Textbook oncologic outcomes in colorectal cancer surgery: a systematic review
Bibliographic record
Abstract
Introduction: The concept of "textbook outcome" has been updated to encompass the principles of surgical oncology and the related outcomes [textbook oncologic outcome (TOO)]. This systematic review aims to synthesize the numerous definitions of TOO in the context of colorectal surgery. The goal is to promote the development of a definition that has universal recognition and worldwide acceptability, hence improving surgical quality standards and patient outcomes. Methods: A systematic literature review was conducted using PRISMA guidelines. The databases PubMed, Web of Science, and Scopus were searched for studies that addressed TOO in colorectal cancer surgeries. The database search was conducted on 30 April 2024, and the primary study's quality was assessed using the Newcastle-Ottawa Scale. Results: A total of 13 studies were included. Common TOO parameters included radical resection, lymph node (LN) yield ≥12, no Clavien-Dindo grade ≥III complications, length of stay (75th percentile), no 30-day readmissions, and no 30-day mortality. Factors influencing TOO achievement included surgical risk, gender, tumor stage, and socioeconomic factors. Patients achieving TOO showed better long-term survival. Variability in TOO definitions highlighted the need for standardization. Conclusion: TOO is an effective indicator for evaluating the quality of colorectal cancer surgery. It provides a comprehensive evaluation of surgical outcomes, which helps in guiding patient decisions and measuring hospital performance. By standardizing the parameters of TOO, the consistency and quality of care across different institutions can be improved. We propose a unified definition of TOO for colorectal cancer surgery: radical resection, LN yield ≥12, no Clavien-Dindo grade ≥III complications, length of stay (75th percentile), no 30-day readmissions, and no 30-day mortality.
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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 | 0.010 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".