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Associations between safety and tolerability and reporting of health-related quality of life in phase III randomized trials in common solid tumors.

2020· article· en· W3030582648 on OpenAlexaff
Ramy Saleh, Nick Meti, Domen Ribnikar, Hadar Goldvaser, Alberto Ocaña, Arnoud J. Templeton, Boštjan Šeruga, Eitan Amir

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsMcGill UniversityPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineTolerabilityInternal medicineDiscontinuationAdverse effectQuality of life (healthcare)Clinical trialRandomized controlled trialBreast cancerOncologyCancer

Abstract

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e19206 Background: Anti-cancer drugs are approved typically on the basis of efficacy and safety as evaluated in phase III randomized trials (RCTs). Health related quality of life (HRQoL) is a direct measure of patient benefit from drugs. Despite this, HRQoL is not reported universally for all anti-cancer drugs. Here we explore associations with reporting of HRQoL data in phase III RCTs in common solid tumors. Methods: We searched ClinicalTrials.gov to identify phase III oncology RCTs evaluating new drugs in adult patients with breast, colorectal, lung, or prostate cancers. We included all completed or active trials that completed accrual between January 1, 2005 and October 31, 2016. Data were extracted from published trials including HRQoL data and toxicity data on toxic death, treatment discontinuation and commonly reported grade 3 or 4 adverse events (AEs). Then, we explored associations between these safety and tolerability measures and the odds of reporting HRQoL data and whether HRQoL were favourable or not. Analysis comprised logistic regression and was performed in SPSS version 25. Results: A total of 377 phase III RCTs were initially identified. After excluding ineligible studies, a total of 143 studies were analysed. All trials (100%) were in the metastatic setting with 79 (55%) being positive trials. 40 (28%) were breast cancer trials, 38 (26%) were focused on evaluating chemotherapy, and 128 (90%) of trials were industry sponsored. 84 (59%) trials reported measuring HRQoL data, however of these, only 47 (56%) reported HRQoL data. In 14 (30%) HRQoL was improved with experimental therapy. There was no association between treatment related death (OR 1.25, 95%CI 0.74-2.12, p = 0.398) or treatment discontinuation (OR 1.12, 95%CI 0.73-1.72, p = 0.61) with reporting of HRQoL data. Associations with grade 3 or 4 AEs are shown in the Table. Conclusions: HRQoL is reported for only around a half of RCTs that collect such data. Reporting of HRQoL is not associated with safety and tolerability of anti-cancer drugs. [Table: see text]

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Reporting · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
gptMetaresearchMeta-epidemiology (broad)
Domain: Reporting · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.585
metaresearch head score (Gemma)0.606
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.5850.606
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0250.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.818
GPT teacher head0.641
Teacher spread0.177 · 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

Labeled directly by 2 models reading the full record.

MetaresearchMeta-epidemiology (broad)

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational
DomainReporting
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

Citations0
Published2020
Admission routes1
Has abstractyes

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