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Record W2131182971 · doi:10.1002/hed.20510

Merkel cell carcinoma of the head and neck: Is adjuvant radiotherapy necessary?

2006· article· en· W2131182971 on OpenAlexaffabout
Jonathan R. Clark, Michael Veness, Ralph Gilbert, Christopher J. O’Brien, Patrick Gullane

Bibliographic record

VenueHead & Neck · 2006
Typearticle
Languageen
FieldMedicine
TopicPolyomavirus and related diseases
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMerkel cell carcinomaMedicineRadiation therapyStage (stratigraphy)SurgeryRetrospective cohort studySurvival analysisCohortCarcinomaInternal medicineAdjuvant therapyProportional hazards modelT-stageOncologyChemotherapyOverall survival

Abstract

fetched live from OpenAlex

BACKGROUND: Controversy exists regarding the optimal management of patients with Merkel cell carcinoma. The primary aim of this study was to determine whether combined treatment with surgery and radiotherapy improves outcome in a multi-institutional cohort of patients with Merkel cell carcinoma of the head and neck. The secondary aims were to determine by stage, which patients derive benefit from combined therapy and to identify predictors for survival on multivariable analysis. METHODS: A retrospective analysis of 110 patients with Merkel cell carcinoma of the head and neck was performed. Data were collected from 3 tertiary care institutions (Westmead Hospital, Sydney, Australia; Princess Margaret Hospital, Toronto, Canada; Royal Prince Alfred Hospital, Sydney). There were 78 males and 32 females, median age was 70 years, and mean follow-up of survivors was 2.3 years. Sixty-six patients underwent combined treatment, and 44 patients had either surgery or radiotherapy alone. Analysis by stage was performed using 2 staging systems. RESULTS: Local and regional control at 5 years was 84% and 69%, respectively. Combined treatment improved both local (p = .009) and regional control (p = .006). Overall and disease-specific survival at 5 years was 49% and 62%, respectively. Combined treatment was associated with significantly better disease-free survival on univariable analysis (p = .013) When analyzed by stage, patients with stage IIb (primary >1 cm, node negative) disease who underwent combined treatment had improved disease-free (p = .005) and disease-specific survival (p = .035). Predictors of survival on multivariable analysis were age >70 years (HR 6.19, p < .001), primary tumor size >1 cm (HR 7.55, p < .001), number of nodal metastases divided into none, 2 (HR 3.71 per stratum, p < .001). When analyzed with age and disease stage, treatment modality trended toward significance as a predictor of disease-specific (p = .081) and overall survival (p = .076). Disease stage was the most powerful independent predictor on Cox regression (HR 5.43 per stratum, p < .001). CONCLUSIONS: Merkel cell carcinoma is an aggressive cutaneous malignancy. Age and disease stage are the most important predictors of survival. Combined surgery and radiotherapy improves both locoregional control and disease-free survival. Patients with stage II disease appear to derive the greatest benefit from adjuvant radiotherapy, including improved disease specific survival.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.255
Teacher spread0.245 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations142
Published2006
Admission routes2
Has abstractyes

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