Roberts Emmert, Strang John, Horgan Patrick, Eastwood Brian
National Addiction Centre and the Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
South London and the Maudsley NHS Foundation Trust, London, UK.
Diagn Progn Res. 2024 Apr 16;8(1):7. doi: 10.1186/s41512-024-00170-8.
People with opioid use disorder have substantially higher standardised mortality rates compared to the general population; however, lack of clear individual prognostic information presents challenges to prioritise or target interventions within drug treatment services. Previous prognostic models have been developed to estimate the risk of developing opioid use disorder and opioid-related overdose in people routinely prescribed opioids but, to our knowledge, none have been developed to estimate mortality risk in people accessing drug services with opioid use disorder. Initial presentation to drug services is a pragmatic time to evaluate mortality risk given the contemporaneous routine collection of prognostic indicators and as a decision point for appropriate service prioritisation and targeted intervention delivery. This study aims to develop and internally validate a model to estimate 6-month mortality risk for people with opioid use disorder from prognostic indicators recorded at initial assessment in drug services in England.
An English national dataset containing records from individuals presenting to drug services between 1 April 2013 and 1 April 2023 (n > 800,000) (the National Drug Treatment Monitoring System (NDTMS)) linked to their lifetime hospitalisation and death records (Hospital Episode Statistics-Office of National Statistics (HES-ONS)). Twelve candidate prognostic indicator variables were identified based on literature review of demographic and clinical features associated with increased mortality for people in treatment for opioid use disorder. Variables will be extracted at initial presentation to drug services with mortality measured at 6 months. Two multivariable Cox regression models will be developed one for 6-month all-cause mortality and one for 6-month drug-related mortality using backward elimination with a fractional polynomial approach for continuous variables. Internal validation will be undertaken using bootstrapping methods. Discrimination of both models will be reported using Harrel's c and d-statistics. Calibration curves and slopes will be presented comparing expected and observed event rates.
The models developed and internally validated in this study aim to improve clinical assessment of mortality risk for people with opioid use disorder presenting to drug services in England. External validation in different populations will be required to develop the model into a tool to assist future clinical decision-making.
与普通人群相比，患有阿片类药物使用障碍的人标准化死亡率要高得多；然而，缺乏明确的个体预后信息给药物治疗服务中干预措施的优先排序或靶向治疗带来了挑战。此前已开发出预后模型来估计常规服用阿片类药物的人群中发生阿片类药物使用障碍和阿片类药物相关过量用药的风险，但据我们所知，尚未有模型用于估计接受阿片类药物使用障碍药物服务的人群的死亡风险。鉴于在药物服务初次就诊时会同时常规收集预后指标，且这是进行适当服务优先排序和靶向干预的决策点，所以药物服务的初次就诊是评估死亡风险的务实时机。本研究旨在开发并内部验证一个模型，该模型可根据英格兰药物服务初次评估时记录的预后指标来估计阿片类药物使用障碍患者6个月的死亡风险。
一个英国全国性数据集，包含2013年4月1日至2023年4月1日期间到药物服务机构就诊的个人记录（n>800,000）（国家药物治疗监测系统（NDTMS）），并与他们的终身住院和死亡记录（医院事件统计 - 国家统计局（HES - ONS））相链接。基于对与阿片类药物使用障碍治疗人群死亡率增加相关的人口统计学和临床特征的文献综述，确定了12个候选预后指标变量。变量将在初次就诊时提取，死亡率在6个月时测量。将开发两个多变量Cox回归模型，一个用于6个月全因死亡率，一个用于6个月药物相关死亡率，使用向后逐步回归法并采用分数多项式方法处理连续变量。将使用自助法进行内部验证。将使用Harrel's c和d统计量报告两个模型的区分度。将呈现校准曲线和斜率，比较预期和观察到的事件发生率。
本研究中开发并内部验证的模型旨在改善对在英格兰药物服务机构就诊的阿片类药物使用障碍患者死亡风险的临床评估。需要在不同人群中进行外部验证，以便将该模型开发成有助于未来临床决策的工具。
