In an analysis of incident cases in NEMESIS, Spijker et al. The Netherlands Mental Health Survey and Incidence Study (NEMESIS) reported that physical illness, lack of social support, severity of depression and having had a previous long episode were all associated with increased duration of an index major depressive episode. Much of the research on determinants of episode duration has been conducted in clinical samples, but community studies have also been published. Įpidemiological data about the prognosis of episodes can help to inform clinical decisions. have highlighted a similar issue by noting poor agreement between results from a fully structured lay administered diagnostic interview and a semi-structured interview administered by clinicians. who found that including items relating to "clinical significance" in diagnostic algorithms applied to data from structured diagnostic interviews can substantially alter prevalence estimates. Attention has been drawn to this issue by Narrow et al. These apparent inconsistencies relate to a broader debate within psychiatric epidemiology concerning the clinical significance of depressive episodes identified in community studies. , whereas the UK National Institute for Health and Clinical Excellence (NICE) guidelines indicate that mild episodes may not require treatment with antidepressants. Most CPGs in North America regard fulfillment of DSM-IV criteria for major depression as a de facto indication for pharmacological or non-pharmacological treatment e.g. The process of developing guidelines, however, depends largely on data from randomized controlled trials, and the resulting recommendations are not always generalizable to real-world populations. Watchful waiting may be an appropriate strategy for mild episodes of recent onset, but the risks and benefits of this strategy must be assessed in relation to time since onset of the episode.Ĭlinical practice guidelines (CPGs) provide important mechanisms for integrating scientific evidence with clinical care. This epidemiological feature of depressive disorders can inform prognostic judgments. The duration of an episode is relevant to the probability of recovery. However, after six months of illness, recovery during a subsequent week is less than 1%. The model predicts that approximately 20% will recover in the first week after diagnostic criteria for major depression are met. During the early weeks of an episode, recovery probabilities are high. The resulting estimates were then incorporated into a predictive calculator. This distribution was used to develop a discrete event simulation model for episode duration calibrated using the longitudinal data. ResultsĪ Weibull distribution provided a good description of episode durations reported by subjects with major depression in the cross-sectional survey. One component was a cross-sectional psychiatric epidemiological survey (n = 36,984) and the other was a longitudinal study (n = 17,262). Methodsĭata from two Canadian epidemiological studies were used, both studies were components of a program undertaken by the Canadian national statistical agency. The objective of this study is to incorporate episode duration data into a calculator predicting the probability of recovery during a specified interval of time. Epidemiological data have shown that the probability of recovery from an episode declines with increasing episode duration, such that the duration of an episode may be an important factor in determining whether treatment is required.
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