Thrombotic events in patients with metastatic colorectal cancer treated with FOLFIRI plus bevacizumab.
Bibliographic record
Abstract
540 Background: The rate of venous thromboembolism (VTE) in (mCRC) with bevacizumab was reported in a meta-analysis as 19.1%. We estimated and compared the rate of VTE among mCRC patients receiving FOLFIRI and bevacizumab with patients receiving FOLFIRI without bevacizumab. Methods: We conducted a retrospective cohort study assessing the rate of VTE in a group of 450 mCRC patients seen consecutively at the Juravinski Cancer Center. Patients were classified according to their treatment: chemotherapy plus bevacizumab group (n=261) and control group (n=189) who received only FOLFIRI during the years 2004 to 2012. Demographic, pathologic and treatment data were abstracted. Multivariate analysis was used to adjust for the effect potential confounding variables associated with treatment and VTE and to assess the effect of these variables risk of VTEs in this population. The primary end point was the occurrence of a VTE. Secondary analyses involved classifying site of VTE. Results: The percentage of male, mean age and mean BMI were 64.8%, 60.1 years and 27.2 for the bevacizumab group and 61.9%, 63.69 years and 27.6 are for the control group. The crude incidence of VTEs was 13.1% in bevacizumab and 10.5% in the control groups (p = NS). Multivariate analysis controlled for age, BMI, gender, malignancy, metastatic disease and line of treatment did not suggest a significant increase in risk of VTE associated with bevacizumab (OR=0.83 95% CI: 0.40, 1.70; p=0.602). The only significant factor for thrombosis in bevacizumab group was BMI (OR=1.05; 95% CI: 1.01, 1.10; p=0.016). Other risk factors such as previous VTE, stroke, smoking, and hypertension were not statistically significant when assessed through a composite covariate. For anatomical location of VTEs, see the Table. Conclusions:The rate of VTEs overall was lower in our sample than has been reported in previous studies. We excluded upper limb DVTs associated with central lines which may explain the lower VTEs overall. The incidence of VTEs was not significantly different between the bevacizumab and the control groups. bevacizumab was not associated with increase risk of VTES . This support the safety of bevacizumab in regards to VTEs risk in this population. The incidence of venous thromboembolism (VTE) in FOLFIRI with and without bevacizumab. [Table: see text]
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".