Analyzing the Association between Candida Prevalence, Species Specificity, and Oral Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis— Candida and OSCC
Bibliographic record
Abstract
The present review is a qualitative and quantitative analysis of the overall prevalence of Candida, and its species specificity in oral squamous cell carcinoma (OSCC). PubMed, Scopus, and Web of Science databases were searched using the keywords ‘Candida and oral squamous cell carcinoma’. Only case-control observational studies in the English language evaluating the prevalence and species specificity of Candida in OSCC were included. 297 articles were identified (PubMed-106, Scopus-148, Web of Science-43) using the keywords. After screening the titles and abstracts, 206 articles were removed as they were duplicates (118) or irrelevant to the topic (88). Full text of the remaining 91 articles was assessed using the inclusion criteria, based on which only seven articles were included in the systematic review. For the quantitative analysis, the odds ratio and confidence interval were assessed and a forest plot was generated. Based on the meta-analysis, there is an association between the total Candida, Candida albicans (CA) and OSCC, while the association with non-Candida albicans (NCA) is relatively weak. The number of studies included in the meta-analysis was relatively low (four to five). Further, at least one of the studies included in the meta-analysis for the association of CA., NCA and total Candida with OSCC had a Newcastle–Ottawa score below 7. Thus, although the results showed an association, the quality and quantity of the evidence may not be sufficient for conclusive inference.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.035 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".