ArticleBiometrics2019
Informative group testing for multiplex assays.
Article in Biometrics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Multiple Summary Knowledge-Based Disease Prevalence Estimation for Group Testing Data.Statistics in medicine · 2026Article
- Article
- binGroup2: Statistical Tools for Infection Identification via Group Testing.The R journal · 2023Article
- Bayesian group testing with dilution effects.Biostatistics (Oxford, England) · 2023Article
- Simulation of group testing scenarios can boost COVID-19 screening power.Scientific reports · 2022Article
- Pooling saliva samples as an excellent option to increase the surveillance for SARS-CoV-2 when re-opening community settings.PloS one · 2022Article
- Comparison between Aptima® assays (Hologic) and the CoBAS® 6800 system (Roche) for the diagnosis of sexually transmitted infections caused by Chlamydia trachomatis, Neisseria gonorrhoeae, and Mycoplasma genitalium.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2021Article
- Pooled testing with replication as a mass testing strategy for the COVID-19 pandemics.Scientific reports · 2021Article
- Nonparametric estimation of distributions and diagnostic accuracy based on group-tested results with differential misclassification.Biometrics · 2020Article
- The objective function controversy for group testing: Much ado about nothing?Statistics in medicine · 2019Article
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.
Funding
Abstract
Infectious disease testing frequently takes advantage of two tools-group testing and multiplex assays-to make testing timely and cost effective. Until the work of Tebbs et al. (2013) and Hou et al. (2017), there was no research available to understand how best to apply these tools simultaneously. This recent work focused on applications where each individual is considered to be identical in terms of the probability of disease. However, risk-factor information, such as past behavior and presence of symptoms, is very often available on each individual to allow one to estimate individual-specific probabilities. The purpose of our paper is to propose the first group testing algorithms for multiplex assays that take advantage of individual risk-factor information as expressed by these probabilities. We show that our methods significantly reduce the number of tests required while preserving accuracy. Throughout this paper, we focus on applying our methods with the Aptima Combo 2 Assay that is used worldwide for chlamydia and gonorrhea screening.
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.