Association of Periodontal Red Complex Bacteria With the Incidence of Gastrointestinal Cancers: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Porphyromonas gingivalis is the primary microbe in the “periodontal red complex” bacteria (PRCB) along with Tannerella forsythia and Treponema denticola, which are linked to periodontal disease (PD). These pathogens are also implicated in various systemic disorders, but their association with the incidence of gastrointestinal (GI) cancer is less explored. A systematic review followed by a meta-analysis was conducted as per standard guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2022) to find this association between GI cancers and PRCB after a literature search for full-text papers in the English language (between 2010 and 2023) in databases (Cochrane Library, PubMed, and Web of Science) with suitable keywords using the Boolean search strategy. Data extraction involved titles, abstracts, and full texts retrieved and scored by the modified Newcastle-Ottawa Scale. The data were analyzed by the Review Manager (RevMan 5.2, Cochrane Collaboration, Denmark). Standard Cochran Q test and I2 statistics (for heterogeneity) and a random effects model (pooled OR with 95% CI) were applied to report results. P. gingivalis among the PRCB was linked to GI cancers (OR: 2.16; 95% CI: 1.34-3.47). T. forsythia and T. denticola did not show meaningful associations as per existing evidence for GI cancers.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.032 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".