title: Tackling missing radiographic progression data: multiple imputation technique compared with inverse probability weights and complete case analysis.
abstract: OBJECTIVE
  To describe the results of different statistical ways of addressing radiographic outcome affected by missing data--multiple imputation technique, inverse probability weights and complete case analysis--using data from an observational study.
  
  
  METHODS
  A random sample of 96 RA patients was selected for a follow-up study in which radiographs of hands and feet were scored. Radiographic progression was tested by comparing the change in the total Sharp-van der Heijde radiographic score (TSS) and the joint erosion score (JES) from baseline to the end of the second year of follow-up. MI technique, inverse probability weights in weighted estimating equation (WEE) and CC analysis were used to fit a negative binomial regression.
  
  
  RESULTS
  Major predictors of radiographic progression were JES and joint space narrowing (JSN) at baseline, together with baseline disease activity measured by DAS28 for TSS and MTX use for JES. Results from CC analysis show larger coefficients and s.e.s compared with MI and weighted techniques. The results from the WEE model were quite in line with those of MI.
  
  
  CONCLUSIONS
  If it seems plausible that CC or MI analysis may be valid, then MI should be preferred because of its greater efficiency. CC analysis resulted in inefficient estimates or, translated into non-statistical terminology, could guide us into inaccurate results and unwise conclusions. The methods discussed here will contribute to the use of alternative approaches for tackling missing data in observational studies.
authors.affiliation: Research Unit, Sociedad Española de Reumatología, Madrid, Spain.
authors.forename: Miguel Á
authors.initials: MÁ
authors.lastname: Descalzo
authors.forename: Virginia Villaverde
authors.initials: VV
authors.lastname: Garcia
authors.forename: Isidoro
authors.initials: I
authors.lastname: González-Alvaro
authors.forename: Jordi
authors.initials: J
authors.lastname: Carbonell
authors.forename: Alejandro
authors.initials: A
authors.lastname: Balsa
authors.forename: Raimon
authors.initials: R
authors.lastname: Sanmartí
authors.forename: Pilar
authors.initials: P
authors.lastname: Lisbona
authors.forename: Valentín
authors.initials: V
authors.lastname: Hernandez-Barrera
authors.forename: Rodrigo
authors.initials: R
authors.lastname: Jiménez-Garcia
authors.forename: Loreto
authors.initials: L
authors.lastname: Carmona
mesh_terms: D000328:Adult; D000368:Aged; D001172:Arthritis, Rheumatoid / Q000000981:diagnostic imaging*; D001175:Arthrography / Q000592:standards / Q000706:statistics & numerical data*; D015331:Cohort Studies; D003627:Data Interpretation, Statistical; D018450:Disease Progression; D005260:Female; D005500:Follow-Up Studies; D005528:Foot / Q000000981:diagnostic imaging; D006225:Hand / Q000000981:diagnostic imaging; D006801:Humans; D008297:Male; D008875:Middle Aged; D012042:Registries; D012720:Severity of Illness Index