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Record W4413816738 · doi:10.3390/healthcare13172165

Systematic Review of Fear of Cancer Recurrence Patient-Reported Outcome Measures: Evaluating Methodological Quality and Measurement Properties Using the COSMIN Checklist

2025· review· en· W4413816738 on OpenAlexafffund
Christine Maheu, Wing Lam Tock, Peter Fisher, Jacqueline Galica, Mina Singh, Isabel Centeno, Maude Hébert, Chelsea Moran, Paulina Pietruczuk, Andreas Dinkel, Caroline Zwaal, Belinda Thewes, Tania Estapé

Bibliographic record

VenueHealthcare · 2025
Typereview
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsJewish General HospitalUniversity of OttawaUniversité du Québec à Trois-RivièresYork UniversityMcMaster UniversityQueen's UniversityCentre Hospitalier de l’Université de MontréalMcGill University
FundersRéseau de recherche portant sur les interventions en sciences infirmières du Québec
KeywordsChecklistPatient-reported outcomeQuality (philosophy)Outcome (game theory)MedicinePhysical therapyPsychologyPhysical medicine and rehabilitationQuality of life (healthcare)Cognitive psychologyMathematicsNursing

Abstract

fetched live from OpenAlex

Background: Fear of cancer recurrence (FCR) is a common, distressing concern among cancer survivors, with implications for psychological well-being and quality of life. Despite the proliferation of patient-reported outcome measures (PROMs) to assess FCR, consensus on the most valid and reliable instruments remains limited. Objective: To conduct a comprehensive psychometric evaluation of FCR PROMs developed or validated between 2011 and 2023, using the full COSMIN methodology. This review builds on earlier work by systematically appraising both newly developed and adapted instruments to inform evidence-based PROM selection for clinical and research use. Methods: This review followed the COSMIN 10-step procedure and PRISMA 2020 guidelines. Six databases were searched from January 2011 to December 2023. A search cut-off of 31 December 2023 was applied to align with COSMIN feasibility recommendations and ensure sufficient time and resources for full psychometric evaluation across all included PROMs. Eligible studies included adults diagnosed with cancer and reported on the psychometric evaluation of a self-reported, Likert-scale-based FCR PROM. PROMs were appraised across eight psychometric properties using COSMIN’s Risk of Bias checklist, criteria for good measurement properties, and modified Grading of Recommendations Assessment, Development, and Evaluation (GRADE) for evidence quality. Instruments were categorized as A, B, or C according to COSMIN’s recommendations. Results: Of the 34 PROMs evaluated across 32 studies, 28 achieved COSMIN Category A status, indicating sufficient psychometric quality for clinical or research use. Among the 19 FCRI and FoP-Q instruments validated in new cultural or population contexts, 15 received a Category A rating, reflecting strong cross-cultural performance. Short forms such as the FCRI-SF and FoP-Q-SF demonstrated consistent psychometric strength across French, English, Portuguese, and Asian-language versions. Of the 14 newly developed PROMs—including the CWS-6, FCR4/7, CARQ-4, and FCR-1—12 achieved Category A. The FCR-1 was the only single-item PROM to demonstrate responsiveness, supporting its use in both screening and longitudinal monitoring. For practical guidance, five PROMs (FCR-1, FCRI-SF, FoP-Q-SF, FCR-7, and CWS) emerged as the most strongly supported for clinical use. Conclusions: This review provides a comprehensive evaluation of contemporary FCR PROMs and highlights substantial progress in the development of valid, reliable, and culturally adaptable tools. The FCRI, FoP-Q-SF, and several newly developed short forms, such as FCR7, CWS, and particularly, the FCR-1, emerge as strong candidates for use in clinical screening and longitudinal assessment. These findings offer clear evidence-based guidance for instrument selection in research and survivorship care. PROSPERO registration: CRD42023453783.

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)0.013
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.145
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0000.001
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 head0.797
GPT teacher head0.572
Teacher spread0.225 · 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 designSystematic review
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

Citations5
Published2025
Admission routes2
Has abstractyes

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