Computer-aided X-ray screening for tuberculosis and HIV testing among adults with cough in Malawi (the PROSPECT study): A randomised trial and cost-effectiveness analysis
Background Suboptimal tuberculosis (TB) diagnostics and HIV contribute to the high global burden of TB. We investigated costs and yield from systematic HIV-TB screening, including computer-aided digital chest X-ray (DCXR-CAD). Methods and findings In this open, three-arm randomised trial, adults (&g...
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creator | MacPherson, Peter G. Webb, Emily H. Kamchedzera, Wala T. Joekes, Elizabeth M. Mjoli, Gugu Lalloo, David Divala, Titus Choko, Augustine Burke, Rachael L. Maheswaran, Hendramoorthy Pai, Madhukar Squire, S. Bertel Nliwasa, Marriott Corbett, Elizabeth |
description | Background
Suboptimal tuberculosis (TB) diagnostics and HIV contribute to the high global burden of TB. We investigated costs and yield from systematic HIV-TB screening, including computer-aided digital chest X-ray (DCXR-CAD).
Methods and findings
In this open, three-arm randomised trial, adults (>= 18 years) with cough attending acute primary services in Malawi were randomised (1:1:1) to standard of care (SOC); oral HIV testing (HIV screening) and linkage to care; or HIV testing and linkage to care plus DCXR-CAD with sputum Xpert for high CAD4TBv5 scores (HIV-TB screening). Participants and study staff were not blinded to intervention allocation, but investigator blinding was maintained until final analysis. The primary outcome was time to TB treatment. Secondary outcomes included proportion with same-day TB treatment; prevalence of undiagnosed/untreated bacteriologically confirmed TB on day 56; and undiagnosed/untreated HIV. Analysis was done on an intention-to-treat basis. Cost-effectiveness analysis used a health-provider perspective. Between 15 November 2018 and 27 November 2019, 8,236 were screened for eligibility, with 473, 492, and 497 randomly allocated to SOC, HIV, and HIV-TB screening arms; 53 (11%), 52 (9%), and 47 (9%) were lost to follow-up, respectively. At 56 days, TB treatment had been started in 5 (1.1%) SOC, 8 (1.6%) HIV screening, and 15 (3.0%) HIV-TB screening participants. Median (IQR) time to TB treatment was 11 (6.5 to 38), 6 (1 to 22), and 1 (0 to 3) days (hazard ratio for HIV-TB versus SOC: 2.86, 1.04 to 7.87), with same-day treatment of 0/5 (0%) SOC, 1/8 (12.5%) HIV, and 6/15 (40.0%) HIV-TB screening arm TB patients (p = 0.03). At day 56, 2 SOC (0.5%), 4 HIV (1.0%), and 2 HIV-TB (0.5%) participants had undiagnosed microbiologically confirmed TB. HIV screening reduced the proportion with undiagnosed or untreated HIV from 10 (2.7%) in the SOC arm to 2 (0.5%) in the HIV screening arm (risk ratio [RR]: 0.18, 0.04 to 0.83), and 1 (0.2%) in the HIV-TB screening arm (RR: 0.09, 0.01 to 0.71). Incremental costs were US$3.58 and US$19.92 per participant screened for HIV and HIV-TB; the probability of cost-effectiveness at a US$1,200/quality-adjusted life year (QALY) threshold was 83.9% and 0%. Main limitations were the lower than anticipated prevalence of TB and short participant follow-up period; cost and quality of life benefits of this screening approach may accrue over a longer time horizon.
Conclusions
DCXR-CAD with universal HIV scre |
doi_str_mv | 10.1371/journal.pmed.1003752 |
format | Article |
fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_gale_infotracmisc_A677985579</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A677985579</galeid><doaj_id>oai_doaj_org_article_078f45c122f64d7b8d3e462485082161</doaj_id><sourcerecordid>A677985579</sourcerecordid><originalsourceid>FETCH-LOGICAL-c631t-57209ad31ae7b94dffb367ce94640cfad1f5c20e92fca0096ddc4128197e5bcd3</originalsourceid><addsrcrecordid>eNqNU9tqFDEYHkSxtfoGogFvKjJrMqdMvBDKUu1CpUWreBcyyZ_dlNlkTTIt-0o-pZnubrGyFzLDJGS-w3_In2UvCZ6QkpL3127wVvST1RLUhGBc0rp4lB2SumI5aWjzeLcvKD3InoVwjXHBMMNPs4Oyqhhrmvow-z11y9UQwefCKFDoZ-7FGgXpAayxc6SdR3HowMuhd8EEJKxCZ7MfKEKII0As3fhVQx8DujVxgaQb5gtkLPoienFr0HFcALr8evHt8nR6hUIc1PrtB3SCfJJySxOSa_RG9HfS0oWYg9Ygo7kBC2F0FP06WT_PnmjRB3ixXY-y759Or6Zn-fnF59n05DyXTUliXtMCM6FKIoB2rFJad2VDJbCqqbDUQhFdywIDK7QUGLNGKVmRoiWMQt1JVR5lrze6q5Qx35Y58KJu09syVifEbINQTlzzlTdL4dfcCcPvDpyfc-GjkT1wTFtd1ZIUhW4qRbtWlVA1RdXWuC1IQ5LWx63b0KVOSrDRi_6B6MM_1iz43N3wtqpTD1kSON4KePdrSF3hqaYS-l5YcMMYNyWsaNt6jPvNP9D92W1Rc5ESMFa75CtHUX7SUMqSEh1t8z2oeWpZCtJZ0CYdP8BP9uDTo2Bp5F5CtSFI70LwoO9rQjAfJ2AXPB8ngG8nINFe_V3Pe9LuyidAuwHcQud0kAashHsYxjjdH9KWbdphMjVRROPs1A02Juq7_6eWfwAvjiVI</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2582588995</pqid></control><display><type>article</type><title>Computer-aided X-ray screening for tuberculosis and HIV testing among adults with cough in Malawi (the PROSPECT study): A randomised trial and cost-effectiveness analysis</title><source>Public Library of Science (PLoS) Journals Open Access</source><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>Web of Science - Science Citation Index Expanded - 2021<img src="https://exlibris-pub.s3.amazonaws.com/fromwos-v2.jpg" /></source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central</source><creator>MacPherson, Peter G. ; Webb, Emily H. ; Kamchedzera, Wala T. ; Joekes, Elizabeth M. ; Mjoli, Gugu ; Lalloo, David ; Divala, Titus ; Choko, Augustine ; Burke, Rachael L. ; Maheswaran, Hendramoorthy ; Pai, Madhukar ; Squire, S. Bertel ; Nliwasa, Marriott ; Corbett, Elizabeth</creator><contributor>Barnabas, Ruanne V.</contributor><creatorcontrib>MacPherson, Peter G. ; Webb, Emily H. ; Kamchedzera, Wala T. ; Joekes, Elizabeth M. ; Mjoli, Gugu ; Lalloo, David ; Divala, Titus ; Choko, Augustine ; Burke, Rachael L. ; Maheswaran, Hendramoorthy ; Pai, Madhukar ; Squire, S. Bertel ; Nliwasa, Marriott ; Corbett, Elizabeth ; Barnabas, Ruanne V.</creatorcontrib><description>Background
Suboptimal tuberculosis (TB) diagnostics and HIV contribute to the high global burden of TB. We investigated costs and yield from systematic HIV-TB screening, including computer-aided digital chest X-ray (DCXR-CAD).
Methods and findings
In this open, three-arm randomised trial, adults (>= 18 years) with cough attending acute primary services in Malawi were randomised (1:1:1) to standard of care (SOC); oral HIV testing (HIV screening) and linkage to care; or HIV testing and linkage to care plus DCXR-CAD with sputum Xpert for high CAD4TBv5 scores (HIV-TB screening). Participants and study staff were not blinded to intervention allocation, but investigator blinding was maintained until final analysis. The primary outcome was time to TB treatment. Secondary outcomes included proportion with same-day TB treatment; prevalence of undiagnosed/untreated bacteriologically confirmed TB on day 56; and undiagnosed/untreated HIV. Analysis was done on an intention-to-treat basis. Cost-effectiveness analysis used a health-provider perspective. Between 15 November 2018 and 27 November 2019, 8,236 were screened for eligibility, with 473, 492, and 497 randomly allocated to SOC, HIV, and HIV-TB screening arms; 53 (11%), 52 (9%), and 47 (9%) were lost to follow-up, respectively. At 56 days, TB treatment had been started in 5 (1.1%) SOC, 8 (1.6%) HIV screening, and 15 (3.0%) HIV-TB screening participants. Median (IQR) time to TB treatment was 11 (6.5 to 38), 6 (1 to 22), and 1 (0 to 3) days (hazard ratio for HIV-TB versus SOC: 2.86, 1.04 to 7.87), with same-day treatment of 0/5 (0%) SOC, 1/8 (12.5%) HIV, and 6/15 (40.0%) HIV-TB screening arm TB patients (p = 0.03). At day 56, 2 SOC (0.5%), 4 HIV (1.0%), and 2 HIV-TB (0.5%) participants had undiagnosed microbiologically confirmed TB. HIV screening reduced the proportion with undiagnosed or untreated HIV from 10 (2.7%) in the SOC arm to 2 (0.5%) in the HIV screening arm (risk ratio [RR]: 0.18, 0.04 to 0.83), and 1 (0.2%) in the HIV-TB screening arm (RR: 0.09, 0.01 to 0.71). Incremental costs were US$3.58 and US$19.92 per participant screened for HIV and HIV-TB; the probability of cost-effectiveness at a US$1,200/quality-adjusted life year (QALY) threshold was 83.9% and 0%. Main limitations were the lower than anticipated prevalence of TB and short participant follow-up period; cost and quality of life benefits of this screening approach may accrue over a longer time horizon.
Conclusions
DCXR-CAD with universal HIV screening significantly increased the timeliness and completeness of HIV and TB diagnosis. If implemented at scale, this has potential to rapidly and efficiently improve TB and HIV diagnosis and treatment.
Author summary
Why was this study done?
Tuberculosis (TB), one of the leading infectious killers worldwide, remains challenging to diagnose in low-resource settings, and patients frequently face multiple health centre visits at high cost before TB is diagnosed and treatment started. HIV is a major risk factor for TB.
Robust digital X-ray equipment can now be deployed at a primary care level in sub-Saharan Africa, and automated computer software packages that can interpret chest X-rays providing a probabilistic score for pulmonary TB have accuracy similar to, or greater than, expert human readers.
We therefore set out to investigate whether offering adults with cough attending primary care in Blantyre, Malawi universal HIV testing and linkage to antiretroviral therapy (ART)-either alone or combined with computer-aided digital chest X-ray (DCXR-CAD) and subsequent sputum Xpert confirmation-could improve the timeliness and completeness of HIV and TB diagnosis and treatment compared to current standard approaches (health worker-directed TB and HIV screening).
What did the researchers do and find?
A total of 1,462 adults attending a primary clinic in Blantyre, Malawi with cough were randomly allocated to receive either standard of care (SOC) health worker-directed HIV-TB screening; oral HIV testing and linkage to treatment (HIV screening); or oral HIV testing and linkage to treatment with additional digital chest X-ray screening for TB interpreted by computer-aided diagnosis software (CAD4TBv5), with sputum Xpert testing for participants with a CAD4TBv5 score above 45 (HIV/TB screening). Participants were followed for 56 days to investigate initiation of TB treatment, missed TB and HIV diagnosis, and cost-effectiveness.
Median time to TB treatment initiation was shorter (1 day) in the HIV-TB screening arm compared to the SOC arm (11 days) and HIV screening arm (6 days). HIV screening reduced undiagnosed/untreated HIV from 10 (2.7%) in the SOC arm to 2 (0.5%) in the HIV screening arm and 1 (0.2%) in the HIV-TB screening arm.
Over the trial follow-up period (56 days), oral HIV testing and linkage to care were likely to be cost-effective, but digital chest X-ray with computer-aided interpretation was not.
What do these findings mean?
Digital chest X-ray screening with computer-aided interpretation for TB with universal HIV screening increased the timeliness and completeness of HIV and TB diagnosis.
If implemented at scale, these interventions have the potential to rapidly and efficiently improve TB and HIV diagnosis and treatment.</description><identifier>ISSN: 1549-1277</identifier><identifier>ISSN: 1549-1676</identifier><identifier>EISSN: 1549-1676</identifier><identifier>DOI: 10.1371/journal.pmed.1003752</identifier><identifier>PMID: 34499665</identifier><language>eng</language><publisher>SAN FRANCISCO: Public Library Science</publisher><subject>Adult ; Adults ; Analysis ; Anti-HIV Agents - therapeutic use ; Antitubercular Agents - therapeutic use ; Biology and Life Sciences ; Coinfection ; Computer-aided medical diagnosis ; Cost analysis ; Cost-Benefit Analysis ; Cough ; Cough - diagnosis ; Cough - microbiology ; Data collection ; Diagnosis ; Diagnosis, Computer-Assisted - economics ; Economic aspects ; Female ; General & Internal Medicine ; Health Care Costs ; Health facilities ; Health Services Accessibility ; HIV ; HIV infection ; HIV Infections - diagnosis ; HIV Infections - drug therapy ; HIV Infections - epidemiology ; HIV Testing - economics ; Human immunodeficiency virus ; Humans ; Investigations ; Life Sciences & Biomedicine ; Malawi - epidemiology ; Male ; Medical care, Cost of ; Medical diagnosis ; Medical tests ; Medicine and Health Sciences ; Medicine, General & Internal ; Methods ; Microscopy ; Middle Aged ; Mortality ; Predictive Value of Tests ; Prevalence ; Primary care ; Primary Health Care ; Quality of life ; Questionnaires ; Radiography, Thoracic - economics ; Science & Technology ; Social Sciences ; Software ; Sputum ; Statistical analysis ; Tuberculosis ; Tuberculosis - diagnostic imaging ; Tuberculosis - drug therapy ; Tuberculosis - epidemiology ; Tuberculosis - microbiology ; Workers ; X rays ; Young Adult</subject><ispartof>PLoS medicine, 2021-09, Vol.18 (9), p.e1003752-e1003752, Article 1003752</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>2021 MacPherson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 MacPherson et al 2021 MacPherson et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>true</woscitedreferencessubscribed><woscitedreferencescount>18</woscitedreferencescount><woscitedreferencesoriginalsourcerecordid>wos000720183800001</woscitedreferencesoriginalsourcerecordid><citedby>FETCH-LOGICAL-c631t-57209ad31ae7b94dffb367ce94640cfad1f5c20e92fca0096ddc4128197e5bcd3</citedby><cites>FETCH-LOGICAL-c631t-57209ad31ae7b94dffb367ce94640cfad1f5c20e92fca0096ddc4128197e5bcd3</cites><orcidid>0000-0002-3100-5512 ; 0000-0002-7375-4845 ; 0000-0002-6709-4270 ; 0000-0001-6095-9430 ; 0000-0002-5577-210X ; 0000-0001-7173-9038 ; 0000-0002-2156-5030 ; 0000-0002-4019-7456 ; 0000-0002-6052-5859 ; 0000-0002-0329-9613 ; 0000-0003-3029-9579 ; 0000-0001-7680-2200 ; 0000-0002-3552-3181 ; 0000-0003-3667-4536</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459969/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459969/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,315,729,782,786,866,887,2106,2118,2932,23875,27933,27934,39267,53800,53802</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34499665$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Barnabas, Ruanne V.</contributor><creatorcontrib>MacPherson, Peter G.</creatorcontrib><creatorcontrib>Webb, Emily H.</creatorcontrib><creatorcontrib>Kamchedzera, Wala T.</creatorcontrib><creatorcontrib>Joekes, Elizabeth M.</creatorcontrib><creatorcontrib>Mjoli, Gugu</creatorcontrib><creatorcontrib>Lalloo, David</creatorcontrib><creatorcontrib>Divala, Titus</creatorcontrib><creatorcontrib>Choko, Augustine</creatorcontrib><creatorcontrib>Burke, Rachael L.</creatorcontrib><creatorcontrib>Maheswaran, Hendramoorthy</creatorcontrib><creatorcontrib>Pai, Madhukar</creatorcontrib><creatorcontrib>Squire, S. Bertel</creatorcontrib><creatorcontrib>Nliwasa, Marriott</creatorcontrib><creatorcontrib>Corbett, Elizabeth</creatorcontrib><title>Computer-aided X-ray screening for tuberculosis and HIV testing among adults with cough in Malawi (the PROSPECT study): A randomised trial and cost-effectiveness analysis</title><title>PLoS medicine</title><addtitle>PLOS MED</addtitle><addtitle>PLoS Med</addtitle><description>Background
Suboptimal tuberculosis (TB) diagnostics and HIV contribute to the high global burden of TB. We investigated costs and yield from systematic HIV-TB screening, including computer-aided digital chest X-ray (DCXR-CAD).
Methods and findings
In this open, three-arm randomised trial, adults (>= 18 years) with cough attending acute primary services in Malawi were randomised (1:1:1) to standard of care (SOC); oral HIV testing (HIV screening) and linkage to care; or HIV testing and linkage to care plus DCXR-CAD with sputum Xpert for high CAD4TBv5 scores (HIV-TB screening). Participants and study staff were not blinded to intervention allocation, but investigator blinding was maintained until final analysis. The primary outcome was time to TB treatment. Secondary outcomes included proportion with same-day TB treatment; prevalence of undiagnosed/untreated bacteriologically confirmed TB on day 56; and undiagnosed/untreated HIV. Analysis was done on an intention-to-treat basis. Cost-effectiveness analysis used a health-provider perspective. Between 15 November 2018 and 27 November 2019, 8,236 were screened for eligibility, with 473, 492, and 497 randomly allocated to SOC, HIV, and HIV-TB screening arms; 53 (11%), 52 (9%), and 47 (9%) were lost to follow-up, respectively. At 56 days, TB treatment had been started in 5 (1.1%) SOC, 8 (1.6%) HIV screening, and 15 (3.0%) HIV-TB screening participants. Median (IQR) time to TB treatment was 11 (6.5 to 38), 6 (1 to 22), and 1 (0 to 3) days (hazard ratio for HIV-TB versus SOC: 2.86, 1.04 to 7.87), with same-day treatment of 0/5 (0%) SOC, 1/8 (12.5%) HIV, and 6/15 (40.0%) HIV-TB screening arm TB patients (p = 0.03). At day 56, 2 SOC (0.5%), 4 HIV (1.0%), and 2 HIV-TB (0.5%) participants had undiagnosed microbiologically confirmed TB. HIV screening reduced the proportion with undiagnosed or untreated HIV from 10 (2.7%) in the SOC arm to 2 (0.5%) in the HIV screening arm (risk ratio [RR]: 0.18, 0.04 to 0.83), and 1 (0.2%) in the HIV-TB screening arm (RR: 0.09, 0.01 to 0.71). Incremental costs were US$3.58 and US$19.92 per participant screened for HIV and HIV-TB; the probability of cost-effectiveness at a US$1,200/quality-adjusted life year (QALY) threshold was 83.9% and 0%. Main limitations were the lower than anticipated prevalence of TB and short participant follow-up period; cost and quality of life benefits of this screening approach may accrue over a longer time horizon.
Conclusions
DCXR-CAD with universal HIV screening significantly increased the timeliness and completeness of HIV and TB diagnosis. If implemented at scale, this has potential to rapidly and efficiently improve TB and HIV diagnosis and treatment.
Author summary
Why was this study done?
Tuberculosis (TB), one of the leading infectious killers worldwide, remains challenging to diagnose in low-resource settings, and patients frequently face multiple health centre visits at high cost before TB is diagnosed and treatment started. HIV is a major risk factor for TB.
Robust digital X-ray equipment can now be deployed at a primary care level in sub-Saharan Africa, and automated computer software packages that can interpret chest X-rays providing a probabilistic score for pulmonary TB have accuracy similar to, or greater than, expert human readers.
We therefore set out to investigate whether offering adults with cough attending primary care in Blantyre, Malawi universal HIV testing and linkage to antiretroviral therapy (ART)-either alone or combined with computer-aided digital chest X-ray (DCXR-CAD) and subsequent sputum Xpert confirmation-could improve the timeliness and completeness of HIV and TB diagnosis and treatment compared to current standard approaches (health worker-directed TB and HIV screening).
What did the researchers do and find?
A total of 1,462 adults attending a primary clinic in Blantyre, Malawi with cough were randomly allocated to receive either standard of care (SOC) health worker-directed HIV-TB screening; oral HIV testing and linkage to treatment (HIV screening); or oral HIV testing and linkage to treatment with additional digital chest X-ray screening for TB interpreted by computer-aided diagnosis software (CAD4TBv5), with sputum Xpert testing for participants with a CAD4TBv5 score above 45 (HIV/TB screening). Participants were followed for 56 days to investigate initiation of TB treatment, missed TB and HIV diagnosis, and cost-effectiveness.
Median time to TB treatment initiation was shorter (1 day) in the HIV-TB screening arm compared to the SOC arm (11 days) and HIV screening arm (6 days). HIV screening reduced undiagnosed/untreated HIV from 10 (2.7%) in the SOC arm to 2 (0.5%) in the HIV screening arm and 1 (0.2%) in the HIV-TB screening arm.
Over the trial follow-up period (56 days), oral HIV testing and linkage to care were likely to be cost-effective, but digital chest X-ray with computer-aided interpretation was not.
What do these findings mean?
Digital chest X-ray screening with computer-aided interpretation for TB with universal HIV screening increased the timeliness and completeness of HIV and TB diagnosis.
If implemented at scale, these interventions have the potential to rapidly and efficiently improve TB and HIV diagnosis and treatment.</description><subject>Adult</subject><subject>Adults</subject><subject>Analysis</subject><subject>Anti-HIV Agents - therapeutic use</subject><subject>Antitubercular Agents - therapeutic use</subject><subject>Biology and Life Sciences</subject><subject>Coinfection</subject><subject>Computer-aided medical diagnosis</subject><subject>Cost analysis</subject><subject>Cost-Benefit Analysis</subject><subject>Cough</subject><subject>Cough - diagnosis</subject><subject>Cough - microbiology</subject><subject>Data collection</subject><subject>Diagnosis</subject><subject>Diagnosis, Computer-Assisted - economics</subject><subject>Economic aspects</subject><subject>Female</subject><subject>General & Internal Medicine</subject><subject>Health Care Costs</subject><subject>Health facilities</subject><subject>Health Services Accessibility</subject><subject>HIV</subject><subject>HIV infection</subject><subject>HIV Infections - diagnosis</subject><subject>HIV Infections - drug therapy</subject><subject>HIV Infections - epidemiology</subject><subject>HIV Testing - economics</subject><subject>Human immunodeficiency virus</subject><subject>Humans</subject><subject>Investigations</subject><subject>Life Sciences & Biomedicine</subject><subject>Malawi - epidemiology</subject><subject>Male</subject><subject>Medical care, Cost of</subject><subject>Medical diagnosis</subject><subject>Medical tests</subject><subject>Medicine and Health Sciences</subject><subject>Medicine, General & Internal</subject><subject>Methods</subject><subject>Microscopy</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>Predictive Value of Tests</subject><subject>Prevalence</subject><subject>Primary care</subject><subject>Primary Health Care</subject><subject>Quality of life</subject><subject>Questionnaires</subject><subject>Radiography, Thoracic - economics</subject><subject>Science & Technology</subject><subject>Social Sciences</subject><subject>Software</subject><subject>Sputum</subject><subject>Statistical analysis</subject><subject>Tuberculosis</subject><subject>Tuberculosis - diagnostic imaging</subject><subject>Tuberculosis - drug therapy</subject><subject>Tuberculosis - epidemiology</subject><subject>Tuberculosis - microbiology</subject><subject>Workers</subject><subject>X rays</subject><subject>Young Adult</subject><issn>1549-1277</issn><issn>1549-1676</issn><issn>1549-1676</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>HGBXW</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>DOA</sourceid><recordid>eNqNU9tqFDEYHkSxtfoGogFvKjJrMqdMvBDKUu1CpUWreBcyyZ_dlNlkTTIt-0o-pZnubrGyFzLDJGS-w3_In2UvCZ6QkpL3127wVvST1RLUhGBc0rp4lB2SumI5aWjzeLcvKD3InoVwjXHBMMNPs4Oyqhhrmvow-z11y9UQwefCKFDoZ-7FGgXpAayxc6SdR3HowMuhd8EEJKxCZ7MfKEKII0As3fhVQx8DujVxgaQb5gtkLPoienFr0HFcALr8evHt8nR6hUIc1PrtB3SCfJJySxOSa_RG9HfS0oWYg9Ygo7kBC2F0FP06WT_PnmjRB3ixXY-y759Or6Zn-fnF59n05DyXTUliXtMCM6FKIoB2rFJad2VDJbCqqbDUQhFdywIDK7QUGLNGKVmRoiWMQt1JVR5lrze6q5Qx35Y58KJu09syVifEbINQTlzzlTdL4dfcCcPvDpyfc-GjkT1wTFtd1ZIUhW4qRbtWlVA1RdXWuC1IQ5LWx63b0KVOSrDRi_6B6MM_1iz43N3wtqpTD1kSON4KePdrSF3hqaYS-l5YcMMYNyWsaNt6jPvNP9D92W1Rc5ESMFa75CtHUX7SUMqSEh1t8z2oeWpZCtJZ0CYdP8BP9uDTo2Bp5F5CtSFI70LwoO9rQjAfJ2AXPB8ngG8nINFe_V3Pe9LuyidAuwHcQud0kAashHsYxjjdH9KWbdphMjVRROPs1A02Juq7_6eWfwAvjiVI</recordid><startdate>20210901</startdate><enddate>20210901</enddate><creator>MacPherson, Peter G.</creator><creator>Webb, Emily H.</creator><creator>Kamchedzera, Wala T.</creator><creator>Joekes, Elizabeth M.</creator><creator>Mjoli, Gugu</creator><creator>Lalloo, David</creator><creator>Divala, Titus</creator><creator>Choko, Augustine</creator><creator>Burke, Rachael L.</creator><creator>Maheswaran, Hendramoorthy</creator><creator>Pai, Madhukar</creator><creator>Squire, S. Bertel</creator><creator>Nliwasa, Marriott</creator><creator>Corbett, Elizabeth</creator><general>Public Library Science</general><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>BLEPL</scope><scope>DTL</scope><scope>HGBXW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><scope>CZK</scope><orcidid>https://orcid.org/0000-0002-3100-5512</orcidid><orcidid>https://orcid.org/0000-0002-7375-4845</orcidid><orcidid>https://orcid.org/0000-0002-6709-4270</orcidid><orcidid>https://orcid.org/0000-0001-6095-9430</orcidid><orcidid>https://orcid.org/0000-0002-5577-210X</orcidid><orcidid>https://orcid.org/0000-0001-7173-9038</orcidid><orcidid>https://orcid.org/0000-0002-2156-5030</orcidid><orcidid>https://orcid.org/0000-0002-4019-7456</orcidid><orcidid>https://orcid.org/0000-0002-6052-5859</orcidid><orcidid>https://orcid.org/0000-0002-0329-9613</orcidid><orcidid>https://orcid.org/0000-0003-3029-9579</orcidid><orcidid>https://orcid.org/0000-0001-7680-2200</orcidid><orcidid>https://orcid.org/0000-0002-3552-3181</orcidid><orcidid>https://orcid.org/0000-0003-3667-4536</orcidid></search><sort><creationdate>20210901</creationdate><title>Computer-aided X-ray screening for tuberculosis and HIV testing among adults with cough in Malawi (the PROSPECT study): A randomised trial and cost-effectiveness analysis</title><author>MacPherson, Peter G. ; Webb, Emily H. ; Kamchedzera, Wala T. ; Joekes, Elizabeth M. ; Mjoli, Gugu ; Lalloo, David ; Divala, Titus ; Choko, Augustine ; Burke, Rachael L. ; Maheswaran, Hendramoorthy ; Pai, Madhukar ; Squire, S. Bertel ; Nliwasa, Marriott ; Corbett, Elizabeth</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c631t-57209ad31ae7b94dffb367ce94640cfad1f5c20e92fca0096ddc4128197e5bcd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adult</topic><topic>Adults</topic><topic>Analysis</topic><topic>Anti-HIV Agents - therapeutic use</topic><topic>Antitubercular Agents - therapeutic use</topic><topic>Biology and Life Sciences</topic><topic>Coinfection</topic><topic>Computer-aided medical diagnosis</topic><topic>Cost analysis</topic><topic>Cost-Benefit Analysis</topic><topic>Cough</topic><topic>Cough - diagnosis</topic><topic>Cough - microbiology</topic><topic>Data collection</topic><topic>Diagnosis</topic><topic>Diagnosis, Computer-Assisted - economics</topic><topic>Economic aspects</topic><topic>Female</topic><topic>General & Internal Medicine</topic><topic>Health Care Costs</topic><topic>Health facilities</topic><topic>Health Services Accessibility</topic><topic>HIV</topic><topic>HIV infection</topic><topic>HIV Infections - diagnosis</topic><topic>HIV Infections - drug therapy</topic><topic>HIV Infections - epidemiology</topic><topic>HIV Testing - economics</topic><topic>Human immunodeficiency virus</topic><topic>Humans</topic><topic>Investigations</topic><topic>Life Sciences & Biomedicine</topic><topic>Malawi - epidemiology</topic><topic>Male</topic><topic>Medical care, Cost of</topic><topic>Medical diagnosis</topic><topic>Medical tests</topic><topic>Medicine and Health Sciences</topic><topic>Medicine, General & Internal</topic><topic>Methods</topic><topic>Microscopy</topic><topic>Middle Aged</topic><topic>Mortality</topic><topic>Predictive Value of Tests</topic><topic>Prevalence</topic><topic>Primary care</topic><topic>Primary Health Care</topic><topic>Quality of life</topic><topic>Questionnaires</topic><topic>Radiography, Thoracic - economics</topic><topic>Science & Technology</topic><topic>Social Sciences</topic><topic>Software</topic><topic>Sputum</topic><topic>Statistical analysis</topic><topic>Tuberculosis</topic><topic>Tuberculosis - diagnostic imaging</topic><topic>Tuberculosis - drug therapy</topic><topic>Tuberculosis - epidemiology</topic><topic>Tuberculosis - microbiology</topic><topic>Workers</topic><topic>X rays</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>MacPherson, Peter G.</creatorcontrib><creatorcontrib>Webb, Emily H.</creatorcontrib><creatorcontrib>Kamchedzera, Wala T.</creatorcontrib><creatorcontrib>Joekes, Elizabeth M.</creatorcontrib><creatorcontrib>Mjoli, Gugu</creatorcontrib><creatorcontrib>Lalloo, David</creatorcontrib><creatorcontrib>Divala, Titus</creatorcontrib><creatorcontrib>Choko, Augustine</creatorcontrib><creatorcontrib>Burke, Rachael L.</creatorcontrib><creatorcontrib>Maheswaran, Hendramoorthy</creatorcontrib><creatorcontrib>Pai, Madhukar</creatorcontrib><creatorcontrib>Squire, S. Bertel</creatorcontrib><creatorcontrib>Nliwasa, Marriott</creatorcontrib><creatorcontrib>Corbett, Elizabeth</creatorcontrib><collection>Web of Science Core Collection</collection><collection>Science Citation Index Expanded</collection><collection>Web of Science - Science Citation Index Expanded - 2021</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Neurosciences Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><collection>PLoS Medicine</collection><jtitle>PLoS medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>MacPherson, Peter G.</au><au>Webb, Emily H.</au><au>Kamchedzera, Wala T.</au><au>Joekes, Elizabeth M.</au><au>Mjoli, Gugu</au><au>Lalloo, David</au><au>Divala, Titus</au><au>Choko, Augustine</au><au>Burke, Rachael L.</au><au>Maheswaran, Hendramoorthy</au><au>Pai, Madhukar</au><au>Squire, S. Bertel</au><au>Nliwasa, Marriott</au><au>Corbett, Elizabeth</au><au>Barnabas, Ruanne V.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Computer-aided X-ray screening for tuberculosis and HIV testing among adults with cough in Malawi (the PROSPECT study): A randomised trial and cost-effectiveness analysis</atitle><jtitle>PLoS medicine</jtitle><stitle>PLOS MED</stitle><addtitle>PLoS Med</addtitle><date>2021-09-01</date><risdate>2021</risdate><volume>18</volume><issue>9</issue><spage>e1003752</spage><epage>e1003752</epage><pages>e1003752-e1003752</pages><artnum>1003752</artnum><issn>1549-1277</issn><issn>1549-1676</issn><eissn>1549-1676</eissn><abstract>Background
Suboptimal tuberculosis (TB) diagnostics and HIV contribute to the high global burden of TB. We investigated costs and yield from systematic HIV-TB screening, including computer-aided digital chest X-ray (DCXR-CAD).
Methods and findings
In this open, three-arm randomised trial, adults (>= 18 years) with cough attending acute primary services in Malawi were randomised (1:1:1) to standard of care (SOC); oral HIV testing (HIV screening) and linkage to care; or HIV testing and linkage to care plus DCXR-CAD with sputum Xpert for high CAD4TBv5 scores (HIV-TB screening). Participants and study staff were not blinded to intervention allocation, but investigator blinding was maintained until final analysis. The primary outcome was time to TB treatment. Secondary outcomes included proportion with same-day TB treatment; prevalence of undiagnosed/untreated bacteriologically confirmed TB on day 56; and undiagnosed/untreated HIV. Analysis was done on an intention-to-treat basis. Cost-effectiveness analysis used a health-provider perspective. Between 15 November 2018 and 27 November 2019, 8,236 were screened for eligibility, with 473, 492, and 497 randomly allocated to SOC, HIV, and HIV-TB screening arms; 53 (11%), 52 (9%), and 47 (9%) were lost to follow-up, respectively. At 56 days, TB treatment had been started in 5 (1.1%) SOC, 8 (1.6%) HIV screening, and 15 (3.0%) HIV-TB screening participants. Median (IQR) time to TB treatment was 11 (6.5 to 38), 6 (1 to 22), and 1 (0 to 3) days (hazard ratio for HIV-TB versus SOC: 2.86, 1.04 to 7.87), with same-day treatment of 0/5 (0%) SOC, 1/8 (12.5%) HIV, and 6/15 (40.0%) HIV-TB screening arm TB patients (p = 0.03). At day 56, 2 SOC (0.5%), 4 HIV (1.0%), and 2 HIV-TB (0.5%) participants had undiagnosed microbiologically confirmed TB. HIV screening reduced the proportion with undiagnosed or untreated HIV from 10 (2.7%) in the SOC arm to 2 (0.5%) in the HIV screening arm (risk ratio [RR]: 0.18, 0.04 to 0.83), and 1 (0.2%) in the HIV-TB screening arm (RR: 0.09, 0.01 to 0.71). Incremental costs were US$3.58 and US$19.92 per participant screened for HIV and HIV-TB; the probability of cost-effectiveness at a US$1,200/quality-adjusted life year (QALY) threshold was 83.9% and 0%. Main limitations were the lower than anticipated prevalence of TB and short participant follow-up period; cost and quality of life benefits of this screening approach may accrue over a longer time horizon.
Conclusions
DCXR-CAD with universal HIV screening significantly increased the timeliness and completeness of HIV and TB diagnosis. If implemented at scale, this has potential to rapidly and efficiently improve TB and HIV diagnosis and treatment.
Author summary
Why was this study done?
Tuberculosis (TB), one of the leading infectious killers worldwide, remains challenging to diagnose in low-resource settings, and patients frequently face multiple health centre visits at high cost before TB is diagnosed and treatment started. HIV is a major risk factor for TB.
Robust digital X-ray equipment can now be deployed at a primary care level in sub-Saharan Africa, and automated computer software packages that can interpret chest X-rays providing a probabilistic score for pulmonary TB have accuracy similar to, or greater than, expert human readers.
We therefore set out to investigate whether offering adults with cough attending primary care in Blantyre, Malawi universal HIV testing and linkage to antiretroviral therapy (ART)-either alone or combined with computer-aided digital chest X-ray (DCXR-CAD) and subsequent sputum Xpert confirmation-could improve the timeliness and completeness of HIV and TB diagnosis and treatment compared to current standard approaches (health worker-directed TB and HIV screening).
What did the researchers do and find?
A total of 1,462 adults attending a primary clinic in Blantyre, Malawi with cough were randomly allocated to receive either standard of care (SOC) health worker-directed HIV-TB screening; oral HIV testing and linkage to treatment (HIV screening); or oral HIV testing and linkage to treatment with additional digital chest X-ray screening for TB interpreted by computer-aided diagnosis software (CAD4TBv5), with sputum Xpert testing for participants with a CAD4TBv5 score above 45 (HIV/TB screening). Participants were followed for 56 days to investigate initiation of TB treatment, missed TB and HIV diagnosis, and cost-effectiveness.
Median time to TB treatment initiation was shorter (1 day) in the HIV-TB screening arm compared to the SOC arm (11 days) and HIV screening arm (6 days). HIV screening reduced undiagnosed/untreated HIV from 10 (2.7%) in the SOC arm to 2 (0.5%) in the HIV screening arm and 1 (0.2%) in the HIV-TB screening arm.
Over the trial follow-up period (56 days), oral HIV testing and linkage to care were likely to be cost-effective, but digital chest X-ray with computer-aided interpretation was not.
What do these findings mean?
Digital chest X-ray screening with computer-aided interpretation for TB with universal HIV screening increased the timeliness and completeness of HIV and TB diagnosis.
If implemented at scale, these interventions have the potential to rapidly and efficiently improve TB and HIV diagnosis and treatment.</abstract><cop>SAN FRANCISCO</cop><pub>Public Library Science</pub><pmid>34499665</pmid><doi>10.1371/journal.pmed.1003752</doi><tpages>17</tpages><orcidid>https://orcid.org/0000-0002-3100-5512</orcidid><orcidid>https://orcid.org/0000-0002-7375-4845</orcidid><orcidid>https://orcid.org/0000-0002-6709-4270</orcidid><orcidid>https://orcid.org/0000-0001-6095-9430</orcidid><orcidid>https://orcid.org/0000-0002-5577-210X</orcidid><orcidid>https://orcid.org/0000-0001-7173-9038</orcidid><orcidid>https://orcid.org/0000-0002-2156-5030</orcidid><orcidid>https://orcid.org/0000-0002-4019-7456</orcidid><orcidid>https://orcid.org/0000-0002-6052-5859</orcidid><orcidid>https://orcid.org/0000-0002-0329-9613</orcidid><orcidid>https://orcid.org/0000-0003-3029-9579</orcidid><orcidid>https://orcid.org/0000-0001-7680-2200</orcidid><orcidid>https://orcid.org/0000-0002-3552-3181</orcidid><orcidid>https://orcid.org/0000-0003-3667-4536</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adult Adults Analysis Anti-HIV Agents - therapeutic use Antitubercular Agents - therapeutic use Biology and Life Sciences Coinfection Computer-aided medical diagnosis Cost analysis Cost-Benefit Analysis Cough Cough - diagnosis Cough - microbiology Data collection Diagnosis Diagnosis, Computer-Assisted - economics Economic aspects Female General & Internal Medicine Health Care Costs Health facilities Health Services Accessibility HIV HIV infection HIV Infections - diagnosis HIV Infections - drug therapy HIV Infections - epidemiology HIV Testing - economics Human immunodeficiency virus Humans Investigations Life Sciences & Biomedicine Malawi - epidemiology Male Medical care, Cost of Medical diagnosis Medical tests Medicine and Health Sciences Medicine, General & Internal Methods Microscopy Middle Aged Mortality Predictive Value of Tests Prevalence Primary care Primary Health Care Quality of life Questionnaires Radiography, Thoracic - economics Science & Technology Social Sciences Software Sputum Statistical analysis Tuberculosis Tuberculosis - diagnostic imaging Tuberculosis - drug therapy Tuberculosis - epidemiology Tuberculosis - microbiology Workers X rays Young Adult |
title | Computer-aided X-ray screening for tuberculosis and HIV testing among adults with cough in Malawi (the PROSPECT study): A randomised trial and cost-effectiveness analysis |
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