Barts Health Liver Centre, The Blizard Institute, Queen Mary University of London, The Hepatitis C Trust, London, UK.
Population Health Sciences, Bristol Medical School, Bristol University, Bristol, UK.
J Viral Hepat. 2022 Jan;29(1):43-51. doi: 10.1111/jvh.13626. Epub 2021 Oct 27.
Many people with chronic hepatitis C infection don't engage in treatment. To eliminate hepatitis C and avoid health inequalities therapy must be provided to everyone. In other diseases peers with lived experience of the condition have improved care but, for hepatitis C, studies have not shown unequivocal benefit. We completed a retrospective analysis of the English National Health Service treatment registry comparing treatment networks with and without peers using Bayesian Poisson (for count outcomes) or Bayesian Binomial (for proportion outcomes) mixed effects models with time fixed effects. For each outcome, we estimated relative ratio (RR-Poisson model) or odds ratio (Odds Ratio (OR)-Binomial model) between peer and non-peer networks. We analysed 30,729 patients within 20 operational delivery networks. In networks with peers there was an increase in the number of people initiating therapy (RR 1.12 95%, credible interval 1.02-1.21) and an increase in the proportion completing therapy (OR 2.45 95%, credible interval 1.49-3.84). However, we saw no change in proportions of people using drugs who initiated therapy nor any significant change in virological response (OR 1.14 95% credible interval 0.979-1.36). We repeated the analysis looking at the impact of peers two months after they had been introduced, when they had established networks of contacts, and saw an increase in the proportion of people treated in addiction services. In treating patients with chronic hepatitis C infection the inclusion of peer supporters may increase the number of people who initiate and complete antiviral therapy.
许多慢性丙型肝炎感染者不接受治疗。为了消除丙型肝炎并避免健康不平等,必须为每个人提供治疗。在其他疾病中,具有该疾病经验的同行已经改善了护理,但对于丙型肝炎,研究并未显示出明确的益处。我们对英国国家卫生服务治疗登记处进行了回顾性分析,比较了有和没有同伴的治疗网络,使用具有时间固定效应的贝叶斯泊松(用于计数结果)或贝叶斯二项式(用于比例结果)混合效应模型。对于每个结果,我们在同行和非同行网络之间估计了相对比(泊松模型的 RR)或比值比(二项式模型的 OR)。我们分析了 20 个运营交付网络中的 30729 名患者。在有同伴的网络中,开始治疗的人数增加(RR 1.12,95%置信区间 1.02-1.21),完成治疗的比例增加(OR 2.45,95%置信区间 1.49-3.84)。然而,我们没有看到使用药物开始治疗的人群比例有任何变化,也没有看到病毒学反应有任何显著变化(OR 1.14,95%置信区间 0.979-1.36)。我们重复了分析,观察了引入同伴两个月后的影响,此时他们已经建立了联系网络,我们看到了在成瘾服务中接受治疗的人数比例增加。在治疗慢性丙型肝炎感染患者时,包括同伴支持者可能会增加开始和完成抗病毒治疗的人数。