Population-based prevalence and incidence estimates of primary discoid lupus erythematosus from the Manhattan Lupus Surveillance Program
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Epidemiological data for primary discoid lupus erythematosus (pDLE) remain limited, particularly for racial/ethnic populations in the USA. The Manhattan Lupus Surveillance Program (MLSP) is a population-based retrospective registry of cases with SLE and related diseases including pDLE in Manhattan and was used to provide estimates of the prevalence and incidence of pDLE across major racial/ethnic populations. METHODS: MLSP cases were identified from rheumatologists, hospitals and population databases. Two case definitions were used for pDLE: the primary case definition which was any physician diagnosis found in the chart and a secondary case definition which was limited to cases diagnosed by a rheumatologist and/or dermatologist. Rates among Manhattan residents were age-adjusted, and capture-recapture analyses were conducted to assess case under-ascertainment. RESULTS: Based on the primary definition, age-adjusted overall prevalence and incidence rates of pDLE among Manhattan residents were 6.5 and 0.8 per 100 000 person-years, which increased to 9.0 and 1.3 after capture-recapture adjustment. Prevalence and incidence rates were approximately two and six times higher, respectively, among women compared with men (p<0.0001). Higher prevalence was also found among non-Latino blacks (23.5) and Latinos (8.2) compared with non-Latino whites (1.8) and non-Latino Asians (0.6) (p<0.0001). Incidence was highest among non-Latino blacks (2.4) compared with all other racial/ethnic groups. Similar relationships were observed for the secondary case definition. CONCLUSION: Data from the MLSP provide epidemiological estimates for pDLE among the major racial/ethnic populations in the USA and reveal disparities in pDLE prevalence and incidence by sex and race/ethnicity among Manhattan residents.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it