ArticleStatistics in medicine2010
Adherence to antiretroviral therapy, virological response, and time to resistance in the Dakar cohort.
Article in Statistics in medicine, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed, 2 citations in OpenAlex.
- HIV-1 genetic diversity and drug resistance among Senegalese patients in the public health system.Journal of clinical microbiology · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
Abstract
In 1998, with the launch of the Senegalese Initiative for Antiretroviral Access (ISAARV), Senegal became one of the first African countries to propose an antiretroviral access program. Our objective in this paper is to study the time to any first drug resistance, as well as predictors of the time to resistance. We propose a joint model to study the effect of adherence to the HAART therapy, and virological response on the time to resistance mutations. A logistic mixed model is used to model the time-dependent adherence process; and a Markov model is used to study the virological response. Given the presence of missing data in the adherence process and in the virological response, the latent adherence and virological states are then included in the linear predictor of the time to resistance model. The proposed time to resistance model takes into account interval-censored data as well as null hazard periods, during which the viral replication is very low. A Bayesian approach is used for accommodating with missing data and for prediction. We also propose model checking tools to study model adequacy.
Indexed as
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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.