Trajectory Pathways for Depressive Symptoms and Their Associated Factors in a Chinese Primary Care Cohort by Growth Mixture Modelling

BackgroundThe naturalistic course for patients suffering from depressive disorders can be quite varied. Whilst some remit with little or no intervention, others may suffer a more prolonged course of symptoms. The aim of this study was to identify trajectory patterns for depressive symptoms in a Chinese primary care cohort and their associated factors.Methods and ResultsA 12-month cohort study was conducted. Patients recruited from 59 primary care clinics across Hong Kong were screened for depressive symptoms using the Centre for Epidemiologic Studies Depression Scale (CES-D) and monitored over 12 months using the Patient Health Questionnaire-9 items (PHQ-9) administered at 12, 26 and 52 weeks. 721 subjects were included for growth mixture modelling analysis. Using Akaike Information Criterion, Bayesian Information Criterion, Entropy and Lo-Mendell-Rubin adjusted likelihood ratio test, a seven-class trajectory path model was identified. Over 12 months, three trajectory groups showed improvement in depressive symptoms, three remained static, whilst one deteriorated. A mild severity of depressive symptoms with gradual improvement was the most prevalent trajectory identified. Multivariate, multinomial regression analysis was used to identify factors associated with each trajectory. Risk factors associated with chronicity included: female gender; not married; not in active employment; presence of multiple chronic disease co-morbidities; poor self-rated general health; and infrequent health service use.ConclusionsWhilst many primary care patients may initially present with a similar severity of depressive symptoms, their course over 12 months can be quite heterogeneous. Although most primary care patients improve naturalistically over 12 months, many do not remit and it is important for doctors to be able to identify those who are at risk of chronicity. Regular follow-up and greater treatment attention is recommended for patients at risk of chronicity.背景 抑郁障碍患者的自然病程差异显著。部分患者仅需极少干预甚至无需干预即可实现症状缓解，而另一些患者则可能经历更长时间的症状迁延。本研究旨在明确中国初级卫生保健队列中抑郁症状的轨迹模式及其相关影响因素。 方法与结果 本研究开展了一项为期12个月的队列研究。研究从香港全境59家初级保健诊所招募受试者，采用流行病学研究抑郁量表（Centre for Epidemiologic Studies Depression Scale, CES-D）筛查其抑郁症状，并在随访的第12、26和52周，通过患者健康问卷9项版（Patient Health Questionnaire-9 items, PHQ-9）进行抑郁症状监测。最终纳入721名受试者进行增长混合模型分析。结合赤池信息准则（Akaike Information Criterion）、贝叶斯信息准则（Bayesian Information Criterion）、熵值以及Lo-Mendell-Rubin校正似然比检验，最终确定了7类轨迹路径模型。在12个月的随访周期内，3类轨迹组的抑郁症状呈改善趋势，3类轨迹组症状维持稳定，另有1类轨迹组症状出现恶化。以轻度抑郁症状并随时间逐渐改善为特征的轨迹类型为本次研究中最常见的抑郁症状轨迹。本研究采用多变量多项回归分析，明确了与各轨迹类型相关的影响因素，与抑郁症状慢性化相关的危险因素包括：女性性别、未婚状态、未处于在职就业状态、合并多种慢性共病、自我评定的总体健康状况较差以及卫生服务利用频率较低。 结论 尽管多数初级保健患者初次就诊时抑郁症状严重程度相近，但在12个月的随访期间，其病程表现出显著的异质性。尽管大多数初级保健患者的抑郁症状可在自然病程下得到改善，但仍有大量患者无法实现症状完全缓解，因此临床医生能够识别存在慢性化风险的患者至关重要。对于存在慢性化风险的患者，建议定期随访并给予更强化的治疗关注。