title: A novel approach to estimation of the time to biomarker threshold: applications to HIV.
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 © 2016 John Wiley & Sons, Ltd.
authors: Biostatistics Unit, Medical Research Council, Durban, South Africa.|I-BioStat, Universiteit Hasselt, Diepenbeek, Belgium.
authors: Tarylee
authors: T
authors: Reddy
authors: I-BioStat, Universiteit Hasselt, Diepenbeek, Belgium.|I-BioStat, KU Leuven, Leuven, Belgium.
authors: Geert
authors: G
authors: Molenberghs
authors: I-BioStat, Universiteit Hasselt, Diepenbeek, Belgium.|Cancer Research UK Cancer Survival Group, London School of Hygiene & Tropical Medicine, London, United Kingdom.
authors: Edmund Njeru
authors: EN
authors: Njagi
authors: I-BioStat, Universiteit Hasselt, Diepenbeek, Belgium.
authors: Marc
authors: M
authors: Aerts
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000032:analysis*; D018791:CD4 Lymphocyte Count; D018450:Disease Progression; D005260:Female; D005500:Follow-Up Studies; D015658:HIV Infections / Q000175:diagnosis* / Q000503:physiopathology; D015528:HIV Seroprevalence; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D015233:Models, Statistical; D013019:South Africa; D013997:Time Factors
chemical_list: D015415:Biomarkers
keywords: CD4 count; HIV progression; persistence criteria; prediction; seroprevalent cohort; threshold