terminal events
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2021 ◽  
Author(s):  
Song Yang ◽  
James Troendle ◽  
Daewoo Pak ◽  
Eric Leifer
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Author(s):  
Julie K. Furberg ◽  
Per K. Andersen ◽  
Sofie Korn ◽  
Morten Overgaard ◽  
Henrik Ravn

2021 ◽  
pp. 5-6
Author(s):  
Bilal Ahmad Rather ◽  
Zubair Ahmad Khuja ◽  
Tariq A Mir

Aims And Objectives:This retrospective study was conducted in SKIMS Soura Srinagar to study co morbidities associated with SLE as well as to analyse pattern of mortality of SLE patients. Methods:We analyzed the data of one decade from Jan 2004 to Dec 2014 for total deaths which occurred in SKIMS soura Srinagar during this period. Files of 133 patients on whom Rheumatic disease was mentioned were separately fully analyzed for patient's age, sex, type of rheumatic disease, any other underlying disease and terminal events which lead to death of patient. Particular attention was paid to data of SLE patients. Observations:There were 41 SLE patients with a male female ratio of 1: 12.6. Mean age at death was 32.46±13.739 years (range 15 – 68). Most of the patients 34 (82.9%) were in the age group of 20-59 years. The main associated co morbidities were HTN in 23 (56.1%), CRF in 20 (48.8%) patients. The common causes of death were sepsis in 12 (29.3%), ARF in 11 (26.8%) , heart failure in 9 (22.0%). Conclusion:We found that Rheumatic disease patients particularly SLE have premature mortality compared to the non Rheumatic patients and sepsis being the leading cause of death in SLE patients. Mortally of SLE is bimodal with an early mortality due to disease ares and a late mortality due to disease plus other associated co-morbidities like DM, HTN, Malignancy and cardiovascular conditions.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Anja Rappl ◽  
Andreas Mayr ◽  
Elisabeth Waldmann

Abstract The development of physical functioning after a caesura in an aged population is still widely unexplored. Analysis of this topic would need to model the longitudinal trajectories of physical functioning and simultaneously take terminal events (deaths) into account. Separate analysis of both results in biased estimates, since it neglects the inherent connection between the two outcomes. Thus, this type of data generating process is best modelled jointly. To facilitate this several software applications were made available. They differ in model formulation, estimation technique (likelihood-based, Bayesian inference, statistical boosting) and a comparison of the different approaches is necessary to identify their capabilities and limitations. Therefore, we compared the performance of the packages JM, joineRML, JMbayes and JMboost of the R software environment with respect to estimation accuracy, variable selection properties and prediction precision. With these findings we then illustrate the topic of physical functioning after a caesura with data from the German ageing survey (DEAS). The results suggest that in smaller data sets and theory driven modelling likelihood-based methods (expectation maximation, JM, joineRML) or Bayesian inference (JMbayes) are preferable, whereas statistical boosting (JMboost) is a better choice with high-dimensional data and data exploration settings.


2020 ◽  
pp. 174077452097240
Author(s):  
Song Yang ◽  
James Troendle

Background/aims In clinical trials, the primary outcome is often a composite endpoint defined as time to the first occurrence of either death or certain non-fatal events. Thus, a portion of available data would be omitted. In the win ratio approach, priorities are given to the clinically more important events, and more data are used. However, its power may be low if the treatment effect is predominantly on the non-terminal event. Methods We propose event-specific win ratios obtained separately on the terminal and non-terminal events. They can then be used to form global tests such as a linear combination test, the maximum test, or a [Formula: see text] test. Results In simulations, these tests often improve the power of the original win ratio test. Furthermore, when the terminal and non-terminal events experience differential treatment effects, the new tests are often more powerful than the log-rank test for the composite outcome. Whether the treatment effect is primarily on the terminal events or not, the new tests based on the event-specific win ratios can be useful when different types of events are present. The new tests can reject the null hypothesis of no difference in the event distributions in the two treatment arms with the terminal event showing detrimental effect and the non-terminal event showing beneficial effect. The maximum test and the [Formula: see text] test do not have test-estimation coherency, but the maximum test has the coherency that the global null is rejected if and only if the null for one of the event types is rejected. When applied to data from the trial Aldosterone Antagonist Therapy for Adults With Heart Failure and Preserved Systolic Function (TOPCAT), the new tests all reject the null hypothesis of no treatment effect while both the log-rank test used in TOPCAT and the original win ratio approach show non-significant p-values. Conclusion Whether the treatment effect is primarily on the terminal events or the non-terminal events, the maximum test based on the event-specific win ratios can be a useful alternative for testing treatment effect in clinical trials with time-to-event outcomes when different types of events are present.


Biometrics ◽  
2020 ◽  
Vol 76 (4) ◽  
pp. 1330-1339
Author(s):  
Dongxiao Han ◽  
Xiaogang Su ◽  
Liuquan Sun ◽  
Zhou Zhang ◽  
Lei Liu

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