Objective : To compare the efficacy between SKI306X and Diclofenac by using generalized estimating equations (GEE) methodology in the analysis of correlated bivariate binary outcome data in Osteoarthritis (OA) diseases. Methods : A randomized, double-blind, active comparator-controlled, non-inferior...
Objective : To compare the efficacy between SKI306X and Diclofenac by using generalized estimating equations (GEE) methodology in the analysis of correlated bivariate binary outcome data in Osteoarthritis (OA) diseases. Methods : A randomized, double-blind, active comparator-controlled, non-inferiority clinical trial was conducted at 5 institutions in Korea with the random assignment of 248 patients aged 35 to 75 years old with OA of the knee and clinical evidence of OA. Patients were enrolled in this study if they had at least moderate pain in the affected knee joint and a score larger than 35mm as assessed by VAS (Visual Analog Scale). The main exposure variable was treatment (SKI 306X vs. Diclofenac) and other covariates were age, sex, BMI, baseline VAS, center, operation history (Yes/No), NSAIDS (Y/N), acupuncture (Y/N), herbal medicine (Y/N), past history of musculoskeletal disease (Y/N), and previous therapy related with OA (Y/N). The main study outcome was the change of VAS pain scores from baseline to the 2nd and 4th weeks after treatment. Pain scores were obtained as baseline, 2nd and 4th weeks after treatment. We applied GEE approach with empirical covariance matrix and independent(or exchangeable) working correlation matrix to evaluate the relation of several risk factors to the change of VAS pain scores with correlated binary bivariate outcomes. Results : While baseline VAS, age, and acupuncture variables had protective effects for reducing the OA pain, its treatment (Joins/Diclofenac) was not statistically significant through GEE methodology (ITT:aOR=1.37, 95% CI=(0.8200, 2.26), PP:aOR=1.47, 95% CI=(0.73, 2.95)). The goodness-of-fit statistic for GEE (6.55, p=0.68) was computed to assess the adequacy of the fitted final model. Conclusions : Both ANCOVA and GEE methods yielded non statistical significance in the evaluation of non-inferiority of the efficacy between SKI306X and Diclofenac. While VAS outcome for each visit was applied in GEE, only VAS outcome for the fourth visit was applied in ANCOVA. So the GEE methodology is more accurate for the analysis of correlated outcomes.
Objective : To compare the efficacy between SKI306X and Diclofenac by using generalized estimating equations (GEE) methodology in the analysis of correlated bivariate binary outcome data in Osteoarthritis (OA) diseases. Methods : A randomized, double-blind, active comparator-controlled, non-inferiority clinical trial was conducted at 5 institutions in Korea with the random assignment of 248 patients aged 35 to 75 years old with OA of the knee and clinical evidence of OA. Patients were enrolled in this study if they had at least moderate pain in the affected knee joint and a score larger than 35mm as assessed by VAS (Visual Analog Scale). The main exposure variable was treatment (SKI 306X vs. Diclofenac) and other covariates were age, sex, BMI, baseline VAS, center, operation history (Yes/No), NSAIDS (Y/N), acupuncture (Y/N), herbal medicine (Y/N), past history of musculoskeletal disease (Y/N), and previous therapy related with OA (Y/N). The main study outcome was the change of VAS pain scores from baseline to the 2nd and 4th weeks after treatment. Pain scores were obtained as baseline, 2nd and 4th weeks after treatment. We applied GEE approach with empirical covariance matrix and independent(or exchangeable) working correlation matrix to evaluate the relation of several risk factors to the change of VAS pain scores with correlated binary bivariate outcomes. Results : While baseline VAS, age, and acupuncture variables had protective effects for reducing the OA pain, its treatment (Joins/Diclofenac) was not statistically significant through GEE methodology (ITT:aOR=1.37, 95% CI=(0.8200, 2.26), PP:aOR=1.47, 95% CI=(0.73, 2.95)). The goodness-of-fit statistic for GEE (6.55, p=0.68) was computed to assess the adequacy of the fitted final model. Conclusions : Both ANCOVA and GEE methods yielded non statistical significance in the evaluation of non-inferiority of the efficacy between SKI306X and Diclofenac. While VAS outcome for each visit was applied in GEE, only VAS outcome for the fourth visit was applied in ANCOVA. So the GEE methodology is more accurate for the analysis of correlated outcomes.
Shin DY, Park TS, A Study on the Use of Working Correlation Matrices in the GEE Approach to the Analysis of Repeated Binary Data, Appl Statistic 1996; M: 15-27 (Korean)
Heimendinger J, Feng Z, Emmons K, Stoddard A, Kinne S, Biener L, Sorensen G, Abrams D, Varnes J, Boutwell B. The working well trial: baseline dietary and smoking behaviors of employees and related worksite characteristics. The working well research group, Prev Med 1995;24: 180-193
aston JF, Gustafasson M, Rheumatoid arthritis: determination of pain characteristics and comparison of RAJ and VAS in its measurement. Pain 1990; 41: 35-40
Jung YB, Seong SC, Lee MC et al. A four-week, randomized, double-blind trial of the efficacy and safety of SKI306X, a herbal anti-arthritic agent versus diclofenac in osteoarhritis of the knee. Clinical Trial Report of SK Pharm 2000; M-74I(Korean)
Bendel RB, Afifi AA. Comparison of stopping rules in forward regression. JASA 1977; 72: 4653
Mickey J, Greenland S. A study of the impact of confounder-selection criteria on effect estimation. Am J Epidemiol 1989; 129: 125-137
Horton NJ, Bebchuk JD, Jones CL et al. Goodness-of-fit for GEE: An example with mental health service utilization. Statist Med 1999; 18: 213-222
SAS/STAT User' s Guide, Versoion 8, Cary, NC, USA: SAS Instiute lnc.; 1999
Zhang Y, Glynn RJ, Fekson DT. Misculoskeletal disease research: should we analyze the joint or the person? J Rheumatol 1996; 23: 1130-1134
Koo HW, Kwark M, Lee Y, Park BJ. Comparison of Efficiency between Individual Randomization and Ouster Randomization in the Field Trial. Korean J Prev Med 2000; 33(1):51-55
※ AI-Helper는 부적절한 답변을 할 수 있습니다.