Evidence map›Paper›PMID 27418848›Full record

ReviewClinicoEconomics and outcomes research : CEOR2016

Screening strategies for active tuberculosis: focus on cost-effectiveness.

Claudia Caroline Dobler

Open access · goldAbstract readReview
In one paragraph

Review in ClinicoEconomics and outcomes research : CEOR, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
2.9field-weighted citation impact, top 10% 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

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 40 citations in OpenAlex.

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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

1 author at 1 institution in 1 country.

Claudia Caroline DoblerClinical Management Group, Woolcock Institute of Medical Research, University of Sydney, Sydney, NSW, Australia.
University of Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, there has been renewed interest in screening for active tuberculosis (TB), also called active case-finding (ACF), as a possible means to achieve control of the global TB epidemic. ACF aims to increase the detection of TB, in order to diagnose and treat patients with TB earlier than if they had been diagnosed and treated only at the time when they sought health care because of symptoms. This will reduce or avoid secondary transmission of TB to other people, with the long-term goal of reducing the incidence of TB. Here, the history of screening for active TB, current screening practices, and the role of TB-diagnostic tools are summarized and the literature on cost-effectiveness of screening for active TB reviewed. Cost-effectiveness analyses indicate that community-wide ACF can be cost-effective in settings with a high incidence of TB. ACF among close TB contacts is cost-effective in settings with a low as well as a high incidence of TB. The evidence for cost-effectiveness of screening among HIV-infected persons is not as strong as for TB contacts, but the reviewed studies suggest that the intervention can be cost-effective depending on the background prevalence of TB and test volume. None of the cost-effectiveness analyses were informed by data from randomized controlled trials. As the results of randomized controlled trials evaluating different ACF strategies will become available in future, we will hopefully gain a better understanding of the role that ACF can play in achieving global TB control.

Indexed as

active case-findingdisease eliminationepidemicreview

Identifiers

PMID27418848
PMCPMC4934456
OpenAlexW2462995762

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.