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下肢石膏固定后的静脉血栓形成风险:三项基于人群的病例对照研究中临床预测评分L-TRiP(石膏固定)的推导与验证

Venous Thrombosis Risk after Cast Immobilization of the Lower Extremity: Derivation and Validation of a Clinical Prediction Score, L-TRiP(cast), in Three Population-Based Case-Control Studies.

作者信息

Nemeth Banne, van Adrichem Raymond A, van Hylckama Vlieg Astrid, Bucciarelli Paolo, Martinelli Ida, Baglin Trevor, Rosendaal Frits R, le Cessie Saskia, Cannegieter Suzanne C

机构信息

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.

Department of Orthopaedic Surgery, Leiden University Medical Center, Leiden, the Netherlands.

出版信息

PLoS Med. 2015 Nov 10;12(11):e1001899; discussion e1001899. doi: 10.1371/journal.pmed.1001899. eCollection 2015 Nov.

Abstract

BACKGROUND

Guidelines and clinical practice vary considerably with respect to thrombosis prophylaxis during plaster cast immobilization of the lower extremity. Identifying patients at high risk for the development of venous thromboembolism (VTE) would provide a basis for considering individual thromboprophylaxis use and planning treatment studies. The aims of this study were (1) to investigate the predictive value of genetic and environmental risk factors, levels of coagulation factors, and other biomarkers for the occurrence of VTE after cast immobilization of the lower extremity and (2) to develop a clinical prediction tool for the prediction of VTE in plaster cast patients.

METHODS AND FINDINGS

We used data from a large population-based case-control study (MEGA study, 4,446 cases with VTE, 6,118 controls without) designed to identify risk factors for a first VTE. Cases were recruited from six anticoagulation clinics in the Netherlands between 1999 and 2004; controls were their partners or individuals identified via random digit dialing. Identification of predictor variables to be included in the model was based on reported associations in the literature or on a relative risk (odds ratio) > 1.2 and p ≤ 0.25 in the univariate analysis of all participants. Using multivariate logistic regression, a full prediction model was created. In addition to the full model (all variables), a restricted model (minimum number of predictors with a maximum predictive value) and a clinical model (environmental risk factors only, no blood draw or assays required) were created. To determine the discriminatory power in patients with cast immobilization (n = 230), the area under the curve (AUC) was calculated by means of a receiver operating characteristic. Validation was performed in two other case-control studies of the etiology of VTE: (1) the THE-VTE study, a two-center, population-based case-control study (conducted in Leiden, the Netherlands, and Cambridge, United Kingdom) with 784 cases and 523 controls included between March 2003 and December 2008 and (2) the Milan study, a population-based case-control study with 2,117 cases and 2,088 controls selected between December 1993 and December 2010 at the Thrombosis Center, Fondazione IRCCS Ca' Granda-Ospedale Maggiore Policlinico, Milan, Italy. The full model consisted of 32 predictors, including three genetic factors and six biomarkers. For this model, an AUC of 0.85 (95% CI 0.77-0.92) was found in individuals with plaster cast immobilization of the lower extremity. The AUC for the restricted model (containing 11 predictors, including two genetic factors and one biomarker) was 0.84 (95% CI 0.77-0.92). The clinical model (consisting of 14 environmental predictors) resulted in an AUC of 0.77 (95% CI 0.66-0.87). The clinical model was converted into a risk score, the L-TRiP(cast) score (Leiden-Thrombosis Risk Prediction for patients with cast immobilization score), which showed an AUC of 0.76 (95% CI 0.66-0.86). Validation in the THE-VTE study data resulted in an AUC of 0.77 (95% CI 0.58-0.96) for the L-TRiP(cast) score. Validation in the Milan study resulted in an AUC of 0.93 (95% CI 0.86-1.00) for the full model, an AUC of 0.92 (95% CI 0.76-0.87) for the restricted model, and an AUC of 0.96 (95% CI 0.92-0.99) for the clinical model. The L-TRiP(cast) score resulted in an AUC of 0.95 (95% CI 0.91-0.99). Major limitations of this study were that information on thromboprophylaxis was not available for patients who had plaster cast immobilization of the lower extremity and that blood was drawn 3 mo after the thrombotic event.

CONCLUSIONS

These results show that information on environmental risk factors, coagulation factors, and genetic determinants in patients with plaster casts leads to high accuracy in the prediction of VTE risk. In daily practice, the clinical model may be the preferred model as its factors are most easy to determine, while the model still has good predictive performance. These results may provide guidance for thromboprophylaxis and form the basis for a management study.

摘要

背景

在下肢石膏固定期间,血栓预防的指南和临床实践差异很大。识别静脉血栓栓塞(VTE)发生高危患者可为考虑个体化血栓预防措施的使用及规划治疗研究提供依据。本研究的目的是:(1)调查基因和环境风险因素、凝血因子水平及其他生物标志物对下肢石膏固定后VTE发生的预测价值;(2)开发一种用于预测石膏固定患者VTE的临床预测工具。

方法与结果

我们使用了一项基于大人群的病例对照研究(MEGA研究,4446例VTE患者,6118例无VTE的对照)的数据,该研究旨在确定首次发生VTE的风险因素。病例于1999年至2004年期间从荷兰的6个抗凝诊所招募;对照为其伴侣或通过随机数字拨号识别的个体。模型中纳入预测变量的确定基于文献报道的关联或所有参与者单因素分析中相对风险(比值比)>1.2且p≤0.25。使用多因素逻辑回归创建了一个完整的预测模型。除了完整模型(所有变量)外,还创建了一个受限模型(预测因子数量最少且预测价值最大)和一个临床模型(仅环境风险因素,无需采血或检测)。为确定石膏固定患者(n = 230)的鉴别能力,通过受试者工作特征曲线计算曲线下面积(AUC)。在另外两项VTE病因病例对照研究中进行了验证:(1)THE-VTE研究,一项基于人群的两中心病例对照研究(在荷兰莱顿和英国剑桥进行),2003年3月至2008年12月期间纳入784例病例和523例对照;(2)米兰研究,一项基于人群的病例对照研究,1993年12月至2010年12月期间在意大利米兰Fondazione IRCCS Ca' Granda-Ospedale Maggiore Policlinico血栓中心选取2117例病例和2088例对照。完整模型由32个预测因子组成包括3个基因因素和6个生物标志物。对于该模型,下肢石膏固定个体的AUC为0.85(95%CI 0.77 - 0.92)。受限模型(包含11个预测因子,包括2个基因因素和1个生物标志物)的AUC为0.84(95%CI 0.77 - 0.92)。临床模型(由14个环境预测因子组成)的AUC为0.77(95%CI 0.66 - 0.87)。临床模型转换为风险评分,即L-TRiP(cast)评分(下肢石膏固定患者的莱顿血栓风险预测评分),其AUC为0.76(95%CI 0.66 - 0.86)。在THE-VTE研究数据中的验证显示L-TRiP(cast)评分的AUC为0.77(95%CI 0.58 - 0.96)。在米兰研究中的验证显示完整模型的AUC为0.93(95%CI 0.86 - 1.00),受限模型的AUC为0.92(95%CI 0.76 - 0.87),临床模型的AUC为0.96(95%CI 0.92 - 0.99)。L-TRiP(cast)评分的AUC为0.95(95%CI 0.91 - 0.99)。本研究的主要局限性在于无法获取下肢石膏固定患者的血栓预防信息,且在血栓事件发生3个月后采血。

结论

这些结果表明,石膏固定患者的环境风险因素、凝血因子和基因决定因素信息在预测VTE风险方面具有较高准确性。在日常实践中,临床模型可能是首选模型,因为其因素最容易确定,同时该模型仍具有良好的预测性能。这些结果可为血栓预防提供指导,并为管理研究奠定基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bb68/4640574/53b472387aa0/pmed.1001899.g001.jpg

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