Evidence map›Paper›PMID 26930400›Full record

ArticlePloS one2016

Comparing Tuberculosis Diagnostic Yield in Smear/Culture and Xpert® MTB/RIF-Based Algorithms Using a Non-Randomised Stepped-Wedge Design.

Pren Naidoo, Rory Dunbar, Carl Lombard, Elizabeth du Toit, Judy Caldwell, Anne Detjen, S Bertel Squire, Donald A Enarson, Nulda Beyers

Registry-linked trialAbstract readComparative Study
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04433195 (Xpert MTB/RIF Test as the Initial Diagnostic Test in the Diagnosis of Pulmonary Tuberculosis), which is not on this map. Cited by 12 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 4 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.

NCT04433195 naunknown statusnot on this mapstarted 2020, after this paper: background citation

Xpert MTB/RIF Test as the Initial Diagnostic Test in the Diagnosis of Pulmonary Tuberculosis: a Pragmatic Trial

TypeinterventionalSponsorTaipei Medical University WanFang HospitalRan2020 to 2022Enrolled6,900ConditionsPulmonary Tuberculosis Confirmation by CultureArmsXpert MTB/RIF test
3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Review
  6. Article
  7. Cost-effectiveness of Xpert®MTB/RIF in the diagnosis of tuberculosis: pragmatic study.Revista da Sociedade Brasileira de Medicina Tropical · 2021
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. 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

9 authors.

Pren NaidooDesmond Tutu TB Centre, Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
Rory DunbarDesmond Tutu TB Centre, Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
Carl LombardBiostatistics Unit, South African Medical Research Council, Cape Town, South Africa.
Elizabeth du ToitDesmond Tutu TB Centre, Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
Judy CaldwellCity of Cape Town Health Directorate, Cape Town, South Africa.
Anne DetjenThe International Union against TB and Lung Disease, Paris, France.
S Bertel SquireLiverpool School of Tropical Medicine, Liverpool, United Kingdom.
Donald A EnarsonThe International Union against TB and Lung Disease, Paris, France.
Nulda BeyersDesmond Tutu TB Centre, Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

settingPrimary health services in Cape Town, South Africa. STUDY

aimTo compare tuberculosis (TB) diagnostic yield in an existing smear/culture-based and a newly introduced Xpert® MTB/RIF-based algorithm.

methodsTB diagnostic yield (the proportion of presumptive TB cases with a laboratory diagnosis of TB) was assessed using a non-randomised stepped-wedge design as sites transitioned to the Xpert® based algorithm. We identified the full sequence of sputum tests recorded in the electronic laboratory database for presumptive TB cases from 60 primary health sites during seven one-month time-points, six months apart. Differences in TB yield and temporal trends were estimated using a binomial regression model.

resultsTB yield was 20.9% (95% CI 19.9% to 22.0%) in the smear/culture-based algorithm compared to 17.9% (95%CI 16.4% to 19.5%) in the Xpert® based algorithm. There was a decline in TB yield over time with a mean risk difference of -0.9% (95% CI -1.2% to -0.6%) (p<0.001) per time-point. When estimates were adjusted for the temporal trend, TB yield was 19.1% (95% CI 17.6% to 20.5%) in the smear/culture-based algorithm compared to 19.3% (95% CI 17.7% to 20.9%) in the Xpert® based algorithm with a risk difference of 0.3% (95% CI -1.8% to 2.3%) (p = 0.796). Culture tests were undertaken for 35.5% of smear-negative compared to 17.9% of Xpert® negative low MDR-TB risk cases and for 82.6% of smear-negative compared to 40.5% of Xpert® negative high MDR-TB risk cases in respective algorithms.

conclusionIntroduction of an Xpert® based algorithm did not produce the expected increase in TB diagnostic yield. Studies are required to assess whether improving adherence to the Xpert® negative algorithm for HIV-infected individuals will increase yield. In light of the high cost of Xpert®, a review of its role as a screening test for all presumptive TB cases may be warranted.

Indexed as

AdolescentAdultAgedAged, 80 and overAlgorithmsChildChild, PreschoolClinical Laboratory TechniquesFemaleHumansInfantMaleMiddle AgedSensitivity and SpecificitySouth AfricaSputum

Identifiers

PMID26930400
PMCPMC4773132

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.