ArticleOncology and therapy2022
Measuring the Patient Experience in Rare Disorders: Benefit of Pragmatic Mixed-Methods Research in NUT Carcinoma.
Article in Oncology and therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 26 citations in OpenAlex.
- Article
- Mixed-methods research to support the use of new lymphoma-specific patient-reported symptom measures derived from the EORTC item library.Journal of patient-reported outcomes · 2024Review
- A Mixed-Methods Study to Better Measure Patient-Reported Pain and Fatigue in Soft Tissue Sarcoma.Oncology and therapy · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionPatient-centered outcome measurement (PCOM) is essential to capture the outcomes important to patients. However, it presents unique challenges in rare diseases, particularly those that are "young" (not diagnosed before the twenty-first century), with limited literature, lack of disease-specific patient-reported outcome (PRO) measures, and difficult sampling and data collection. One example of this is NUT (nuclear protein in testis) carcinoma (NUTca), a rare and rapidly progressing cancer, with tumors preliminary in the head, neck, and lungs. The published literature on NUTca is scarce. The limited number of case reports focus primarily on the clinical development and presentation of tumors. Currently, there are no publications describing the patient experience of NUTca and no specific PRO measures to assess the patient experience. We conducted mixed-methods research, including concept elicitation interviews, cognitive debriefing, and quantitative data analyses, to fill this evidence gap and describe challenges and solutions in the context of NUTca.
methodsAs published previously, our conceptualization of NUTca was based on elicitation interviews with 27 participants (n = 10 patients; n = 17 caregivers) using a semi-structured format; this framework formed the basis for a bolt-on strategy to develop a bespoke PRO measure based on the EORTC QLQ-C30, supplemented by targeted items from the EORTC Item Library and new items. In this publication, 20 participants were interviewed (n = 10 patients; n = 10 caregivers) to debrief items. Given the variety of tumor locations and related symptoms, and the small sample of patients providing responses to location-specific symptom items, we used response option endorsement frequencies to illuminate the variability of response for the concepts measured.
resultsThis study highlights the challenges in implementing patient-centric research to inform and develop PRO measures in rare diseases.
conclusionsOur mixed-methods research used pragmatic solutions to collect patient experience data and provides an evidence base to inform PCOM in clinical programs in this rapidly progressing rare cancer with high unmet need.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.