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Record W3047793726 · doi:10.1186/s41687-020-00232-7

Patient-reported outcome measures for retinoblastoma: a scoping review

2020· review· en· W3047793726 on OpenAlexafffund
Ana Janić, Sylvie Bowden, Sarah Levy, Jennifer Stinson, Helen Dimaras

Bibliographic record

VenueJournal of Patient-Reported Outcomes · 2020
Typereview
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsSickKids FoundationUniversity of TorontoCentre for Global Health ResearchInstitute for Clinical Evaluative SciencesCanada Research ChairsHospital for Sick Children
FundersHospital for Sick ChildrenUniversity of Toronto
KeywordsPromMedicinePatient-reported outcomeRetinoblastomaMEDLINEQuality of life (healthcare)Pediatric ophthalmologyConstruct validityHealth related quality of lifeFamily medicinePsychometricsInternal medicineStrabismusClinical psychologySurgeryNursingDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Retinoblastoma is a childhood retinal cancer with lifelong consequences such as vision loss and increased risk of second cancer. Patient-reported outcome measures (PROMs) are instruments that measure outcomes related to health directly reported by patients. The purpose of this study was to determine the scope, characteristics and quality of PROMs used in retinoblastoma and related fields of pediatric ophthalmology and pediatric oncology. METHODS: Databases MEDLINE and Embase were searched for studies in the English language that reported on PROMs used in retinoblastoma, pediatric oncology, or pediatric ophthalmology; grey literature and studies reporting on developmental PROM phases were excluded. PROMs were grouped by the construct measured and domains assessed, and classified as condition-specific or generic. A subsequent search was then conducted in MEDLINE and Embase for studies assessing measurement properties of the identified PROMs. PROMs with associated studies were assessed for their methodologic quality using the COnsensus-based standard for the Selection of health Measurement INstruments (COSMIN) strategy. RESULTS: Among 110 eligible studies uncovered by the database searches, 143 PROMs were identified: one retinoblastoma-specific, 56 ophthalmology- and 86 oncology-related. The most common construct measured was 'health-related quality of life' and the most common domain assessed was emotional well-being. Of the 143 PROMs, 100 had associated validation studies; the one retinoblastoma-specific PROM was not validated. Quality assessment revealed 34/100 PROMs received a score of sufficient quality in both subcategories of 'overall content validity'; 3/100 received a score of sufficient quality in both subcategories of 'internal structure'; 0/100 received a score of sufficient quality in all three subcategories of 'remaining measurement properties'. The Patient-Reported Outcome Measure Information System (PROMIS) Pediatric Profile-25 was the highest-scoring PROM identified, meeting COSMIN standards for 2/3 measurement property categories (and 5/7 subcategories). Eleven additional PROMs were identified which had sufficient scores in 1/3 measurement property categories (and 5/7 subcategories). CONCLUSION: The study identified several PROMs from the pediatric ophthalmology and pediatric oncology literature that could be relevant to the retinoblastoma population, but many have limits to their validation. Future development of a retinoblastoma-specific PROM, performed in partnership with retinoblastoma patients to support optimal content validity, could first focus on the selection and definition of the optimal construct to measure, followed potentially by adaptation and further validation of the relevant PROMs with strong methodologic quality identified in this study.

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)0.034
metaresearch head score (Gemma)0.150
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.034
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.150
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.007
Bibliometrics0.0210.022
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.102
GPT teacher head0.409
Teacher spread0.308 · 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 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

Citations9
Published2020
Admission routes2
Has abstractyes

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