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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/23066

Title: A novel approach to estimation of the time to biomarker threshold: applications to HIV
Authors: Reddy, Tarylee
Molenberghs, Geert
Njagi, Edmund Njeru
Aerts, Marc
Issue Date: 2016
Citation: PHARMACEUTICAL STATISTICS, 15(6), p. 541-549
Abstract: In longitudinal studies of biomarkers, an outcome of interest is the time at which a biomarker reaches a particular threshold. The CD4 count is a widely used marker of human immunodeficiency virus progression. Because of the inherent variability of this marker, a single CD4 count below a relevant threshold should be interpreted with caution. Several studies have applied persistence criteria, designating the outcome as the time to the occurrence of two consecutive measurements less than the threshold. In this paper, we propose a method to estimate the time to attainment of two consecutive CD4 counts less than a meaningful threshold, which takes into account the patient-specific trajectory and measurement error. An expression for the expected time to threshold is presented, which is a function of the fixed effects, random effects and residual variance. We present an application to human immunodeficiency virus-positive individuals from a seroprevalent cohort in Durban, South Africa. Two thresholds are examined, and 95% bootstrap confidence intervals are presented for the estimated time to threshold. Sensitivity analysis revealed that results are robust to truncation of the series and variation in the number of visits considered for most patients. Caution should be exercised when interpreting the estimated times for patients who exhibit very slow rates of decline and patients who have less than three measurements. We also discuss the relevance of the methodology to the study of other diseases and present such applications. We demonstrate that the method proposed is computationally efficient and offers more flexibility than existing frameworks. Copyright (c) 2016 John Wiley & Sons, Ltd.
Notes: [Reddy, Tarylee] MRC, Biostat Unit, Durban, South Africa. [Reddy, Tarylee; Molenberghs, Geert; Njagi, Edmund Njeru; Aerts, Marc] Univ Hasselt, I BioStat, Diepenbeek, Belgium. [Molenberghs, Geert] Katholieke Univ Leuven, I BioStat, Leuven, Belgium. [Njagi, Edmund Njeru] London Sch Hyg Trop Med, Canc Res UK Canc Survival Grp, London, England.
URI: http://hdl.handle.net/1942/23066
DOI: 10.1002/pst.1774
ISI #: 000388565400009
ISSN: 1539-1604
Category: A1
Type: Journal Contribution
Validation: ecoom, 2017
Appears in Collections: Research publications

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