Abstract
BackgroundIt has been proposed that bipolar disorder onsets in a predictable progressive sequence of clinical stages. However, there is some debate in regard to a statistical approach to test this hypothesis. The objective of this paper is to investigate two different analysis strategies to determine the best suited model to assess the longitudinal progression of clinical stages in the development of bipolar disorder.MethodsData previously collected on 229 subjects at high risk of developing bipolar disorder were used for the statistical analysis. We investigate two statistical approaches for analyzing the relationship between the proposed stages of bipolar disorder: 1) the early stages are considered as time-varying covariates affecting the hazard of bipolar disorder in a Cox proportional hazards model, 2) the early stages are explicitly modelled as states in a non-parametric multi-state model.ResultsWe found from the Cox model thatthere was evidence that the hazard of bipolar disorder is increased by the onset of major depressive disorder. From the multi-state model, in high-risk offspring the probability of bipolar disorder by age 29 was estimated as 0.2321. Cumulative incidence functions representing the probability of bipolar disorder given major depressive disorder at or before age 18 were estimated using both approaches and found to be similar.ConclusionsBoth the Cox model and multi-state model are useful approaches to the modelling of antecedent risk syndromes. They lead to similar cumulative incidence functions but otherwise each method offers a different advantage.
Highlights
It has been proposed that bipolar disorder onsets in a predictable progressive sequence of clinical stages
Duffy et al (2010) suggested that specific types of psychopathological manifestations are precursors for bipolar disorder in this high-risk population. They showed that individuals at familial risk for bipolar disorder develop the illness in a forward sequence of clinical stages: evolving from non-mood disorders followed by minor mood disorders, major mood disorders, and bipolar disorder (Figure 1)
Cox model A Cox model is presented with time to bipolar disorder as the event of interest and one time-varying covariate representing the absence or presence of a major depressive disorder: αi(t) = α0(t) exp{β1xi(t)}
Summary
It has been proposed that bipolar disorder onsets in a predictable progressive sequence of clinical stages. Duffy et al (2010) suggested that specific types of psychopathological manifestations are precursors for bipolar disorder in this high-risk population They showed that individuals at familial risk for bipolar disorder develop the illness in a forward sequence of clinical stages: evolving from non-mood disorders followed by minor mood disorders, major mood disorders, and bipolar disorder (Figure 1). In this developmental clinical staging model, nonmood disorders include primarily anxiety and sleep disorders, and in a subgroup of offspring from lithium non-responsive parents, attention deficit hyperactivity disorders (ADHD), and learning disabilities. Understanding the natural history of psychiatric disease is a critical advance supporting the identification of associated markers of illness risk and development This approach has been very successful in other complex
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