The objective of this study was to describe SymptoMScreen, an in-house developed tool for rapid assessment of MS symptom severity in routine clinical practice, and to validate SymptoMScreen against Performance Scales (PS). MS patients typically experience symptoms in many neurologic domains. A tool that would enable MS patients to efficiently relay their symptom severity across multiple domains to the healthcare providers could lead to improved symptom management. We developed "SymptoMScreen," a battery of 7-point Likert scales for 12 distinct domains commonly affected by MS: mobility, dexterity, body pain, sensation, bladder function, fatigue, vision, dizziness, cognition, depression, and anxiety. We administered SymptoMScreen and PS scales to consecutive MS patients at a specialty MS Care Center. We assessed the criterion and construct validity of SymptoMScreen by calculating Spearmen rank correlations between the SymptoMScreen composite score and PS composite score, and between SymptoMScreen subscale and the respective PS subscale scores, where applicable. A total of 410 patients with MS (age 46.6 ± 12.9 years; 74% female; mean disease duration 12.2 ± 8.7 years) completed the SymptoMScreen and PSs during their clinic visit. Composite SymptoMScreen score correlated strongly with combined PS score (r = 0.88, p < 0.0001). SymptoMScreen sub scores correlated strongly with the criterion measures of the respective PS (r = 0.69-0.87, p < 0.0001). Test-retest reliability of SymptoMScreen and its subscales was excellent (r = 0.71-0.94, p < .0001). SymptoMScreen is a single-page battery of Likert scales that assesses symptom impact in 12 domains commonly affected in MS. It has excellent criterion and construct validity. SymptoMScreen is patient and clinician friendly, takes approximately one minute to complete, and can help better document, understand, and manage patients' symptoms in routine clinical practice. SymptoMScreen is freely available to clinicians and researchers.
Keywords: Multiple Sclerosis; scale design; symptom validity testing.