Survival Outcomes in Squamous Cell Carcinoma of the External Auditory Canal: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Squamous cell carcinomas (SCC) of the external auditory canal (EAC) are rare tumors representing a surgical challenge. Current knowledge is based largely on case series; thus, the level of evidence is weak. This study sought to systematically review the available SCC of the EAC literature and to identify risk factors for overall survival (OS) and disease-specific survival (DSS). A systematic review and meta-analysis of papers searched up to December 2022 through PubMed, Scopus, Web of Science, and Cochrane Library databases was conducted. Quality assessment of the eligible studies was done according to the Newcastle-Ottawa Scale. Pooled univariate and multivariable analyses and meta-analysis using a random-effects or fixed-effects Mantel-Haenszel model were performed. Fifteen articles (282 patients) met the inclusion criteria and were included in the quantitative analysis. The pooled multivariable analysis revealed cT3 and cT4 as independent prognostic factors for OS (p = 0.005, and p < 0.001, respectively) and DSS (p = 0.002, and p < 0.001, respectively). Local recurrence rate was 32.3%. The meta-analysis estimated significantly higher odds ratios for advanced T categories, than cT1-T2 tumors for OS and DSS (OR = 3.55; 95% CI, 1.93–6.52, and OR = 3.73; 95% CI, 2.00–6.97, respectively). In conclusion, locally advanced tumors were associated with poor prognosis. Poor outcomes mostly occurred due to local recurrence.
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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) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.040 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".