October 1992

Stability of Psychiatric DiagnosesAn Application to the Affective Disorders

Author Affiliations

From the Department of Psychiatry (Dr Rice and Mss Rochberg and Miller) and the Division of Biostatistics (Dr Rice), Washington University School of Medicine and the Jewish Hospital of St Louis (Mo); Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY (Dr Endicott); and Brown University, Providence, RI (Dr Lavori).

Arch Gen Psychiatry. 1992;49(10):824-830. doi:10.1001/archpsyc.1992.01820100068012

• In the National Institute of Mental Health Collaborative Program on the Psychobiology of Depression study, data were collected on 2226 first-degree relatives of 612 probands. A second, "blind" reassessment of all relatives was attempted 6 years after the initial evaluation. We report on a final sample of 1629 relatives assessed twice using the Schedule for Affective Disorders and Schizophrenia— Lifetime version. We summarize methods for using stability of diagnosis to model the relationship between clinical covariates and the probability of being a true case. Moreover, we define an index of caseness that can be used to narrow the criteria for who is a case. Of those positive for major depressive disorder at initial evaluation, 74% were positive (on a lifetime basis) at follow-up (ie, were stable). There is a gradient: 48% of those who had three symptoms and no treatment were stable, compared with 96% of those with eight symptoms and treatment. For major depressive disorder, we found the caseness index for those with lifetime mania more severe than that of nonbipolar patients, with those who had hypomania being intermediate. A hierarchical analysis indicated that bipolar I tends to be diagnosed as schizoaffective-manic across occasions, and vice versa. This is consistent with the prior familial analyses that suggest these two diagnoses be combined into a single bipolar phenotype. The analysis for major depressive disorder indicates that caseness appears to represent quantitative, rather than qualitative, differences, with no natural cutoff to identify distinct subgroups. Finally, we discuss implications including utility in genetic analyses, estimation of incidence or prevalence allowing for diagnostic error, and examination of cohort effects.