Familial Versus Non-Familial Vitiligo: Clinical Features, Anatomical Distribution, and Autoimmune Comorbidity from a Southern Taiwan Hospital
Bibliographic record
Abstract
Background and Objectives: Familial clustering and autoimmune multimorbidity are frequently observed in vitiligo. However, the clinical implications of a positive family history across generations remain unclear. In this study, a positive family history was defined as having at least one affected parent or grandparent. Materials and Methods: We retrospectively reviewed the electronic medical records of 972 adults with vitiligo who attended the rheumatology division in a regional teaching hospital in southern Taiwan between 2006 and 2022. Demographic characteristics, family history, clinical features, and autoimmune comorbidities were extracted from electronic medical records. Associations between family history and clinical parameters were assessed using logistic regression analyses adjusted for age and sex. Results: A total of 157 patients (16.2%) reported a family history, more often through parents than grandparents; maternal history was more common than paternal. Compared with those without a family history, affected families showed significantly younger age at diagnosis and a higher prevalence of lower-limb involvement. In adjusted models, family history was associated with greater odds of lower-limb involvement (adjusted odds ratio [aOR] 1.78, 95% confidence interval [CI] 1.22–2.58) and lower odds of eyebrow/eyelash depigmentation (aOR 0.39, 95% CI 0.16–0.92). Hashimoto thyroiditis was more frequent among familial cases (aOR 7.56, 95% CI 1.23–46.65). In sex-stratified analyses, associations were stronger in females, notably for lower-limb involvement (aOR 1.87), axillary depigmentation (aOR 2.33), and Hashimoto thyroiditis (aOR 11.27). Conclusions: Familial vitiligo shows earlier onset, distinct anatomical patterns, and increased thyroid autoimmunity, supporting systematic family-history assessment and targeted thyroid screening.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".