Development and Validation of a Nomogram to Predict the Probability of Venous Thromboembolism in Patients with Epithelial Ovarian Cancer

Gynecological Cancer and Venous Thromboembolism: A Narrative Review to Increase Awareness and Improve Risk Assessment and Prevention

The prevention and appropriate management of venous thromboembolism in cancer patients is of paramount importance. However, the literature data report an underestimation of this major problem in patients with gynecological cancers, with an inconsistent venous thromboembolism risk assessment and prophylaxis in this patient setting. This narrative review provides a comprehensive overview of the available evidence regarding the management of venous thromboembolism in cancer patients, focusing on the specific context of gynecological tumors, exploring the literature discussing risk factors, risk assessment, and pharmacological prophylaxis. We found that the current understanding and management of venous thromboembolism in gynecological malignancy is largely based on studies on solid cancers in general. Hence, further, larger, and well-designed research in this area is needed.

Development and validation of a nomogram model for predicting the risk of venous thromboembolism in lymphoma patients undergoing chemotherapy: a prospective cohort study conducted in China

BACKGROUND

The mechanism of Venous thromboembolism (VTE) is complicated and difficult to prevent due to factors such as bone marrow invasion, therapy, and immune-mediated effects. This study aims to establish a nomogram model for predicting the risk of thrombosis in lymphoma patients undergoing chemotherapy, which has been increasing over the past 30 years.

METHODS

The data of lymphoma patients from the Affiliated Cancer Hospital of Chongqing University in China between 2018 and 2020 were analyzed. This included age, sex, body mass index, ECOG score, histological type, Ann Arbour Stage, white blood cells count, haemoglobin level, platelet count, D-dimer level, and chemotherapy cycle. Univariate and multivariate cox analysis was used to determine the risk factors for VTE. Characteristic variables were selected to construct a nomogram model which was then evaluated using ROC curve and calibration.

RESULTS

Age, sex, PLT, D-dimer and chemotherapy cycle were considered as independent influencing factors of VTE. The mean (standard deviation) of the C index, AUC and Royston D statistics of 1000 cross-validations of the Nomogram model were 0.78 (0.01), 0.81 (0.01) and 1.61(0.07), respectively. It indicates a good calibration degree and applicability value as shown by the calibration curve. The DCA curve showed a rough threshold range of 0.05-0.60 with a good model.

CONCLUSIONS

We have established and validated a nomogram model for predicting the risk of thrombosis in lymphoma patients. This model can assess the risk of thrombosis in each individual patient, enabling the identification of high-risk groups and targeted preventive treatment.

Nomogram model combined thrombelastography for venous thromboembolism risk in patients undergoing lung cancer surgery

Background: The aim of this study was to develop a nomogram model in combination with thromboelastography (TEG) to predict the development of venous thromboembolism (VTE) after lung cancer surgery. Methods: The data of 502 patients who underwent surgical treatment for lung cancer from December 2020 to December 2022 were retrospectively analyzed. Patients were then randomized into training and validation groups. Univariate and multivariate logistic regression analyses were carried out in the training group and independent risk factors were included in the nomogram to construct risk prediction models. The predictive capability of the model was assessed by the consistency index (C-index), receiver operating characteristic curves (ROC), the calibration plot and decision curve analysis (DCA). Results: The nomogram risk prediction model comprised of the following five independent risk factors: age, operation time, forced expiratory volume in one second and postoperative TEG parameters k value(K) and reaction time(R). The nomogram model demonstrated better predictive power than the modified Caprini model, with the C-index being greater. The calibration curve verified the consistency of nomogram between the two groups. Furthermore, DCA demonstrated the clinical value and potential for practical application of the nomogram. Conclusion: This study is the first to combine TEG and clinical risk factors to construct a nomogram to predict the occurrence of VTE in patients after lung cancer surgery. This model provides a simple and user-friendly method to assess the probability of VTE in postoperative lung cancer patients, enabling clinicians to develop individualized preventive anticoagulation strategies to reduce the incidence of such complications.

Clear cell carcinoma of the ovary and venous thromboembolism: a systematic review and meta-analysis

OBJECTIVES

As the second most common subtype of Epithelial ovarian cancers (EOCs), ovarian clear cell carcinoma (OCCC) is associated with a high rate of cancer-associated thrombosis. Previous studies revealed the wide range prevalence (6-42%) of venous thromboembolism (VTE) among OCCC patients. This study aimed to determine the prevalence of VTE among OCCC patients as well as factors affecting it.

METHODS

PubMed, Scopus, Embase, and Cochrane Library databases were searched up to December 12th, 2022. Studies reporting venous thromboembolic events in women with clear cell carcinoma of the ovary were included. Demographic data, clinical, and paraclinical features of the patients were independently extracted by two reviewers.

RESULTS

Out of the 2254 records, 43 studies were processed for final review. The qualified studies involved 573 VTE cases among 2965 patients with OCCC. The pooled prevalence of VTE among OCCC patients was 21.32% (95%CI=(17.38-25.87)). Most VTE events were reported in Japanese women (26.15%), followed by Americans (24.41%) and UK (21.57%), and Chinese (13.61%) women. VTE was more common in patients with advanced stages (37.79%) compared to those with early stages of the disease (16.54%).

CONCLUSIONS

Ovarian clear cell carcinoma is associated with a high rate of cancer-associated thrombosis. VTE events in OCCC patients were higher in advanced stages and Japanese women.

Nomogram prediction for the risk of venous thromboembolism in patients with lung cancer

OBJECTIVE

The aim of this study was to establish a nomogram graph model to accurately predict the venous thromboembolism (VTE) risk probability in the general population with lung cancer.

METHODS

Based on data from patients with lung cancer in Chongqing University Cancer Hospital of China, the independent risk factors of VTE were identified by the logistic univariable and multivariable analysis and were integrated to construct a nomogram, which was validated internally. The predictive effectiveness of the nomogram was evaluated by the receiver operating characteristic curve (ROC) and calibration curve.

RESULTS

A total of 3398 lung cancer patients were included for analysis. The nomogram incorporated eleven independent VTE risk factors including karnofsky performance scale (KPS), stage of cancer, varicosity, chronic obstructive pulmonary disease (COPD), central venous catheter (CVC), albumin, prothrombin time (PT), leukocyte counts, epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), dexamethasone, and bevacizumab. The C-index of the nomogram model was 0.843 and 0.791 in the training and validation cohort, respectively, demonstrating good discriminative power. The calibration plots of the nomogram revealed excellent agreement between the predicted and actual probabilities.

CONCLUSIONS

We established and validated a novel nomogram for predicting the risk of VTE in patients with lung cancer. The nomogram model could precisely estimate the VTE risk of individual lung cancer patients and identify high-risk patients who are in need of a specific anticoagulation treatment strategy.