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Record W3013640632 · doi:10.1200/edbk_280687

Novel Strategies to Effectively De-escalate Curative-Intent Therapy for Patients With HPV-Associated Oropharyngeal Cancer: Current and Future Directions

2020· article· en· W3013640632 on OpenAlexaff
Katharine A. Price, Anthony C. Nichols, Colette J. Shen, Almoaidbellah Rammal, Pencilla Lang, David A. Palma, Ari J. Rosenberg, Bhisham Chera, Nishant Agrawal

Bibliographic record

VenueAmerican Society of Clinical Oncology Educational Book · 2020
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineCetuximabDe-escalationRadiation therapyChemoradiotherapyOncologyInternal medicineAdjuvantChemotherapyCancerIntensive care medicine

Abstract

fetched live from OpenAlex

The treatment of patients with HPV-associated oropharyngeal cancer (HPV-OPC) is rapidly evolving and challenging the standard of care of definitive radiotherapy with concurrent cisplatin. There are numerous promising de-escalation strategies under investigation, including deintensified definitive chemoradiotherapy, transoral surgery followed by de-escalated adjuvant therapy, and induction chemotherapy followed by de-escalated locoregional therapy. Definitive radiotherapy alone or with cetuximab is not recommended for curative-intent treatment of patients with locally advanced HPV-OPC. The results of ongoing phase III studies are awaited to help answer key questions and address ongoing controversies to transform the treatment of patients with HPV-OPC. Strategies for de-escalation under investigation include the incorporation of immunotherapy and the use of novel biomarkers for patient selection for de-escalation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.621
Threshold uncertainty score0.469

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.064
GPT teacher head0.448
Teacher spread0.383 · 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

Citations40
Published2020
Admission routes1
Has abstractyes

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