Impact of multidisciplinary bladder cancer care for muscle invasive bladder cancer: A propensity score matched analysis of survival outcomes.
Bibliographic record
Abstract
455 Background: We started in 2008 a Multidisciplinary Bladder Cancer Clinic (MDBCC), where complex bladder cancer patients are assessed concurrently by urologic and radiation oncologists, with support from medical oncologists. Patients have the opportunity to discuss various treatment options including radical cystectomy (RC) or bladder sparing trimodal therapy (TMT; endoscopic resection, radiotherapy and chemotherapy). Although reports have shown comparable outcomes of TMT to cystectomy, no direct comparison to RC has been published and no randomized studies are available. We report our long term outcomes of multidisciplinary care, comparing TMT to surgery using propensity-matched analyses. Methods: Patients seen in our MDBCC receiving TMT for MIBC from 2008 to 2012 were identified and matched, using propensity scores, to patients operated by RC. Matching occurred on age, ECOG status, Charlson comorbidity score, cT stage, cN stage and date of treatment. Overall survival (OS) and disease-specific survival (DSS) were assessed with Cox Proportional hazards modeling and competing risk analysis, respectively. Results: Between 2008 and 2012, 248 patients were assessed in the MDBCC. Of these, 162 (65%) had MIBC. Nearly half (80) opted for radiotherapy +/- concurrent cisplatin chemotherapy and 49 underwent full bladder preservation with TMT as their primary therapy. We matched 48 TMT patients with 48 RC patients with no imbalances. Median age of the cohort was 67.5 years with 29.2% cT3/cT4. With a median follow up time of 3.62 years, there were 19 (39.6%) deaths (7 from bladder cancer) in the RC group and 15 (31.3%) deaths (6 from bladder cancer) in the TMT group. 5 year DSS was 85.2% and 84.7% with TMT and surgery, respectively (p > 0.05). There was no statistically significant difference in DSS between the two groups (HR for TMT 1.31 (0.40-4.23), p = 0.66) or in OS (HR for TMT 0.77 (0.34-1.75), p = 0.53). Conclusions: Bladder cancer patients benefit from a multidisciplinary approach.. In selected patients with MIBC, chemo-radiation yields survival outcomes similar to matched RC patients. BC patients should be offered the possibility to discuss various treatment options.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".