Patten Scott B
Department of Community Health Sciences & Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada.
Clin Pract Epidemiol Ment Health. 2006 Jun 14;2:13. doi: 10.1186/1745-0179-2-13.
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. 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.
Data from two Canadian epidemiological studies were used, both studies were components of a program undertaken by the Canadian national statistical agency. One component was a cross-sectional psychiatric epidemiological survey (n = 36,984) and the other was a longitudinal study (n = 17,262).
A Weibull distribution provided a good description of episode durations reported by subjects with major depression in the cross-sectional survey. This distribution was used to develop a discrete event simulation model for episode duration calibrated using the longitudinal data. The resulting estimates were then incorporated into a predictive calculator. During the early weeks of an episode, recovery probabilities are high. The model predicts that approximately 20% will recover in the first week after diagnostic criteria for major depression are met. However, after six months of illness, recovery during a subsequent week is less than 1%.
The duration of an episode is relevant to the probability of recovery. This epidemiological feature of depressive disorders can inform prognostic judgments. 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.
流行病学数据表明,发作持续时间越长,从一次发作中恢复的概率越低,因此发作持续时间可能是决定是否需要治疗的一个重要因素。本研究的目的是将发作持续时间数据纳入一个计算器,以预测在特定时间段内恢复的概率。
使用了两项加拿大流行病学研究的数据,这两项研究都是加拿大国家统计机构开展的一个项目的组成部分。一个部分是横断面精神病流行病学调查(n = 36,984),另一个是纵向研究(n = 17,262)。
在横断面调查中,威布尔分布很好地描述了重度抑郁症患者报告的发作持续时间。利用该分布建立了一个针对发作持续时间的离散事件模拟模型,并使用纵向数据进行校准。然后将得到的估计值纳入一个预测计算器中。在发作的最初几周内,恢复概率很高。该模型预测,在符合重度抑郁症诊断标准后的第一周,约20%的患者会康复。然而,患病六个月后,接下来一周内的康复率不到1%。
发作持续时间与恢复概率相关。抑郁症的这一流行病学特征可为预后判断提供参考。对于近期发作的轻度发作,观察等待可能是一种合适的策略,但必须根据发作开始后的时间来评估该策略的风险和益处。