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Home >> Publications >> A causal framework for understanding the effect of losses to follow-up on epidemiologic analyses in clinic-based cohorts: the case of HIV-infected patients on antiretroviral therapy in Africa.

Publication

Author(s):

Geng EH, Glidden DV, Bangsberg DR, Bwana MB, Musinguzi N, Nash D, Metcalfe JZ, Yiannoutsos CT, Martin JN, Petersen ML.

Pub Title:

A causal framework for understanding the effect of losses to follow-up on epidemiologic analyses in clinic-based cohorts: the case of HIV-infected patients on antiretroviral therapy in Africa.

Pub Date:

May 15 2012

Pub Region(s):

East Africa

Journal Issue:

10

Page Number:
1080-7

Journal:

Title: 
American Journal of Epidemiology
Link: 
http://aje.oxfordjournals.org/content/175/10/1080.long

PubMed: 22306557
Pub PDF: PDF icon 22306557.pdf

Abstract
Although clinic-based cohorts are most representative of the "real world," they are susceptible to loss to follow-up. Strategies for managing the impact of loss to follow-up are therefore needed to maximize the value of studies conducted in these cohorts. The authors evaluated adult patients starting antiretroviral therapy at an HIV/AIDS clinic in Uganda, where 29% of patients were lost to follow-up after 2 years (January 1, 2004-September 30, 2007). Unweighted, inverse probability of censoring weighted (IPCW), and sampling-based approaches (using supplemental data from a sample of lost patients subsequently tracked in the community) were used to identify the predictive value of sex on mortality. Directed acyclic graphs (DAGs) were used to explore the structural basis for bias in each approach. Among 3,628 patients, unweighted and IPCW analyses found men to have higher mortality than women, whereas the sampling-based approach did not. DAGs encoding knowledge about the data-generating process, including the fact that death is a cause of being classified as lost to follow-up in this setting, revealed "collider" bias in the unweighted and IPCW approaches. In a clinic-based cohort in Africa, unweighted and IPCW approaches-which rely on the "missing at random" assumption-yielded biased estimates. A sampling-based approach can in general strengthen epidemiologic analyses conducted in many clinic-based cohorts, including those examining other diseases.

PMID: 22306557 [PubMed - indexed for MEDLINE]

PMCID: PMC3353135

 
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Citation:

Geng EH, Glidden DV, Bangsberg DR, Bwana MB, Musinguzi N, Nash D, Metcalfe JZ, Yiannoutsos CT, Martin JN, Petersen ML. A causal framework for understanding the effect of losses to follow-up on epidemiologic analyses in clinic-based cohorts: the case of HIV-infected patients on antiretroviral therapy in Africa. Am J Epidemiol. 2012 May 15;175(10):1080-7. doi: 10.1093/aje/kwr444. Epub 2012 Feb 3. PubMed PMID: 22306557; PubMed Central PMCID: PMC3353135.