Tolley Chloe, Piani-Meier Daniela, Bentley Sarah, Bennett Bryan, Jones Eddie, Pike James, Dahlke Frank, Tomic Davorka, Ziemssen Tjalf
Adelphi Values Ltd, Macclesfield, United Kingdom.
Novartis Pharma AG, Basel, Switzerland.
JMIR Med Inform. 2020 Apr 14;8(4):e17592. doi: 10.2196/17592.
There is an unmet need for a tool that helps to evaluate patients who are at risk of progressing from relapsing-remitting multiple sclerosis to secondary progressive multiple sclerosis (SPMS). A new tool supporting the evaluation of early signs suggestive of progression in multiple sclerosis (MS) has been developed. In the initial stage, concepts relevant to progression were identified using a mixed method approach involving regression on data from a real-world observational study and qualitative research with patients and physicians. The tool was drafted in a questionnaire format to assess these variables.
This study aimed to develop the scoring algorithm for the tool, using both quantitative and qualitative research methods.
The draft scoring algorithm was developed using two approaches: quantitative analysis of real-world data and qualitative analysis based on physician interviews and ranking and weighting exercises. Variables that were included in the draft tool and regarded as most clinically relevant were selected for inclusion in a multiple logistic regression. The analyses were run using physician-reported data and patient-reported data. Subsequently, a ranking and weighting exercise was conducted with 8 experienced neurologists as part of semistructured interviews. Physicians were presented with the variables included in the draft tool and were asked to rank them in order of strength of contribution to progression and assign a weight by providing a percentage of the overall contribution. Physicians were also asked to explain their ranking and weighting choices. Concordance between physicians was explored.
Multiple logistic regression identified age, MS disease activity, and Expanded Disability Status Scale score as the most significant physician-reported predictors of progression to SPMS. Patient age, mobility, and self-care were identified as the strongest patient-reported predictors of progression to SPMS. In physician interviews, the variables ranked and weighted as most important were stability or worsening of symptoms, intermittent or persistent symptoms, and presence of ambulatory and cognitive symptoms. Across all physicians, the level of concordance was 0.278 (P<.001), indicating a low to moderate, but statistically significant, level of agreement. Variables were categorized as high (n=8), moderate (n=8), or low (n=10) importance based on the findings from the different approaches described above. Accordingly, the respective questions in the tool were assigned a weight of "three," "two," or "one" to inform the draft scoring algorithm.
This study further confirms the need for a tool to provide a consistent, comprehensive approach across physicians to support the early evaluation of signs indicative of progression to SPMS. The novel and comprehensive approach to develop the draft scoring algorithm triangulates data obtained from ranking and weighting exercises, qualitative interviews, and a real-world observational study. Variables that go beyond the clinically most obvious impairment in lower limbs have been identified as relevant subtle/sensitive signs suggestive of progressive disease.
对于一种有助于评估有从复发缓解型多发性硬化症进展为继发进展型多发性硬化症(SPMS)风险的患者的工具,仍存在未满足的需求。已开发出一种支持评估多发性硬化症(MS)进展早期迹象的新工具。在初始阶段,采用混合方法确定与进展相关的概念,该方法包括对来自真实世界观察性研究的数据进行回归分析以及对患者和医生进行定性研究。该工具以问卷形式起草,用于评估这些变量。
本研究旨在使用定量和定性研究方法为该工具开发评分算法。
评分算法草案通过两种方法制定:对真实世界数据进行定量分析以及基于医生访谈、排序和加权练习进行定性分析。从草案工具中选取被认为在临床上最相关的变量纳入多元逻辑回归。分析使用医生报告的数据和患者报告的数据。随后,作为半结构化访谈的一部分,对8位经验丰富的神经科医生进行了排序和加权练习。向医生展示草案工具中包含的变量,并要求他们按照对进展的贡献强度进行排序,并通过提供总体贡献的百分比来分配权重。还要求医生解释他们的排序和加权选择。探讨了医生之间的一致性。
多元逻辑回归确定年龄、MS疾病活动度和扩展残疾状态量表评分是医生报告的进展为SPMS的最显著预测因素。患者年龄、活动能力和自我护理被确定为患者报告的进展为SPMS的最强预测因素。在医生访谈中,被排序和加权为最重要的变量是症状的稳定性或恶化、间歇性或持续性症状以及存在行走和认知症状。在所有医生中,一致性水平为0.278(P<0.001),表明一致性水平低至中等,但具有统计学意义。根据上述不同方法的结果,将变量分为高(n = 8)、中(n = 8)或低(n = 10)重要性。因此,工具中的各个问题被赋予“三”“二”或“一”的权重,以告知评分算法草案。
本研究进一步证实需要一种工具,为医生提供一种一致、全面的方法,以支持对进展为SPMS迹象的早期评估。开发评分算法草案的新颖且全面的方法对从排序和加权练习、定性访谈以及真实世界观察性研究中获得的数据进行了三角测量。已确定超出下肢临床上最明显损伤的变量为提示疾病进展的相关细微/敏感迹象。