Frontal Fibrosing Alopecia: An Emerging Epidemic
Bibliographic record
Abstract
Since the initial description of frontal fibrosing alopecia (FFA) in 1994, increasingly more cases of FFA have been reported in literature. Although clear epidemiologic data on the incidence and prevalence of FFA is not available, it is intriguing to consider whether FFA should be labeled as an emerging epidemic. A medline trend analysis as well as literature review using keywords "alopecia," "hair loss," and "cicatrical" were performed. Medline trend analysis of published FFA papers from 1905 to 2016 showed that the number of publications referenced in Medline increased from 1 (0.229%) in 1994 to 44 (3.5%) in 2016. The number of patients per published cohort also increased dramatically since the first report of FFA. Over the time period of January 2006-2016, our multi hair-referral centers collaboration study also showed a significant increase in new diagnoses of FFA. At this juncture, the cause for the rapid rise in cases is one of speculation. It is plausible that a cumulative environmental or toxic factor may trigger hair loss in FFA. Once perhaps a "rare type" of cicatricial alopecia, FFA is now being seen in a frequency in excess of what is expected, thus suggestive of an emerging epidemic.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".