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Patient decision aid for chemotherapy or exclusion in cisplatin-intolerant patients with locally advanced cervical cancer (CECIL): Development, alpha testing, and peer-validation.

2023· article· en· W4379283735 on OpenAlexaboutno aff
Warren Bacorro, Kathleen Baldivia, Jocelyn Mariano, Evelyn Dancel, Linda Antonio, Aida Bautista, Gil Gonzalez, Teresa Sy Ortin, Rodel Canlas

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsnot available
FundersPhilippine Council for Health Research and Development
KeywordsMedicineCervical cancerDecision aidsGynecologic oncologyDelphi methodOncologyFamily medicineMedical physicsCancerInternal medicineAlternative medicinePathology

Abstract

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e13506 Background: In locally advanced cervical cancer (LACC), adding chemotherapy (ChT) to radiotherapy (RT) improves survival but increases toxicity. In the Philippines, about 33% of cervical cancers are diagnosed in the elderly and about 36% present with ureteral obstruction. RT compliance may be compromised by cisplatin toxicity. Shared decision-making (SDM) better engages the patient in the decision-making and implementation planning process. Patient decision aids (PtDA) may increase knowledge and self-efficacy, thereby decreasing decisional conflict and attitudinal barriers and improving treatment compliance. Methods: The Interprofessional Shared Decision-Making Model was used as a conceptual framework. The PtDA defines the index decision, facilitates information exchange and examination of values and preferences, towards the determination of a practicable choice. Using a mixed-methods design and following International Patient Decision Aid Standards (IPDAS) guidelines, a steering panel consisting of radiation oncologists (RO) (2), gynecologic oncologists (GO) (1), oncology nurse (1), clinical psychologist (1), cancer survivor (1), and caregiver (1) developed the CECIL prototype, a PtDA for cisplatin-intolerant LACC patients faced with the decision of adding ChT to RT. The elements were based on the Decision Support Framework and the content, on current international and local guidelines, and a recent systematic review. The prototype was alpha-tested by the steering committee using the e-Delphi method. The PtDR Ottawa Acceptability Practitioner and Patient Questionnaires were used to evaluate comprehensibility, length, amount of information, neutrality, and overall suitability for decision-making. The prototype was then independently evaluated by local internal (RO, 1) and external (GO, 1), and international (RO, 1) reviewers using the IPDAS checklist version 4, which covers 9 relevant domains: information, probabilities, values, guidance, development, evidence, disclosure, plain language, and evaluation. Results: Alpha testing showed high practitioner acceptability (all items with mean and median scores ≥4; overall mean score 4.70/5) and good patient acceptability (all items good to excellent). Content validation showed that the PtDA satisfied all IPDAS qualifying (6) and certification (6) criteria, with high overall mean score (3.63/4) for applicable quality (17) criteria. All reviewers' comments were considered in the subsequent revision of the prototype. Conclusions: The CECIL prototype shows good practitioner and patient acceptability, and content validity on peer review. It will be pilot-tested and subjected to the phase 2 of the clinical trial (NCT05701735) to determine its utility in preparation for decision-making and effectiveness in reducing decisional conflict. Clinical trial information: NCT05701735 .

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)0.032
metaresearch head score (Gemma)0.114
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.114
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.252
GPT teacher head0.530
Teacher spread0.277 · 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 designQualitative
Domainnot available
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

Citations1
Published2023
Admission routes1
Has abstractyes

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