title: Mapping the neck disability index to SF-6D in patients with chronic neck pain.
abstract: BACKGROUND
  This study sought to statistically map the neck disability index (NDI) to the six-dimension health state short form (SF-6D) to estimate algorithms for use in economic analyses in patients with chronic neck pain (CNP).
  
  
  METHODS
  The relationships between NDI and SF-6D scores were estimated by using data from a cohort of patients with chronic neck pain (n = 272). By using ordinary least squares (OLS), generalized linear modeling (GLM), censored least absolute deviations (CLAD) and Tobit regression, scores from all 10 items of the NDI instruments were univariately tested against SF-6D values and retained in a multivariate regression model, if statistically significant. The predictive ability of the model was assessed by mean absolute error (MAE), root mean square error (RMSE) and normalized RMSE.
  
  
  RESULTS
  The mean age of the 272 CNP patients was 39.9 ± 12.3 years; 57.8 % of the CNP patients were female. An OLS regression equation that included recreation item of NDI was optimal, with a MAE of 0.04and 0.04 and an RMSE of 0.06and 0.05in the derivation set and validation set, respectively. Predicted utilities accurately represented the observed ones.
  
  
  CONCLUSIONS
  We have provided algorithms for the estimation of health state utility values from the response of NDI. Future economic evaluations of the interventions for chronic neck pain could be informed by these algorithms.
authors.affiliation: Department of Pain Management, Huadong Hospital, Fudan University, Shanghai, China. zhengyongjun1971@126.com.
authors.forename: Yongjun
authors.initials: Y
authors.lastname: Zheng
authors.affiliation: Department of Anesthesiology, Tongren Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, 200336, China. 13651687299@126.com.
authors.forename: Kun
authors.initials: K
authors.lastname: Tang
authors.affiliation: Department of Pain Management, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, 200127, China. foxyele2000@yahoo.com.cn.
authors.forename: Le
authors.initials: L
authors.lastname: Ye
authors.affiliation: Department of Preventive Medicine, College of Medicine, Tongji University, Shanghai, 200092, China. 13774380743@126.com.
authors.forename: Zisheng
authors.initials: Z
authors.lastname: Ai
authors.affiliation: Clinical Outcomes and Economics Group, Department of pharmacy, Ren Ji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, 200127, China. rjwubin@126.com.
authors.forename: Bin
authors.initials: B
authors.lastname: Wu
mesh_terms: D000328:Adult; D000465:Algorithms; D002908:Chronic Disease / Q000523:psychology*; D015331:Cohort Studies; D004185:Disability Evaluation; D005260:Female; D006801:Humans; D016018:Least-Squares Analysis; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D019547:Neck Pain / Q000503:physiopathology* / Q000523:psychology*; D011788:Quality of Life; D011795:Surveys and Questionnaires