Survival Outcomes of Temporal Bone Squamous Cell Carcinoma: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
OBJECTIVE: Temporal bone squamous cell carcinoma (TBSCC) is a rare malignancy with poor prognosis, and optimal treatment for advanced cases is uncertain. Our systematic literature review aimed to assess 5-year survival outcomes for advanced TBSCC across different treatment modalities. DATA SOURCES: EMBASE, Medline, PubMed, and Web of Science. REVIEW METHODS: A systematic literature review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for articles published between January 1989 and June 2023. RESULTS: The review yielded 1229 citations of which 31 provided 5-year survival data for TBSCC. The final analysis included 1289 patients. T classification data was available for 1269 patients and overall stage for 1033 patients. Data for 5-year overall survival (OS) was 59.6%. Five-year OS was 81.9% for T1/2 and 47.5% for T3/4 (P < .0001). OS for T1/T2 cancers did not significantly differ between surgery and radiation (100% vs 81.3%, P = .103). For advanced-stage disease (T3/T4), there was no statistical difference in OS when comparing surgery with postoperative chemoradiotherapy (CRT) (OS 50.0%) versus surgery with postoperative radiotherapy (XRT) (OS 53.3%) versus definitive CRT (OS 58.1%, P = .767-1.000). There was not enough data to assess the role of neoadjuvant CRT. CONCLUSION: Most patients will present with advanced-stage disease, and nodal metastasis is seen in nearly 22% of patients. This study confirms the prognostic correlation of the current T classification system. Our results suggest that OS did not differ significantly between surgery and XRT for early stage disease, and combined treatment modalities yield similar 5-year OS for advanced 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 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.033 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".