开发和验证一个预测成人在初级保健中缓解期抑郁症复发的预后模型：来自多个研究的 pooled 个体参与者数据的二次分析。

Development and validation of a prognostic model to predict relapse in adults with remitted depression in primary care: secondary analysis of pooled individual participant data from multiple studies.

机构信息

Hull York Medical School and Department of Health Sciences, University of York, York, Yorkshire, UK

Hull York Medical School and Department of Health Sciences, University of York, York, Yorkshire, UK.

出版信息

BMJ Ment Health. 2024 Oct 28;27(1):e301226. doi: 10.1136/bmjment-2024-301226.

DOI:10.1136/bmjment-2024-301226

PMID:39467616

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11529744/

Abstract

BACKGROUND

Relapse of depression is common and contributes to the overall associated morbidity and burden. We lack evidence-based tools to estimate an individual's risk of relapse after treatment in primary care, which may help us more effectively target relapse prevention.

OBJECTIVE

The objective was to develop and validate a prognostic model to predict risk of relapse of depression in primary care.

METHODS

Multilevel logistic regression models were developed, using individual participant data from seven primary care-based studies (n=1244), to predict relapse of depression. The model was internally validated using bootstrapping, and generalisability was explored using internal-external cross-validation.

FINDINGS

Residual depressive symptoms (OR: 1.13 (95% CI: 1.07 to 1.20), p<0.001) and baseline depression severity (OR: 1.07 (1.04 to 1.11), p<0.001) were associated with relapse. The validated model had low discrimination (C-statistic 0.60 (0.55-0.65)) and miscalibration concerns (calibration slope 0.81 (0.31-1.31)). On secondary analysis, being in a relationship was associated with reduced risk of relapse (OR: 0.43 (0.28-0.67), p<0.001); this remained statistically significant after correction for multiple significance testing.

CONCLUSIONS

We could not predict risk of depression relapse with sufficient accuracy in primary care data, using routinely recorded measures. Relationship status warrants further research to explore its role as a prognostic factor for relapse.

CLINICAL IMPLICATIONS

Until we can accurately stratify patients according to risk of relapse, a universal approach to relapse prevention may be most beneficial, either during acute-phase treatment or post remission. Where possible, this could be guided by the presence or absence of known prognostic factors (eg, residual depressive symptoms) and targeted towards these.

TRIAL REGISTRATION NUMBER

NCT04666662.

摘要

背景

抑郁症的复发很常见，会导致整体相关发病率和负担增加。我们缺乏基于证据的工具来评估个体在初级保健治疗后的复发风险，这可能有助于我们更有效地针对预防复发。

目的

旨在开发和验证一种预测初级保健中抑郁症复发风险的预后模型。

方法

使用来自七项基于初级保健的研究（n=1244）的个体参与者数据，使用多水平逻辑回归模型来预测抑郁症的复发。使用自举法对内进行验证，并通过内部-外部交叉验证探索通用性。

结果

残留的抑郁症状（OR：1.13（95%CI：1.07-1.20），p<0.001）和基线抑郁严重程度（OR：1.07（1.04-1.11），p<0.001）与复发相关。验证后的模型具有较低的区分度（C 统计量为 0.60（0.55-0.65））和校准问题（校准斜率为 0.81（0.31-1.31））。在二次分析中，处于恋爱关系与降低复发风险相关（OR：0.43（0.28-0.67），p<0.001）；在进行多次显著检验校正后，这仍然具有统计学意义。