT6 can distinguish severity of coronary artery lesions in older adult patients is unknown.</p><p><strong>Objectives: </strong>This study developed a nomogram to demonstrate the functionality of SIRT6 in assessing severity of coronary artery atherosclerosis.</p><p><strong>Methods: </strong>Patients aged 60 years and older with angina pectoris were screened for this single-center clinical study between October 1, 2022, and March 31, 2023. Serum specimens of eligible patients were collected for SIRT6 detection by enzyme-linked immunosorbent assay. Clinical data and putative predictors, including 29 physiological characteristics, biochemical parameters, carotid artery ultrasonographic results, and complete coronary angiography findings, were evaluated, with CAD diagnosis as the primary outcome. The nomogram was derived from the Extreme Gradient Boosting (XGBoost) model, with logistic regression for variable selection. Model performance was assessed by examining discrimination, calibration, and clinical use separately. A 10-fold cross-validation technique was used to compare all models. The models' performance was further evaluated on the internal validation set to ensure that the obtained results were not due to overoptimization.</p><p><strong>Results: </strong>Eligible patients (n=222) were divided into 2 cohorts: the development cohort (n=178) and the validation cohort (n=44). Serum SIRT6 levels were identified as both an independent risk factor and a predictor for CAD in older adults. The area under the receiver operating characteristic curve (AUROC) was 0.725 (95% CI 0.653-0.797). The optimal cutoff value of SIRT6 for predicting CAD was 546.384 pg/mL. Predictors included in this nomogram were serum SIRT6 levels, triglyceride glucose (TyG) index, and apolipoprotein B. The model achieved an AUROC of 0.956 (95% CI 0.928-0.983) in the development cohort. Similarly, in the internal validation cohort, the AUROC was 0.913 (95% CI 0.828-0.999). All models demonstrated satisfactory calibration, with predicted outcomes closely aligning with actual results.</p><p><strong>Conclusions: </strong>SIRT6 shows promise in predicting CAD, with enhanced predictive abilities when combined with the TyG index. In clinical settings, monitoring fluctuations in SIRT6 and TyG may offer valuable insights for early CAD detection. The nomogram for CAD outcome prediction in older adult patients with angina pectoris may aid in clinical trial design and personalized clinical decision-making, particularly in institutions where SIRT6 is being explored as a biomarker for aging or cardiovascular health.</p>\",\"PeriodicalId\":36245,\"journal\":{\"name\":\"JMIR Aging\",\"volume\":\"8 \",\"pages\":\"e64374\"},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2025-01-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11758378/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JMIR Aging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2196/64374\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GERIATRICS & GERONTOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JMIR Aging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2196/64374","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GERIATRICS & GERONTOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
背景:血清沉默信息调节因子6 (SIRT6)水平是衰老的关键生物标志物,已被确定为冠状动脉疾病(CAD)的预测因子,但SIRT6是否可以区分老年患者冠状动脉病变的严重程度尚不清楚。目的:本研究开发了一种图来证明SIRT6在评估冠状动脉粥样硬化严重程度方面的功能。方法:在2022年10月1日至2023年3月31日期间,筛选年龄在60岁及以上的心绞痛患者进行单中心临床研究。收集符合条件的患者血清标本,采用酶联免疫吸附法检测SIRT6。临床资料和推测的预测因素,包括29项生理特征、生化参数、颈动脉超声结果和完整的冠状动脉造影结果,以CAD诊断为主要结果进行评估。nomogram来源于Extreme Gradient Boosting (XGBoost)模型,并使用logistic回归进行变量选择。通过分别检查鉴别、校准和临床使用来评估模型的性能。采用10倍交叉验证技术对所有模型进行比较。在内部验证集上进一步评估模型的性能,以确保获得的结果不是由于过度优化。结果:符合条件的患者(n=222)分为2个队列:发展队列(n=178)和验证队列(n=44)。血清SIRT6水平被确定为老年人CAD的独立危险因素和预测因子。受试者工作特征曲线下面积(AUROC)为0.725 (95% CI 0.653-0.797)。SIRT6预测CAD的最佳临界值为546.384 pg/mL。该nomogram预测因子包括血清SIRT6水平、甘油三酯葡萄糖(TyG)指数和载脂蛋白b。该模型在发展队列中的AUROC为0.956 (95% CI 0.928-0.983)。同样,在内部验证队列中,AUROC为0.913 (95% CI 0.828-0.999)。所有模型都显示出令人满意的校准,预测结果与实际结果密切一致。结论:SIRT6在预测CAD方面显示出希望,与TyG指数结合时,其预测能力增强。在临床环境中,监测SIRT6和TyG的波动可能为早期CAD检测提供有价值的见解。老年心绞痛患者CAD结果预测的nomogram (nomogram)可能有助于临床试验设计和个性化临床决策,特别是在SIRT6作为衰老或心血管健康生物标志物进行探索的机构中。
Development and Validation of a Predictive Model Based on Serum Silent Information Regulator 6 Levels in Chinese Older Adult Patients: Cross-Sectional Descriptive Study.
Background: Serum levels of silent information regulator 6 (SIRT6), a key biomarker of aging, were identified as a predictor of coronary artery disease (CAD), but whether SIRT6 can distinguish severity of coronary artery lesions in older adult patients is unknown.
Objectives: This study developed a nomogram to demonstrate the functionality of SIRT6 in assessing severity of coronary artery atherosclerosis.
Methods: Patients aged 60 years and older with angina pectoris were screened for this single-center clinical study between October 1, 2022, and March 31, 2023. Serum specimens of eligible patients were collected for SIRT6 detection by enzyme-linked immunosorbent assay. Clinical data and putative predictors, including 29 physiological characteristics, biochemical parameters, carotid artery ultrasonographic results, and complete coronary angiography findings, were evaluated, with CAD diagnosis as the primary outcome. The nomogram was derived from the Extreme Gradient Boosting (XGBoost) model, with logistic regression for variable selection. Model performance was assessed by examining discrimination, calibration, and clinical use separately. A 10-fold cross-validation technique was used to compare all models. The models' performance was further evaluated on the internal validation set to ensure that the obtained results were not due to overoptimization.
Results: Eligible patients (n=222) were divided into 2 cohorts: the development cohort (n=178) and the validation cohort (n=44). Serum SIRT6 levels were identified as both an independent risk factor and a predictor for CAD in older adults. The area under the receiver operating characteristic curve (AUROC) was 0.725 (95% CI 0.653-0.797). The optimal cutoff value of SIRT6 for predicting CAD was 546.384 pg/mL. Predictors included in this nomogram were serum SIRT6 levels, triglyceride glucose (TyG) index, and apolipoprotein B. The model achieved an AUROC of 0.956 (95% CI 0.928-0.983) in the development cohort. Similarly, in the internal validation cohort, the AUROC was 0.913 (95% CI 0.828-0.999). All models demonstrated satisfactory calibration, with predicted outcomes closely aligning with actual results.
Conclusions: SIRT6 shows promise in predicting CAD, with enhanced predictive abilities when combined with the TyG index. In clinical settings, monitoring fluctuations in SIRT6 and TyG may offer valuable insights for early CAD detection. The nomogram for CAD outcome prediction in older adult patients with angina pectoris may aid in clinical trial design and personalized clinical decision-making, particularly in institutions where SIRT6 is being explored as a biomarker for aging or cardiovascular health.