Evidence map›Paper›PMID 35777870›Full record

SynthesisBMJ open2022

Xpert Ultra stool testing to diagnose tuberculosis in children in Ethiopia and Indonesia: a model-based cost-effectiveness analysis.

Nyashadzaishe Mafirakureva, Eveline Klinkenberg, Ineke Spruijt, Jens Levy, Debebe Shaweno, Petra de Haas, Nastiti Kaswandani, Ahmed Bedru, Rina Triasih, Melaku Gebremichael and 2 more

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in BMJ open, 2022. 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
3.2field-weighted citation impact, top 6% 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, 33 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

12 authors at 5 institutions in 3 countries.

Nyashadzaishe MafirakurevaScHARR, The University of Sheffield, Sheffield, UK n.mafirakureva@sheffield.ac.uk.ORCID 0000-0001-9775-6581
Eveline KlinkenbergIndependent consultant, Connect TB, Den Haag, The Netherlands.
Ineke SpruijtTechnical Division, KNCV Tuberculosis Foundation, Den Haag, The Netherlands.
Jens LevyTechnical Division, KNCV Tuberculosis Foundation, Den Haag, The Netherlands.
Debebe ShawenoScHARR, The University of Sheffield, Sheffield, UK.
Petra de HaasTechnical Division, KNCV Tuberculosis Foundation, Den Haag, The Netherlands.
Nastiti KaswandaniPediatric Department, RSCM Hospital, University of Indonesia Faculty of Medicine, Jakarta, Indonesia.
Ahmed BedruTechnical Division, KNCV Tuberculosis Foundation, Addis Ababa, Ethiopia.
Rina TriasihDepartment of Paediatrics, Universitas Gadjah Mada Fakultas Kedokteran, Yogyakarta, Indonesia.
Melaku GebremichaelTechnical Division, KNCV Tuberculosis Foundation, Addis Ababa, Ethiopia.
Peter J DoddScHARR, The University of Sheffield, Sheffield, UK.
Edine W TiemersmaTechnical Division, KNCV Tuberculosis Foundation, Den Haag, The Netherlands.ORCID 0000-0002-2071-3038
TuBerculosis Vaccine Initiative · NLUniversity of Sheffield · GBAmsterdam Institute for Global Health and Development · NLUniversitas Gadjah Mada · IDUniversity of Indonesia · ID

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe WHO currently recommends stool testing using GeneXpert MTB/Rif (Xpert) for the diagnosis of paediatric tuberculosis (TB). The simple one-step (SOS) stool method enables processing for Xpert testing at the primary healthcare (PHC) level. We modelled the impact and cost-effectiveness of implementing the SOS stool method at PHC for the diagnosis of paediatric TB in Ethiopia and Indonesia, compared with the standard of care.

settingAll children (age <15 years) presenting with presumptive TB at primary healthcare or hospital level in Ethiopia and Indonesia. PRIMARY OUTCOME: Cost-effectiveness estimated as incremental costs compared with incremental disability-adjusted life-years (DALYs) saved.

methodsDecision tree modelling was used to represent pathways of patient care and referral. We based model parameters on ongoing studies and surveillance, systematic literature review, and expert opinion. We estimated costs using data available publicly and obtained through in-country expert consultations. Health outcomes were based on modelled mortality and discounted life-years lost.

resultsThe intervention increased the sensitivity of TB diagnosis by 19-25% in both countries leading to a 14-20% relative reduction in mortality. Under the intervention, fewer children seeking care at PHC were referred (or self-referred) to higher levels of care; the number of children initiating anti-TB treatment (ATT) increased by 18-25%; and more children (85%) initiated ATT at PHC level. Costs increased under the intervention compared with a base case using smear microscopy in the standard of care resulting in incremental cost-effectiveness ratios of US$132 and US$94 per DALY averted in Ethiopia and Indonesia, respectively. At a cost-effectiveness threshold of 0.5×gross domestic product per capita, the projected probability of the intervention being cost-effective in Ethiopia and Indonesia was 87% and 96%, respectively. The intervention remained cost-effective under sensitivity analyses.

conclusionsThe addition of the SOS stool method to national algorithms for diagnosing TB in children is likely to be cost-effective in both Ethiopia and Indonesia.

Indexed as

SputumTuberculosisAdolescentChildCost-Benefit AnalysisEthiopiaHumansIndonesiaepidemiologyhealth economicsinfectious diseasespaediatric infectious disease & immunisationtuberculosis

Identifiers

PMID35777870
PMCPMC9252203
OpenAlexW4283775360

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.