A systematic review of transoral robotic surgery and radiotherapy for early oropharynx cancer: A systematic review
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To demonstrate the comparative effectiveness of transoral robotic surgery (TORS) to intensity modulated radiotherapy (IMRT) for early T-stage oropharyngeal cancer. DATA SOURCES: The search included MEDLINE, EMBASE, CENTRAL, PsychInfo, CINAHL, and bibliographies of relevant studies through September 2012. METHODS: Studies included patients treated for early T-stage oropharynx cancer with TORS or IMRT. Study retrieval and data extraction were conducted in duplicate and resolved by consensus. Treatment- specific details, as well as recurrence, survival, and adverse events, were collected. Methodologic quality for each study was appraised. RESULTS: Twenty case series, including eight IMRT studies (1,287 patients) and 12 TORS studies (772 patients), were included. Patients receiving definitive IMRT also received chemotherapy (43%) or neck dissections for persistent disease (30%), whereas patients receiving TORS required adjuvant radiotherapy (26%) or chemoradiotherapy (41%). Two-year overall survival estimates ranged from 84% to 96% for IMRT and from 82% to 94% for TORS. Adverse events for IMRT included esophageal stenosis (4.8%), osteoradionecrosis (2.6%), and gastrostomy tubes (43%)-and adverse events for TORS included hemorrhage (2.4%), fistula (2.5%), and gastrostomy tubes at the time of surgery (1.4%) or during adjuvant treatment (30%). Tracheostomy tubes were needed in 12% of patients at the time of surgery, but most were decannulated prior to discharge. CONCLUSION: This review suggests that survival estimates are similar between the two modalities and that the differences lie in adverse events.
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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 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".