title: Using existing data to identify candidate items for a health state classification system in multiple sclerosis.
abstract: OBJECTIVE
  In multiple sclerosis (MS), the use of preference-based measures is limited to generic measures such as Health Utilities Index Mark 2 and 3, the EQ-5D and the SF-6D. However, the challenge of using such generic preference-based measures in people with MS is that they may not capture all domains of health relevant to the disease. Therefore, the main aim of this paper is to describe the development of a health state classification system for MS patients. The specific objectives are: (1) to identify items best reflecting the domains of quality of life important to people with MS and (2) to provide evidence for the discriminative capacity of the response options by cross-walking onto a visual analog scale of health rating.
  
  
  METHODS
  The data come from an epidemiologically sampled population of people with MS diagnosed post-1994. The dataset consisted of 206 items relating to impairments, activity limitations, participation restrictions, health perception and quality of life. Important domains were identified from the responses to the Patient Generated Index, an individualized measure of quality of life. The extent to which the items formed a uni-dimensional, linear construct was estimated using Rasch analysis, and the best item was selected using the threshold map.
  
  
  RESULTS
  The sample was young (mean age 43) and predominantly female (n = 140/189; 74%). The P-PBMSI classification system consisted of five items, with three response levels per item, producing a total of 243 possible health states. Regression coefficient values consistently decreased between response levels and the linear test for trend were statistically significant for all items. The linear test for trend indicated that for each item the response options provided the same discriminative ability within the magnitude of their capacity. A scoring algorithm was estimated using a simple additive formula. The classification system demonstrated convergent validity against other measures of similar constructs and known-groups validity between different clinical subgroups.
  
  
  CONCLUSIONS
  This study produced a health state classifier system based on items impacted upon by MS, and demonstrated the potential to discriminate the health impact of the disease.
authors: Faculty of Medicine, School of Physical and Occupational Therapy, McGill University, 3654 Prom Sir William Osler, Montreal, QC, H3G 1Y5, Canada, ayse.kuspinar@mail.mcgill.ca.
authors: Ayse
authors: A
authors: Kuspinar
authors: Lois
authors: L
authors: Finch
authors: Simon
authors: S
authors: Pickard
authors: Nancy E
authors: NE
authors: Mayo
mesh_terms: D000203:Activities of Daily Living / Q000145:classification / Q000523:psychology; D000328:Adult; D000465:Algorithms; D005260:Female; D006801:Humans; D064702:International Classification of Functioning, Disability and Health; D016014:Linear Models; D008297:Male; D009103:Multiple Sclerosis / Q000145:classification / Q000175:diagnosis / Q000523:psychology*; D010043:Outcome and Process Assessment, Health Care / Q000379:methods*; D017060:Patient Satisfaction; D011788:Quality of Life; D019057:Quality-Adjusted Life Years; D011792:Quebec; D015203:Reproducibility of Results; D012720:Severity of Illness Index; D018434:Sickness Impact Profile; D011795:Surveys and Questionnaires / Q000592:standards* / Q000706:statistics & numerical data; D064232:Visual Analog Scale