A Population-Based Study of Complications After Colorectal Surgery in Patients Who Have Received Bevacizumab
Bibliographic record
Abstract
BACKGROUND: Patients receiving Bevacizumab, a vascular endothelial growth factor inhibitor used to treat metastatic colorectal cancer, may be at greater risk of complications after colorectal surgery because of impaired healing. OBJECTIVE: The purpose of this study was to describe population-based rates of complications of colorectal surgery after Bevacizumab treatment and evaluate the relationship between time since last treatment and risk of complications. DESIGN: This was a population-based retrospective cohort study using administrative and cancer registry data. SETTINGS: The study was conducted in Ontario, Canada. PATIENTS: Patients with metastatic colorectal cancer receiving Bevacizumab between January 2008 and December 2011 were followed for a year after treatment or until death. MAIN OUTCOME MEASURES: Administrative data were used to identify patients who underwent colorectal surgery after initiation of Bevacizumab and to determine whether they experienced a complicated postoperative course. The relationship between time since last Bevacizumab treatment (≤28 d, 29 d to 3 mo, and >3 mo) and risk of postoperative complications was evaluated using logistic regression. RESULTS: Of the 2759 patients who received Bevacizumab for the treatment of metastatic colorectal cancer, 265 underwent a colorectal procedure after exposure. The majority had a bowel resection or repair with no stoma (47.5%) and had emergency surgery (61.1%). Overall, 96 (36.2%) had a complicated postoperative course, including 20.4% readmission, 12.5% wound complications, and 7.9% mortality rate within 30 days of surgery. Adjusted multivariate analysis showed no difference in the likelihood of a complicated postoperative course among patients undergoing surgery within 28 days of receiving their last Bevacizumab dose compared with 29 days to 3 months (OR = 1.23 (95% CI, 0.53-2.84), or 3 to 12 months (OR = 0.98 (95% CI, 0.46-2.09) after receiving Bevacizumab. LIMITATIONS: Reliance on administrative data to measure complications limited the scope of this study. CONCLUSIONS: Patients with metastatic colorectal cancer requiring colorectal surgery after exposure to Bevacizumab experience substantial morbidity and mortality. The risk of complications is not detectably associated with time since exposure. See Video Abstract at http://links.lww.com/DCR/A474.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".