Standard of care for MIBC is becoming more standard.
Bibliographic record
Abstract
e16011 Background: Despite consensus guideline recommendations, the management of muscle invasive bladder cancer (MIBC) varies dependent on institution setting. The risk of recurrence of localized bladder cancer after cystectomy is substantial and associated with stage. The current standard of care for possibly T2 and certainly T3-T4 MIBC is neoadjuvant cisplatin (NAC) based chemotherapy followed by cystectomy. As recent as 2011, only 12% of patients in this category actually received NAC (Feifer et al. 2011). Similar statistics have been confirmed in the US and Canada. Given there is a 13% reduction in risk of death with use of NAC, the adherence to this recommendation needs to improve. We hypothesize that in a multispecialty community practice where barriers to care are reduced that the percentage of eligible patients receiving NAC is significantly higher than previously reported. Methods: After IRB exemption obtained, patients from 2012-2015 with MIBC who underwent cystectomy were examined. Data collection included age, sex, date of consultation, dates and type of chemotherapy received, eGFR, date of surgery and surgical pathology report staging. Data were analyzed using Kolmogorov-Smirnov, Shapiro-Wilk, Mann-Whittney and Kruskal-Wallis statistical tests. Results: The average patient age was 69 years old with a male predominance. Approximately 54% of patients received neoadjuvant chemotherapy; however, three of those patients did not receive the recommended cisplatin based regimen. Fifty percent of patients received NAC and 57% of cisplatin eligible (age < 80, eGFR > 30) patients received NAC. The average time to cystectomy was 171 days among those receiving NAC, with a decrease in time to cystectomy correlating with age. Conclusions: In a community group practice, adherence to standard of care recommendations for higher stage MIBC patients to receive NAC are significantly higher than recently reported values, 50% vs 12%, respectfully. This was achieved while maintaining acceptable time to cystectomy. This supports our hypothesis that when barriers to care are decreased in a community group practice, high quality standards of care can be effectively delivered. In the future, 5 year overall survival will also be important to evaluate in this population.
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.050 | 0.024 |
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".