Pitfalls of practicing cancer epidemiology in resource-limited settings: the case of survival and loss to follow-up after a diagnosis of Kaposi's sarcoma in five countries across sub-Saharan Africa.
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BORIS DOI
Date of Publication
February 6, 2016
Publication Type
Article
Division/Institute
Contributor
Freeman, Esther | |
Semeere, Aggrey | |
Wenger, Megan | |
Bwana, Mwebesa | |
Asirwa, F Chite | |
Busakhala, Naftali | |
Oga, Emmanuel | |
Jedy-Agba, Elima | |
Kwaghe, Vivian | |
Iregbu, Kenneth | |
Jaquet, Antoine | |
Dabis, Francois | |
Yumo, Habakkuk Azinyui | |
Dusingize, Jean Claude | |
Bangsberg, David | |
Anastos, Kathryn | |
Phiri, Sam | |
Yiannoutsos, Constantin | |
Wools-Kaloustian, Kara | |
Martin, Jeffrey |
Series
BMC cancer
ISSN or ISBN (if monograph)
1471-2407
Publisher
BioMed Central
Language
English
Publisher DOI
PubMed ID
26852390
Description
BACKGROUND
Survival after diagnosis is a fundamental concern in cancer epidemiology. In resource-rich settings, ambient clinical databases, municipal data and cancer registries make survival estimation in real-world populations relatively straightforward. In resource-poor settings, given the deficiencies in a variety of health-related data systems, it is less clear how well we can determine cancer survival from ambient data.
METHODS
We addressed this issue in sub-Saharan Africa for Kaposi's sarcoma (KS), a cancer for which incidence has exploded with the HIV epidemic but for which survival in the region may be changing with the recent advent of antiretroviral therapy (ART). From 33 primary care HIV Clinics in Kenya, Uganda, Malawi, Nigeria and Cameroon participating in the International Epidemiologic Databases to Evaluate AIDS (IeDEA) Consortia in 2009-2012, we identified 1328 adults with newly diagnosed KS. Patients were evaluated from KS diagnosis until death, transfer to another facility or database closure.
RESULTS
Nominally, 22% of patients were estimated to be dead by 2 years, but this estimate was clouded by 45% cumulative lost to follow-up with unknown vital status by 2 years. After adjustment for site and CD4 count, age <30 years and male sex were independently associated with becoming lost.
CONCLUSIONS
In this community-based sample of patients diagnosed with KS in sub-Saharan Africa, almost half became lost to follow-up by 2 years. This precluded accurate estimation of survival. Until we either generally strengthen data systems or implement cancer-specific enhancements (e.g., tracking of the lost) in the region, insights from cancer epidemiology will be limited.
Survival after diagnosis is a fundamental concern in cancer epidemiology. In resource-rich settings, ambient clinical databases, municipal data and cancer registries make survival estimation in real-world populations relatively straightforward. In resource-poor settings, given the deficiencies in a variety of health-related data systems, it is less clear how well we can determine cancer survival from ambient data.
METHODS
We addressed this issue in sub-Saharan Africa for Kaposi's sarcoma (KS), a cancer for which incidence has exploded with the HIV epidemic but for which survival in the region may be changing with the recent advent of antiretroviral therapy (ART). From 33 primary care HIV Clinics in Kenya, Uganda, Malawi, Nigeria and Cameroon participating in the International Epidemiologic Databases to Evaluate AIDS (IeDEA) Consortia in 2009-2012, we identified 1328 adults with newly diagnosed KS. Patients were evaluated from KS diagnosis until death, transfer to another facility or database closure.
RESULTS
Nominally, 22% of patients were estimated to be dead by 2 years, but this estimate was clouded by 45% cumulative lost to follow-up with unknown vital status by 2 years. After adjustment for site and CD4 count, age <30 years and male sex were independently associated with becoming lost.
CONCLUSIONS
In this community-based sample of patients diagnosed with KS in sub-Saharan Africa, almost half became lost to follow-up by 2 years. This precluded accurate estimation of survival. Until we either generally strengthen data systems or implement cancer-specific enhancements (e.g., tracking of the lost) in the region, insights from cancer epidemiology will be limited.
File(s)
File | File Type | Format | Size | License | Publisher/Copright statement | Content | |
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Freeman BMCCancer 2016.pdf | text | Adobe PDF | 484.47 KB | Attribution (CC BY 4.0) | published |