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Record W3006308605 · doi:10.1093/ofid/ofaa055

Real-world Effectiveness of Sofosbuvir/Velpatasvir for Treatment of Chronic Hepatitis C in British Columbia, Canada: A Population-Based Cohort Study

2020· article· en· W3006308605 on OpenAlexafffundabout
James Wilton, Stanley Wong, Amanda Yu, Alnoor Ramji, Darrel Cook, Zahid A Butt, Maria Alvarez, Mawuena Binka, Maryam Darvishian, Dahn Jeong, Sofia Bartlett, Margo Pearce, Prince Adu, Eric M. Yoshida, Mel Krajden, Naveed Z. Janjua

Bibliographic record

VenueOpen Forum Infectious Diseases · 2020
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsUniversity of British ColumbiaBC Cancer AgencyUniversity of WaterlooBC Centre for Disease Control
FundersAllerganCanadian Institutes of Health ResearchMinistry of Health, British ColumbiaMerck CanadaBritish Columbia Centre for Disease ControlProvincial Health Services AuthorityCelgeneGilead Sciences
KeywordsMedicineSofosbuvirRegimenCohortInternal medicinePopulationHepatitis C virusHepatitis CRibavirinImmunologyVirusEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Clinical trials show high efficacy of sofosbuvir/velpatasvir (SOF/VEL), but there are limited data from "real-world" settings. We aimed to evaluate SOF/VEL effectiveness for all hepatitis C virus (HCV) genotypes (GTs) in British Columbia (BC), Canada. METHODS: We used the BC Hepatitis Testers Cohort, which includes all HCV cases in the province (1990-2015) linked to administrative databases, including prescriptions to end of 2018. We measured sustained virologic response (SVR; negative RNA ≥10 weeks after treatment end) and identified characteristics associated with non-SVR. Conservatively, we excluded individuals with no assessment for SVR if their last RNA test after treatment initiation was negative (but included if positive). RESULTS: Of 2821 eligible participants, most were infected with GT1 (1076, 38.1%) or GT3 (1072, 38.0%), and a minority (278, 9.9%) were treated with RBV. SVR was 94.6% (2670/2821) overall and 94.5% (1017/1076) for GT1, 96.4% (512/531) for GT2, and 93.7% (1004/1072) for GT3. When disaggregated by GT, treatment regimen, and cirrhosis/treatment experience, SVR was lowest (30/40, 75.0%) among treatment-experienced GT3 individuals treated with RBV. Characteristics associated with non-SVR in multivariable analysis included younger age, RBV addition, and being a person with HIV (PWH) or who injects/injected drugs (PWID). When treatment regimen (±RBV) was removed from multivariable model, treatment experience was associated with non-SVR for GT3. Of 151 non-SVR individuals, 56.3% were nonvirological failures (treatment incomplete/no assessment for SVR) and 43.7% were virological failures (nonresponse/relapse). A disproportionately high percentage of non-SVR among PWID was due to nonvirological failure. CONCLUSIONS: SOF/VEL was highly effective in this "real-world" population-based cohort. Additional support is required for PWID/PWH to reach SVR.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.200

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0030.001
Scholarly communication0.0020.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.018
GPT teacher head0.314
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations39
Published2020
Admission routes3
Has abstractyes

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