Bibliographic record
Abstract
Introduction: Intravesical immunotherapy with Bacillus Calmette-Guérin (BCG) is the standard treatment for non-muscle-invasive bladder cancer (NMIBC) patients.Unfortunately, 40% of patients do not respond to this treatment.Recent studies have highlighted the importance of gut microbiome and the deleterious effect of antibiotics (ATB) on the efficacy of various immunotherapies.However, the impact of ATB intake before BCG treatment initiation is unclear.Methods: This is a single-center retrospective study of 622 NMIBC patients who received BCG immunotherapy following transurethral resection of a bladder tumor at CHU de Québec from 2009-2019.We evaluated ATB intake based on prescriptions and medical records.ATB was evaluated up to 12 months before BCG initiation.The impact of ATB use on BCG response was determined as the rate of bladder cancer recurrence after BCG treatment.Additionally, to explore the impact of ATB on BCG efficacy in vivo in a preclinical bladder cancer model, C3H mice were subjected to a broad-spectrum ATB regimen.One group received ATB for only one week, while the other group continued the ATB treatment throughout the entire experiment.Mice were subcutaneously injected with MBT-2 bladder cancer cells and received weekly intra-tumor BCG treatments starting on day three post-tumor implantation.Results: Of the 622 NMIBC patients, 77 (12%) were exposed to ATB within three months before their BCG treatment, while 545 patients (88%) were not.The use of ATB within this three-month window was associated with the first occurrence following BCG treatment (p=0.01) and showed a notable increase in the recurrence rate two years post-BCG (p<0.0001).Conversely, no significant difference in recurrence rates was observed between patients with or without ATB between 3-12 months before initiating the BCG therapy.Finally, mice with MBT-2 tumors undergoing BCG immunotherapy showed a negatively impacted antitumor effect of BCG when treated with a long-duration ATB regimen compared to controls, suggesting biological importance of the gut microbiota in response to BCG.Conclusions: This study represents the first large single-site retrospective study to evaluate the detrimental effects of ATB use before BCG treatment in NMIBC patients.Our findings support that antibiotic treatment within three months before BCG treatment antagonizes its antitumor activity.This suggests that gut microbiota may play a role in the efficacy of BCG therapy in NMIBC patients.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.303 | 0.136 |
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".