ArticleThe Journal of international medical research2020
Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism.
Article in The Journal of international medical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Development and validation of a nomogram for predicting venous thromboembolism risk in post-surgery patients with cervical cancer.World journal of surgical oncology · 2024Article
- Incidence and risk factors of silent deep venous thromboembolism before interval debulking surgery in ovarian cancer patients, a tertiary centre experience.Gynecologic oncology reports · 2024Article
- Review
- Use of the Khorana score to predict venous thromboembolism in patients undergoing chemotherapy for uterine cancer.Gynecologic oncology reports · 2023Article
- Gynecologic Malignancy-Associated Venous Thromboembolism and Predictive Tool at Thammasat University Hospital.Asian Pacific journal of cancer prevention : APJCP · 2022Article
- Analysis of Risk Factors of Postoperative Lower Extremity Deep Venous Thrombosis in Patients With Cervical Cancer.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/HemostasisArticle
- Risk Factors and Impact on Outcomes of Lung Cancer Patients Concurrent with Deep Vein Thrombosis.Cancer control : journal of the Moffitt Cancer CenterArticle
- Venous Thromboembolism in Women with Breast and Gynaecological Cancers: What Do We Know and What Should We Do?Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/HemostasisReview
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study aimed to investigate a suitable risk assessment model to predict deep vein thrombosis (DVT) in patients with gynecological cancer.
methodsData from 212 patients with gynecological cancer in the Affiliated Tumor Hospital of Guangxi Medical University were retrospectively analyzed. Patients were risk-stratified with three different risk assessment models individually, including the Caprini model, Wells DVT model, and Khorana model.
resultsThe difference in risk level evaluated by the Caprini model was not different between the DVT and control groups. However, the DVT group had a significantly higher risk level than the control group with the Wells DVT or Khorana model. The Wells DVT model was more effective for stratifying patients in the DVT group into the higher risk level and for stratifying those in the control group into the lower risk level. Receiver operating curve analysis showed that the area under the curve of the Wells DVT, Khorana, and Caprini models was 0.995 ± 0.002, 0.642 ± 0.038, and 0.567 ± 0.039, respectively.
conclusionThe Wells DVT model is the most suitable risk assessment model for predicting DVT. Clinicians could also combine the Caprini and Wells DVT models to effectively identify high-risk patients and eliminate patients without DVT.
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