Sampling-based approaches to improve estimation of mortality among patient dropouts

Experience from a large PEPFAR-funded program in Western Kenya

Constantin Yiannoutsos, Ming Wen An, Constantine E. Frangakis, Beverly S. Musick, Paula Braitstein, Kara Wools-Kaloustian, Daniel Ochieng, Jeffrey N. Martin, Melanie C. Bacon, Vincent Ochieng, Sylvester Kimaiyo

Research output: Contribution to journalArticle

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Abstract

Background: Monitoring and evaluation (M&E) of HIV care and treatment programs is impacted by losses to follow-up (LTFU) in the patient population. The severity of this effect is undeniable but its extent unknown. Tracing all lost patients addresses this but census methods are not feasible in programs involving rapid scale-up of HIV treatment in the developing world. Sampling-based approaches and statistical adjustment are the only scaleable methods permitting accurate estimation of M&E indices. Methodology/Principal Findings: In a large antiretroviral therapy (ART) program in western Kenya, we assessed the impact of LTFU on estimating patient mortality among 8,977 adult clients of whom, 3,624 were LTFU. Overall, dropouts were more likely male (36.8% versus 33.7%; p = 0.003), and younger than non-dropouts (35.3 versus 35.7 years old; p = 0.020), with lower median CD4 count at enrollment (160 versus 189 cells/ml; p<0.001) and WHO stage 3-4 disease (47.5% versus 41.1%; p<0.001). Urban clinic clients were 75.0% of non-dropouts but 70.3% of dropouts (p<0.001). Of the 3,624 dropouts, 1,143 were sought and 621 had their vital status ascertained. Statistical techniques were used to adjust mortality estimates based on information obtained from located LTFU patients. Observed mortality estimates one year after enrollment were 1.7% (95% CI 1.3%-2.0%), revised to 2.8% (2.3%-3.1%) when deaths discovered through outreach were added and adjusted to 9.2% (7.8%-10.6%) and 9.9% (8.4%-11.5%) through statistical modeling depending on the method used. The estimates 12 months after ART initiation were 1.7% (1.3%-2.2%), 3.4% (2.9%-4.0%), 10.5% (8.7%-12.3%) and 10.7% (8.9%-12.6%) respectively. Conclusions/Significance Abstract: Assessment of the impact of LTFU is critical in program M&E as estimated mortality based on passive monitoring may underestimate true mortality by up to 80%. This bias can be ameliorated by tracing a sample of dropouts and statistically adjust the mortality estimates to properly evaluate and guide large HIV care and treatment programs.

Original languageEnglish
Article numbere3843
JournalPLoS One
Volume3
Issue number12
DOIs
StatePublished - Dec 2 2008

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dropouts
Patient Dropouts
Kenya
Sampling
Mortality
HIV
sampling
Monitoring
Therapeutics
Social Adjustment
methodology
therapeutics
outreach
monitoring
Censuses
CD4 Lymphocyte Count
death
Population

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Sampling-based approaches to improve estimation of mortality among patient dropouts : Experience from a large PEPFAR-funded program in Western Kenya. / Yiannoutsos, Constantin; An, Ming Wen; Frangakis, Constantine E.; Musick, Beverly S.; Braitstein, Paula; Wools-Kaloustian, Kara; Ochieng, Daniel; Martin, Jeffrey N.; Bacon, Melanie C.; Ochieng, Vincent; Kimaiyo, Sylvester.

In: PLoS One, Vol. 3, No. 12, e3843, 02.12.2008.

Research output: Contribution to journalArticle

Yiannoutsos, Constantin ; An, Ming Wen ; Frangakis, Constantine E. ; Musick, Beverly S. ; Braitstein, Paula ; Wools-Kaloustian, Kara ; Ochieng, Daniel ; Martin, Jeffrey N. ; Bacon, Melanie C. ; Ochieng, Vincent ; Kimaiyo, Sylvester. / Sampling-based approaches to improve estimation of mortality among patient dropouts : Experience from a large PEPFAR-funded program in Western Kenya. In: PLoS One. 2008 ; Vol. 3, No. 12.
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abstract = "Background: Monitoring and evaluation (M&E) of HIV care and treatment programs is impacted by losses to follow-up (LTFU) in the patient population. The severity of this effect is undeniable but its extent unknown. Tracing all lost patients addresses this but census methods are not feasible in programs involving rapid scale-up of HIV treatment in the developing world. Sampling-based approaches and statistical adjustment are the only scaleable methods permitting accurate estimation of M&E indices. Methodology/Principal Findings: In a large antiretroviral therapy (ART) program in western Kenya, we assessed the impact of LTFU on estimating patient mortality among 8,977 adult clients of whom, 3,624 were LTFU. Overall, dropouts were more likely male (36.8{\%} versus 33.7{\%}; p = 0.003), and younger than non-dropouts (35.3 versus 35.7 years old; p = 0.020), with lower median CD4 count at enrollment (160 versus 189 cells/ml; p<0.001) and WHO stage 3-4 disease (47.5{\%} versus 41.1{\%}; p<0.001). Urban clinic clients were 75.0{\%} of non-dropouts but 70.3{\%} of dropouts (p<0.001). Of the 3,624 dropouts, 1,143 were sought and 621 had their vital status ascertained. Statistical techniques were used to adjust mortality estimates based on information obtained from located LTFU patients. Observed mortality estimates one year after enrollment were 1.7{\%} (95{\%} CI 1.3{\%}-2.0{\%}), revised to 2.8{\%} (2.3{\%}-3.1{\%}) when deaths discovered through outreach were added and adjusted to 9.2{\%} (7.8{\%}-10.6{\%}) and 9.9{\%} (8.4{\%}-11.5{\%}) through statistical modeling depending on the method used. The estimates 12 months after ART initiation were 1.7{\%} (1.3{\%}-2.2{\%}), 3.4{\%} (2.9{\%}-4.0{\%}), 10.5{\%} (8.7{\%}-12.3{\%}) and 10.7{\%} (8.9{\%}-12.6{\%}) respectively. Conclusions/Significance Abstract: Assessment of the impact of LTFU is critical in program M&E as estimated mortality based on passive monitoring may underestimate true mortality by up to 80{\%}. This bias can be ameliorated by tracing a sample of dropouts and statistically adjust the mortality estimates to properly evaluate and guide large HIV care and treatment programs.",
author = "Constantin Yiannoutsos and An, {Ming Wen} and Frangakis, {Constantine E.} and Musick, {Beverly S.} and Paula Braitstein and Kara Wools-Kaloustian and Daniel Ochieng and Martin, {Jeffrey N.} and Bacon, {Melanie C.} and Vincent Ochieng and Sylvester Kimaiyo",
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T2 - Experience from a large PEPFAR-funded program in Western Kenya

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AU - An, Ming Wen

AU - Frangakis, Constantine E.

AU - Musick, Beverly S.

AU - Braitstein, Paula

AU - Wools-Kaloustian, Kara

AU - Ochieng, Daniel

AU - Martin, Jeffrey N.

AU - Bacon, Melanie C.

AU - Ochieng, Vincent

AU - Kimaiyo, Sylvester

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N2 - Background: Monitoring and evaluation (M&E) of HIV care and treatment programs is impacted by losses to follow-up (LTFU) in the patient population. The severity of this effect is undeniable but its extent unknown. Tracing all lost patients addresses this but census methods are not feasible in programs involving rapid scale-up of HIV treatment in the developing world. Sampling-based approaches and statistical adjustment are the only scaleable methods permitting accurate estimation of M&E indices. Methodology/Principal Findings: In a large antiretroviral therapy (ART) program in western Kenya, we assessed the impact of LTFU on estimating patient mortality among 8,977 adult clients of whom, 3,624 were LTFU. Overall, dropouts were more likely male (36.8% versus 33.7%; p = 0.003), and younger than non-dropouts (35.3 versus 35.7 years old; p = 0.020), with lower median CD4 count at enrollment (160 versus 189 cells/ml; p<0.001) and WHO stage 3-4 disease (47.5% versus 41.1%; p<0.001). Urban clinic clients were 75.0% of non-dropouts but 70.3% of dropouts (p<0.001). Of the 3,624 dropouts, 1,143 were sought and 621 had their vital status ascertained. Statistical techniques were used to adjust mortality estimates based on information obtained from located LTFU patients. Observed mortality estimates one year after enrollment were 1.7% (95% CI 1.3%-2.0%), revised to 2.8% (2.3%-3.1%) when deaths discovered through outreach were added and adjusted to 9.2% (7.8%-10.6%) and 9.9% (8.4%-11.5%) through statistical modeling depending on the method used. The estimates 12 months after ART initiation were 1.7% (1.3%-2.2%), 3.4% (2.9%-4.0%), 10.5% (8.7%-12.3%) and 10.7% (8.9%-12.6%) respectively. Conclusions/Significance Abstract: Assessment of the impact of LTFU is critical in program M&E as estimated mortality based on passive monitoring may underestimate true mortality by up to 80%. This bias can be ameliorated by tracing a sample of dropouts and statistically adjust the mortality estimates to properly evaluate and guide large HIV care and treatment programs.

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