title: Is it possible to identify early predictors of the future cost of chronic arthritis? The VErA project.
abstract: This study was conducted to identify early predictors of the total cost of inflammatory arthritis (IA). One hundred and eighty patients affected by undifferentiated arthritis (UA) or rheumatoid arthritis (RA) were included in the French Very Early rheumatoid Arthritis (VErA) cohort between 1998 and 2001. Health economic data for 2003 were collected using a patient self-questionnaire. Results were analysed in terms of direct, indirect and total costs in 2003 euros (2003euro) for the population as a whole and in diagnostic subgroups. A payor perspective (the French National Health Insurance, in this case) was adopted. Multiple linear regression models were used to identify predictors of total cost from among the criteria assessed on recruitment. Results of the study showed that for the study population as a whole, the mean total cost was euro4700 per patient. The costs attributable to the RA and UA sub-groups were euro5928 and euro2424 per patient, respectively. In a univariate analysis, certain parameters were significantly correlated with a higher cost of illness. In the multivariate analysis, some of these parameters were further identified as being predictive of higher cost. Two strong significant, early predictors of total cost were identified: higher pain (P = 0.002) and the presence of rheumatoid factor (P = 0.004). In the RA sub-group, lower grip strength of the dominant hand (P = 0.039) was another predictor of the illness's subsequent economic impact. In conclusion, our data show that simple clinical and laboratory parameters can be used early in the course of IA to predict the condition's impact on healthcare budgets.
authors.affiliation: Departments of Rheumatology and Biochemistry, Amiens University Hospital, Amiens, France. flipon.elisabeth@wanadoo.fr
authors.forename: E
authors.initials: E
authors.lastname: Flipon
authors.forename: M
authors.initials: M
authors.lastname: Brazier
authors.forename: G
authors.initials: G
authors.lastname: Clavel
authors.forename: P
authors.initials: P
authors.lastname: Boumier
authors.forename: A
authors.initials: A
authors.lastname: Gayet
authors.forename: X
authors.initials: X
authors.lastname: Le Loët
authors.forename: P
authors.initials: P
authors.lastname: Fardellone
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001168:Arthritis / Q000191:economics* / Q000503:physiopathology; D001172:Arthritis, Rheumatoid / Q000191:economics* / Q000503:physiopathology; D015331:Cohort Studies; D017281:Cost of Illness; D005260:Female; D005544:Forecasting; D005602:France / Q000453:epidemiology; D017048:Health Care Costs / Q000639:trends*; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D010146:Pain / Q000453:epidemiology / Q000209:etiology; D011446:Prospective Studies; D012217:Rheumatoid Factor / Q000378:metabolism; D011795:Surveys and Questionnaires; D055815:Young Adult
chemical_list: D012217:Rheumatoid Factor