0599 The Association Between Obstructive Sleep Apnea and Cancer Incidence and Mortality: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Introduction Sleep related breathing disorders (SRBD) are common (20% prevalence) in the general population and can have multiple health consequences. There is growing evidence that chronic hypoxia - a key consequence of sleep apnea - is a common feature in solid tumour tissue, therapeutic resistance, tumour progression, and metastasis. However, there is conflicting evidence regarding the association between sleep apnea, cancer incidence, or mortality. A review of all available literature and subsequent meta-analysis was done to clarify these relationships. Methods A thorough literature search was completed using Medline, EMBASE and Web of Science databases. The search resulted in 7222 studies, 1551 duplicates were removed, 5552 studies were removed after abstract screening, and full text review was done on 119 studies, yielding 12 full retrospective cohort studies. The risk of bias was assessed using the Newcastle-Ottawa Scale. Review and data extraction were done in duplicate. Results In the pooled analysis, 9 studies totalling 2,358405 subjects with OSA and 3.97% cancer incidence and 2,442794 subjects without OSA and 3.35% cancer incidence. A random effects model with inverse-variance weighting analysis yielded an unadjusted OR = 1.32 (95% CI: 0.76 - 2.30). After 2 studies with a moderate risk of bias were removed the pooling yielded an OR = 1.89 (95% CI: 0.99 - 3.50). Heterogeneity was high at 99.9% p-value less than 0.01. Meta-regression was then done to assess for the cause(s) of heterogeneity sex, age, or BMI were not significant contributors. A review of 3 studies, which included cancer mortality, was done. Hazard ratios in 2 studies suggested OSA increased the risk of cancer mortality. Hazard ratios also increased with increasing OSA severity. Conclusion Sleep apnea significantly increases cancer mortality and is positively associated with increasing severity. Meta-analysis demonstrated an 86% increase in the unadjusted odds of cancer in those with sleep apnea. However, this result was borderline non-significant with high heterogeneity. Further studies may be helpful in determining the true associations between sleep apnea and cancer. Support None.
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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 | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.048 |
| Bibliometrics | 0.009 | 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) | 0.007 | 0.001 |
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".