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Survival of Patients With Head and Neck Merkel Cell Cancer

2023· article· en· W4388834350 on OpenAlexaffabout
Ameeta L. Nayak, Arthur Travis Pickett, Megan Delisle, Brittany Dingley, Ranjeeta Mallick, Trevor D. Hamilton, Heather Stuart, Martha Talbot, Gregory McKinnon, Evan Jost, Eva Thiboutot, Valerie Francescutti, Sal Samman, Alexandra Easson, Angela E. Schellenberg, Shaila J. Merchant, Julie La, Kaitlin Vanderbeck, Frances C. Wright, David Berger‐Richardson, Pamela Hebbard, Olivia Hershorn, Rami Younan, Érica Patocskai, Samuel Rodriguez-Qizilbash, Ari Meguerditichian, Vanina Tchuente, Suzanne Kazandjian, Alex Mathieson, Farisa Hossain, Jessika Hetu, Martin Corsten, A Tohmé, Carolyn Nessim, Stephanie Johnson‐Obaseki

Bibliographic record

VenueJAMA Network Open · 2023
Typearticle
Languageen
FieldMedicine
TopicPolyomavirus and related diseases
Canadian institutionsUniversité de SherbrookeMcGill University Health CentreCentre Hospitalier de l’Université de MontréalUniversity of ManitobaSunnybrook Health Science CentreQueen's UniversityMcMaster UniversityOttawa HospitalUniversity Health NetworkDalhousie UniversityHamilton Health SciencesVancouver General HospitalMount Sinai HospitalUniversity of CalgaryPrincess Margaret Cancer CentreMemorial University of NewfoundlandFoothills Medical Centre
Fundersnot available
KeywordsMedicineMerkel cell carcinomaRadiation therapyStage (stratigraphy)Retrospective cohort studyMerkel cellIncidence (geometry)Cancer registryCancerProportional hazards modelInternal medicineSurgeryCarcinoma

Abstract

fetched live from OpenAlex

Importance: Merkel cell carcinoma (MCC) is an aggressive cutaneous neuroendocrine carcinoma. Due to its relatively low incidence and limited prospective trials, current recommendations are guided by historical single-institution retrospective studies. Objective: To evaluate the overall survival (OS) of patients in Canada with head and neck MCC (HNMCC) according to American Joint Committee on Cancer 8th edition staging and treatment modalities. Design, Setting, and Participants: A retrospective cohort study of 400 patients with a diagnosis of HNMCC between July 1, 2000, and June 31, 2018, was conducted using the Pan-Canadian Merkel Cell Cancer Collaborative, a multicenter national registry of patients with MCC. Statistical analyses were performed from January to December 2022. Main Outcomes and Measures: The primary outcome was 5-year OS. Multivariable analysis using a Cox proportional hazards regression model was performed to identify factors associated with survival. Results: Between 2000 and 2018, 400 patients (234 men [58.5%]; mean [SD] age at diagnosis, 78.4 [10.5] years) with malignant neoplasms found in the face, scalp, neck, ear, eyelid, or lip received a diagnosis of HNMCC. At diagnosis, 188 patients (47.0%) had stage I disease. The most common treatment overall was surgery followed by radiotherapy (161 [40.3%]), although radiotherapy alone was most common for stage IV disease (15 of 23 [52.2%]). Five-year OS was 49.8% (95% CI, 40.7%-58.2%), 39.8% (95% CI, 26.2%-53.1%), 36.2% (95% CI, 25.2%-47.4%), and 18.5% (95% CI, 3.9%-41.5%) for stage I, II, III, and IV disease, respectively, and was highest among patients treated with surgery and radiotherapy (49.9% [95% CI, 39.9%-59.1%]). On multivariable analysis, patients treated with surgery and radiotherapy had greater OS compared with those treated with surgery alone (hazard ratio [HR], 0.76 [95% CI, 0.46-1.25]); however, this was not statistically significant. In comparison, patients who received no treatment had significantly worse OS (HR, 1.93 [95% CI, 1.26-2.96)]. Conclusions and Relevance: In this cohort study of the largest Canada-wide evaluation of HNMCC survival outcomes, stage and treatment modality were associated with survival. Multimodal treatment was associated with greater OS across all disease stages.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.015
Threshold uncertainty score0.239

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.290
Teacher spread0.271 · 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.

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

Citations9
Published2023
Admission routes2
Has abstractyes

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