Effectiveness, Complications, and Costs of Rheumatoid Arthritis Treatment with Biologics in Alberta: Experience of Indigenous and Non-indigenous Patients
Bibliographic record
Abstract
OBJECTIVE: To examine clinical effectiveness, treatment complications, and healthcare costs for indigenous and non-indigenous Albertans with rheumatoid arthritis (RA) participating in the Alberta Biologics Pharmacosurveillance program. METHODS: Patients initiating biologic therapy in Alberta (2004-2012) were characterized for disease severity and treatment response. Provincial hospitalization separations, physician claims, outpatient department data, and emergency department data were used to estimate treatment complication event rates and healthcare costs. RESULTS: Indigenous patients (n = 90) presented with higher disease activity [mean 28-joint count Disease Activity Score (DAS28) 6.11] than non-indigenous patients (n = 1400, mean DAS28 5.19, p < 0.0001). Improvements in DAS28, function, swollen joint count, CRP, and patient and physician global evaluation scores were comparable to non-indigenous patients, but indigenous patients did not have a significant improvement in erythrocyte sedimentation rate (-0.31 per month, 95% CI -0.79 to 0.16, p = 0.199). At the end of study followup, 13% (12/90) of indigenous and 33% (455/1400) of non-indigenous patients were in DAS28 remission (p < 0.001). Indigenous patients had a 40% increased risk of all-cause hospitalization [adjusted incidence rate ratio (IRR) 1.4, 95% CI 1.1-1.8, p = 0.01] and a 4-fold increase in serious infection rate (adjusted IRR 4.0, 95% CI 2.3-7.0, p < 0.001). Non-indigenous patients incurred higher costs for RA-related hospitalizations (difference $896, 95% CI 520-1273, p < 0.001), and outpatient department visits (difference $128, 95% CI 2-255, p = 0.047). CONCLUSION: We identified disparities in treatment outcomes, safety profiles, and patient-experienced effects of RA for the indigenous population in Alberta. These disparities are critical to address to facilitate and achieve desired RA outcomes from individual and population perspectives.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".