Effect of cisplatin-based neoadjuvant chemotherapy on survival in patients with bladder cancer: a meta-analysis
Bibliographic record
Abstract
PURPOSE: Cisplatin-based neoadjuvant chemotherapy (NAC) has been shown to improve survival in patients with muscle-invasive bladder cancer (MIBC) who underwent radical cystectomy as compared with patients who underwent surgery alone. It has also been suggested as current standard of care in surgically-fit patients with MIBC. This meta-analysis assessed the effect of cisplatin-based NAC on survival in patients with bladder cancer. SOURCE: PubMed, CENTRAL, and Embase were searched until November 22, 2016. Two-arm randomized controlled trials that compared cisplatin-based neoadjuvant chemotherapy plus local treatment versus the same local treatment without neoadjuvant chemotherapy were selected. Patients with histologically-confirmed bladder cancer (adenocarcinoma, transitional, or squamous-cell carcinoma) were included. The primary outcome was overall survival (OS). PRINCIPAL FINDINGS: Of the 292 articles initially identified, 14 were included in the final analysis. Patients in the NAC group had similar OS as the local treatment (i.e., radiation therapy or cystectomy) group (pooled hazard ratio [HR] = 0.92, 95% confidence interval [CI]: 0.84 to 1.00, P=0.056). No difference in progress-free survival between two groups was observed (P=0.725). Subgroup analysis showed that OS was similar in patients treated with NAC plus radiotherapy or cystectomy compared with patients who received local treatment alone. CONCLUSIONS: Platinum-based NAC was associated with similar survival benefit as patients undergoing cystectomy and/or radiotherapy. No conclusion can be drawn about the optimal platinum-based combination to be used in the neoadjuvant setting.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.035 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".