Evidence map›Paper›PMID 21996701›Full record

ReviewThe Journal of infectious diseases2011

Evaluation of tuberculosis diagnostics: establishing an evidence base around the public health impact.

Richard J Lessells, Graham S Cooke, Marie-Louise Newell, Peter Godfrey-Faussett

Abstract readReview
In one paragraph

Review in The Journal of infectious diseases, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Review
  5. Review
  6. Review
  7. Article
  8. Review
  9. Review
  10. Challenges in evaluating the cost-effectiveness of new diagnostic tests for HIV-associated tuberculosis.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2013
    Article
  11. Tuberculosis diagnostics: why we need more qualitative research.Journal of epidemiology and global health · 2013
    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

4 authors.

Richard J LessellsDepartment of Clinical Research, London School of Hygiene and Tropical Medicine, London, UK. richard.lessells@lshtm.ac.uk
Graham S Cooke
Marie-Louise Newell
Peter Godfrey-Faussett

Funding

Wellcome Trust 090999
6 · The paper itself

Abstract

The limitations of existing tuberculosis diagnostic tools are significantly hampering tuberculosis control efforts, most noticeably in areas with high prevalence of human immunodeficiency virus (HIV) infection and antituberculosis drug resistance. However, renewed global interest in tuberculosis research has begun to bear fruit, with several new diagnostic technologies progressing through the development pipeline. There are significant challenges in building a sound evidence base to inform public health policies because most diagnostic research focuses on the accuracy of individual tests, with often significant limitations in the design, conduct, and reporting of diagnostic accuracy studies. Diagnostic accuracy studies may not be appropriate to guide public health policies, and clinical trials may increasingly be required to determine the incremental value and cost-effectiveness of new tools. The urgent need for new diagnostics should not distract from pursuing rigorous scientific evaluation focused on public health impact.

Indexed as

Public HealthBacteriological TechniquesClinical Trials as TopicCost-Benefit AnalysisHealth PolicyHumansMycobacterium tuberculosisTuberculosis

Identifiers

PMID21996701
PMCPMC3192544

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.