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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Veröffentlicht in:PLoS medicine 2021-09, Vol.18 (9), p.e1003752-e1003752, Article 1003752
Hauptverfasser: 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
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container_start_page e1003752
container_title PLoS medicine
container_volume 18
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
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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 (&gt;= 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 &amp; 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 &amp; Biomedicine ; Malawi - epidemiology ; Male ; Medical care, Cost of ; Medical diagnosis ; Medical tests ; Medicine and Health Sciences ; Medicine, General &amp; Internal ; Methods ; Microscopy ; Middle Aged ; Mortality ; Predictive Value of Tests ; Prevalence ; Primary care ; Primary Health Care ; Quality of life ; Questionnaires ; Radiography, Thoracic - economics ; Science &amp; 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 (&gt;= 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 &amp; 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 &amp; 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 &amp; 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 &amp; 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. 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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 &amp; 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 &amp; 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 &amp; 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 &amp; 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 &amp; 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 &amp; Medical Complete (Alumni)</collection><collection>Health &amp; 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 (&gt;= 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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