MétaCan
Menu
Back to cohort
Record W2769432517 · doi:10.21873/anticanres.11960

Topical Management of Acute Radiation Dermatitis in Breast Cancer Patients: A Systematic Review and Meta-Analysis

2017· review· en· W2769432517 on OpenAlexaff
Fatimah Haruna, Andrea Lipsett, Laure Marignol

Bibliographic record

VenueAnticancer Research · 2017
Typereview
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsTrinity College
Fundersnot available
KeywordsMedicineMeta-analysisDermatologyCancerBreast cancerRadiation therapySystematic reviewMEDLINEOncologyPathologySurgeryInternal medicineBiology

Abstract

fetched live from OpenAlex

AIM: To evaluate the efficacy of topical corticosteroids in managing acute radiation dermatitis (RD) in female breast cancer patients. MATERIALS AND METHODS: MEDLINE, EMBASE, CINAHL, CENTRAL, ScienceDirect, Google Scholar and Clinicaltrials.gov were searched up to and including March 2017 to identify Randomised Controlled Trials (RCTs) assessing topical corticosteroids for the management and prevention of acute RD. RESULTS: Ten RCTs (919 participants) were identified. Meta-analysis, including results for 845 participants, demonstrated significant benefits of topical corticosteroids in preventing the incidence of wet desquamation (OR: 0.29; 95%CI: 0.19-0.45; p<0.0001) and reducing the mean RD score (SMD: -0.47, 95%CI: -0.61 - -0.33, p<0.00001). CONCLUSION: Topical corticosteroids impacted on the incidence of wet desquamation and the average RD score observed in female breast cancer patients. The use of topical corticosteroids can reduce pruritus in participants and improve quality of life.

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)0.007
metaresearch head score (Gemma)0.019
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0140.020
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.154
GPT teacher head0.506
Teacher spread0.352 · 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".

Quick stats

Citations111
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueAnticancer ResearchSame topicEffects of Radiation ExposureFrench-language works237,207