ArticlePLoS medicine2023
Recommendations on data sharing in HIV drug resistance research.
Article in PLoS medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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
9 citing papers in PubMed, 10 citations in OpenAlex.
- Generating synthetic multi-national longitudinal cohorts for clinically grounded HIV research.Nature communications · 2026Article
- Phylogenetics and molecular evolution to understand and curb the HIV pandemic.Nature reviews. Microbiology · 2026Review
- GenBank2PubMed: bridging viral genomic data and the scientific literature with AI-assisted curation.Scientific reports · 2025Article
- Generating Synthetic Multi-national Longitudinal Cohorts for Clinically Grounded HIV Research.medRxiv : the preprint server for health sciences · 2025Article
- Treatment of Advanced HIV in the Modern Era.Drugs · 2025Review
- MARVEL-minimising the emergence and dissemination of HIV-1 drug resistance in Portuguese-speaking African Countries (PALOP): low-cost portable NGS platform for HIV-1 surveillance in Africa.BMC infectious diseases · 2024Article
- Article
- AUTO-TUNE: SELECTING THE DISTANCE THRESHOLD FOR INFERRING HIV TRANSMISSION CLUSTERS.bioRxiv : the preprint server for biology · 2024Article
- AUTO-TUNE: selecting the distance threshold for inferring HIV transmission clusters.Frontiers in bioinformatics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
46 authors at 20 institutions in 19 countries.
Funding
Abstract
• Human immunodeficiency virus (HIV) drug resistance has implications for antiretroviral treatment strategies and for containing the HIV pandemic because the development of HIV drug resistance leads to the requirement for antiretroviral drugs that may be less effective, less well-tolerated, and more expensive than those used in first-line regimens. • HIV drug resistance studies are designed to determine which HIV mutations are selected by antiretroviral drugs and, in turn, how these mutations affect antiretroviral drug susceptibility and response to future antiretroviral treatment regimens. • Such studies collectively form a vital knowledge base essential for monitoring global HIV drug resistance trends, interpreting HIV genotypic tests, and updating HIV treatment guidelines. • Although HIV drug resistance data are collected in many studies, such data are often not publicly shared, prompting the need to recommend best practices to encourage and standardize HIV drug resistance data sharing. • In contrast to other viruses, sharing HIV sequences from phylogenetic studies of transmission dynamics requires additional precautions as HIV transmission is criminalized in many countries and regions. • Our recommendations are designed to ensure that the data that contribute to HIV drug resistance knowledge will be available without undue hardship to those publishing HIV drug resistance studies and without risk to people living with HIV.
Indexed as
Identifiers
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.