Cancer Trends in Idiopathic Inflammatory Myopathy: A Population-Based Study
Bibliographic record
Abstract
Objectives To assess trends in cancer incidence among patients with dermatomyositis (DM) and polymyositis (PM) compared to the general population. Methods A retrospective cohort was assembled using administrative health data from British Columbia, Canada from 1997-2020. Incident cases of DM and PM were identified using ICD-9 and ICD-10 codes. General population controls were matched 10:1 on gender, age, and index year. The cohort was divided into early (1997-2008) and late (2009-2020) periods. Cancer incidence was determined using the Cancer Registry Database. Cancer cases were included between incident diagnosis date and the end of the early/late period. Multivariable quasi-Poisson regression models were used to estimate the relative risk of cancer compared to controls, adjusting for potential confounders. Interaction terms were included to assess trends in cancer risk. Results Dermatomyositis: In the early cohort of 449 individuals (37.6% male, mean age 52.8 years), there were 47 cancer diagnoses (incidence rate (IR) of 25.3 per 1,000 person-years). There were 1,331 individuals in the late cohort (34.8% male, mean age 53.2 years), with 135 cancer diagnoses (IR of 23.1 per 1,000 person-years). The incidence rate ratio (IRR) for cancer compared to the general population was 2.21 for the early cohort (95% CI 1.40-3.42, p<0.01) and 2.00 for the late cohort (95% CI 1.41-2.80, p<0.01). The adjusted relative risk for cancer in the late compared to the early cohort was 0.84 (95% CI 0.57-1.26, p0.376). The most common cancers in DM were lung, gastrointestinal, urological and gynecological. Polymyositis: In the early cohort of 890 individuals (43.1% male, mean age 55.9 years), there were 60 cancer diagnoses (IR of 14.3 per 1,000 person-years). The late cohort comprised 1,851 individuals (42.9% male, mean age 57.7 years), with 137 cancer diagnoses (IR of 15.75 per 1,000 person-years). The IRR for cancer compared to the general population was 1.06 for the early cohort (95% CI 0.73-1.52, p0.742) and 1.07 for the late cohort (95% CI 0.80-1.42, p0.65). The adjusted relative risk for cancer in the late compared to the early cohort was 0.93 (95% CI 0.65-1.32, p0.672). The most common cancers in PM were urological, gastrointestinal, lung, and breast. Further analysis provided in Table 1. Table 1. Count of Cancer, Rate, and Rate Ratios from Quasipoisson Regression Model Conclusion Unlike PM, early and late DM cohorts both have significantly higher rates of overall cancer compared to the general population. No significant trends in overall cancer incidence were observed among patients with DM or PM in this study. Similar to the existing literature, the most common cancers were lung, gastrointestinal, urological, gynecological and breast.
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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 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".