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BMC Infect Dis ; 9: 66, 2009 May 18.
Article in English | MEDLINE | ID: mdl-19450241

ABSTRACT

BACKGROUND: When a test for diagnosis of infectious diseases is introduced in a resource-limited setting, monitoring quality is a major concern. An optimized design of experiment and statistical models are required for this assessment. METHODS: Interferon-gamma release assay to detect tuberculosis (TB) infection from whole blood was tested in Hanoi, Viet Nam. Balanced incomplete block design (BIBD) was planned and fixed-effect models with heterogeneous error variance were used for analysis. In the first trial, the whole blood from 12 donors was incubated with nil, TB-specific antigens or mitogen. In 72 measurements, two laboratory members exchanged their roles in harvesting plasma and testing for interferon-gamma release using enzyme linked immunosorbent assay (ELISA) technique. After intervention including checkup of all steps and standard operation procedures, the second trial was implemented in a similar manner. RESULTS: The lack of precision in the first trial was clearly demonstrated. Large within-individual error was significantly affected by both harvester and ELISA operator, indicating that both of the steps had problems. After the intervention, overall within-individual error was significantly reduced (P < 0.0001) and error variance was no longer affected by laboratory personnel in charge, indicating that a marked improvement could be objectively observed. CONCLUSION: BIBD and analysis of fixed-effect models with heterogeneous variance are suitable and useful for objective and individualized assessment of proficiency in a multistep diagnostic test for infectious diseases in a resource-constrained laboratory. The action plan based on our findings would be worth considering when monitoring for internal quality control is difficult on site.


Subject(s)
Enzyme-Linked Immunosorbent Assay/methods , Interferon-gamma/blood , Mycobacterium tuberculosis/isolation & purification , Tuberculosis/diagnosis , Analysis of Variance , Antigens, Bacterial , Humans , Laboratories, Hospital/standards , Medical Laboratory Personnel/education , Models, Statistical , Quality Control , Vietnam
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