Measuring Tuberculosis Medication Adherence: A Comparison of Multiple Approaches in Relation to Urine Isoniazid Metabolite Testing Within a Cohort Study in India

Background Nonadherence to tuberculosis medications is associated with poor outcomes. However, measuring adherence in practice is challenging. In this study, we evaluated the accuracy of multiple tuberculosis adherence measures. Methods We enrolled adult Indians with drug-susceptible tuberculosis wh...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Open Forum Infectious Diseases 2021-11, Vol.8 (11), p.ofab532-ofab532
Hauptverfasser: Subbaraman, Ramnath, Thomas, Beena E, Kumar, J Vignesh, Lubeck-Schricker, Maya, Khandewale, Amit, Thies, William, Eliasziw, Misha, Mayer, Kenneth H, Haberer, Jessica E
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page ofab532
container_issue 11
container_start_page ofab532
container_title Open Forum Infectious Diseases
container_volume 8
creator Subbaraman, Ramnath
Thomas, Beena E
Kumar, J Vignesh
Lubeck-Schricker, Maya
Khandewale, Amit
Thies, William
Eliasziw, Misha
Mayer, Kenneth H
Haberer, Jessica E
description Background Nonadherence to tuberculosis medications is associated with poor outcomes. However, measuring adherence in practice is challenging. In this study, we evaluated the accuracy of multiple tuberculosis adherence measures. Methods We enrolled adult Indians with drug-susceptible tuberculosis who were monitored using 99DOTS, a cellphone-based technology. During an unannounced home visit with each participant, we assessed adherence using a pill estimate, 4-day dose recall, a last missed dose question, and urine isoniazid metabolite testing. We estimated the area under the receiver operating characteristic curve (AUC) for each alternate measure in comparison to urine testing. 99DOTS data were analyzed using patient-reported doses alone and patient- and provider-reported doses, the latter reflecting how 99DOTS is implemented in practice. We assessed each measure’s operating characteristics, with particular interest in specificity—that is, the percentage of participants detected as being nonadherent by each alternate measure, among those who were nonadherent by urine testing. Results Compared with urine testing, alternate measures had the following characteristics: 99DOTS patient-reported doses alone (area under the curve [AUC], 0.65; specificity, 70%; 95% CI, 58%–81%), 99DOTS patient- and provider-reported doses (AUC, 0.61; specificity, 33%; 95% CI, 22%–45%), pill estimate (AUC, 0.55; specificity, 21%; 95% CI, 12%–32%), 4-day recall (AUC, 0.60; specificity, 23%; 95% CI, 14%–34%), and last missed dose question (AUC, 0.65; specificity, 52%; 95% CI, 40%–63%). Conclusions Alternate measures missed detecting at least 30% of people who were nonadherent by urine testing. The last missed dose question performed similarly to 99DOTS using patient-reported doses alone. Tuberculosis programs should evaluate the feasibility of integrating more accurate, objective measures, such as urine testing, into routine care.
doi_str_mv 10.1093/ofid/ofab532
format Article
fullrecord <record><control><sourceid>gale_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9088502</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A776147396</galeid><oup_id>10.1093/ofid/ofab532</oup_id><sourcerecordid>A776147396</sourcerecordid><originalsourceid>FETCH-LOGICAL-c483t-31089320bb06de5186c70a753f6ae3088ac7defa5c33032da76dc39d2eff6bcf3</originalsourceid><addsrcrecordid>eNp9kkGP1CAYhhujcTfr3jwbbnpwVihDWzyYNBNXJ9mJic7GI6HwMcXQUoGarP9m_6lMOm7WiyEB8vG-D3zhLYqXBF8RzOk7b6zOk-wYLZ8U5yUtm1XDWf300f6suIzxB8aYEMxwzZ8XZ5QxxklJz4v7Hcg4Bzse0H7uIKjZ-Wgj2oG2SibrR9TqHgKMCt6jFm38MMlgY657g3azS3ZygNppCl6qHiKyI_oKbrEmj24zG9A2G6z8bXUGJ9l5ZxOgPcR0vPi7TX12yQzvfUjoW5r13ZGzHbWVL4pnRroIl6f1ori9_rjffF7dfPm03bQ3K7VuaFpRghtOS9x1uNLASFOpGsuaUVNJoLhppKo1GMkUpZiWWtaVVpTrEoypOmXoRfFh4U5zN4BWMKYgnZiCHWS4E15a8e_JaHtx8L8Ez3CGywx4cwIE_3POvYnBRgXOyRH8HEVZVesGU054ll4t0oN0IOxofCaqPDQMVvkRjM31tq4rsq4pr7Lh7WJQwccYwDy8i2BxTII4JkGckpDlrx738iD---9Z8HoR-Hn6P-oPbxPBwQ</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2664803919</pqid></control><display><type>article</type><title>Measuring Tuberculosis Medication Adherence: A Comparison of Multiple Approaches in Relation to Urine Isoniazid Metabolite Testing Within a Cohort Study in India</title><source>Oxford Journals Open Access Collection</source><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central</source><creator>Subbaraman, Ramnath ; Thomas, Beena E ; Kumar, J Vignesh ; Lubeck-Schricker, Maya ; Khandewale, Amit ; Thies, William ; Eliasziw, Misha ; Mayer, Kenneth H ; Haberer, Jessica E</creator><creatorcontrib>Subbaraman, Ramnath ; Thomas, Beena E ; Kumar, J Vignesh ; Lubeck-Schricker, Maya ; Khandewale, Amit ; Thies, William ; Eliasziw, Misha ; Mayer, Kenneth H ; Haberer, Jessica E</creatorcontrib><description>Background Nonadherence to tuberculosis medications is associated with poor outcomes. However, measuring adherence in practice is challenging. In this study, we evaluated the accuracy of multiple tuberculosis adherence measures. Methods We enrolled adult Indians with drug-susceptible tuberculosis who were monitored using 99DOTS, a cellphone-based technology. During an unannounced home visit with each participant, we assessed adherence using a pill estimate, 4-day dose recall, a last missed dose question, and urine isoniazid metabolite testing. We estimated the area under the receiver operating characteristic curve (AUC) for each alternate measure in comparison to urine testing. 99DOTS data were analyzed using patient-reported doses alone and patient- and provider-reported doses, the latter reflecting how 99DOTS is implemented in practice. We assessed each measure’s operating characteristics, with particular interest in specificity—that is, the percentage of participants detected as being nonadherent by each alternate measure, among those who were nonadherent by urine testing. Results Compared with urine testing, alternate measures had the following characteristics: 99DOTS patient-reported doses alone (area under the curve [AUC], 0.65; specificity, 70%; 95% CI, 58%–81%), 99DOTS patient- and provider-reported doses (AUC, 0.61; specificity, 33%; 95% CI, 22%–45%), pill estimate (AUC, 0.55; specificity, 21%; 95% CI, 12%–32%), 4-day recall (AUC, 0.60; specificity, 23%; 95% CI, 14%–34%), and last missed dose question (AUC, 0.65; specificity, 52%; 95% CI, 40%–63%). Conclusions Alternate measures missed detecting at least 30% of people who were nonadherent by urine testing. The last missed dose question performed similarly to 99DOTS using patient-reported doses alone. Tuberculosis programs should evaluate the feasibility of integrating more accurate, objective measures, such as urine testing, into routine care.</description><identifier>ISSN: 2328-8957</identifier><identifier>EISSN: 2328-8957</identifier><identifier>DOI: 10.1093/ofid/ofab532</identifier><identifier>PMID: 35559123</identifier><language>eng</language><publisher>US: Oxford University Press</publisher><subject>Analysis ; Comparative analysis ; Drugs ; Isoniazid ; Major ; Metabolites ; Patient compliance ; Tuberculosis ; Urine</subject><ispartof>Open Forum Infectious Diseases, 2021-11, Vol.8 (11), p.ofab532-ofab532</ispartof><rights>The Author(s) 2021. Published by Oxford University Press on behalf of Infectious Diseases Society of America. 2021</rights><rights>The Author(s) 2021. Published by Oxford University Press on behalf of Infectious Diseases Society of America.</rights><rights>COPYRIGHT 2021 Oxford University Press</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c483t-31089320bb06de5186c70a753f6ae3088ac7defa5c33032da76dc39d2eff6bcf3</citedby><orcidid>0000-0002-2063-943X</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/PMC9088502/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9088502/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,1598,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35559123$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Subbaraman, Ramnath</creatorcontrib><creatorcontrib>Thomas, Beena E</creatorcontrib><creatorcontrib>Kumar, J Vignesh</creatorcontrib><creatorcontrib>Lubeck-Schricker, Maya</creatorcontrib><creatorcontrib>Khandewale, Amit</creatorcontrib><creatorcontrib>Thies, William</creatorcontrib><creatorcontrib>Eliasziw, Misha</creatorcontrib><creatorcontrib>Mayer, Kenneth H</creatorcontrib><creatorcontrib>Haberer, Jessica E</creatorcontrib><title>Measuring Tuberculosis Medication Adherence: A Comparison of Multiple Approaches in Relation to Urine Isoniazid Metabolite Testing Within a Cohort Study in India</title><title>Open Forum Infectious Diseases</title><addtitle>Open Forum Infect Dis</addtitle><description>Background Nonadherence to tuberculosis medications is associated with poor outcomes. However, measuring adherence in practice is challenging. In this study, we evaluated the accuracy of multiple tuberculosis adherence measures. Methods We enrolled adult Indians with drug-susceptible tuberculosis who were monitored using 99DOTS, a cellphone-based technology. During an unannounced home visit with each participant, we assessed adherence using a pill estimate, 4-day dose recall, a last missed dose question, and urine isoniazid metabolite testing. We estimated the area under the receiver operating characteristic curve (AUC) for each alternate measure in comparison to urine testing. 99DOTS data were analyzed using patient-reported doses alone and patient- and provider-reported doses, the latter reflecting how 99DOTS is implemented in practice. We assessed each measure’s operating characteristics, with particular interest in specificity—that is, the percentage of participants detected as being nonadherent by each alternate measure, among those who were nonadherent by urine testing. Results Compared with urine testing, alternate measures had the following characteristics: 99DOTS patient-reported doses alone (area under the curve [AUC], 0.65; specificity, 70%; 95% CI, 58%–81%), 99DOTS patient- and provider-reported doses (AUC, 0.61; specificity, 33%; 95% CI, 22%–45%), pill estimate (AUC, 0.55; specificity, 21%; 95% CI, 12%–32%), 4-day recall (AUC, 0.60; specificity, 23%; 95% CI, 14%–34%), and last missed dose question (AUC, 0.65; specificity, 52%; 95% CI, 40%–63%). Conclusions Alternate measures missed detecting at least 30% of people who were nonadherent by urine testing. The last missed dose question performed similarly to 99DOTS using patient-reported doses alone. Tuberculosis programs should evaluate the feasibility of integrating more accurate, objective measures, such as urine testing, into routine care.</description><subject>Analysis</subject><subject>Comparative analysis</subject><subject>Drugs</subject><subject>Isoniazid</subject><subject>Major</subject><subject>Metabolites</subject><subject>Patient compliance</subject><subject>Tuberculosis</subject><subject>Urine</subject><issn>2328-8957</issn><issn>2328-8957</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><recordid>eNp9kkGP1CAYhhujcTfr3jwbbnpwVihDWzyYNBNXJ9mJic7GI6HwMcXQUoGarP9m_6lMOm7WiyEB8vG-D3zhLYqXBF8RzOk7b6zOk-wYLZ8U5yUtm1XDWf300f6suIzxB8aYEMxwzZ8XZ5QxxklJz4v7Hcg4Bzse0H7uIKjZ-Wgj2oG2SibrR9TqHgKMCt6jFm38MMlgY657g3azS3ZygNppCl6qHiKyI_oKbrEmj24zG9A2G6z8bXUGJ9l5ZxOgPcR0vPi7TX12yQzvfUjoW5r13ZGzHbWVL4pnRroIl6f1ori9_rjffF7dfPm03bQ3K7VuaFpRghtOS9x1uNLASFOpGsuaUVNJoLhppKo1GMkUpZiWWtaVVpTrEoypOmXoRfFh4U5zN4BWMKYgnZiCHWS4E15a8e_JaHtx8L8Ez3CGywx4cwIE_3POvYnBRgXOyRH8HEVZVesGU054ll4t0oN0IOxofCaqPDQMVvkRjM31tq4rsq4pr7Lh7WJQwccYwDy8i2BxTII4JkGckpDlrx738iD---9Z8HoR-Hn6P-oPbxPBwQ</recordid><startdate>20211101</startdate><enddate>20211101</enddate><creator>Subbaraman, Ramnath</creator><creator>Thomas, Beena E</creator><creator>Kumar, J Vignesh</creator><creator>Lubeck-Schricker, Maya</creator><creator>Khandewale, Amit</creator><creator>Thies, William</creator><creator>Eliasziw, Misha</creator><creator>Mayer, Kenneth H</creator><creator>Haberer, Jessica E</creator><general>Oxford University Press</general><scope>TOX</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IAO</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-2063-943X</orcidid></search><sort><creationdate>20211101</creationdate><title>Measuring Tuberculosis Medication Adherence: A Comparison of Multiple Approaches in Relation to Urine Isoniazid Metabolite Testing Within a Cohort Study in India</title><author>Subbaraman, Ramnath ; Thomas, Beena E ; Kumar, J Vignesh ; Lubeck-Schricker, Maya ; Khandewale, Amit ; Thies, William ; Eliasziw, Misha ; Mayer, Kenneth H ; Haberer, Jessica E</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c483t-31089320bb06de5186c70a753f6ae3088ac7defa5c33032da76dc39d2eff6bcf3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Analysis</topic><topic>Comparative analysis</topic><topic>Drugs</topic><topic>Isoniazid</topic><topic>Major</topic><topic>Metabolites</topic><topic>Patient compliance</topic><topic>Tuberculosis</topic><topic>Urine</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Subbaraman, Ramnath</creatorcontrib><creatorcontrib>Thomas, Beena E</creatorcontrib><creatorcontrib>Kumar, J Vignesh</creatorcontrib><creatorcontrib>Lubeck-Schricker, Maya</creatorcontrib><creatorcontrib>Khandewale, Amit</creatorcontrib><creatorcontrib>Thies, William</creatorcontrib><creatorcontrib>Eliasziw, Misha</creatorcontrib><creatorcontrib>Mayer, Kenneth H</creatorcontrib><creatorcontrib>Haberer, Jessica E</creatorcontrib><collection>Oxford Journals Open Access Collection</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale Academic OneFile</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Open Forum Infectious Diseases</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Subbaraman, Ramnath</au><au>Thomas, Beena E</au><au>Kumar, J Vignesh</au><au>Lubeck-Schricker, Maya</au><au>Khandewale, Amit</au><au>Thies, William</au><au>Eliasziw, Misha</au><au>Mayer, Kenneth H</au><au>Haberer, Jessica E</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Measuring Tuberculosis Medication Adherence: A Comparison of Multiple Approaches in Relation to Urine Isoniazid Metabolite Testing Within a Cohort Study in India</atitle><jtitle>Open Forum Infectious Diseases</jtitle><addtitle>Open Forum Infect Dis</addtitle><date>2021-11-01</date><risdate>2021</risdate><volume>8</volume><issue>11</issue><spage>ofab532</spage><epage>ofab532</epage><pages>ofab532-ofab532</pages><issn>2328-8957</issn><eissn>2328-8957</eissn><abstract>Background Nonadherence to tuberculosis medications is associated with poor outcomes. However, measuring adherence in practice is challenging. In this study, we evaluated the accuracy of multiple tuberculosis adherence measures. Methods We enrolled adult Indians with drug-susceptible tuberculosis who were monitored using 99DOTS, a cellphone-based technology. During an unannounced home visit with each participant, we assessed adherence using a pill estimate, 4-day dose recall, a last missed dose question, and urine isoniazid metabolite testing. We estimated the area under the receiver operating characteristic curve (AUC) for each alternate measure in comparison to urine testing. 99DOTS data were analyzed using patient-reported doses alone and patient- and provider-reported doses, the latter reflecting how 99DOTS is implemented in practice. We assessed each measure’s operating characteristics, with particular interest in specificity—that is, the percentage of participants detected as being nonadherent by each alternate measure, among those who were nonadherent by urine testing. Results Compared with urine testing, alternate measures had the following characteristics: 99DOTS patient-reported doses alone (area under the curve [AUC], 0.65; specificity, 70%; 95% CI, 58%–81%), 99DOTS patient- and provider-reported doses (AUC, 0.61; specificity, 33%; 95% CI, 22%–45%), pill estimate (AUC, 0.55; specificity, 21%; 95% CI, 12%–32%), 4-day recall (AUC, 0.60; specificity, 23%; 95% CI, 14%–34%), and last missed dose question (AUC, 0.65; specificity, 52%; 95% CI, 40%–63%). Conclusions Alternate measures missed detecting at least 30% of people who were nonadherent by urine testing. The last missed dose question performed similarly to 99DOTS using patient-reported doses alone. Tuberculosis programs should evaluate the feasibility of integrating more accurate, objective measures, such as urine testing, into routine care.</abstract><cop>US</cop><pub>Oxford University Press</pub><pmid>35559123</pmid><doi>10.1093/ofid/ofab532</doi><orcidid>https://orcid.org/0000-0002-2063-943X</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2328-8957
ispartof Open Forum Infectious Diseases, 2021-11, Vol.8 (11), p.ofab532-ofab532
issn 2328-8957
2328-8957
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9088502
source Oxford Journals Open Access Collection; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central
subjects Analysis
Comparative analysis
Drugs
Isoniazid
Major
Metabolites
Patient compliance
Tuberculosis
Urine
title Measuring Tuberculosis Medication Adherence: A Comparison of Multiple Approaches in Relation to Urine Isoniazid Metabolite Testing Within a Cohort Study in India
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-10T20%3A31%3A01IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Measuring%20Tuberculosis%20Medication%20Adherence:%20A%20Comparison%20of%20Multiple%20Approaches%20in%20Relation%20to%20Urine%20Isoniazid%20Metabolite%20Testing%20Within%20a%20Cohort%20Study%20in%20India&rft.jtitle=Open%20Forum%20Infectious%20Diseases&rft.au=Subbaraman,%20Ramnath&rft.date=2021-11-01&rft.volume=8&rft.issue=11&rft.spage=ofab532&rft.epage=ofab532&rft.pages=ofab532-ofab532&rft.issn=2328-8957&rft.eissn=2328-8957&rft_id=info:doi/10.1093/ofid/ofab532&rft_dat=%3Cgale_pubme%3EA776147396%3C/gale_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2664803919&rft_id=info:pmid/35559123&rft_galeid=A776147396&rft_oup_id=10.1093/ofid/ofab532&rfr_iscdi=true