监测 5-氨基水杨酸盐毒性:预后模型的开发与验证。

Abhishek Abhishek, Georgina Nakafero, Matthew J Grainge, Tim Card, Maarten W Taal, Guruprasad Aithal, Christopher P Fox, Christain D Mallen, Stevenson D Matthew, Richard D Riley
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引用次数: 0

摘要

背景和目的:开发并验证用于风险分级监测 5- 氨基水杨酸盐(5-ASA)毒性的预后模型。方法这项全国性的回顾性队列研究使用了临床实践研究数据链(CPRD)Aurum 和 Gold 的数据,分别用于模型的开发和验证。研究对象包括2007年1月1日至2019年12月31日期间新诊断为炎症性肠病(IBD)并服用5-ASA的成人。停用 5-ASA 并伴有监测血液检测结果异常是研究的主要结果。对服用5-ASA≥6个月的患者(即确定接受治疗的患者)进行长达5年的随访。采用惩罚性 Cox 回归建立风险方程。根据校准和区分度对模型性能进行评估。使用 STATA (StataCorp LLC) 进行统计分析。结果开发组和验证组分别有 14109 和 7523 名参与者,分别发生了 401 和 243 起事件。在衍生队列中,分别有 185 人、172 人和 64 人因细胞减少症、肌酐升高和肝酶升高而中止治疗。有害酒精摄入、慢性肾病、硫嘌呤的使用以及随访前血液检测异常都是强有力的预后因素。开发数据的乐观调整 R2D 为 0.08。验证队列中的校准斜率和罗伊斯顿 D 统计量(95% 置信区间)分别为 0.90 (0.61-1.19) 和 0.57 (0.37-0.77)。结论该预后模型利用了常规临床护理过程中可获得的信息,可用于为监测血液检测间隔时间的决策提供依据。指南编写小组应考虑本研究的结果,以便在既定的 5-ASA 治疗期间对血液检测监测进行风险分级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Monitoring for 5-aminosalicylate toxicity: prognostic model development and validation.
Background and aim: To develop and validate a prognostic model for risk-stratified monitoring of 5-aminosalicylate (5-ASA) toxicity. Methods: This nationwide retrospective cohort study used data from the Clinical Practice Research Datalink (CPRD) Aurum and Gold for model development and validation respectively. It included adults newly diagnosed with inflammatory bowel disease (IBD) and established on 5-ASAs between 01/01/2007 and 31/12/2019. 5-ASA discontinuation with abnormal monitoring blood test result was the outcome of interest. Patients prescribed 5-ASAs for ≥6 months i.e., established on treatment, were followed-up for up to five years. Penalised Cox-regression was used to develop the risk equation. Model performance was assessed in terms of calibration and discrimination. Statistical analysis was performed using STATA (StataCorp LLC). Results: 14,109 and 7,523 participants formed the development and validation cohorts with 401 and 243 events respectively. 185, 172, and 64 discontinuations were due to cytopenia, elevated creatinine and elevated liver enzymes respectively in the derivation cohort. Hazardous alcohol intake, chronic kidney disease, thiopurine use, and blood test abnormalities before follow-up were strong prognostic factors. The optimism adjusted R2D in development data was 0.08. The calibration slope and Royston D statistic (95% Confidence Interval) in validation cohort were 0.90 (0.61-1.19) and 0.57 (0.37-0.77) respectively. Conclusion: This prognostic model utilises information available during routine clinical care and can be used to inform decisions on the interval between monitoring blood-tests. The results of this study ought to be considered by guideline writing groups to risk-stratify blood test monitoring during established 5-ASA treatment.
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