Stigmatization related to cutaneous neurofibromas in neurofibromatosis 1: development, validation and severity strata of the cNF-PUSH-D
Bibliographic record
Abstract
BACKGROUND: Cutaneous neurofibromas (cNFs) are benign skin tumours affecting over 95% of individuals with neurofibromatosis type 1 (NF1). Their visible appearance often leads to altered body image, social isolation and discrimination. Although stigma is a well-recognized burden in NF1 and has been identified by the Response Evaluation in Neurofibromatosis and Schwannomatosis consortium as a key outcome subdomain for future cNF clinical trials, no specific tool has been developed to assess stigma in relation to cNFs. OBJECTIVES: To adapt, develop and validate a patient-reported outcome measure (PROM) specifically designed to assess stigma in adults with NF1 and cNFs, and to define its severity strata. METHODS: An expert working group including patients with NF1 modified the existing Patient Unique Stigmatization Holistic tool in Dermatology (PUSH-D) (used in chronic dermatoses) to create the 19-item cNF-PUSH-D. Following a pilot phase, a 13-item version was tested and validated through two cross-sectional studies: one in France (n = 224) via the ComPaRe NF1 cohort, and another in the USA (n = 142) via the NF Genetics Cohort. Psychometric properties were evaluated through exploratory and confirmatory factor analyses, Cronbach's α and intraclass correlation coefficients (ICCs). Convergent validity was assessed against the cNF-Skindex, the Generalized Anxiety Disorder (GAD-7) and the nine-item Patient Health Questionnaire (PHQ-9). Severity strata were defined using responses to a stigma anchor item. RESULTS: The cNF-PUSH-D demonstrated excellent reliability (Cronbach's α = 0.941, ICC = 0.939) and strong construct validity. We identified two dimensions: 'felt stigma' and 'enacted stigma'. The score correlated significantly with anxiety, depression and quality-of-life measures (all P < 0.001). Severity strata were defined as low (0-21), moderate (22-32) and high (> 33) stigma (κ = 0.516). A higher number of cNFs (≥ 100) was significantly associated with greater stigma. Scores were comparable between the US and French cohorts, and measurement invariance testing confirmed that the factorial structure remained consistent across countries. CONCLUSIONS: The cNF-PUSH-D is the first validated PROM to assess stigma specific to cNFs. It demonstrates strong psychometric properties across international populations and fills a critical gap for ongoing and future clinical trials in NF1. By quantifying stigma, the tool enables better understanding, monitoring and management of this key aspect of the cNF disease burden. An author video to accompany this article is available online.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".