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Record W2804546048 · doi:10.14338/ijpt-18-00003.1

Proton Radiotherapy for Recurrent or Metastatic Head and Neck Cancers with Palliative Quad Shot

2018· article· en· W2804546048 on OpenAlexaff
Jennifer Ma, Benjamin H. Lok, Jingfeng Zong, Stanley I. Gutiontov, Xin Cai, Andrew Bell, Marina Shcherba, Han Xiao, Eric J. Sherman, C. Jillian Tsai, Nadeem Riaz, Sean M. McBride, Oren Cahlon, Nancy Y. Lee

Bibliographic record

VenueInternational Journal of Particle Therapy · 2018
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsPrincess Margaret Cancer Centre
FundersNational Cancer InstituteNational Institutes of Health
KeywordsHead and neckMedicineRadiation therapyOncologyProton therapyHead and neck cancerRadiologyNuclear medicineSurgery

Abstract

fetched live from OpenAlex

PURPOSE: Some patients with previously treated, unresectable, recurrent or metastatic head and neck malignancies are not amenable to curative-intent treatment. Here, we investigated the quad-shot (RTOG 8502) regimen of hypofractionated proton radiotherapy (RT) in that patient population. MATERIALS AND METHODS: From 2013 to 2015, 26 patients with recurrent or metastatic cancers were treated with palliative proton RT to the head and neck with quad shot (3.7 Gy twice daily for 2 days). Patient characteristics and survival data were reviewed. RESULTS: Seventeen (65%) patients received ≥ 3 quad-shot cycles and 23 (88%) had prior head and neck RT. Overall palliative response was 73% (n = 19). The most common presenting symptom was pain (50%; n = 13), which improved in 85% (n = 22) of all patients. The overall grade-1 acute-toxicity rate was 58% (n = 15), and no acute grade 3 to 5 toxicities were observed. CONCLUSIONS: The proton quad-shot regimen demonstrates favorable palliative response and toxicity profile, even in patients that received prior RT.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.493
Threshold uncertainty score0.243

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 head0.118
GPT teacher head0.442
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations13
Published2018
Admission routes1
Has abstractyes

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