scholarly journals Joint modelling of longitudinal and time-to-event data with application to predicting abdominal aortic aneurysm growth and rupture

2011 ◽  
Vol 53 (5) ◽  
pp. 750-763 ◽  
Author(s):  
Michael J. Sweeting ◽  
Simon G. Thompson
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Event Data ◽  
Time To Event ◽  
Joint Modelling ◽  
Time To Event Data ◽  
Abdominal Aortic ◽  
Aneurysm Growth

scholarly journals Complement Factor C5a Is Increased in Blood of Patients with Abdominal Aortic Aneurysm and Has Prognostic Potential for Aneurysm Growth

2020 ◽  
Author(s):  
Branislav Zagrapan ◽  
Wolf Eilenberg ◽  
Andreas Scheuba ◽  
Johannes Klopf ◽  
Annika Brandau ◽  
...  
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Leukotriene B4 ◽  
Complement Factor ◽  
Diagnosis And Prognosis ◽  
Abdominal Aortic ◽  
Aneurysm Growth ◽  
Log Linear

AbstractIn this observational case-control study, circulating levels of complement factors C3a and C5a and leukotriene B4 (LTB4) were analysed in abdominal aortic aneurysm (AAA) patients regarding their association with diagnosis and prognosis. Serum C5a was significantly raised in AAA patients compared to healthy controls—median 84.5 ng/ml (IQR = 37.5 ng/ml) vs. 67.7 ng/ml (IQR = 26.2 ng/ml), p = 0.007—but was not elevated in patients with athero-occlusive disease. Serum C5a levels correlated significantly with the increase in maximum AAA diameter over the following 6 months (r = 0.319, p = 0.021). The median growth in the lowest quartile of C5a (< 70 ng/ml) was 50% less compared to the highest C5a quartile (> 101 ng/ml): 1.0 mm/6 months (IQR = 0.8 mm) vs. 2.0 mm/6 months (IQR = 1.5 mm), p = 0.014. A log-linear mixed model predicted AAA expansion based on current diameter and C5a level. To our knowledge, this is the first study linking complement activation, in particular C5a serum level, with AAA progression. Graphical Abstract

Abstract 297: Segmental Aortic Stiffening is a Mechanism Driving Early Abdominal Aortic Aneurysm Pathogenesis

2014 ◽  
Vol 34 (suppl_1) ◽  
Author(s):  
Uwe Raaz ◽  
Alexander M Zöllner ◽  
Ryuji Toh ◽  
Futoshi Nakagami ◽  
Isabel N Schellinger ◽  
...  
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Aortic Wall ◽  
Ex Vivo ◽  
Wall Stress ◽  
Finite Elements Analysis ◽  
External Application ◽  
Abdominal Aortic ◽  
Aneurysm Growth ◽  
Aortic Stiffening

Stiffening of the aortic wall is a phenomenon consistently observed in abdominal aortic aneurysm (AAA). However, its role in AAA pathophysiology is largely undefined. Using an established murine elastase-induced AAA model, we demonstrate that segmental aortic stiffening (SAS) precedes aneurysm growth. Finite elements analysis (FEA)-based wall stress calculations reveal that early stiffening of the aneurysm-prone aortic segment leads to axial (longitudinal) stress generated by cyclic (systolic) tethering of adjacent, more compliant wall segments. Interventional stiffening of AAA-adjacent segments (via external application of surgical adhesive) significantly reduces aneurysm growth. These changes correlate with reduced segmental stiffness of the AAA-prone aorta (due to equalized stiffness in adjacent aortic segments), reduced axial wall stress, decreased production of reactive oxygen species (ROS), attenuated elastin breakdown, and decreased expression of inflammatory cytokines and macrophage infiltration, as well as attenuated apoptosis within the aortic wall. Cyclic pressurization of stiffened aortic segments ex vivo increases the expression of genes related to inflammation and extracellular matrix (ECM) remodeling. Finally, human ultrasound studies reveal that aging, a significant AAA risk factor, is accompanied by segmental infrarenal aortic stiffening. The present study introduces the novel concept of segmental aortic stiffening (SAS) as an early pathomechanism generating aortic wall stress and thereby triggering AAA growth. Therefore monitoring SAS by ultrasound might help to better identify patients at risk for AAA disease and better predict the susceptibility of small AAA to further growth. Moreover our results suggest that interventional mechanical stiffening of the AAA-adjacent aorta may be further tested as a novel treatment option to limit early AAA growth.

scholarly journals Metformin Prescription Associated with Reduced Abdominal Aortic Aneurysm Growth Rate and Reduced Chemokine Expression in a Swedish Cohort

2021 ◽  
Vol 70 ◽  
pp. 425-433 ◽  
Author(s):  
Jon Unosson ◽  
Dick Wågsäter ◽  
Niclas Bjarnegård ◽  
Rachel De Basso ◽  
Martin Welander ◽  
...  
Keyword(s):  
Growth Rate ◽  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Chemokine Expression ◽  
Abdominal Aortic ◽  
Aneurysm Growth ◽  
Swedish Cohort

scholarly journals Joint modelling of longitudinal and time-to-event data: An illustration using CD4 count and mortality in a cohort of patients initiated on antiretroviral therapy

2020 ◽  
Author(s):  
Nobuhle Nokubonga Mchunu ◽  
Henry Mwambi ◽  
Tarylee Reddy ◽  
Nonhlanhla Yende-Zuma ◽  
Kogieleum Naidoo
Keyword(s):  
Cox Model ◽  
Joint Model ◽  
Cd4 Count ◽  
Time Varying ◽  
Event Data ◽  
Time To Event ◽  
Joint Modelling ◽  
Risk Of Death ◽  
Time To Event Data ◽  
Over Time

Abstract Background: Modelling of longitudinal biomarkers and time-to-event data are important to monitor disease progression. However, these two variables are traditionally analyzed separately or time-varying Cox models are used. The former strategy fails to recognize the shared random-effects from the two processes while the latter assumes that longitudinal biomarkers are exogenous covariates, resulting in inefficient or biased estimates for the time-to-event model. Therefore, we used joint modelling for longitudinal and time-to-event data to assess the effect of longitudinal CD4 count on mortality. Methods: We studied 4014 patients from the Centre for the AIDS Programme of Research in South Africa (CAPRISA) who initiated ART between June 2004 and August 2013. We used proportional hazards regression model to assess the effect of baseline characteristics (excluding CD4 count) on mortality, and linear mixed effect models to evaluate the effect of baseline characteristics on the CD4 count evolution over time. Thereafter, the two analytical approaches were amalgamated to form an advanced joint model for studying the effect of longitudinal CD4 count on mortality. To illustrate the virtues of the joint model, the results from the joint model were compared to those from the time-varying Cox model. Results: Using joint modelling, we found that lower CD4 count over time was associated with a 1.3-fold increase in the risk of death, (HR: 1.34, 95% CI: 1.27-1.42). Whereas, results from the time-varying Cox model showed lower CD4 count over time was associated with a 1.2-fold increase in the risk of death, (HR: 1.17, 95% CI: 1.12-1.23). Conclusions: Joint modelling enabled the assessment of the effect of longitudinal CD4 count on mortality while correcting for shared random effects between longitudinal and time-to-event models. In the era of universal test and treat, the evaluation of CD4 count is still crucial for guiding the initiation and discontinuation of opportunistic infections prophylaxis and assessment of late presenting patients. CD4 count can also be used when immunological failure is suspected as we have shown that it is associated with mortality. Keywords: Time-to-event data; longitudinal data; joint models; CD4 count; mortality; bias

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