Marc A Bailey1, Paul D Baxter2, Tao Jiang2, Aimee M Charnell3, Kathryn J Griffin1, Anne B Johnson4, Katherine I Bridge1, Soroush Sohrabi4, D Julian A Scott1. 1. Multidisciplinary Cardiovascular Research Centre, Division of Cardiovascular and Diabetes Research, The Leeds Institute of Genetics, Health and Therapeutics, The University of Leeds, Leeds, United Kingdom; ; The Leeds Vascular Institute, The General Infirmary at Leeds, Leeds, United Kingdom; and. 2. The Division of Epidemiology and Biostatistics, The Leeds Institute of Genetics, Health and Therapeutics, The University of Leeds, Leeds, United Kingdom. 3. Multidisciplinary Cardiovascular Research Centre, Division of Cardiovascular and Diabetes Research, The Leeds Institute of Genetics, Health and Therapeutics, The University of Leeds, Leeds, United Kingdom; ; The Division of Epidemiology and Biostatistics, The Leeds Institute of Genetics, Health and Therapeutics, The University of Leeds, Leeds, United Kingdom. 4. Multidisciplinary Cardiovascular Research Centre, Division of Cardiovascular and Diabetes Research, The Leeds Institute of Genetics, Health and Therapeutics, The University of Leeds, Leeds, United Kingdom;
Abstract
BACKGROUND: Abdominal aortic aneurysm (AAA) growth is a complex process that is incompletely understood. Significant heterogeneity in growth trajectories between patients has led to difficulties in accurately modeling aneurysm growth across cohorts of patients. We set out to compare four models of aneurysm growth commonly used in the literature and confirm which best fits the patient data of our AAA cohort. METHODS: Patients with AAA were included in the study if they had two or more abdominal ultrasound scans greater than 3 months apart. Patients were censored from analysis once their AAA exceeded 5.5 cm. Four models were applied using the R environment for statistical computing. Growth estimates and goodness of fit (using the Akaike Information Criterion, AIC) were compared, with p-values based on likelihood ratio testing. RESULTS: Of 510 enrolled patients, 264 met the inclusion criteria, yielding a total of 1861 imaging studies during 932 cumulative years of surveillance. Overall, growth rates were: (1) 0.35 (0.31,0.39) cm/yr in the growth/time calculation, (2) 0.056 (0.042,0.068) cm/yr in the linear regression model, (3) 0.19 (0.17,0.21) cm/yr in the linear multilevel model, and (4) 0.21 (0.18,0.24) cm/yr in the quadratic multilevel model at time 0, slowing to 0.15 (0.12,0.17) cm/yr at 10 years. AIC was lowest in the quadratic multilevel model (1508) compared to other models (P < 0.0001). CONCLUSION: AAA growth was heterogeneous between patients; the nested nature of the data is most appropriately modeled by multilevel modeling techniques.
BACKGROUND:Abdominal aortic aneurysm (AAA) growth is a complex process that is incompletely understood. Significant heterogeneity in growth trajectories between patients has led to difficulties in accurately modeling aneurysm growth across cohorts of patients. We set out to compare four models of aneurysm growth commonly used in the literature and confirm which best fits the patient data of our AAA cohort. METHODS:Patients with AAA were included in the study if they had two or more abdominal ultrasound scans greater than 3 months apart. Patients were censored from analysis once their AAA exceeded 5.5 cm. Four models were applied using the R environment for statistical computing. Growth estimates and goodness of fit (using the Akaike Information Criterion, AIC) were compared, with p-values based on likelihood ratio testing. RESULTS: Of 510 enrolled patients, 264 met the inclusion criteria, yielding a total of 1861 imaging studies during 932 cumulative years of surveillance. Overall, growth rates were: (1) 0.35 (0.31,0.39) cm/yr in the growth/time calculation, (2) 0.056 (0.042,0.068) cm/yr in the linear regression model, (3) 0.19 (0.17,0.21) cm/yr in the linear multilevel model, and (4) 0.21 (0.18,0.24) cm/yr in the quadratic multilevel model at time 0, slowing to 0.15 (0.12,0.17) cm/yr at 10 years. AIC was lowest in the quadratic multilevel model (1508) compared to other models (P < 0.0001). CONCLUSION: AAA growth was heterogeneous between patients; the nested nature of the data is most appropriately modeled by multilevel modeling techniques.
Authors: Marc A Bailey; Kathryn J Griffin; Soroush Sohrabi; Daniel J Whalley; Anne B Johnson; Paul D Baxter; Robert A S Ariëns; D Julian A Scott Journal: J Vasc Surg Date: 2013-03-13 Impact factor: 4.268
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