Construction of a risk prediction model for postoperative deep vein thrombosis in lung cancer patients

Huaxi LIU; Haidong WANG; Li NIE; Yanan WEI; Zhao ZHANG; Lei LIU

doi:10.16016/j.2097-0927.202401068

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Construction of a risk prediction model for postoperative deep vein thrombosis in lung cancer patients

Clinical Medicine | 更新时间：2026-01-09

- Construction of a risk prediction model for postoperative deep vein thrombosis in lung cancer patients
- Journal of Army Medical University Vol. 46, Issue 17, Pages: 1994-2001(2024)
- 作者机构：
  
  1.400038 重庆，陆军军医大学(第三军医大学)第一附属医院：预防保健科
  2.400038 重庆，陆军军医大学(第三军医大学)第一附属医院：胸外科
  3.400030 重庆，重庆大学附属肿瘤医院肿瘤内科
  4.400038 重庆，陆军军医大学(第三军医大学)第一附属医院：院办
- 作者简介：
- 基金信息：
  
  the Special Key Project for Technological Innovation and Application Development of Chongqing(CSTB2022TIAD-KPX0148)
- DOI：10.16016/j.2097-0927.202401068
  CLC： R364.15;R619;R734.2
- Received：25 January 2024，
  
  Revised：2024-04-24，
  
  Published：15 September 2024
- 稿件说明：
移动端阅览
Huaxi LIU, Haidong WANG, Li NIE, et al. Construction of a risk prediction model for postoperative deep vein thrombosis in lung cancer patients[J]. Journal of Army Medical University, 2024, 46(17): 1994-2001.
DOI：

Huaxi LIU, Haidong WANG, Li NIE, et al. Construction of a risk prediction model for postoperative deep vein thrombosis in lung cancer patients[J]. Journal of Army Medical University, 2024, 46(17): 1994-2001. DOI： 10.16016/j.2097-0927.202401068.

摘要

目的

探讨肺癌患者术后深静脉血栓形成(deep vein thrombosis，DVT)的独立危险因素，并构建风险预测模型。

方法

收集2019年5月至2023年5月在陆军军医大学第一附属医院胸外科接受肺癌胸腔镜手术的354例住院患者。采用LASSO回归筛选潜在因素后，行多因素Logistic回归筛选危险因素并构建列线图预测模型，通过绘制校准度曲线、接受者操作特征(receiver operating characteristic，ROC)曲线和决策曲线分析法(decision curve analysis，DCA)评价模型的校准度、区分度、灵敏度、特异度及临床有效性。使用净重新分类改善指数(net reclassification index，NRI)和综合判别改善指数(integrated discrimination improvement，IDI)比较本研究构建模型与Caprini模型对于结局事件的预测性能优劣。

结果

LASSO回归筛选出17个潜在的影响因素，以此行多因素回归分析结果显示，D-二聚体、中心静脉导管(central venous catheter，CVC)和下肢静脉曲张为肺癌患者胸腔镜术后DVT的独立危险因素(

0.05)。模型校准曲线结果显示，预测曲线与标准曲线拟优度良好。ROC曲线分析结果显示，建模组最佳截断值敏感度和特异度分别为0.812和0.963，建模组曲线下面积(area under curve，AUC)为0.912(95%

：0.840~0.983)，而Caprini模型敏感度和特异度分别为0.625和0.860，AUC为0.752(95%

：0.657~0.846)，建模组相较于Caprini模型的NRI为0.709，IDI为0.431。DCA结果显示，应用本研究模型的净收益高于Caprini模型。

结论

D-二聚体、CVC和下肢静脉曲张为肺癌患者胸腔镜术后DVT的独立危险因素，本研究构建的列线图模型能够有效预测肺癌患者胸腔镜术后DVT发生风险。

Abstract

Objective

To investigate the independent risk factors for postoperative deep vein thrombosis in lung cancer patients and to construct a risk prediction model.

Methods

Clinical data of 354 inpatients who underwent thoracoscopic surgery for lung cancer in Department of Thoracic Surgery of First Affiliated Hospital of Army Medical University between May 2019 and May 2023 were retrospectively collected and analyzed. LASSO regression was used to screen potential factors

followed by multivariate logistic regression to identify risk factors

and then a nomogram prediction model was constructed. Calibration curves

receiver operating characteristic (ROC) curves

and decision curves were drawn to evaluate the model's calibration

discrimination

sensitivity

specificity

and clinical utility. The net reclassification improvement (NRI) and integrated discrimination improvement (IDI) indices were employed to compare the predictive performance of the constructed model with the Caprini score for outcome events.

Results

LASSO regression identified 17 potential influencing factors. Multivariate regression analysis showed that D-dimer

central venous catheter (CVC) placement

and lower extremity varicose veins were independent risk factors for postoperative DVT in lung cancer patients (

0.05). Calibration curve analysis showed the model had good agreement between the predicted and observed values. ROC curve analysis indicated that the sensitivity

and specificity of the model was 0.812 and 0.963

respectively

with an area under the curve (AUC) value of 0.912 (95%

: 0.840~0.983). In comparison

the Caprini model had a sensitivity and specificity of 0.625 and 0.860

respectively

with an AUC value of 0.752 (95%

: 0.657~0.846). The NRI and IDI for the model group compared to the Caprini model were 0.709 and 0.431

respectively. Decision curve analysis showed that the net benefit of applying the model from this study was higher than that of the Caprini model.

Conclusion

D-dimer

CVC

and varicose veins of lower extremities are independent risk factors for DVT after thoracoscopic surgery in patients with lung cancer. Our constructed nomogram model can effectively predict the risk of DVT after thoracoscopic surgery in patients with lung cancer.

关键词

Keywords

references

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