Epidemiology of Isolated Cutaneous Lupus Erythematosus in the Multiethnic Population of Reunion Island: A Retrospective Multicenter Study
Bibliographic record
Abstract
OBJECTIVE: Few data are available about the epidemiology of cutaneous lupus erythematosus (CLE) in the Southern hemisphere and in multiethnic populations. We describe the prevalence, incidence, and clinical characteristics of isolated CLE in the multiethnic population of Reunion Island, France, including patients with dark skin. METHODS: The study was performed in all public hospitals and private dermatology practices in Reunion Island. Cases were identified through informatics databases. Cases were defined as isolated CLE, meaning they did not fulfill the criteria for systemic lupus erythematosus (SLE). Incident cases were collected from 2008 to 2021. Prevalence was calculated on January 1, 2022. A capture-recapture analysis was performed to estimate both prevalence and incidence. RESULTS: A total of 268 cases of CLE were identified and 218 were incident cases. The standardized prevalence of CLE was 43 out of 100,000 persons and the average annual standardized incidence was 3.1 per 100,000 person-years (PY). With a capture-recapture analysis, prevalence and annual incidence were estimated to be 99 out of 100,000 persons (95% CI 77.10-136.45) and 5.7 per 100,000 PY (95% CI 4.40-7.95), respectively. The mean age at diagnosis was 41.7 years and the ratio of female to male individuals was 4:1. Patients with dark skin had a higher rate of discoid CLE and were more likely to receive immunosuppressants. Generalized discoid CLE, panniculitis, and overlapping subtypes of CLE appeared as predictive markers of progression toward SLE. CONCLUSION: The prevalence and incidence of CLE in the multiethnic population of Reunion Island seem higher than in light-skinned populations. We highlight new risk factors of evolution toward SLE that should be known by practitioners to adjust follow-up.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".