Predictors of Venous Thromboembolism and Early Mortality in Lung Cancer: Results from a Global Prospective Study (CANTARISK)
Bibliographic record
Abstract
Abstract 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".