Assessing the impact of probiotics on immunotherapy effectiveness and antibiotic-mediated resistance in cancer: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Probiotics have been demonstrated to exert a potential clinical enhancing effect in cancer patients receiving immune checkpoint inhibitors (ICIs), while antibiotics exert a detrimental impact. Prior meta-analysis papers have substantial limitations and are devoid of recent published studies. Therefore, this study aimed to perform an updated meta-analysis and, for the first time, assess whether probiotics can restore the damage of antibiotics to immunotherapy. Methods A comprehensive literature search was conducted in three English databases and three Chinese databases with a cutoff date of August 11, 2024. The methodological quality of the studies was evaluated using the Newcastle-Ottawa Quality Assessment Scale (NOS) or the Revised Cochrane risk-of-bias tool (RoB 2). Engauge Digitizer v12.1 was employed to extract hazard ratios (HRs) with 95% confidence interval (CI) for survival outcomes when these data were not explicitly provided in the manuscripts. Meta-analysis was conducted using Stata 14 software. Results The study sample comprised eight retrospective and four prospective studies, involving a total of 3,142 participants. The findings indicate that probiotics significantly prolong the overall survival (OS) (I2 = 31.2%; HR=0.58, 95% CI: 0.46-0.73, p < 0.001) and progression-free survival (PFS) (I2 = 65.2%; HR=0.66, 95% CI: 0.54-0.81, p < 0.001) in cancer patients receiving ICIs, enhance the objective response rate (ORR) (I2 = 33.5%; OR=1.75, 95% CI: 1.27-2.40, p = 0.001) and disease control rate (DCR) (I2 = 50.0%; OR=1.93, 95% CI: 1.11-3.35, p = 0.002). For non-small cell lung cancer (NSCLC) patients exposed to antibiotics, the use of probiotics was associated with superior OS (I2 = 0.0%; HR=0.45, 95% CI: 0.34-0.59, p < 0.001) and PFS (I2 = 0.0%; HR=0.48, 95% CI: 0.38-0.62, p < 0.001) when compared to non-users. Subgroup differences were observed regarding the cancer type (P=0.006) and ethnic backgrounds (P=0.011) in OS. Conclusions The meta-analysis findings suggest that probiotics can effectively extend the survival of cancer treated with ICIs. In NSCLC, probiotics appear to mitigate the negative impact of antibiotics on immunotherapy effectiveness, which has profound clinical significance. Nevertheless, additional large-scale, high-quality randomized controlled trials are necessary to further validate these findings. Systematic review registration https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=579047 , identifier CRD42024579047.
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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 | 0.020 | 0.040 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.053 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".