Neoadjuvant radiotherapy for resectable retroperitoneal sarcoma: a meta-analysis
Bibliographic record
Abstract
Abstract Background Neoadjuvant radiotherapy (NRT) for resectable retroperitoneal sarcoma (RPS) has been shown to be systematically feasible. Whether NRT has equivalent or better clinical effects compared to surgery alone for RPS patients remains controversial. Methods We performed a systematic literature search of PubMed, Web of Science, Embase, ASCO Abstracts, and Cochrane library databases for studies in humans with defined search terms. Articles were independently assessed by 2 reviewers, and only randomized controlled trials and cohort studies were included. The hazard ratios (HRs) of overall survival (OS), recurrence-free survival (RFS), and local recurrence (LR) were extracted from included studies. Heterogeneity among study-specific HRs was assessed by the Q statistic and I 2 statistic. Overall HR was assessed by random-effects or fixed-effects models. Publication bias was tested by Begg’s tests, and the quality of each study was assessed with the Newcastle Ottawa Scale. Results A total of 12 eligible studies with 7778 resectable RPS patients were finally included in this study. The pooled analysis revealed the distinct advantages of NRT as compared to surgery alone, including longer OS (HR = 0.81, P < 0.001), longer RFS (HR = 0.58, P = 0.04), and lower LR (HR = 0.70, P = 0.03). No evidence of publication bias was observed. Conclusion NRT is likely to be beneficial for resectable RPS patients in terms of OS and RFS . However, more multicenter clinical trials are needed to confirm these findings.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| 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) | 0.008 | 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 teacher head, 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".