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Record W2777076440 · doi:10.1136/bmjopen-2017-017282

Evaluation of patient-reported outcome protocol content and reporting in UK cancer clinical trials: the EPiC study qualitative protocol

2018· article· en· W2777076440 on OpenAlexaff
Ameeta Retzer, Thomas Keeley, Khaled Ahmed, Jo Armes, Julia Brown, Lynn Calman, Chris Copland, Fabio Efficace, Anna Gavin, Adam Glaser, David Greenfield, Anne Lanceley, Rachel M. Taylor, Galina Velikova, Michael Brundage, Rebecca Mercieca‐Bebber, Madeleine King, Melanie Calvert, Derek Kyte

Bibliographic record

VenueBMJ Open · 2018
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsQueen's University
FundersUniversity of BirminghamNational Institute for Health and Care ResearchNational Cancer Research InstituteMacmillan Cancer SupportCancer Research Institute
KeywordsMedicineProtocol (science)EPICClinical trialCancerFamily medicineAlternative medicineInternal medicinePathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Patient-reported outcomes (PROs) are increasingly included within cancer clinical trials. If appropriately collected, analysed and transparently reported, these data might provide invaluable evidence to inform patient care. However, there is mounting indication that the design and reporting of PRO data in cancer trials may be suboptimal. This programme of research will establish via three interlinked studies whether these findings are applicable to UK cancer trials, and if so, how to best enhance the way PROs are assessed, managed and reported in clinical trials. This study will explore with key stakeholders factors that influence optimal PRO protocol content, implementation and reporting and make recommendations for training and guidance. METHODS AND ANALYSIS: Semistructured interviews will be conducted with members of key stakeholder groups. The purposive sample of up to 48 participants will include: (1) trial chief investigators, trial management group members, statisticians and research nurses of cancer trials including primary or secondary PRO recruited via the National Cancer Research Institute (NCRI) Clinical Studies Group and Consumer Liaison Group and the UK Clinical Research Collaboration Registered UK Clinical Trial Unit Network; (2) NCRI Consumer Liaison Group members; (3) international experts in PRO oncology trial design; and (4) journal editors and funding bodies. Data will be analysed using directed thematic analysis employing a coding frame and modified as analysis progresses. Formal triangulation of coding and member checking will be employed to enhance credibility. ETHICS AND DISSEMINATION: This study was approved by the University of Birmingham Ethics Committee (Ref: ERN_17-0085). Findings will be disseminated via conference presentations, peer-reviewed journals, patient groups and social media (@CPROR_UoB; http://www.birmingham.ac.uk/cpror). PROSPERO REGISTRATION NUMBER: CRD42016036533.

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)0.582
metaresearch head score (Gemma)0.531
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.418
Threshold uncertainty score0.516

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5820.531
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0060.006
Science and technology studies0.0060.009
Scholarly communication0.0080.007
Open science0.0050.010
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0250.008

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 head0.866
GPT teacher head0.722
Teacher spread0.144 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designQualitative
DomainReporting
GenreProtocol

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

Citations7
Published2018
Admission routes1
Has abstractyes

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