The aim of the study was to investigate the prognostic significance of selected risk assessment models (RAMs) for predicting venous thromboembolism (VTE) events in patients undergoing outpatient chemotherapy for lung cancer. We evaluated the following VTE-risk assessment tools: Khorana risk score (KRS), PROTECHT score, CONKO score and COMPASS-cancer-associated thrombosis score (COMPASS-CAT). Retrospective analyses were performed on 118 patients with lung cancer, 20 of whom developed VTE with a median of 2.5 months from diagnosis. Patients receiving gemcitabine-based regimen (25%), patients with a history of atrial fibrillation (AF) and patients with chronic kidney disease developed VTE more often than other patients. In the multivariate analysis, high COMPASS-CAT score (OR 8.73; 95% CI 1.01-75.22, P = 0.049), gemcitabine chemotherapy (OR 3.37; 95% CI 1.09-10.39, P = 0.035) and AF (OR 7.19; 95% CI 1.89-27.33, P = 0.004) were all significantly associated with VTE development. VTE occurred in; 13% (n = 2) of the KRS high-risk group, 17.7% (n = 11) of the PROTECHT high-risk group, 15% (n = 4) of the CONKO high-risk group and 23.8% (n = 20) of the COMPASS-CAT high-risk group (n = 84). Only the COMPASS-CAT score was able to identify 100% of patients who developed VTE, and best discriminated between patients with high and low risk of VTE development (C statistic 0.89). The ROC analysis indicated a cutoff value of 11 points (95% CI 0.821-0.962) for COMPASS-CAT for VTE development in patients with lung cancer. In conclusion, in our study of all the VTE-RAMs analyzed, the COMPASS-CAT model was the most accurate predictor of VTE development in patients with lung cancer.
Cancer-associated venous thromboembolism (VTE) is one of the leading causes of mortality and morbidity among patients with malignancy. The Khorana risk score (KRS) is currently the best validated risk assessment model to stratify risks of VTE development in ambulatory patients with cancer. In the current study, we assessed the performance of KRS in patients with hepatocellular carcinoma (HCC). We retrospectively analyzed patients with diagnosis of HCC (screened by International Classification of Diseases [ ICD-9] and ICD-10 code, confirmed with radiographic examination and/or histopathology) at a large public hospital over 15 years (January 2000 through July 2015). Cases with VTE were identified through radiographic examination and blindly adjudicated. Khorana risk score was calculated for each patient, and its association with VTE development and mortality was assessed. Among 270 patients with HCC, 16 (5.9%) cases of VTE were identified, including 7 (43.8%) pulmonary embolism, 4 (25%) peripheral deep vein thrombosis, and 6 (37.5%) intra-abdominal thrombosis. One hundred eighty-four (68.1%) patients had a KRS of 0 and 86 (31.9%) patients had a KRS >0. Most of the thrombotic (n = 9, 56%) events occurred in the low-risk group. In univariate analysis, only prechemotherapy leukocyte count equal to or greater than 11 000/μL was statistically significant in the prediction of VTE incidence. After adjusting for confounding factors in multivariate analysis, KRS >0 was not predictive of VTE (hazard ratio [HR] = 1.83, 95% confidence interval [CI] = 0.81-4.15, P = .15) or mortality (HR = 1.61, 95% CI = 0.92-2.81, P = .09). Khorana risk score did not predict VTE development or mortality in patients with HCC. Design of HCC-specific risk assessment model for VTE development is necessary.
BACKGROUND: Venous thromboembolism is a common complication of cancer, but the risk of developing venous thromboembolism varies greatly among individuals and depends on numerous factors, including type of cancer. We aimed to develop and externally validate a clinical prediction model for cancer-associated venous thromboembolism.
METHODS: We used data from the prospective Vienna Cancer and Thrombosis Study (CATS) cohort (n=1423) to select prognostic variables for inclusion in the model. We then validated the model in the prospective Multinational Cohort Study to Identify Cancer Patients at High Risk of Venous Thromboembolism (MICA) cohort (n=832). We calculated c-indices to show how the predicted incidence of objectively confirmed venous thromboembolism at 6 months compared with the cumulative 6-month incidences observed in both cohorts.
FINDINGS: Two variables were selected for inclusion in the final clinical prediction model: tumour-site risk category (low or intermediate vs high vs very high) and continuous D-dimer concentrations. The multivariable subdistribution hazard ratios were 1·96 (95% CI 1·41-2·72; p=0·0001) for high or very high versus low or intermediate and 1·32 (95% CI 1·12-1·56; p=0·001) per doubling of D-dimer concentration. The cross-validated c-indices of the final model were 0·66 (95% CI 0·63-0·67) in CATS and 0·68 (0·62-0·74) in MICA. The clinical prediction model was adequately calibrated in both cohorts.
INTERPRETATION: An externally validated clinical prediction model incorporating only one clinical factor (tumour-site category) and one biomarker (D-dimer) predicted the risk of venous thromboembolism in ambulatory patients with solid cancers. This simple model is a considerable improvement on previous models for predicting cancer-associated venous thromboembolism, and could aid physicians in selection of patients who will likely benefit from thromboprophylaxis.
FUNDING: Austrian Science Fund, Austrian National Bank Memorial Fund, and participating hospitals.
BACKGROUND: Patients with lung cancer are known to be at increased risk for venous thromboembolism (VTE). Venous thromboembolism is associated with increased risk for early mortality. However, there have been no studies performing a comprehensive assessment of risk factors for VTE or early mortality in lung cancer patients undergoing systemic chemotherapy in a global real-world setting.
MATERIALS AND METHODS: CANTARISK is a prospective, global, noninterventional cohort study including patients with lung cancer initiating a new cancer therapy. Clinical data were collected until 6-month follow-up. The impact of patient-, disease-, and treatment-related factors on the occurrence of VTE and early mortality was evaluated in univariable and multivariable Cox regression analyses. A previously validated VTE risk score (VTE-RS) was also calculated (also known as Khorana score).
RESULTS: Of 1,980 patients with lung cancer who were enrolled from 2011 to 2012, 84% had non-small cell lung cancer. During the first 6 months, 121 patients developed a VTE (6.1%), of which 47% had pulmonary embolism, 46% deep vein thrombosis, 3% catheter-associated thrombosis, and 4% visceral thrombosis. Independent predictors for VTE included female sex, North America location, leg immobilization, and presence of a central venous catheter. The VTE-RS was not significantly associated with VTE in either univariable or multivariable analysis in this population. During the study period, 472 patients died, representing 20%, 24%, 36%, and 25% with VTE-RS 1, 2, ≥3, or unknown, respectively (p < .0001). Significant independent predictors of early mortality include older age, current/former smoking, chronic obstructive pulmonary disease, Eastern Cooperative Oncology Group performance status ≥2, no prior surgery, and metastatic disease, as well as the VTE-RS.
CONCLUSION: In this global, prospective, real-world analysis, several demographic, geographic, and clinical factors are independent risk factors for VTE and early mortality in patients with lung cancer. The VTE-RS represents a significant independent predictor of early mortality but not for VTE in lung cancer in the era of targeted therapy.
IMPLICATIONS FOR PRACTICE: Multiple risk factors for both venous thromboembolism (VTE) and early mortality in patients with lung cancer receiving systemic chemotherapy should guide best practice by better informing clinical evaluation and treatment decision-making. The Khorana risk score is of value in assessing the risk of early all-cause mortality along with other clinical parameters in patients with lung cancer receiving systemic therapy. Further study is needed to fully evaluate the validity of the risk score in predicting the risk of VTE in the modern era of lung cancer therapy.
