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dc.contributor.authorAlger, E
dc.contributor.authorMinchom, A
dc.contributor.authorLee Aiyegbusi, O
dc.contributor.authorSchipper, M
dc.contributor.authorYap, C
dc.coverage.spatialEngland
dc.date.accessioned2023-10-11T11:58:26Z
dc.date.available2023-10-11T11:58:26Z
dc.date.issued2023-10-01
dc.identifier102228
dc.identifierS2589-5370(23)00405-4
dc.identifier.citationEClinicalMedicine, 2023, 64 pp. 102228 -
dc.identifier.issn2589-5370
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/6014
dc.identifier.eissn2589-5370
dc.identifier.eissn2589-5370
dc.identifier.doi10.1016/j.eclinm.2023.102228
dc.description.abstractBACKGROUND: Traditionally, within dose-finding clinical trials, treatment toxicity and tolerability are assessed by clinicians. Research has shown that clinician reporting may have inadequate inter-rater reliability, poor correlation with patient reported outcomes, and under capture the true toxicity burden. The introduction of patient-reported outcomes (PROs), where the patient can assess their own symptomatic adverse events or quality of life, has potential to complement current practice to aid dose optimisation. There are no international recommendations offering guidance for the inclusion of PROs in dose-finding trial design and analysis. Our review aimed to identify and describe current statistical methods and data visualisation techniques employed to analyse and visualise PRO data in published early phase dose-finding oncology trials (DFOTs). METHODS: DFOTs published from June 2016-December 2022, which presented PRO analysis methods, were included in this methodological review. We extracted 35 eligible papers indexed in PubMed. Study characteristics extracted included: PRO objectives, PRO measures, statistical analysis and visualisation techniques, and whether the PRO was involved in interim and final dose selection decisions. FINDINGS: Most papers (30, 85.7%) did not include clear PRO objectives. 20 (57.1%) papers used inferential statistical techniques to analyse PROs, including survival analysis and mixed-effect models. One trial used PROs to classify a clinicians' assessed dose-limiting toxicities (DLTs). Three (8.6%) trials used PROs to confirm the tolerability of the recommended dose. 25 trial reports visually presented PRO data within a figure or table within their publication, of which 12 papers presented PRO score longitudinally. INTERPRETATION: This review highlighted that the statistical methods and reporting of PRO analysis in DFOTs are often poorly described and inconsistent. Many trials had PRO objectives which were not clearly described, making it challenging to evaluate the appropriateness of the statistical techniques used. Drawing conclusions based on DFOTs which are not powered for PROs may be misleading. With no guidance and standardisation of analysis methods for PROs in early phase DFOTs, it is challenging to compare study findings across trials. Therefore, there is a crucial need to establish international guidance to enhance statistical methods and graphical presentation for PRO analysis in the dose-finding setting. FUNDING: EA has been supported to undertake this work as part of a PhD studentship from the Institute of Cancer Research within the MRC/NIHR Trials Methodology Research Partnership. AM is supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at the Royal Marsden NHS Foundation Trust, the Institute of Cancer Research and Imperial College.
dc.formatElectronic-eCollection
dc.format.extent102228 -
dc.languageeng
dc.language.isoeng
dc.publisherELSEVIER
dc.relation.ispartofEClinicalMedicine
dc.subjectDose-finding
dc.subjectMethodological review
dc.subjectOncology
dc.subjectPatient-reported outcomes
dc.subjectStatistical methods
dc.titleStatistical methods and data visualisation of patient-reported outcomes in early phase dose-finding oncology trials: a methodological review.
dc.typeJournal Article
dcterms.dateAccepted2023-09-05
dc.date.updated2023-10-11T10:59:51Z
rioxxterms.versionVoR
rioxxterms.versionofrecord10.1016/j.eclinm.2023.102228
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
rioxxterms.licenseref.startdate2023-10-01
rioxxterms.typeJournal Article/Review
pubs.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/37781154
pubs.organisational-groupICR
pubs.organisational-groupICR/Primary Group
pubs.organisational-groupICR/Primary Group/ICR Divisions
pubs.organisational-groupICR/Primary Group/ICR Divisions/Clinical Studies
pubs.organisational-groupICR/Primary Group/ICR Divisions/Clinical Studies/Clinical Trials & Statistics Unit
pubs.organisational-groupICR/Students
pubs.organisational-groupICR/Students/PhD and MPhil
pubs.organisational-groupICR/Students/PhD and MPhil/22/23 Starting Cohort
pubs.publication-statusPublished online
pubs.publisher-urlhttp://dx.doi.org/10.1016/j.eclinm.2023.102228
pubs.volume64
icr.researchteamClin Trials & Stats Unit
dc.contributor.icrauthorAlger, Emily
dc.contributor.icrauthorMinchom, Anna
dc.contributor.icrauthorYap, Christina
icr.provenanceDeposited by Mrs Jessica Perry (impersonating Prof Christina Yap) on 2023-10-11. Deposit type is initial. No. of files: 1. Files: Statistical methods and data visualisation of patient-reported outcomes in early phase dose-finding oncology trials a method.pdf


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