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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
medicine
Multidrug resistance among new tuberculosis cases: Detecting local variation through lot quality-assurance sampling
Epidemiology, Volume 23, No. 2, Year 2012
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Description
Background: Current methodology for multidrug-resistant tuberculosis (MDR TB) surveys endorsed by the World Health Organization provides estimates of MDR TB prevalence among new cases at the national level. On the aggregate, local variation in the burden of MDR TB may be masked. This paper investigates the utility of applying lot quality-assurance sampling to identify geographic heterogeneity in the proportion of new cases with multidrug resistance. Methods: We simulated the performance of lot quality-assurance sampling by applying these classification-based approaches to data collected in the most recent TB drug-resistance surveys in Ukraine, Vietnam, and Tanzania. We explored 3 classification systems - two-way static, three-way static, and three-way truncated sequential sampling - at 2 sets of thresholds: low MDR TB = 2%, high MDR TB = 10%, and low MDR TB = 5%, high MDR TB = 20%. Results: The lot quality-assurance sampling systems identified local variability in the prevalence of multidrug resistance in both high-resistance (Ukraine) and low-resistance settings (Vietnam). In Tanzania, prevalence was uniformly low, and the lot quality-assurance sampling approach did not reveal variability. The three-way classification systems provide additional information, but sample sizes may not be obtainable in some settings. New rapid drug-sensitivity testing methods may allow truncated sequential sampling designs and early stopping within static designs, producing even greater efficiency gains. Conclusions: Lot quality-assurance sampling study designs may offer an efficient approach for collecting critical information on local variability in the burden of multidrug-resistant TB. Before this methodology is adopted, programs must determine appropriate classification thresholds, the most useful classification system, and appropriate weighting if unbiased national estimates are also desired. Copyright © 2012 by Lippincott Williams & Wilkins.
Authors & Co-Authors
Hedt-Gauthier, Bethany Lynn
United States, Boston
Harvard Medical School
van Leth, Frank C.M.
Netherlands, Amsterdam
Amsterdam Umc - University of Amsterdam
Netherlands, The Hague
Kncv Tuberculosis Foundation
Zignol, Matteo
Switzerland, Geneva
Organisation Mondiale de la Santé
Cobelens, Frank G.J.
Netherlands, Amsterdam
Amsterdam Umc - University of Amsterdam
van Gemert, Wayne
Switzerland, Geneva
Organisation Mondiale de la Santé
Nguyen, Nhung Viet
Viet Nam, Hanoi
National Lung Hospital
Lyepshina, Svetlana
Ukraine, Lyman
Donetsk State Medical University
Egwaga, Saidi M.
Tanzania
National Tuberculosis Control Program
Cohen, Ted
United States, Boston
Brigham and Women's Hospital
United States, Boston
Harvard T.h. Chan School of Public Health
Statistics
Citations: 15
Authors: 9
Affiliations: 9
Identifiers
Doi:
10.1097/EDE.0b013e3182459455
ISSN:
10443983
e-ISSN:
15315487
Research Areas
Genetics And Genomics
Infectious Diseases
Study Design
Cross Sectional Study
Study Locations
Tanzania