ArticleStatistical communications in infectious diseases2019
Designing & Conducting Trials To Reliably Evaluate HIV Prevention Interventions.
Article in Statistical communications in infectious diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed, 1 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
While much has been achieved, much remains to be accomplished in the science of preventing the spread of HIV infection. Clinical trials that are properly designed, conducted and analyzed are of integral importance in the pursuit of reliable insights about HIV prevention. As we build on previous scientific breakthroughs, there will be an increasing need for clinical trials to be designed to efficiently achieve insights without compromising their reliability and generalizability. Key design features should continue to include: 1) the use of randomization and evidence-based controls, 2) specifying the use of intention-to-treat analyses to preserve the integrity of randomization and to increase interpretability of results, 3) obtaining direct assessments of effects on clinical endpoints such as the risk of HIV infection, 4) using either superiority designs or non-inferiority designs with rigorous non-inferiority margins, and 5) enhancing generalizability through the choice of a relative risk rather than risk difference metric. When interventions have complementary and potentially synergistic effects, factorial designs should be considered to increase efficiency as well as to obtain clinically important insights about interaction and the contribution of component interventions to the efficacy and safety of combination regimens. Key trial conduct issues include timely enrollment of participants at high HIV risk recruited from populations with high viral burden, obtaining 'best real-world achievable' levels of adherence to the interventions being assessed and ensuring high levels of retention. High quality of trial conduct occurs through active rather than passive monitoring, using pre-specified targeted levels of performance with defined methods to achieve those targets. During trial conduct, active monitoring of the performance standards not only holds the trial leaders accountable but also can assist in the development and implementation of creative alternative approaches to increase the quality of trial conduct. Designing, conducting and analyzing HIV prevention trials with the quality needed to obtain reliable insights is an ethical as well as scientific imperative.
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.