SynthesisPloS one2017
Development of an evidence evaluation and synthesis system for drug-drug interactions, and its application to a systematic review of HIV and malaria co-infection.
Synthesis in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.
- Pharmacokinetics of antiretroviral and tuberculosis drugs in children with HIV/TB co-infection: a systematic review.The Journal of antimicrobial chemotherapy · 2020Pooled it
- Trial
- Trial
- Effect of Antiretroviral Therapy on Plasma Concentrations of Chloroquine and Desethyl-chloroquine.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2018Trial
- Traveling with HIV.Tropical diseases, travel medicine and vaccines · 2026Review
- DeepARV: ensemble deep learning to predict drug-drug interaction of clinical relevance with antiretroviral therapy.NPJ systems biology and applications · 2024Article
- Clinical Relevance of Drug Interactions in People Living with Human Immunodeficiency Virus on Antiretroviral Therapy-Update 2022: Systematic Review.Pharmaceutics · 2023Review
- Drug genetic associations with COVID-19 manifestations: a data mining and network biology approach.The pharmacogenomics journal · 2022Article
- Practical recommendations to combine small-molecule inhibitors and direct oral anticoagulants in patients with nonsmall cell lung cancer.European respiratory review : an official journal of the European Respiratory Society · 2022Review
- Drug-Drug Interaction Potential with Once-Weekly Isoniazid/Rifapentine (3HP) for the Treatment of Latent Tuberculosis Infection.Clinical pharmacokinetics · 2022Article
- Drug interactions: a review of the unseen danger of experimental COVID-19 therapies.The Journal of antimicrobial chemotherapy · 2020Review
- Automatically classifying the evidence type of drug-drug interaction research papers as a step toward computer supported evidence curation.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020Article
- Testing the face validity and inter-rater agreement of a simple approach to drug-drug interaction evidence assessment.Journal of biomedical informatics · 2020Article
- A Minimal Information Model for Potential Drug-Drug Interactions.Frontiers in pharmacology · 2020Article
- Tissue Parasites in HIV Infection.Current infectious disease reports · 2019Review
- Drug-Drug Interactions of Infectious Disease Treatments in Low-Income Countries: A Neglected Topic?Clinical pharmacology and therapeutics · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn all settings, there are challenges associated with safely treating patients with multimorbidity and polypharmacy. The need to characterise, understand and limit harms resulting from medication use is therefore increasingly important. Drug-drug interactions (DDIs) are prevalent in patients taking antiretrovirals (ARVs) and if unmanaged, may pose considerable risk to treatment outcome. One of the biggest challenges in preventing DDIs is the substantial gap between theory and clinical practice. There are no robust methods published for formally assessing quality of evidence relating to DDIs, despite the diverse sources of information. We defined a transparent, structured process for developing evidence quality summaries in order to guide therapeutic decision making. This was applied to a systematic review of DDI data with considerable public health significance: HIV and malaria. METHODS AND
findingsThis was a systematic review of DDI data between antiretrovirals and drugs used in prophylaxis and treatment of malaria. The data comprised all original research in humans that evaluated pharmacokinetic data and/or related adverse events when antiretroviral agents were combined with antimalarial agents, including healthy volunteers, patients with HIV and/or malaria, observational studies, and case reports. The data synthesis included 36 articles and conference presentations published via PubMed and conference websites/abstract books between 1987-August 2016. There is significant risk of DDIs between HIV protease inhibitors, or NNRTIs and artemesinin-containing antimalarial regimens. For many antiretrovirals, DDI studies with antimalarials were lacking, and the majority were of moderate to very low quality. Quality of evidence and strength of recommendation categories were defined and developed specifically for recommendations concerning DDIs.
conclusionsThere is significant potential for DDIs between antiretrovirals and antimalarials. The application of quality of evidence and strength of recommendation criteria to DDI data is feasible, and allows the assessment of DDIs to be robust, consistent, transparent and evidence-based.
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What OpenQuestion holds
Registered trials
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.