Epidemiology of Antisynthetase Syndrome and Risk of Malignancy in a Population-Based Cohort (1998-2019)
Bibliographic record
Abstract
OBJECTIVE: Population-based epidemiology studies about antisynthetase syndrome (ASS) are lacking. Our aims were to determine the incidence and prevalence of ASS and assess malignancy risk among patients following ASS diagnosis. METHODS: A retrospective, population-based cohort of adults with incident ASS residing in Olmsted County, Minnesota, in 1998-2019, was assembled. Fulfillment of Solomon classification criteria for ASS and clinical data were collected by manual chart review. Patients were followed until death, migration from the area, or December 31, 2019. Malignancy was defined by physician diagnosis in the medical record. Incidence rate was age- and sex-adjusted to the 2010 US White population. Point prevalence rate was obtained on January 1, 2015. RESULTS: Thirteen patients with ASS were identified (7 [54%] female, 13 [100%] White, median age 44.9 [IQR 41.9-58.3] years). The age- and sex-adjusted incidence of ASS was 0.56 (95% CI 0.25-0.87) per 100,000 population. Incidence was highest in the 50-59 age group. Age- and sex-adjusted prevalence was 9.21 per 100,000 (95% CI 3.44-14.98). Two of 13 (15%) were diagnosed with malignancy within the follow-up interval and none within 3 years of ASS diagnosis. At median 11.9 (IQR 7.0-13.4) years of follow-up, 12/13 (92%) of patients were alive. CONCLUSION: ASS is rare, with an incidence of 0.56 per 100,000 population and prevalence of 9.21 per 100,000. In this cohort, incidence was similar between male and female individuals, and was highest in persons aged 50-59 years. None of the patients developed malignancy within 3 years of ASS diagnosis.
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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 | 0.002 |
| 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".