Evidence map›Paper›PMID 20619072›Full record

ArticleEpidemiology and infection2011

Uncertain outcomes: adjusting for misclassification in antimalarial efficacy studies.

K A Porter, C L Burch, C Poole, J J Juliano, S R Cole, S R Meshnick

Open access · bronzeAbstract read
In one paragraph

Article in Epidemiology and infection, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 31% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 2 countries.

K A PorterDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, NC 27599, USA. kporter@email.unc.edu
C L Burch
C Poole
J J Juliano
S R Cole
S R Meshnick
University of North Carolina at Chapel Hill · US

Funding

Training in Infectious Disease Epidemiology (TIDE)T32AI070114 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Brian W Pence · 2007 to 2026
$4.0M
NIAID NIH HHS 1-T32-AI070114-01A1NIAID NIH HHS T32 AI070114
6 · The paper itself

Abstract

Evaluation of antimalarial efficacy is difficult because recurrent parasitaemia can be due to recrudescence or re-infection. PCR is used to differentiate between recrudescences and re-infections by comparing parasite allelic variants before and after treatment. However, PCR-corrected results are susceptible to misclassification: false positives, due to re-infection by the same variant present in the patient before treatment; and false negatives, due to variants that are present but too infrequent to be detected in the pre-treatment PCR, but are then detectable post-treatment. This paper aimed to explore factors affecting the probability of false positives and proposes a Monte Carlo uncertainty analysis to account for both types of misclassification. Higher levels of transmission intensity, increased multiplicity of infection, and limited allelic variation resulted in more false recrudescences. The uncertainty analysis exploits characteristics of study data to minimize bias in the estimate of efficacy and can be applied to areas of different transmission intensity.

Indexed as

AntimalarialsBiomedical ResearchFalse Positive ReactionsHumansMalariaParasitologyPolymerase Chain ReactionRecurrenceTreatment OutcomeAntimalarials

Identifiers

PMID20619072
PMCPMC4829077
OpenAlexW2041365406

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.