Predictors of Venous Thmromboembolism in Colorectal Cancer: Results from a Global Prospective Study
Bibliographic record
Abstract
Abstract BACKGROUND Venous thromboembolism (VTE) is an important complication among patients with colorectal cancer but its prevalence and predictors are incompletely understood. The Khorana Score (KS), comprising primary site, baseline hemoglobin, leukocyte and platelet counts, and body mass index [Khorana et al, Blood, 2008], has been demonstrated to predict VTE in various cancer settings. We evaluated the value of this Score and other key prognostic variables in a global prospective cohort study to define the incidence, predictors and consequences of VTE in patients undergoing adjuvant or palliative chemotherapy for colorectal cancer. METHODS CANTARISK was a prospective, non-interventional, international cohort study in patients with lung and colorectal cancer on chemotherapy; data for the colorectal cohort are presented here. Clinical data were collected at baseline, and at 2, 4 and 6 months. All data were compiled centrally and analyzed after the study had closed. KS categories were as defined previously [Blood, 2008]. Statistically significant univariable associations and a priori variables were tested in multivariable models; adjusted odds ratios (OR) with confidence intervals (CIs) are presented. RESULTS A total of 1,789 patients with colorectal cancer were enrolled from 2011 to 2012. Median age was 62 years; 61% were male; 71% were Caucasian; 18% were Asian; 37% were from Europe, 28% from North America, 23% from Asia, and 12% from South America. During the six-month follow-up period, 92 (5.1%) patients experienced VTE events; 18 patients experienced 2 events each, and 2 patients experienced 3 events each, for a total of 112 VTE events. Of these 112 events, 69 (61.6%) were deep venous thromboses (DVT), 22 (19.6%) were pulmonary emboli (PE), 14 (12.5%) were catheter-associated thrombi, and 7 (6.3%) were visceral thrombi. The majority (n=94, 83.9%) were symptomatic. For low, intermediate, and high KS, there were 4.3% (n=42), 6.8% (n=39), and 12.5% (n=5) VTE events, respectively (N=1596 due to some missing values for KS components). In adjusted multivariable analyses, KS (OR for high/intermediate vs. low = 1.82, 95% CI = 1.15-2.87), ECOG performance score (OR for 2/3/4 vs. 0/1 = 2.17, 95% CI=1.07-4.43), and central venous catheter (OR for yes vs. no = 4.01, 95% CI=2.32-6.94) were independent predictors of VTE. Notably, age, metastatic (vs. non-metastatic) disease, surgery or immobilization within the prior 6 months, current smoking, and history of VTE were not associated with new VTE events. CONCLUSIONS This global prospective study demonstrates that VTE events are prevalent among patients with colorectal cancer receiving systemic chemotherapy. Khorana Score category is a strong predictor of risk. Ongoing clinical trials are focusing on the benefit of prophylactic anticoagulation in high-risk patients in these settings. Disclosures Kuderer: Janssen Scientific Affairs, LLC: Consultancy, Honoraria. Lyman:Amgen: Research Funding. Khorana:Amgen: Consultancy, Honoraria, Research Funding; Bayer: Consultancy, Honoraria; Halozyme: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Leo: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Janssen Scientific Affairs, LLC: Consultancy, Honoraria, Research Funding.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".