Optimal interval to surgery after chemoradiotherapy in rectal cancer
Bibliographic record
Abstract
BACKGROUND: Rectal cancer is the second leading cause of cancer-related death in the Western world. Preoperative neoadjuvant chemoradiotherapy (nCRT) has been widely performed in the treatment of rectal cancer patients. However, there is no consensus on the length of waiting interval between the end of preoperative nCRT and surgery. Present network meta-analysis (NMA) aims to compare the differences of effect between all available interval to surgery after nCRT in rectal cancer in improving overall survival, disease-free survival and pathologic complete response (pCR) rate, and to rate the certainty of evidence from present NMA. METHOD: We will systematically search PubMed, EMBASE, Chinese Biomedical Literature Database, and Cochrane Central Register of Controlled Trials (CENTRAL) databases to identify studies assessing the interval to surgery after CRT in rectal cancer. We will conduct this systematic review and meta-analysis using Bayesian method and report the full-text according to Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) Extension Vision statement (PRISMA-NMA). We will assess the risk of bias of individual study using the Newcastle-Ottawa Scale and Cochrane Handbook V.5.1.0. We will also use the advance of GRADE to rate the certainty of NMA. Data will be analyzed by using R software V.3.4.1. RESULTS: The results of this study will be published in a peer-reviewed journal. CONCLUSION: To the best of our knowledge, this systematic review and NMA will first use both direct and indirect evidence to compare the differences of all available interval to surgery after CRT in rectal cancer. This is a protocol of systematic review and meta-analysis, so the ethical approval and patient consent are not required.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".