Validating online approaches for rare disease research using latent class mixture modeling.
Validating online approaches for rare disease research using latent class mixture modeling.
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DOI：
10.1186/s13023-021-01827-z
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发表时间：
2021-05-10
影响因子：
3.7
通讯作者：
Lee CS
中科院分区：
文献类型：
--
作者：
Dwyer AA;Zeng Z;Lee CS
罕见病患者在地理上分散，给研究带来了挑战。一些研究人员与患者组织合作，使用基于网络的方法来克服地理招聘障碍。这种方法的批评者声称，样本是同质的，并不代表更广泛的病人群体，因为从病人组织招募的病人被认为有很高的需求。我们应用潜在类混合模型（LCMM）来定义基于潜在特征的患者群。我们使用了先前收集的先天性低促性腺激素性性腺功能减退症患者队列的数据，这些患者是与患者组织合作在线招募的。患者的人口统计学资料，临床信息，修订的疾病感知问卷（IPQ-R）评分和Zung抑郁自评量表（SDS）作为变量进行LCMM分析。具体来说，我们的目的是测试经典的批评，病人招募在线与病人组织合作是一个同质的群体，高需求。我们假设可以识别不同类别的患者（临床特征），从而证明在线招募的有效性并支持结果的可转移性。共纳入154例CHH患者。LCMM分析确定了三个不同的亚组（I类：n = 84 [54.5%]，II类：n = 41 [26.6%]，III类：n = 29 [18.8%]），在年龄、教育、疾病后果、情绪后果、疾病连贯性和抑郁症状（均P < 0.001）以及诊断时的年龄（P = 0.045）。课程描述了从严重到相对温和的心理社会影响的连续性。其他分析显示，晚期诊断（I类：19.2 ± 6.7年[95%CI 17.8-20.7]）与较差的心理适应和应对显著相关，如通过疾病后果、情绪反应、理解自己的疾病和SDS抑郁症状评估的（所有p < 0.001）。我们确定了三个不同类别的患者，他们是与患者组织合作在网上招募的。研究结果反驳了先前对罕见疾病研究中患者伙伴关系和基于网络的招募的批评。这是第一个经验数据表明，负面的心理社会后遗症，后来的诊断（“诊断奥德赛”）经常观察到的CHH。
Rare disease patients are geographically dispersed, posing challenges to research. Some researchers have partnered with patient organizations and used web-based approaches to overcome geographic recruitment barriers. Critics of such methods claim that samples are homogenous and do not represent the broader patient population—as patients recruited from patient organizations are thought to have high levels of needs. We applied latent class mixture modeling (LCMM) to define patient clusters based on underlying characteristics. We used previously collected data from a cohort of patients with congenital hypogonadotropic hypogonadism who were recruited online in collaboration with a patient organization. Patient demographics, clinical information, Revised Illness Perception Questionnaire (IPQ-R) scores and Zung self-rating depression Scale (SDS) were used as variables for LCMM analysis. Specifically, we aimed to test the classic critique that patients recruited online in collaboration with a patient organization are a homogenous group with high needs. We hypothesized that distinct classes (clinical profiles) of patients could be identified—thereby demonstrating the validity of online recruitment and supporting transferability of findings. In total, 154 patients with CHH were included. The LCMM analysis identified three distinct subgroups (Class I: n = 84 [54.5%], Class II: n = 41 [26.6%], Class III: n = 29 [18.8%]) that differed significantly in terms of age, education, disease consequences, emotional consequences, illness coherence and depression symptoms (all p < 0.001) as well as age at diagnosis (p = 0.045). Classes depict a continuum of psychosocial impact ranging from severe to relatively modest. Additional analyses revealed later diagnosis (Class I: 19.2 ± 6.7 years [95% CI 17.8–20.7]) is significantly associated with worse psychological adaptation and coping as assessed by disease consequences, emotional responses, making sense of one’s illness and SDS depressive symptoms (all p < 0.001). We identify three distinct classes of patients who were recruited online in collaboration with a patient organization. Findings refute prior critiques of patient partnership and web-based recruitment for rare disease research. This is the first empirical data suggesting negative psychosocial sequelae of later diagnosis (“diagnostic odyssey”) often observed in CHH.
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影响因子：
7.4
作者：
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通讯作者：
Gutmann, David H.