Probiotics Evaluation in Oncological Surgery: A Systematic Review of 36 Randomized Controlled Trials Assessing 21 Diverse Formulations
Bibliographic record
Abstract
Background: Objectives were to evaluate probiotics safety and efficacy in oncological surgery. Methods: Systematic review methodology guided by Cochrane, PRISMA, SWiM, and CIOMS. Protocol registered on PROSPERO (CRD42018086168). Results: 36 RCTs (on 3305 participants) and 6 nonrandomized/observational studies were included, mainly on digestive system cancers. There was evidence of a beneficial effect on preventing infections, with 70% of RCTs’ (21/30) direction of effect favoring probiotics. However, five RCTs (17%) favored controls for infections, including one trial with RR 1.57 (95% CI: 0.79, 3.12). One RCT that changed (balanced) its antibiotics protocol after enrolling some participants had mortality risk RR 3.55 (95% CI: 0.77, 16.47; 7/64 vs. 2/65 deaths). The RCT identified with the most promising results overall administered an oral formulation of Lactobacillus acidophilus LA-5 + Lactobacillus plantarum + Bifidobacterium lactis BB-12 + Saccharomyces boulardii. Methodological quality appraisals revealed an overall substantial risk-of-bias, with only five RCTs judged as low risk-of-bias. Conclusions: This large evidence synthesis found encouraging results from most formulations, though this was contrasted by potential harms from a few others, thus validating the literature that “probiotics” are not homogeneous microorganisms. Given microbiome developments and infections morbidity, further high-quality research is warranted using those promising probiotics identified herein.
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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 | 0.021 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.019 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".