A cross-sectional study of gender differences in quality of life domains in patients with neurofibromatosis type 1
Bibliographic record
Abstract
BACKGROUND: There is limited data regarding gender differences in quality of life between women and men with Neurofibromatosis type 1. We aimed to study differences in quality of life domains between women and men with Neurofibromatosis type 1 living in Canada. METHODS: This is a cross sectional study of adults with Neurofibromatosis type 1 attending a tertiary NF centre at Toronto General Hospital between January 2016 to December 2017. Demographic and clinical data were collected. We compared scores of generic measures (SF-36, EQ-5D-5L, pain interference) and a disease-specific measure (PedsQL-NF1 module) between women and men. We also assessed the relationship between disease visibility scored by an examiner (Ablon's visibility index) and self-reported perceived physical appearance, stratified by gender. RESULTS: One hundred and sixty-two participants were enrolled, 92 females and 70 males. Ablon's index score 1 was in 43% and score 2 in 44%, while only 13% of patients had a score 3. Women had worse scores on the total PedsQL-NF1 scales, and also in the perceived physical appearance, anxiety and emotional health domains. In women, there was a low but significant correlation between Ablon's index and perceived physical appearance (r = - 0.27, p = 0.01, ANOVA p < 0.001). In men, there was no difference in self-reported physical appearance by Ablon's index. There were no differences between men and women in the SF-36 or EQ-5D-5L scores. CONCLUSION: Women with NF1 reported worse NF1-related quality of life than men, with worse perceived physical appearance, anxiety, and mental health. Perceived physical appearance does not always correlate to disease visibility; therefore, healthcare providers should inquire about body image, physical appearance concerns, and mental health, especially among women with NF1.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".