A Retrospective Descriptive Analysis of a British Columbian Myositis Cohort
Bibliographic record
Abstract
Objectives To describe clinical phenotypes of inflammatory myopathies (IIM), serologies, treatment regimens, remission status, and survival outcomes, in a single center in BC. Methods This is retrospective chart review of all IIM patients seen from March 2019 until June 2024 at Mary Pack Artheritis Centre myositis clinic. We reviewed patient demographics, myositis antibodies, treatments, and clinical courses. This study was approved by the University Research Ethics Board. Results A total of 268 patients were included with mean follow-up of 69.6 months. The patient baseline demographics and clinical characteristics at the last follow-up are summarized in Table 1. Anti-synthetase syndrome, dermatomyositis, immune-mediated necrotizing myopathy, and scleromyositis constituted most of the cohort. Polymyositis made up only 6.7% of the patients. Seventeen patients (6.3%) had a cancer diagnosis within 3 years of their myositis diagnosis. Prevalence of myositis-specific antibody (MSA) and myositis-associated antibody (MAA) was 83.2%. Anti-Jo-1 was the most common MSA at 14.2%. Anti-Ro52 was the most common MAA at 28.0%. For treatment, patients on average were trialed on 2-3 conventional synthetic disease-modifying anti-rheumatic drugs (csDMARDs). 31.7% were on biologics/targeted synthetic (ts) DMARDs at the last follow-up or at the time of death, including 16.4% on rituximab, 10.1% on Tofacitinib, 4.5% on Upadacitinib and 0.8% on both rituximab and Tofacitinib. Additionally, 40% of the cohort have used IVIG at 1 point. Overall, 64% of patients were in remission, 24% had active disease, 11% deceased, and 1% lost to follow-up. Causes of death included infections, cancer, heart failure, pulmonary emboli, and rapid progressive interstitial lung disease refractory to immunosuppression. Table 1. Patient baseline demographics and clinical characteristics at last follow up Conclusion This study summarizes the diverse clinical characteristics and treatment paradigms in the largest myositis cohort in BC. Consistent with the literature, polymyositis is a diagnosis of exclusion and only 6.7% of patients received a diagnosis of polymyositis. Despite immunosuppressives and IVIG, mortality was high at 11% in this cohort and the remission rate was only achieved in 64%, underscoring the importance of personalized management approaches in improving early diagnosis, remission rates and survival in myositis patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".