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Risk of chronic opioid use after radiation for head and neck cancer: A systematic review and meta-analysis.

2020· review· en· W3031543858 on OpenAlexaff
Sondos Zayed, Cindy Lin, Gabriel Boldt, Nancy Read, Lucas C. Mendez, Varagur Venkatesan, Jinka Sathya, Dwight E. Moulin, David A. Palma

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typereview
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsCancer Care OntarioWestern UniversityLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineMeta-analysisHead and neck cancerCochrane LibraryChemoradiotherapyRadiation therapyInternal medicineMEDLINELarynxCancerHazard ratioOpioidIncidence (geometry)Confidence intervalSurgeryOncology

Abstract

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6579 Background: Opioid overuse is a major international public health concern. The prevalence and risk factors for chronic opioid use (COU) in radiation-induced head and neck pain are poorly understood. The aim of this study was to estimate the rates of COU and to identify risk factors for COU in head and neck cancer (HNC) patients undergoing curative-intent radiotherapy (RT) or chemoradiotherapy (CRT). Methods: We performed a systematic review and meta-analysis based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, using the PubMed (Medline), EMBASE, and Cochrane library databases, queried from dates of inception until present. COU was defined as persistent opioid use ≥3 months after treatment completion. Studies in the English language that reported on COU in HNC patients who received RT/CRT were included. Meta-analyses were performed using random effects models. Heterogeneity was assessed using the I2 value. Results: A total of 134 studies were identified, with 7 retrospective studies (reporting on 1841 patients) meeting inclusion criteria. Median age was 59.4 years (range 56.0-62.0) with 1343 (72.9%) men and 498 (27.1%) women. Primary tumour locations included oropharynx (891, 48.4%), oral cavity (533, 29.0%), larynx (93, 5.1%), hypopharynx (32, 1.7%), and nasopharynx (29, 1.6%). 846 (46.0%) patients had stage I/II disease and 926 (50.3%) had stage III-IV disease. 301 (16.3%) patients had RT alone, 738 (40.1%) received CRT, and 594 (32.3%) underwent surgery followed by adjuvant RT/CRT. The proportion of HNC patients who received radiotherapy and developed COU was 40.7% at 3 months (95% CI 22.6%-61.7%, I2= 97.1%), 15.5% at 6 months (95% CI 7.3%-29.7%, I2= 94.3%) and 7.0% at 1 year. There were significant differences in COU based on primary tumor sites (P < 0.0001), with the highest rate (46.6%) in oropharyngeal malignancies. Other factors associated with COU included history of psychiatric disorder (61.7%), former/current alcohol abuse (53.9%), and start of opioids prior to radiation treatment (51.6%). There was no significant difference in the proportion of COU by gender (P = 0.683), disease stage (I/II vs III/IV; P = 0.443), or treatment received (RT, CRT, or adjuvant RT/CRT; P = 0.711). Conclusions: A significant proportion of patients who undergo radiotherapy for head and neck cancer suffer from COU. High-risk factors for COU include an oropharyngeal primary tumour, history of psychiatric disorder, former/current alcohol abuse, and pre-treatment opioid use. New strategies to mitigate opioid use are needed.

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)0.010
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.023
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0140.043
Bibliometrics0.0050.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.299
GPT teacher head0.547
Teacher spread0.248 · 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 designMeta-analysis
Domainnot available
GenreReview

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".

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Citations2
Published2020
Admission routes1
Has abstractyes

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