Chronic sinusitis in association to increased risk of site-specific cancer: A systematic review and meta-analysis.
Bibliographic record
Abstract
e22509 Background: Chronic inflammatory states are linked with increased cancer risk. However, it is unclear if chronic sinusitis (CS) is involved in the development of certain malignancies. Several observational studies reported conflicting results regarding its association with cancer risk. Methods: We searched MEDLINE, EMBASE, Scopus, and Web of Science from their inception till October 2020. The fully adjusted risk estimates were abstracted independently and pooled using the generic inverse variant random-effects model. The Newcastle Ottawa Scale (NOS) was used to assess the quality of included studies. Results: Of 184 articles meeting our eligibilty criteria, 6 cohort and 6 case-control studies reporting data from USA (n = 2), Japan (n = 3), Singapore (n = 1), Taiwan (n = 5), and France (n = 1) were included in the final analysis. Compared to patients without CS (n = 562818), the RR of overall cancer risk in patients with CS (n = 51436) pooled from two studies was = 1.06 (95% CI: 1.00 - 1.13, P = 0.037). CS was associated with an increased cancer risk of head and neck (RR = 1.42, 95%CI: 1.28 - 1.58, P < 0.001), nasopharyngeal (NP) (RR = 1.62, 95%CI: 1.40 - 1.88, P < 0.001), sinonasal (RR = 1.75, 95% CI: 1.34 - 2.29, P < 0.001), and lung cancers (RR = 1.19, 95% CI: 1.14 - 1.23, P < 0.001). No significant assocation was identified with colorectal (RR = 1.02, 95% CI: 0.72 – 1.45, P = 0.89), liver (RR = 1.06, 95% CI: 0.77 - 1.45, P = 0.73), prostate (RR = 1.43, 95% CI: 0.87 – 2.33, P = 0.16), bladder (RR = 1.20, 95% CI: 0.82 - 1.75, P = 0.36), and stomach cancer (RR = 0.97, 95% CI: 0.88 - 1.06, P = 0.47). On the subgroup analysis, CS was associated with an increased risk of lung cancer in females (HR = 2.32, 95% CI: 1.23–4.39) but not in males (HR = 1.32, 95% CI: 0.79 – 2.21). In addition, the association between CS and NP cancer disappeared 1 year or more after diagnosis with RR = 1.82, 95% CI: 0.98 – 3.39) when pooling results from the three studies reporting the interval between CS diagnosis and cancer occurence. According to the NOS, 8 of the included studies were with low risk of bias, 2 with moderate risk, and 2 with high risk of bias. Conclusions: Our analysis found a significant association between CS and risk of overall, head and neck, nasopharyngeal, sinonasal, and lung cancers. Paradoxically, The risk of CS and NP cancer was significant only in subjects with a shorter duration of CS diagnosis, suggesting that CS is a coexistent complication of yet undiagnosed NP cancer. The results of this meta-analysis should be interpreted carefully due to the high heterogeneity and the small number of included studies in the site-specific cancer analyses. This association warrants further investigation using proper study design taking into consideration the years of follow-up, the interval between CS diagnosis and cancer occurrence, as well as gender disparities.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.036 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".