Correcting Mortality for Loss to Follow-Up: A Nomogram Applied to Antiretroviral Treatment Programmes in Sub-Saharan Africa

Egger, Matthias; Spycher, Ben D.; Sidle, John E.; Weigel, Ralf; Geng, Elvin; Fox, Matthew P.; MacPhail, Patrick; Cutsem, Gilles van; Messou, Eugène; Wood, Robin; Nash, Denis; Pascoe, Margaret; Dickinson, Diana; Etard, Jean‐François; McIntyre, James; Brinkhof, Martin W. G.; Africa, West; Africa, Southern

doi:10.1371/journal.pmed.1000390

Cited by 139 publications

(168 citation statements)

References 29 publications

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“…Not receiving ART was the single factor significantly associated with overall attrition among the 1162 patients studied, while both baseline BMI z-score and receipt of ART were significantly negatively associated with LTFU among all patients in this cohort. The higher rate of LTFU and relatively lower death rate observed in this study are in line with the literature, and most likely due to considerable misclassification of LTFU, that is, many deaths among patients considered LTFU [21,22]. We also think that the high LTFU rate may be due in part to delays in obtaining and entering data, such that patients considered LTFU may actually have unrecorded visits or unrecorded deaths.…”

Section: Discussionsupporting

confidence: 89%

Attrition and Loss to Follow-up Among Children and Adolescents in a Community Home-Based Care HIV Programme in Uganda

Massavon¹

2013

Pediat Therapeut

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Section: Discussionsupporting

confidence: 89%

Attrition and Loss to Follow-up Among Children and Adolescents in a Community Home-Based Care HIV Programme in Uganda

Massavon¹

2013

Pediat Therapeut

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“…We borrowed from the idea underlying the nomogram approach published by Egger and colleagues31 but adjusted it to fit the needs of the current project. The nomogram approach considers the inverse relationship between the size of lost to follow-up (LTFU) and per cent of LTFU patients who are dead in order to extrapolate the correct (but unknown) death rate among patients who drop out from care.…”

Section: Resultsmentioning

confidence: 99%

“…This has been observed in a number of instances throughout sub-Saharan Africa where rapid scale-up of care and treatment services result in often chaotic patient self-referral patterns from one clinic to another, which accounts for an increasing proportion of losses to follow-up 30. Using a structured survey of a number of programmes throughout the region, Egger and colleagues constructed a nomogram where a correction factor is estimated according to the mortality ratio between patients who were lost or not and the level of loss to follow-up at a particular programme 31. This correction factor is then used to produce adjusted estimates of 1-year mortality.…”

Section: Introductionmentioning

confidence: 99%

Estimated mortality of adult HIV-infected patients starting treatment with combination antiretroviral therapy

et al. 2012

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ObjectiveTo provide estimates of mortality among HIV-infected patients starting combination antiretroviral therapy.MethodsWe report on the death rates from 122 925 adult HIV-infected patients aged 15 years or older from East, Southern and West Africa, Asia Pacific and Latin America. We use two methods to adjust for biases in mortality estimation resulting from loss from follow-up, based on double-sampling methods applied to patient outreach (Kenya) and linkage with vital registries (South Africa), and apply these to mortality estimates in the other three regions. Age, gender and CD4 count at the initiation of therapy were the factors considered as predictors of mortality at 6, 12, 24 and >24 months after the start of treatment.ResultsPatient mortality was high during the first 6 months after therapy for all patient subgroups and exceeded 40 per 100 patient years among patients who started treatment at low CD4 count. This trend was seen regardless of region, demographic or disease-related risk factor. Mortality was under-reported by up to or exceeding 100% when comparing estimates obtained from passive monitoring of patient vital status.ConclusionsDespite advances in antiretroviral treatment coverage many patients start treatment at very low CD4 counts and experience significant mortality during the first 6 months after treatment initiation. Active patient tracing and linkage with vital registries are critical in adjusting estimates of mortality, particularly in low- and middle-income settings.

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“…Although such an assumption is common in practice, it is strong and likely violated in observational HIV studies, and can lead to biased estimates. 28,29 As seen in the current study and elsewhere, 30 LTFU rates can be quite heterogeneous between cohorts, and differential ascertainment of death may explain heterogeneity. 31 The best approach for handling LTFU is through targeted patient tracing, 32 which was not done in this study.…”

Section: Fig 3 (A B)mentioning

confidence: 52%

“…31 The best approach for handling LTFU is through targeted patient tracing, 32 which was not done in this study. Sensitivity analyses can also be employed by assuming specific mortality rates of patients LTFU, 28,33 but were beyond the scope of this study.…”

Section: Fig 3 (A B)mentioning

confidence: 99%

A Comparison of Seven Cox Regression-Based Models to Account for Heterogeneity Across Multiple HIV Treatment Cohorts in Latin America and the Caribbean

Giganti

Luz²,

Caro-Vega³

et al. 2015

AIDS Research and Human Retroviruses

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Many studies of HIV/AIDS aggregate data from multiple cohorts to improve power and generalizability. There are several analysis approaches to account for cross-cohort heterogeneity; we assessed how different approaches can impact results from an HIV/AIDS study investigating predictors of mortality. Using data from 13,658 HIVinfected patients starting antiretroviral therapy from seven Latin American and Caribbean cohorts, we illustrate the assumptions of seven readily implementable approaches to account for across cohort heterogeneity with Cox proportional hazards models, and we compare hazard ratio estimates across approaches. As a sensitivity analysis, we modify cohort membership to generate specific heterogeneity conditions. Hazard ratio estimates varied slightly between the seven analysis approaches, but differences were not clinically meaningful. Adjusted hazard ratio estimates for the association between AIDS at treatment initiation and death varied from 2.00 to 2.20 across approaches that accounted for heterogeneity; the adjusted hazard ratio was estimated as 1.73 in analyses that ignored across cohort heterogeneity. In sensitivity analyses with more extreme heterogeneity, we noted a slightly greater distinction between approaches. Despite substantial heterogeneity between cohorts, the impact of the specific approach to account for heterogeneity was minimal in our case study. Our results suggest that it is important to account for across cohort heterogeneity in analyses, but that the specific technique for addressing heterogeneity may be less important. Because of their flexibility in accounting for cohort heterogeneity, we prefer stratification or meta-analysis methods, but we encourage investigators to consider their specific study conditions and objectives.

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Correcting Mortality for Loss to Follow-Up: A Nomogram Applied to Antiretroviral Treatment Programmes in Sub-Saharan Africa

Abstract: Matthias Egger and colleagues present a nomogram and a web-based calculator to correct estimates of program-level mortality for loss to follow-up, for use in antiretroviral treatment programs.

Cited by 139 publications

References 29 publications

Attrition and Loss to Follow-up Among Children and Adolescents in a Community Home-Based Care HIV Programme in Uganda

Attrition and Loss to Follow-up Among Children and Adolescents in a Community Home-Based Care HIV Programme in Uganda

Estimated mortality of adult HIV-infected patients starting treatment with combination antiretroviral therapy

A Comparison of Seven Cox Regression-Based Models to Account for Heterogeneity Across Multiple HIV Treatment Cohorts in Latin America and the Caribbean

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