Davies Vinny, Reid Jacqueline, Scott E Marian
School of Computing Science, University of Glasgow, Glasgow, United Kingdom.
School of Veterinary Medicine, University of Glasgow, Glasgow, United Kingdom.
Front Vet Sci. 2021 Jan 6;7:601304. doi: 10.3389/fvets.2020.601304. eCollection 2020.
Using methodology previously described for the dog health-related quality of life (HRQL) tool (VetMetrica™), the aim was to optimize the scores profile of a comparable feline online HRQL instrument for monitoring HRQL in cats, to assist in its interpretation. Measuring HRQL helps quantify the impact of disease and its treatment on well-being, aids clinical decision making and provides information in clinical trials. In Study 1, using data collected from previous studies, scores generated for three domains of HRQL (Vitality, Comfort, Emotional Well-being) in healthy cats were normalized using standard statistical techniques of logit transformation and -scores, such that the average healthy cat has a score of 50 in all three HRQL domains. Using normalized scores from healthy and sick cats, a threshold score of 44.8 was determined, above which 70% of healthy cats should score. Study 2 determined the Minimal Important Difference (MID) in normalized score that constituted a clinically significant improvement in each domain. Three methods were tested in order to determine the MID, with the final choice made based on statistical and clinical considerations. Thresholds of 5, 7.5, and 5 were chosen for the three HRQL domains representing Vitality, Comfort and Emotional Well-being, respectively. This study makes available a means of displaying HRQL scores from an online application in an easily interpretable manner and quantifies a clinically meaningful improvement in score. To illustrate the practical application of these developments, three case examples are presented. Example 1 illustrates the raw and normalized scores for a group of overweight cats enrolled in a Feline Weight Management Programme. Example 2 shows three groups of osteoarthritic cats, each with different severity of disease. The third is an elderly, un-well cat whose HRQL was recorded over time, specifically to facilitate end of life discussion between owner and veterinary clinician.
使用先前描述的用于犬健康相关生活质量（HRQL）工具（VetMetrica™）的方法，目的是优化一种可比的猫在线HRQL工具的评分概况，以监测猫的HRQL，辅助其解读。测量HRQL有助于量化疾病及其治疗对健康的影响，有助于临床决策，并在临床试验中提供信息。在研究1中，利用从先前研究收集的数据，采用logit变换和z分数的标准统计技术对健康猫的HRQL三个领域（活力、舒适度、情绪健康）产生的分数进行标准化，使平均健康猫在所有三个HRQL领域的分数为50。利用健康和患病猫的标准化分数，确定了阈值分数44.8，高于该分数，70%的健康猫应得分。研究2确定了构成每个领域临床上显著改善的标准化分数的最小重要差异（MID）。测试了三种方法以确定MID，并根据统计和临床考虑做出最终选择。分别为代表活力、舒适度和情绪健康的三个HRQL领域选择了5、7.5和5的阈值。本研究提供了一种以易于解释的方式显示来自在线应用程序的HRQL分数的方法，并量化了分数在临床上有意义的改善。为了说明这些进展的实际应用，给出了三个案例示例。示例1说明了参加猫体重管理计划的一组超重猫的原始分数和标准化分数。示例2展示了三组骨关节炎猫，每组疾病严重程度不同。第三个是一只老年病猫，其HRQL随时间记录，特别是为了便于主人和兽医临床医生之间进行临终讨论。
