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Record W4311018631 · doi:10.1200/jco.22.01873

Mepitel Film for the Prevention of Acute Radiation Dermatitis in Breast Cancer: A Randomized Multicenter Open-Label Phase III Trial

2022· article· en· W4311018631 on OpenAlexaff
Tara Behroozian, Lauren Milton, Irene Karam, Liying Zhang, Keyue Ding, Julia Lou, François Gallant, Eileen Rakovitch, William T. Tran, Hany Soliman, Eric Leung, Danny Vesprini, Ewa Szumacher, Hanbo Chen, E. Donovan, Jacqueline Lam, Silvana Spadafora, Matt Wronski, Chris Lavoie, Natalie Walde, Emily Lam, Gina Wong, Erin McKenzie, Krista Ariello, Samantha Kennedy, Saba Shariati, Katherine Carothers, Glen Gonzales, Y. Bilge Kagan, Edward Chow

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsSault Area HospitalQueen's UniversityMcMaster UniversityHealth Sciences NorthHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineRandomized controlled trialCommon Terminology Criteria for Adverse EventsBreast cancerClinical endpointAdverse effectLumpectomyInternal medicineOdds ratioSurgeryMastectomyRadiation therapyCancer

Abstract

fetched live from OpenAlex

PURPOSE Radiation dermatitis (RD) is common in patients undergoing breast radiotherapy. Mepitel film (MF) can reduce RD, but the results from two randomized controlled trials are conflicting. We aimed to conduct a confirmatory randomized controlled trial in patients at risk of RD. METHODS Patients were randomly assigned to receive MF or standard care (2:1 ratio). Patients with large breasts after lumpectomy (bra size ≥ 36 inches or cup size ≥ C) or after mastectomy were eligible. Stratification factors included surgery type, dose fractionation, and administration of boost/bolus. The primary end point was grade (G) 2 or 3 RD using the Common Terminology Criteria for Adverse Events v5.0. Secondary end points included patient- and clinician-reported outcomes. RESULTS Between January 2020 and May 2022, 376 patients were included in the modified intention-to-treat analysis. The incidence of G2 or 3 RD was significantly lower in MF patients compared with standard care (n = 39/251, 15.5%; 95% CI, 11.3 to 20.6% v n = 57/125, 45.6%; 95% CI, 36.7 to 54.8% respectively, odds ratio (OR): 0.20, P < .0001). Benefits of MF remained significant in patients who developed G 3 RD (n = 7, 2.8%; 95% CI, 1.1 to 5.7% v n = 17, 13.6%; 95% CI, 8.1 to 20.9%, OR: 0.19) and moist desquamation (n = 20, 8.0%; 95% CI, 4.9 to 12.0% v n = 24, 19.2%; 95% CI, 12.7 to 27.1%, OR: 0.36). When evaluating the combined patient and health care provider score using Radiation-Induced Skin Reaction Assessment Scale, the MF arm had significantly lower scores ( P < .0001). Individual items on the Radiation-Induced Skin Reaction Assessment Scale also favored the MF for both patient- and clinician-reported outcomes. Blistering/peeling, erythema, pigmentation, and edema were significantly reduced in the MF arm. Three patients removed the film prematurely because of rash (n = 2) and excessive pruritus (n = 1). CONCLUSION MF significantly reduces RD in patients undergoing breast radiotherapy.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.079
GPT teacher head0.504
Teacher spread0.425 · 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 designRandomized trial
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

Citations68
Published2022
Admission routes1
Has abstractyes

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