The meta-analysis of rare binary data is a difficulty in the field of medical research, and its methodology remains immature. The traditional meta-analysis technique is based on the normal-normal model of fixed effects analysis or random-effects analysis, however there are methodological problems in this method. Stijnen proposed an exact within-study likelihood models (EWLM) meta-analysis technique based on the generalized linear mixed model (GLMM), including the binomial-normal model (BN) and Hypergeometric-normal model (HNM), which can be used to achieve random effects meta-analysis of rare binary data. This paper introduces the model in detail and its implementation in SAS software with examples to provide relevant SAS code.
ObjectiveTo introduce a meta-analysis of linear or nonlinear multilevel models using SAS MIXED and SAS NLMIXED.MethodsA systematic review performed to evaluate the risk of local recurrence in patients with cervical cancer treated with radical chemoradiotherapy and adjuvant surgery published by Shim et al. was selected as an illustration. An SAS software was used to implement meta-analysis based on linear or nonlinear multi-level models, and programming codes were provided.ResultsIn the absence of covariates, the OR combined effect values of PROC MIXED based on the bivariate random effects model and PROC NLMIXED of the nonlinear mixed effects model were 0.63 (95%CI 0.46 to 0.87, P=0.005 7) and 0.60 (95%CI 0.39 to 0.81, P=0.000 3), respectively. In the case of covariates, the bivariate random effects model and the nonlinear mixed effects model provided an effect value of OR=0.65 (95%CI 0.47 to 0.91, P=0.011) and 0.59 (95%CI 0.38 to 0.80, P=0.000 3). Covariate OR effect values were 2.70 (95%CI 0.16 to 45.23, P>0.05) and 1.86 (95%CI −0.07 to 3.79, P=0.06).ConclusionsThe meta-analysis results of the SAS NLMIXED nonlinear mixed-effects model are similar to those of the SAS MIXED linear mixed-effects model. PROC NLMIXED has powerful programming capability and nonlinear mixed-effects model has flexible modeling capabilities for sparse data. Therefore, PROC NLMIXED will play an increasingly important role in meta-analysis.
Longitudinal data had intrinsic correlation problems at different time points, and traditional meta-analysis techniques cannot resolve this problem. Regression coefficients based on multi-level models can fully consider the correlations of longitudinal data at various time points. This paper uses SAS software to perform multi-level regression coefficient model meta-analysis and provides programming code which is simple and easy to operate.
Despite the rapid development of meta-analysis technology, there were currently no consolidation technology for longitudinal data. The meta-analysis model based on the generalized linear mixed-effects model can fully encapsulate the correlation between various time points and accurately estimate the final combined effect, which is an ideal model for longitudinal-data meta-analysis. Through example data, this paper used SAS software to realize longitudinal-data meta-analysis and provided programming codes.
ObjectivesTo compare the efficacy and safety of weekly nedaplatin compared with weekly cisplatin as postoperative concurrent chemoradiotherapy scheme for cervical cancer patients.MethodsThis trial was performed in the Department of Radiation Oncology in the Second Affiliated Hospital of Fujian Medical University from June 2016 to January 2017. A total of 200 patients with stage ⅠB1-ⅡB cervical cancer were randomly assigned to the nedaplatin group and the cisplatin group after signing informed content. The dose of nedaplatin or cisplatin ranged 35 to 40 mg/m2, once a week for 5 weeks. Intensity-modulated radiation therapy or three-dimensional conformal radiation therapy were used for patients. The progression-free survival, overall survival and adverse reactions were compared between two groups. Statistical analysis was performed by SPSS 24.0 software.ResultsA total of 105 patients were enrolled in the nedaplatin group, and 95 patients were in cisplatin group. The three-year progression-free survival rate was 80.5% vs. 79.5% in the nedaplatin group and the cisplatin group, respectively; and no statistical significant difference was found (χ2=0.198, P=0.656) between two groups. The 3-year overall survival rates were 72.5% and 69.9% for the nedaplatin group and the cisplatin group, respectively, and there was no significant difference between the two groups (χ2=0.261, P=0.609). The incidence of grade 3/4 nausea and vomiting in the nedaplatin group was 6.67%, which was significantly lower than that of 15.79% in the cisplatin group, and statistical significant difference was found (χ2=2.555, P=0.011); however, the incidence of grade 3/4 thrombocytopenia in the nedaplatin group was 9.52%, which was significantly higher than that in the cisplatin group (3.15%); and the difference was statistically significant (χ2=1.985, P=0.047). There was no difference in the incidence of adverse reactions such as anemia, neutropenia, and radiological proctitis in both groups.ConclusionsNedaplatin-based concurrent chemoradiotherapy has similar efficacy compared to cisplatin-based concurrent chemoradiotherapy, and it could significantly reduce the digestive tract reaction, which can be used as an alternative to cisplatin.