Negative impact of comorbidities on all-cause mortality of patients with psoriasis is partially alleviated by biologic treatment: A real-world case-control study
Bibliographic record
Abstract
BACKGROUND: Cardiovascular comorbidities are believed to cause higher mortality in psoriasis patients. Conversely, systemic therapy may improve overall survival. OBJECTIVE: To evaluate the impact of different comorbidities and therapy on mortality risk of psoriasis patients in the entire population of Alberta, Canada (population 4.37 million). METHODS: Cohorts of psoriasis cases (n = 18,618) and controls (ambulatory patients matched 1:3 by age and sex) were retrieved from Alberta Health Services Data Repository of Reporting database within the period 2012 to 2019. Cases were stratified according to Charlson Comorbidity Index, and the type of therapy. RESULTS: Mortality in psoriasis cohort was significantly higher than in the controls (median age of death 72.0 years vs 74.4 years, respectively). Charlson Comorbidity Index and comorbidities were strong predictors of mortality, in particular drug induced liver injury (hazard ratio 1.8, affective bipolar disease, hazard ratio 1.6, and major cardiovascular diseases. Mortality was lower in patients treated with biologics (hazard ratio 0.54). LIMITATIONS: Some factors (psoriasis type and severity, response to treatment, smoking, alcohol intake) could not be measured. CONCLUSIONS: Hepatic injury, psychiatric affective disorders and cardiovascular disease were major determinants of overall survival in psoriasis. Biologic therapy was associated with a reduced mortality risk.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".