Assessment of a Bidirectional Association Between Major Depressive Disorder and Alopecia Areata
Bibliographic record
Abstract
Importance: Alopecia areata (AA) is an autoimmune disease characterized by hair loss that can impose a substantial psychological burden on patients, including major depressive disorder (MDD), yet many patients report mental health symptoms prior to the onset of AA. As such, there may be an association between MDD and AA that acts in both directions. Objective: To assess the bidirectional association between MDD and AA. Design, Setting, and Participants: This population-based retrospective cohort study included patients 10 to 90 years of age registered with The Health Improvement Network in general practices in the United Kingdom between January 1, 1986, and May 16, 2012. Statistical analysis was conducted from August 17, 2017, to April 23, 2018. To assess the risk of AA, the following 2 cohorts were defined: patients with an incident diagnosis of MDD (exposure) and a reference general population cohort. To assess the risk of MDD, the following 2 cohorts were defined: patients with an incident diagnosis of AA (exposure) and a reference general population cohort. Person-time was partitioned into unexposed and exposed time in the exposure cohorts. Main Outcomes and Measures: In the analysis of the risk of AA, development of incident AA during follow-up was considered the main outcome measure. In the analysis of the risk of MDD, development of incident MDD during follow-up was considered the primary outcome measure. Results: In the analysis of the risk of AA, 405 339 patients who developed MDD (263 916 women and 141 423 men; median age, 36.7 years [interquartile range, 26.6-50.5 years]) and 5 738 596 patients who did not develop MDD (2 912 201 women and 2 826 395 men; median age, 35.8 years [interquartile range, 25.3-52.6 years]) were followed up for 26 years. After adjustment for covariates, MDD was found to increase the risk of subsequently developing AA by 90% (hazard ratio, 1.90; 95% CI, 1.67-2.15; P < .001). Antidepressants demonstrated a protective effect on the risk of AA (hazard ratio, 0.57; 95% CI, 0.53-0.62; P < .001). In the analysis of the risk of MDD, 6861 patients who developed AA (3846 women and 3015 men; median age, 31.5 years [interquartile range, 18.2 years]) and 6 137 342 patients who did not develop AA (3 172 371 women and 2 964 971 men; median age, 35.9 years [interquartile range, 27.0 years]) were followed up for 26 years. After adjustment for covariates, AA was found to increase the risk of subsequently developing MDD by 34% (hazard ratio, 1.34; 95% CI, 1.23-1.46; P < .001). Conclusions and Relevance: These temporal analyses suggest that, while patients with AA are at risk for subsequently developing MDD, having MDD also appears to be a significant risk factor for development of AA, with antidepressant use confounding this risk.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".