Institute of Health Policy, Management & Evaluation, The Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada.
Haemophilia. 2021 Jul;27(4):666-673. doi: 10.1111/hae.14345. Epub 2021 May 20.
The primary objective of this study was to assess whether there are different patterns (classes) of joint health in young boys with severe haemophilia A (SHA) prescribed primary tailored prophylaxis. We also assessed whether age at first index joint bleed, blood group, FVIII gene abnormality variant, factor VIII trough level, first-year bleeding rate and adherence to the prescribed prophylaxis regimen significantly predicted joint damage trajectory, and thus class membership.
Using data collected prospectively as part of the Canadian Hemophilia Primary Prophylaxis Study (CHPS), we implemented a latent class growth mixture model technique to determine how many joint damage classes existed within the cohort. We used a multinomial logistic regression to predict the odds of class membership based on the above predictors. We fitted a survival model to assess whether there were differences in the rate of dose escalation across the groups.
We identified three distinct classes of trajectory: persistently low, moderately increasing and rapidly increasing joint scores. By multinomial regression, we found that only age at first index joint bleed predicted rapidly increasing joint scores. The rapidly increasing joint score class group moved through dose escalation significantly faster than the other two groups.
Using tailored prophylaxis, boys with SHA follow one of three joint health trajectories. By using knowledge of disease trajectories, clinicians may be able to adjust treatment according to a subject's predicted long-term joint health and institute cost-effective programmes of prophylaxis targeted at the individual subject level.
本研究的主要目的是评估接受初级个体化预防治疗的重度甲型血友病(SHA)男童是否存在不同的关节健康模式(类别)。我们还评估了首次关节内出血年龄、血型、FVIII 基因异常变异、VIII 因子低谷水平、首年出血率和对既定预防治疗方案的依从性是否显著预测关节损伤轨迹,从而预测类别归属。
本研究使用加拿大血友病初级预防研究(CHPS)前瞻性收集的数据,采用潜在类别增长混合模型技术来确定队列中存在多少种关节损伤类别。我们使用多项逻辑回归来预测上述预测因子基础上的类别归属概率。我们拟合了生存模型来评估不同组间剂量升级率是否存在差异。
我们确定了三种不同的轨迹类别:持续低、中度增加和快速增加的关节评分。通过多项回归,我们发现只有首次关节内出血年龄预测了快速增加的关节评分。快速增加关节评分类组的剂量升级速度明显快于其他两组。
使用个体化预防治疗,SHA 男童的关节健康状况遵循三种轨迹之一。通过了解疾病轨迹,临床医生可以根据患者的长期关节健康预测来调整治疗,并制定针对个体患者的具有成本效益的预防治疗方案。