Evidence map›Paper›PMID 36074319›Full record

ArticleHepatology international2022

Drug-drug interactions between direct-acting antivirals and co-medications: a territory-wide cohort study.

Vicki Wing-Ki Hui, Christopher Langjun Au, Amy Shuk Man Lam, Terry Cheuk-Fung Yip, Yee-Kit Tse, Jimmy Che-To Lai, Henry Lik-Yuen Chan, Vincent Wai-Sun Wong, Grace Lai-Hung Wong

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Article in Hepatology international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.9field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 14 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 2 countries.

Vicki Wing-Ki Hui *Medical Data Analytics Centre (MDAC), The Chinese University of Hong Kong, Hong Kong SAR, China.
Christopher Langjun Au *Medical Data Analytics Centre (MDAC), The Chinese University of Hong Kong, Hong Kong SAR, China.
Amy Shuk Man LamMedical Data Analytics Centre (MDAC), The Chinese University of Hong Kong, Hong Kong SAR, China.
Terry Cheuk-Fung YipMedical Data Analytics Centre (MDAC), The Chinese University of Hong Kong, Hong Kong SAR, China.
Yee-Kit TseMedical Data Analytics Centre (MDAC), The Chinese University of Hong Kong, Hong Kong SAR, China.
Jimmy Che-To LaiMedical Data Analytics Centre (MDAC), The Chinese University of Hong Kong, Hong Kong SAR, China.
Henry Lik-Yuen ChanDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, 9/F Prince of Wales Hospital, 30-32 Ngan Shing Street, Shatin, Hong Kong SAR, China.
Vincent Wai-Sun WongMedical Data Analytics Centre (MDAC), The Chinese University of Hong Kong, Hong Kong SAR, China.
Grace Lai-Hung WongMedical Data Analytics Centre (MDAC), The Chinese University of Hong Kong, Hong Kong SAR, China. wonglaihung@cuhk.edu.hk.ORCID http://orcid.org/0000-0002-2863-9389
Chinese University of Hong Kong · HKUnion Hospital · CN

Funding

Gilead Sciences IN-HK-987-6069
6 · The paper itself

Abstract

backgroundThe increasing number of direct-acting antiviral (DAA) regimens along with limited number of subjects and co-medications involved in clinical trials results in drug-drug interactions (DDIs) with DAAs is to be determined. We aimed to examine the prevalence and degree of DDIs between DAAs and other co-medications in a territory-wide cohort of chronic hepatitis C virus (HCV) patients.

methodsDDIs were assigned to three risk categories: Category 1-no clinically significant DDI; category 2-potential clinically significant interaction (monitoring and caution required); category 3-contraindicated (should not be co-administered).

resultsOf 2981 patients (mean age 59.3 ± 12.3 years; male 60.6%), 810 (48.8%) had genotype 1 and 552 (33.2%) genotype 6 HCV among the 1661 patients with HCV genotype tested; 769 (25.8%) received sofosbuvir/velpatasvir, 510 (17.1%) sofosbuvir/ledipasvir, and 865 (29.0%) glecaprevir/pibrentasvir. More than one-fourth (26.3%) of the patients have polypharmacy (≥ 3 co-medications) in all patients, 27.0% in patients received sofosbuvir/velpatasvir, 25.1% in elbasvir/grazoprevir, and 21.2% in glecaprevir/pibrentasvir. 2037 (68.3%) patient experienced DDI (Category 2: 53.1%; Category 3: 15.2%). The commonest drugs leading to DDIs were calcium channel blockers (31.5%) and proton pump inhibitors (23.0%) in category 2; statins (10.2%), antiplatelet/anticoagulants (3.0%) and antipsychotics (2.9%) in category 3. Changing medication was the most common response from physicians in both category 2 and 3 DDIs.

conclusionThe commonest co-medications leading to contraindication during DAA treatment were statins and antipsychotics. Category 2 and 3 DDIs are often managed by appropriate dose adjustments or temporary discontinuation of relevant co-medications. Careful assessment for potential DDI before DAA use is mandatory to avoid potential harmful effects.

Indexed as

Hepatitis C, ChronicHydroxymethylglutaryl-CoA Reductase InhibitorsAgedAminoisobutyric AcidsAntiviral AgentsBenzimidazolesBenzopyransCarbamatesCohort StudiesCyclopropanesDrug InteractionsHepacivirusHeterocyclic Compounds, 4 or More RingsHumansLactams, MacrocyclicLeucineAminoisobutyric AcidsAntiviral AgentsBenzimidazolesBenzopyransCarbamatesCyclopropanesglecaprevirHeterocyclic Compounds, 4 or More RingsHydroxymethylglutaryl-CoA Reductase InhibitorsLactams, MacrocyclicLeucineProlineQuinoxalinesSofosbuvirSulfonamidesvelpatasvirAntipsychoticCalcium channel blockerChronic hepatitis CDirect-acting antiviralDrug–drug interactionHepatitis C virusHepatocellular carcinomaProton pump inhibitorStatinSustained virologic response

Identifiers

PMID36074319
OpenAlexW4294991507

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.