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Record W4408999921 · doi:10.3390/curroncol32040202

Merkel-Cell Carcinoma: Local Recurrence Rate Versus Radiation Dose Study from a 949-Patient Database

2025· article· en· W4408999921 on OpenAlexaffvenue
Patricia Tai, Michael Veness, Vimal H. Prajapati, Aoife Jones Thachuthara, Jidong Lian, Avi Assouline, Kurian Joseph

Bibliographic record

VenueCurrent Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicPolyomavirus and related diseases
Canadian institutionsWestern UniversityUniversity of TorontoUniversity of AlbertaUniversity of CalgaryUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineRadiation therapyMerkel cell carcinomaAdjuvantCarcinomaAdjuvant radiotherapyOncologyInternal medicine

Abstract

fetched live from OpenAlex

(1) Background: Knowledge regarding the optimal radiotherapy dose for Merkel-cell carcinoma (MCC) remains limited. (2) Methods: Following a PubMed search, equivalent doses in 2 Gy fractions (Gy2) were compared. (3) Results: Of the 949 patients, 939 were evaluable, with 728 (77.5%) cases localized to the primary site and 171 irradiated without chemotherapy. The overall local recurrence rate (LRR) was 23% (40/171). After definitive radiotherapy with EQD2 < 50 Gy2 versus ≥50 Gy2, the LRRs were 23.1% (3/13) and 12.5% a(1/8), respectively (p = 0.0004). (4) Conclusions: For definitive radiotherapy, EQD2 < 50 Gy2 demonstrates a significantly higher LRR than ≥50 Gy2 (p = 0.0004). This study is clinically useful and unique with stratification by definitive/adjuvant settings and positive/negative resection margins. A future prospective multicenter study is needed to determine the optimal radiotherapy doses.

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)0.004
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.071
GPT teacher head0.394
Teacher spread0.324 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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