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Record W2765900544 · doi:10.21037/apm.2017.09.06

A critical evaluation of quality of life in clinical trials of breast cancer patients treated with radiation therapy

2017· review· en· W2765900544 on OpenAlexaff
Gustavo Nader Marta, Fábio Ynoe de Moraes, Elton Trigo Teixeira Leite, Edward Chow, David Cella, Andrew Bottomley

Bibliographic record

VenueAnnals of Palliative Medicine · 2017
Typereview
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsSunnybrook Health Science CentrePrincess Margaret Cancer CentreHealth Sciences CentreUniversity Health Network
Fundersnot available
KeywordsMedicineClinical endpointClinical trialQuality of life (healthcare)Health related quality of lifeBreast cancerRadiation therapyCancerInternal medicineOncologyPhysical therapyDisease

Abstract

fetched live from OpenAlex

The aim of this study was to investigate the extent to which health-related quality of life (HRQOL) parameters have been reported in phase III trials with breast cancer patients (BCPs) who received radiation therapy (RT). We also examine the frequency and correlates of significant HRQOL gains. A systematic review was conducted. When HRQOL was a study endpoint, we extracted data on the instruments used for HRQOL analysis, assessing if there was formal statistical comparison between study groups and the results of such comparisons as reported by the authors of the studies. In result, 182 trials were included. HRQOL was considered as endpoint in 38 (20.8%) of the studies and it was used as primary endpoint in 10.9% of them. Of 22 trials that had a positive primary endpoint, 18 had a significant benefit in HRQOL, in favor of the experimental arm. Of 13 trials that had a negative primary endpoint, there were no differences in HRQOL among the study groups. With respect to HRQOL assessment, statistical methods and definition of timing of evaluation were described in 32 (84.2%) and 36 (94.7%) trials, respectively. In conclusion, HRQOL has been infrequently investigated in trials in BCP who received RT. Statistical methods and timing of evaluation were infrequently described with sufficient detail to be informative.

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)0.017
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.789
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0080.001
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 head0.710
GPT teacher head0.648
Teacher spread0.062 · 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.

Study designObservational
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

Citations23
Published2017
Admission routes1
Has abstractyes

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