scholarly journals A discrete-time survival model with random effects for designing and analyzing repeated low-dose challenge experiments

Biostatistics ◽  
2014 ◽  
Vol 16 (2) ◽  
pp. 295-310 ◽  
Author(s):  
C. Kang ◽  
Y. Huang ◽  
C. J. Miller
Rheumatology ◽  
2020 ◽  
Vol 59 (8) ◽  
pp. 1826-1833
Author(s):  
Xinyi Jia ◽  
Xiao Du ◽  
Shuxian Bie ◽  
Xiaobing Li ◽  
Yunguang Bao ◽  
...  

Abstract Objective The use of IVIG plus high- or low-dose aspirin for the initial treatment of Kawasaki disease remains controversial. The aim of this study was to evaluate the efficacy of IVIG plus high-dose aspirin compared with IVIG plus low-dose aspirin in the treatment of Kawasaki disease. Methods Studies related to aspirin therapy for Kawasaki disease were selected by searching the databases of Medline (PubMed), Embase and the Cochrane Library before March 2019. Statistical analyses were performed by using a Review Manager Software package and STATA v.15.1. Results Eight retrospective cohort studies, characterizing 12 176 patients, were analysed. Overall, no significant difference was found in the incidence of coronary artery abnormalities between the high- and low-dose aspirin groups [relative risk (RR) 1.15; 95% CI: 0.93, 1.43; P = 0.19; random-effects model]. The patients treated with high-dose aspirin had slightly faster resolution of fever [mean difference (MD) −0.30; 95% CI: −0.58, −0.02; P = 0.04; random-effects model]. but the rates of IVIG resistance (RR, 1.26; 95% CI: 0.55, 2.92; P = 0.59; random-effects model) and days in hospital (MD, 0.22; 95% CI: −0.93, 1.37; P = 0.71; random-effects model) were similar between the two groups. Conclusion Low-dose aspirin plus IVIG might be as effective as high-dose aspirin plus IVIG for the initial treatment of Kawasaki disease. Considering that high-dose aspirin may cause more adverse reactions than low-dose aspirin, low-dose aspirin plus IVIG should be recommended as the first-line therapy in the initial treatment of Kawasaki disease.


Methodology ◽  
2018 ◽  
Vol 14 (2) ◽  
pp. 45-55 ◽  
Author(s):  
Mirjam Moerbeek ◽  
Lieke Hesen

Abstract. In a discrete-time survival model the occurrence of some event is measured by the end of each time interval. In practice it is not always possible to measure all subjects at the same point in time. In this study the consequences of varying measurement occasions are investigated by means of a simulation study and the analysis of data from an empirical study. The results of the simulation study suggest that the effects of varying measurement occasions are negligible, at least for the scenarios that were covered in the simulation. The empirical example shows varying measurement occasions have minor effects on parameter estimates, standard errors, and significance levels.


Sign in / Sign up

Export Citation Format

Share Document