Impact of availability of direct-acting antivirals for hepatitis C on Canadian hospitalization rates, 2012–2016
Bibliographic record
Abstract
BACKGROUNDS: Hospitalizations associated with hepatitis C virus (HCV) infection and liver disease increased on average by 6.0% per year from 2004 to 2010 in Canada and were projected (in 2010) to increase by another 4% by 2016. The first generation of direct-acting antivirals (DAAs) became available in 2012. In 2014, a second generation of effective and well-tolerated DAA therapy was authorized in Canada. The impact of DAA therapy on the HCV-associated disease burden in Canada has not been documented. OBJECTIVES: To assess the potential impact of DAA therapy on the disease burden by a) comparing the actual hospitalization rates associated with HCV infection and liver disease following the introduction of DAAs in Canada with the 2010 baseline projection and b) documenting the associated uptake of anti-HCV therapy. METHODS: The hospital records of inpatients diagnosed with chronic HCV and chronic liver disease were extracted from the Canadian Discharge Abstract Database (DAD) by fiscal year for 2004-2016. We compared the actual number of hospitalizations to the baseline projection by year and for selected 5-year birth cohorts (1925-1989). The monthly number of new prescriptions for anti-HCV regimens was extracted from the IQVIA CDH CompuScript database (formerly IMS Health), aggregated to annual levels by age group and compared with hospitalization trends. RESULTS: Compared to the baseline projection, there was a slight reduction in hospitalizations in 2014/15 and 2015/16. This slight reduction was followed by a more significant decline in 2016/17 (32% below expected; 95% confidence interval [CI]: 27%-37%). The largest declines were observed for patients born before 1960 (age 55 or older) at 40% below expected in 2016/17. The number of new anti-HCV prescriptions increased from 5,484 in fiscal year 2012/13 to a peak of 17,775 in 2015/2016. The number of new prescriptions corresponds to approximately 1.3 and five times the number of hospitalizations in 2012/13 and 2015/16, respectively. CONCLUSIONS: In Canada there has been a modest decrease in HCV and liver-related hospitalizations following a significant increase in uptake of second-generation DAAs in 2015. However, the burden is still high. Linked health administrative databases created to monitor the disease burden in the new treatment era should provide additional insight with the linkage of treatment history and disease stage to individual outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".