COLLAB: A Global Survey of Clinical and Laboratory Assessment in Alopecia Areata by Hair Specialists
Bibliographic record
Abstract
ABSTRACT Background Alopecia areata (AA) is a common non‐scarring alopecia. Data continue to emerge on associations with autoimmune and other conditions. Janus kinase inhibitors (JAKi) are increasingly used to treat AA. Objectives The aim was to assess variation in laboratory testing in patients with AA among hair experts internationally and to compare subspecialized clinical practice to current guidelines. Methods Thirty hair experts from 14 countries and six continents contributed to develop a 24‐item survey collecting demographic information on respondents; methods of severity assessment; and laboratory testing practices in AA for mimics, contributory factors, associations, and workup for systemic therapy. The survey was distributed to a global network of expert hair specialists. Results Of 214 respondents, 79.9% (171/214) had special interest/expertise in hair loss disorders, and 35.5% ( n = 76) were based in Europe. Most cared for both adults and children (87.9%, n = 188). For clinical assessment, almost two‐thirds (63.6%, n = 136) used the Severity of Alopecia Tool and 38% ( n = 84) used the Dermatology Life Quality Index. Only 24.3% ( n = 52) typically tested for alternative infectious or inflammatory diagnoses, 39.7% ( n = 85) typically tested for contributory conditions such as nutritional deficiencies, and 50.9% ( n = 109) typically tested for co‐existent autoimmune illnesses. Thyroid function testing was routinely performed in 73.4% ( n = 157) and complete blood count (CBC) was checked in 65.9% ( n = 141). Compared to conventional systemic therapy, experts were more likely to check lipid levels, creatine kinase, coagulation profiles, thrombophilia screens, tuberculosis blood testing, hepatitis B and C serology before prescribing JAKi. Conclusions Real world practice of laboratory testing for AA by hair experts, who may see more severe or complex alopecia, is variable. Most experts routinely perform thyroid function and CBC testing. We discuss evidence for indications for testing for AA mimics, contributory factors, associated autoimmune conditions, and before systemic therapy. Further research is required to characterise the role of laboratory testing in AA.
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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 | 0.009 | 0.072 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".