Idiopathic Inflammatory Myopathy Associated with Malignancy: A Retrospective Cohort of 151 Korean Patients with Dermatomyositis and Polymyositis
Bibliographic record
Abstract
OBJECTIVE: To define the standardized incidence ratio (SIR) of malignancy and factors associated with malignancies in Korean patients with dermatomyositis (DM) and polymyositis (PM). METHODS: The demographic, clinical, and laboratory features of 151 patients diagnosed with DM/PM were compared in patients with and without malignancies. RESULTS: Malignancies were found in 23 of 98 patients with DM (23.5%) and in 2 of 53 with PM (3.8%). Lung cancer (8 patients) was the most common malignancy. Compared with the period-specific, sex-matched, and age-matched Korean population, the SIR for malignancy in patients with DM was 14.2 (95% CI 9.0-21.3). Univariate analysis showed that factors associated with malignancy included older age (p < 0.001), DM (p = 0.002), dysphagia (p < 0.001), the absence of interstitial lung disease (ILD; p = 0.001), and lower elevations in aspartate aminotransferase (p = 0.005) and lactate dehydrogenase concentrations (p < 0.001). Multivariate analysis showed that factors independently associated with malignancy included older age (per 10 years, OR 2.3, 95% CI 1.6-3.5, p < 0.001), DM (OR 5.9, 95% CI 1.3-26.2, p = 0.020), dysphagia (OR 2.6, 95% CI 1.2-6.6, p = 0.042), and the absence of ILD (OR 0.1, 95% CI 0.01-0.9, p = 0.040). CONCLUSION: DM was associated with a greater risk of concomitant malignancies, especially lung cancer, than PM. Independent factors associated with malignancies in patients with DM/PM were older age, the presence of dysphagia, and the absence of ILD.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".