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Record W4402334456 · doi:10.1002/hed.27928

Clinical outcome of salvage surgery in patients with recurrent oral cavity cancer: A systematic review and meta‐analysis

2024· review· en· W4402334456 on OpenAlexaboutno aff
Oh‐Hyeong Lee, Jooin Bang, Geun‐Jeon Kim, Dong‐Il Sun, Sang‐Yeon Kim

Bibliographic record

VenueHead & Neck · 2024
Typereview
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisMedicineSalvage surgerySurgeryOutcome (game theory)CancerOral cavityCancer surgeryInternal medicineRadiation therapyDentistry

Abstract

fetched live from OpenAlex

This systematic review and meta-analysis investigated the impact of salvage surgery on 5-year overall survival (OS) and prognostic factors in recurrent oral cavity cancer (rOCC) patients. Relevant literature before May 2022 was reviewed, including retrospective cohort studies and observational studies comparing salvage surgery to other treatments. Risk-of-bias assessments were conducted using the Newcastle-Ottawa scale. Statistical and subgroup analyses assessed the impact of salvage surgery on 5-year OS and prognostic factors. 3036 documents were initially retrieved, with 14 retrospective cohort studies (2069 participants) included. Meta-analysis of 5-year OS in salvage surgery patients yielded a rate of 43.0%. Subgroup analysis showed higher OS in Asians (49.9% vs. 36.9%, p = 0.003) and late-relapse (63.8% vs. 30.0%, p = 0.004) groups. Prognostic factors revealed hazards associated with nodal recurrence, extranodal extension, and perineural invasion. Salvage surgery is a viable option for rOCC patients, showing favorable 5-year OS outcomes. Low publication bias enhances study reliability, but its single-arm design limits conclusions on salvage surgery superiority over other treatments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.576
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0240.003
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.210
GPT teacher head0.475
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations4
Published2024
Admission routes1
Has abstractyes

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