A systematic review of risk prediction model of venous thromboembolism for patients with lung cancer

Abstract

BackgroundVenous thromboembolism (VTE) increases the risk of death or adverse outcomes in patients with lung cancer. Therefore, early identification and treatment of high‐risk groups of VTE have been the research focus. In this systematic review, the risk assessment tools of VTE in patients with lung cancer were systematically analyzed and evaluated to provide a reference for VTE management.MethodsRelevant studies were retrieved from major English databases (The Cochrane Library, Embase, Web of Science, PubMed, Scopus, Medline) and Chinese databases (China National Knowledge Infrastructure [CNKI] and WanFang Data) until July 2023 and extracted by two researchers. This systematic review was registered at PROSPERO (no. CRD42023409748).ResultsFinally, two prospective cohort studies and four retrospective cohort studies were included from 2019. There was a high risk of bias in all included studies according to the Prediction Model Risk of Bias Assessment tool (PROBAST). In the included studies, Cox and logistic regression were used to construct models. The area under the receiver operating characteristic curve (AUC) of the model ranged from 0.670 to 0.904, and the number of predictors ranged from 4 to 11. The D‐dimer index was included in five studies, but significant differences existed in optimal cutoff values from 0.0005 mg/L to 2.06 mg/L. Then, three studies validated the model externally, two studies only validated the model internally, and only one study validated the model using a combination of internal and external validation.ConclusionVTE risk prediction models for patients with lung cancer have received attention for no more than 5 years. The included model shows a good predictive effect and may help identify the risk population of VTE at an early stage. In the future, it is necessary to improve data modeling and statistical analysis methods, develop predictive models with good performance and low risk of bias, and focus on external validation and recalibration of models.

Navigating venous thromboembolism risks in lung cancer patients

“…To the Editor, Dr Liang and colleagues' review provided valuable insights into the venous thromboembolism (VTE) risk prediction models for patients with lung cancer. 1 VTE manifests as deep venous thrombosis or pulmonary embolism, presenting as a severe clinical condition. However, VTE is a dynamic condition with constantly changing features across clinical, radiological, functional, and laboratory findings, not a static disease.…”

“…Dr Liang and colleagues' review provided valuable insights into the venous thromboembolism (VTE) risk prediction models for patients with lung cancer. 1 …”

“…There is a limitation of the study by Liang et al in not distinguishing between symptomatic and asymptomatic VTE cases, 1 a crucial differentiation given the clinical significance and impact on patient outcomes of symptomatic cases. Underestimation of VTE is prevalent due to the lack of systematic screening, which has been mentioned in many studies.…”