Effect of Annual Influenza Vaccination on the Risk of Lung Cancer Among Patients With Hypertension: A Population-Based Cohort Study in Taiwan.

Objectives: Lung cancer is a main contributor to all newly diagnosed cancers worldwide. The chemoprotective effect of the influenza vaccine among patients with hypertension remains unclear. Methods: A total of 37,022 patients with hypertension were retrospectively enrolled from the Taiwan National Health Insurance Research Database. These patients were further divided into a vaccinated group (n = 15,697) and an unvaccinated group (n = 21,325). Results: After adjusting for sex, age, comorbidities, medications, level of urbanization and monthly income, vaccinated patients had a significantly lower risk of lung cancer occurrence than unvaccinated patients (adjusted hazard ratio [aHR]: 0.56, 95% confidence interval [CI]: 0.47-0.67). A potential protective effect was observed for both sexes and in the elderly age group. With a greater total number of vaccinations, a potentially greater protective effect was observed (aHR: 0.75, 95% CI 0.60-0.95; aHR: 0.66, 95% CI: 0.53-0.82; aHR: 0.26, 95% CI: 0.19-0.36, after receiving 1, 2-3 and ≥4 vaccinations, respectively). Conclusion: Influenza vaccination was associated with a lower risk of lung cancer among patients with hypertension. The potentially chemoprotective effect appeared to be dose dependent.

The Effects of Different Types of Sleep Disorder on Colorectal Cancer: A Nationwide Population-Based Cohort Study.

The impact of sleep disorders (SDs), particularly sleep apnea (SA), on the development of colorectal cancer (CRC) has been the subject of significant research. However, the potential contribution of other SDs to the incidence of CRC remains unexplored. The objective of this study was to examine the effects of SDs on the risk of developing CRC. This study assessed CRC risk among individuals diagnosed with SDs compared with age- and sex-matched unaffected individuals. A longitudinal, nationwide, population-based cohort study was conducted using data from the Taiwan National Health Insurance Research Database (NHIRD) encompassing 177,707 individuals diagnosed with SDs and 177,707 matched controls. Cox proportional hazard regression analysis was used to determine the relative increased risk of CRC in individuals with SDs and specific subgroups of SDs. The CRC incidences were 1.32-fold higher (95% CI 1.23-1.42) in the overall SD cohort, 1.17-fold higher (95% CI 0.82-1.68) in the SA cohort, 1.42-fold higher (95% CI 1.31-1.55) in the insomnia cohort, 1.27-fold higher (95% CI 1.17-1.38) in the sleep disturbance cohort, and 1.00-fold higher (95% CI 0.77-1.29) in the other SD cohort, after adjusting for age, sex, and comorbidities.

The Association between Statins and Liver Cancer Risk in Patients with Heart Failure: A Nationwide Population-Based Cohort Study.

Heart failure (HF) and cancer have similar risk factors. HMG-CoA reductase inhibitors, also known as statins, are chemoprotective agents against carcinogenesis. We aimed to evaluate the chemoprotective effects of statins against liver cancer in patients with HF. This cohort study enrolled patients with HF aged ≥20 years between 1 January 2001 and 31 December 2012 from the National Health Insurance Research Database in Taiwan. Each patient was followed to assess liver cancer risk. A total of 25,853 patients with HF were followed for a 12-year period; 7364 patients used statins and 18,489 did not. The liver cancer risk decreased in statin users versus non-users (adjusted hazard ratio (aHR) = 0.26, 95% confidence interval (CI): 0.20-0.33) in the entire cohort in the multivariate regression analysis. In addition, both lipophilic and hydrophilic statins reduced the liver cancer risk in patients with HF (aHR 0.34, 95% CI: 0.26-0.44 and aHR 0.42, 95% CI: 0.28-0.54, respectively). In the sensitivity analysis, statin users in all dose-stratified subgroups had a reduced liver cancer risk regardless of age, sex, comorbidity, or other concomitant drug use. In conclusion, statins may decrease liver cancer risk in patients with HF.

Protective Effects of Influenza Vaccine against Colorectal Cancer in Populations with Chronic Kidney Disease: A Nationwide Population-Based Cohort Study.

Chronic kidney disease (CKD) is associated with malignancy, including colorectal cancer, via the potential mechanism of chronic inflammation status. This study aimed to determine whether influenza vaccines can reduce the risk of colorectal cancer in patients with CKD. Our cohort study enrolled 12,985 patients older than 55 years with a diagnosis of CKD in Taiwan from the National Health Insurance Research Database at any time from 1 January 2001 to 31 December 2012. Patients enrolled in the study were divided into a vaccinated and an unvaccinated group. In this study, 7490 and 5495 patients were unvaccinated and vaccinated, respectively. A propensity score was utilized to reduce bias and adjust the results. Cox proportional hazards regression was used to estimate the correlation between the influenza vaccine and colorectal cancer in patients with CKD. The results showed that the influenza vaccine exerted a protective effect against colorectal cancer in populations with CKD. The incidence rate of colon cancer in the vaccinated group was significantly lower than in the unvaccinated group, with an adjusted hazard rate (HR) of 0.38 (95% CI: 0.30-0.48, p < 0.05). After the propensity score was adjusted for Charlson comorbidity index, age, sex, dyslipidemia, hypertension, diabetes, monthly income, and level of urbanization, the dose-dependent effect was found, and it revealed adjusted HRs of 0.74 (95% CI: 0.54-1.00, p < 0.05), 0.41 (95% CI: 0.30-0.57, p < 0.001), 0.16 (95% CI: 0.11-0.25, p < 0.001) for one, two to three, and four or more vaccinations, respectively. In summary, the influenza vaccine was found to be associated with a reduced risk of colorectal cancer in CKD patients. This study highlights the potential chemopreventive effect of influenza vaccination among patients with CKD. Future studies are required to determine whether the aforementioned relationship is a causal one.

Investigating the spatial interaction of immune cells in colon cancer.

The intricate network of interactions between cells and molecules in the tumor microenvironment creates a heterogeneous ecosystem. The proximity of the cells and molecules to their activators and inhibitors is essential in the progression of tumors. Here, we develop a system of partial differential equations coupled with linear elasticity to investigate the effects of spatial interactions on the tumor microenvironment. We observe interesting cell and cytokine distribution patterns, which are heavily affected by macrophages. We also see that cytotoxic T cells get recruited and suppressed at the site of macrophages. Moreover, we observe that anti-tumor macrophages reorganize the patterns in favor of a more spatially restricted cancer and necrotic core. Furthermore, the adjoint-based sensitivity analysis indicates that the most sensitive model's parameters are directly related to macrophages. The results emphasize the widely acknowledged effect of macrophages in controlling cancer cells population and spatially arranging cells in the tumor microenvironment.

Bifurcation analysis of a free boundary model of vascular tumor growth with a necrotic core and chemotaxis.

A considerable number of research works has been devoted to the study of tumor models. Several biophysical factors, such as cell proliferation, apoptosis, chemotaxis, angiogenesis and necrosis, have been discovered to have an impact on the complicated biological system of tumors. An indicator of the aggressiveness of tumor development is the instability of the shape of the tumor boundary. Complex patterns of tumor morphology have been explored in Lu et al. (J Comput Phys 459:111153, 2022). In this paper, we continue to carry out a bifurcation analysis on such a vascular tumor model with a controlled necrotic core and chemotaxis. This bifurcation analysis, to the parameter of cell proliferation, is built on the explicit formulas of radially symmetric steady-state solutions. By perturbing the tumor free boundary and establishing rigorous estimates of the free boundary system, we prove the existence of the bifurcation branches with Crandall-Rabinowitz theorem. The parameter of chemotaxis is found to influence the monotonicity of the bifurcation point as the mode l increases both theoretically and numerically.

Influenza Vaccination Reduces the Risk of Liver Cancer in Patients with Chronic Kidney Disease: A Nationwide Population-Based Cohort Study.

Previous studies have indicated that influenza vaccination reduces the development of lung cancer. However, the protective effects of influenza vaccination on primary liver cancer in patients with chronic kidney disease (CKD) are unclear. This cohort study identified 12,985 patients aged at least 55 years who had received a diagnosis of CKD between 1 January 2001 and 31 December 2012 from the National Health Insurance Research Database of Taiwan. The patients were classified according to vaccination status. Propensity score matching was used to reduce selection bias. Cox proportional hazards regression analysis was used to evaluate the correlation between influenza vaccination and primary liver cancer in patients with CKD. The prevalence of primary liver cancer was lower in patients with CKD who had received an influenza vaccine (adjusted hazard ratio: 0.45, 95% confidence interval [CI]: 0.35−0.58, p < 0.001). The protective effects were observed regardless of sex, age, and comorbidities. Moreover, dose-dependent protective effects were observed. In the subgroup analysis, where the patients were classified by the number of vaccinations received, the adjusted hazard ratios for 1, 2−3, and ≥4 vaccinations were 0.86 (95% CI: 0.63−1.17), 0.45 (95% CI: 0.31−0.63), and 0.21 (95% CI: 0.14−0.33), respectively. In conclusion, influenza vaccination was associated with a lower incidence of liver cancer in patients with CKD.

A cancer model with nonlocal free boundary dynamics.

Cancer cells at the tumor boundary move in the direction of the oxygen gradient, while cancer cells far within the tumor are in a necrotic state. This paper introduces a simple mathematical model that accounts for these facts. The model consists of cancer cells, cytotoxic T cells, and oxygen satisfying a system of partial differential equations. Some of the model parameters represent the effect of anti-cancer drugs. The tumor boundary is a free boundary whose dynamics is determined by the movement of cancer cells at the boundary. The model is simulated for radially symmetric and axially symmetric tumors, and it is shown that the tumor may increase or decrease in size, depending on the "strength" of the drugs. Existence theorems are proved, global in-time in the radially symmetric case, and local in-time for any shape of tumor. In the radially symmetric case, it is proved, under different conditions, that the tumor may shrink monotonically, or expand monotonically.

Exploring approaches for predictive cancer patient digital twins: Opportunities for collaboration and innovation.

We are rapidly approaching a future in which cancer patient digital twins will reach their potential to predict cancer prevention, diagnosis, and treatment in individual patients. This will be realized based on advances in high performance computing, computational modeling, and an expanding repertoire of observational data across multiple scales and modalities. In 2020, the US National Cancer Institute, and the US Department of Energy, through a trans-disciplinary research community at the intersection of advanced computing and cancer research, initiated team science collaborative projects to explore the development and implementation of predictive Cancer Patient Digital Twins. Several diverse pilot projects were launched to provide key insights into important features of this emerging landscape and to determine the requirements for the development and adoption of cancer patient digital twins. Projects included exploring approaches to using a large cohort of digital twins to perform deep phenotyping and plan treatments at the individual level, prototyping self-learning digital twin platforms, using adaptive digital twin approaches to monitor treatment response and resistance, developing methods to integrate and fuse data and observations across multiple scales, and personalizing treatment based on cancer type. Collectively these efforts have yielded increased insights into the opportunities and challenges facing cancer patient digital twin approaches and helped define a path forward. Given the rapidly growing interest in patient digital twins, this manuscript provides a valuable early progress report of several CPDT pilot projects commenced in common, their overall aims, early progress, lessons learned and future directions that will increasingly involve the broader research community.

Influenza Vaccination and Risk of Lung Cancer in Patients with Chronic Kidney Disease: A Nationwide, Population-Based Cohort Study.

Chronic kidney disease (CKD) is significantly associated with lung cancer incidence. The aim of this study was to elucidate whether influenza vaccination reduces the incidence of lung cancer in patients with CKD. This cohort study enrolled patients with a record of CKD diagnosis from 2000 to 2012 in Taiwan's National Health Insurance Research Database. Included patients were divided into vaccinated and unvaccinated groups. In total 12,985 patients with CKD were enrolled. Among these patients, 5495 were vaccinated and 7490 were unvaccinated. The risk of lung cancer was significantly lower in the influenza vaccination group after adjusting for age, sex, dialysis status, lung diseases, comorbidities, level of urbanization, and monthly income (adjusted hazard ratio (HR): 0.50, 95% confidence interval (CI; 0.38−0.65), p < 0.05). Lower risk of lung cancer was observed in both sexes, all age groups, dialysis status and co-existed lung diseases. The association between the risk of lung cancer and vaccination appeared to be dose-dependent (adjusted HRs: 0.91 (0.66−1.25), 0.49 (0.34−0.71), and 0.25 (0.17−0.38) for patients who received 1, 2 or 3, and ≥4 vaccinations during the follow-up period, respectively). In conclusion, Influenza vaccination decreased the risk of lung cancer in patients diagnosed with CKD. This potentially protective effect against lung cancer appeared to be dose dependent.

A PDE Model of Breast Tumor Progression in MMTV-PyMT Mice.

The evolution of breast tumors greatly depends on the interaction network among different cell types, including immune cells and cancer cells in the tumor. This study takes advantage of newly collected rich spatio-temporal mouse data to develop a data-driven mathematical model of breast tumors that considers cells' location and key interactions in the tumor. The results show that cancer cells have a minor presence in the area with the most overall immune cells, and the number of activated immune cells in the tumor is depleted over time when there is no influx of immune cells. Interestingly, in the case of the influx of immune cells, the highest concentrations of both T cells and cancer cells are in the boundary of the tumor, as we use the Robin boundary condition to model the influx of immune cells. In other words, the influx of immune cells causes a dominant outward advection for cancer cells. We also investigate the effect of cells' diffusion and immune cells' influx rates in the dynamics of cells in the tumor micro-environment. Sensitivity analyses indicate that cancer cells and adipocytes' diffusion rates are the most sensitive parameters, followed by influx and diffusion rates of cytotoxic T cells, implying that targeting them is a possible treatment strategy for breast cancer.

A Mathematical Model of Breast Tumor Progression Based on Immune Infiltration.

Breast cancer is the most prominent type of cancer among women. Understanding the microenvironment of breast cancer and the interactions between cells and cytokines will lead to better treatment approaches for patients. In this study, we developed a data-driven mathematical model to investigate the dynamics of key cells and cytokines involved in breast cancer development. We used gene expression profiles of tumors to estimate the relative abundance of each immune cell and group patients based on their immune patterns. Dynamical results show the complex interplay between cells and molecules, and sensitivity analysis emphasizes the direct effects of macrophages and adipocytes on cancer cell growth. In addition, we observed the dual effect of IFN-γ on cancer proliferation, either through direct inhibition of cancer cells or by increasing the cytotoxicity of CD8+ T-cells.

Role of Annual Influenza Vaccination against Lung Cancer in Type 2 Diabetic Patients from a Population-Based Cohort Study.

Type 2 diabetes mellitus (DM) patients are at a higher risk for developing lung cancer due to immune dysfunction and chronic inflammation. They also have increased morbidity and mortality related to influenza, and it is recommended that they receive an annual influenza vaccination. In this study, we evaluate whether influenza vaccination could reduce the incidence of lung cancer in DM patients. This cohort study included DM patients (≥55 years old) between 1 January 2002 and 31 December 2012 by using the Taiwan Health Insurance Database. Cox proportional hazard regression method was used to compare the relation between the influenza vaccination and lung cancer incidence after adjusting for potential confounders. Sub-group analyses were done according to vaccination status (unvaccinated, total number of vaccinations: 1, 2-3, ≥4) and evaluated the dose-dependent effects on lung cancer events. Among 22,252 eligible DM patients, 7860 (35.32%) received an influenza vaccination and 67.68% (14392) did not receive an influenza vaccination. Lung cancer incidence was significantly lower in the vaccinated group versus the unvaccinated group (adjusted HR 0.77; 95% CI 0.62-0.95, p < 0.05). Significant protective effects were observed among male sex (adjusted HR 0.72; 95% CI 0.55-0.94, p < 0.05) and 55-64 year (adjusted HR 0.61; 95% CI 0.40-0.94, p < 0.05) and ≥75 year (adjusted HR 0.63; 95% CI 0.42-0.92, p < 0.05) age groups, respectively. A dose-dependent protective effect was noted with a significant protective effect in those that received ≥4 vaccinations (adjusted HR 0.42; 95% CI 0.29-0.61, p < 0.001). In sub-group analysis, elder patients with ≥65 years of age were significantly protected from ≥4 vaccinations (adjusted HR 0.37; 95% CI 0.23-0.62, p < 0.001 in 65-74 years and adjusted HR 0.31; 95% CI 0.15-0.66, p = 0.002 in ≥75 years group, respectively). Male sex with ≥4 vaccinations had a significantly lower risk of lung cancer (adjusted HR 0.35; 95% CI 0.21-0.57, p < 0.001). Patients with comorbid conditions that received ≥4 vaccinations were also protected, and was especially significant among those with CCI ≥ 3 (adjusted HR 0.38; 95% CI 0.18-0.80, p = 0.009) as compared to 1 and 2-3 vaccination groups, including those with hypertension (adjusted HR 0.35; 95% CI 0.22-0.57, p < 0.001). This population-based cohort study demonstrated that annual influenza vaccination significantly reduced the lung cancer risk in DM patients and specifically demonstrates that a higher number of vaccinations is related with a more protective effect. Whether this is due to vaccine booster effects on anti-tumor immune regulation among DM patients still needs to be explored.

Data Driven Mathematical Model of Colon Cancer Progression.

Every colon cancer has its own unique characteristics, and therefore may respond differently to identical treatments. Here, we develop a data driven mathematical model for the interaction network of key components of immune microenvironment in colon cancer. We estimate the relative abundance of each immune cell from gene expression profiles of tumors, and group patients based on their immune patterns. Then we compare the tumor sensitivity and progression in each of these groups of patients, and observe differences in the patterns of tumor growth between the groups. For instance, in tumors with a smaller density of naive macrophages than activated macrophages, a higher activation rate of macrophages leads to an increase in cancer cell density, demonstrating a negative effect of macrophages. Other tumors however, exhibit an opposite trend, showing a positive effect of macrophages in controlling tumor size. Although the results indicate that for all patients the size of the tumor is sensitive to the parameters related to macrophages, such as their activation and death rate, this research demonstrates that no single biomarker could predict the dynamics of tumors.

TNF-α inhibitor reduces drug-resistance to anti-PD-1: A mathematical model.

Drug resistance is a primary obstacle in cancer treatment. In many patients who at first respond well to treatment, relapse occurs later on. Various mechanisms have been explored to explain drug resistance in specific cancers and for specific drugs. In this paper, we consider resistance to anti-PD-1, a drug that enhances the activity of anti-cancer T cells. Based on results in experimental melanoma, it is shown, by a mathematical model, that resistances to anti-PD-1 can be significantly reduced by combining it with anti-TNF-α. The model is used to simulate the efficacy of the combined therapy with different range of doses, different initial tumor volume, and different schedules. In particular, it is shown that under a course of treatment with 3-week cycles where each drug is injected in the first day of either week 1 or week 2, injecting anti-TNF-α one week after anti-PD-1 is the most effective schedule in reducing tumor volume.

Nicorandil prevents doxorubicin-induced human umbilical vein endothelial cell apoptosis.

Nicorandil is an adenosine triphosphate-sensitive potassium channel opener with additional antioxidant properties. Doxorubicin (DOX) is an anticancer drug that exerts oxidation-mediated adverse cardiovascular effects. This study examined the effects of nicorandil on DOX-induced cytotoxicity in human umbilical vein endothelial cells (HUVECs) and underlying intracellular signaling mechanisms. Cultured HUVECs were pretreated with nicorandil (0.1, 0.3, 1, 3, and 10 µM) for 12 h and then treated with DOX (1 µM) for 24 h. Cell viability and cytotoxicity were measured using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide and lactate dehydrogenase assays, respectively. Cell apoptosis was examined using a caspase-3 activity assay, and DNA fragmentation was detected through TUNEL (terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling) staining. Western blot analysis was conducted to determine the related protein expression. DOX markedly increased reactive oxygen species production, p53 expression, caspase-3 activity, cleaved caspase-3 levels, and TUNEL-positive cell numbers but reduced Bcl-2 expression and intracellular antioxidant enzyme levels; these effects were effectively antagonized through nicorandil (3 µM, 12 h) pretreatment, which resulted in HUVECs being protected from DOX-induced apoptosis. Activating transcription factor 3 (ATF3), a stress-induced transcription factor, was induced by nicorandil (3 µM). Furthermore, nicorandil (3 µM) enhanced nuclear factor erythroid 2-related factor 2 (Nrf2) translocation and heme oxygenase-1 (HO-1) expression. ATF3 short interfering RNA significantly attenuated nicorandil-mediated Nrf2 translocation, HO-1 expression, and inhibitory effects on DOX-stimulated reactive oxygen species production and cell apoptosis. In summary, nicorandil may protect HUVECs from DOX-induced apoptosis, in part through ATF3-mediated Nrf2/HO-1 signaling pathways, which potentially protect the vessels from severe DOX toxicity.

Cafestol Activates Nuclear Factor Erythroid-2 Related Factor 2 and Inhibits Urotensin II-Induced Cardiomyocyte Hypertrophy.

Through population-based studies, associations have been found between coffee drinking and numerous health benefits, including a reduced risk of cardiovascular disease. Active ingredients in coffee have therefore received considerable attention from researchers. A wide variety of effects have been attributed to cafestol, one of the major compounds in coffee beans. Because cardiac hypertrophy is an independent risk factor for cardiovascular events, this study examined whether cafestol inhibits urotensin II (U-II)-induced cardiomyocyte hypertrophy. Neonatal rat cardiomyocytes were exposed only to U-II (1 nM) or to U-II (1 nM) following 12-h pretreatment with cafestol (1-10 µ M). Cafestol (3-10 µ M) pretreatment significantly inhibited U-II-induced cardiomyocyte hypertrophy with an accompanying decrease in U-II-induced reactive oxygen species (ROS) production. Cafestol also inhibited U-II-induced phosphorylation of redox-sensitive extracellular signal-regulated kinase (ERK) and epidermal growth factor receptor transactivation. In addition, cafestol pretreatment increased Src homology region 2 domains-containing phosphatase-2 (SHP-2) activity, suggesting that cafestol prevents ROS-induced SHP-2 inactivation. Moreover, nuclear factor erythroid-2-related factor 2 (Nrf2) translocation and heme oxygenase-1 (HO-1) expression were enhanced by cafestol. Addition of brusatol (a specific inhibitor of Nrf2) or Nrf2 siRNA significantly attenuated cafestol-mediated inhibitory effects on U-II-stimulated ROS production and cardiomyocyte hypertrophy. In summary, our data indicate that cafestol prevented U-II-induced cardiomycyte hypertrophy through Nrf2/HO-1 activation and inhibition of redox signaling, resulting in cardioprotective effects. These novel findings suggest that cafestol could be applied in pharmacological therapy for cardiac diseases.

The Role of Exosomes in Pancreatic Cancer Microenvironment.

Exosomes are nanovesicles shed by cells as a means of communication with other cells. Exosomes contain mRNAs, microRNAs (miRs) and functional proteins. In the present paper, we develop a mathematical model of tumor-immune interaction by means of exosomes shed by pancreatic cancer cells and dendritic cells. Cancer cells' exosomes contain miRs that promote their proliferation and that inhibit immune response by dendritic cells, and by CD4+ and CD8+ T cells. Dendritic cells release exosomes with proteins that induce apoptosis of cancer cells and that block regulatory T cells. Simulations of the model show how the size of the pancreatic cancer can be determined by measurement of specific miRs (miR-21 and miR-203 in the case of pancreatic cancer), suggesting these miRs as biomarkers for cancer.

Mathematical model of chronic pancreatitis.

Chronic pancreatitis (CP) is a progressive inflammatory disease of the pancreas, leading to its fibrotic destruction. There are currently no drugs that can stop or slow the progression of the disease. The etiology of the disease is multifactorial, whereas recurrent attacks of acute pancreatitis are thought to precede the development of CP. A better understanding of the pathology of CP is needed to facilitate improved diagnosis and treatment strategies for this disease. The present paper develops a mathematical model of CP based on a dynamic network that includes macrophages, pancreatic stellate cells, and prominent cytokines that are present at high levels in the CP microenvironment. The model is represented by a system of partial differential equations. The model is used to explore in silico potential drugs that could slow the progression of the disease, for example infliximab (anti-TNF-[Formula: see text]) and tocilizumab or siltuximab (anti-IL-6/IL-6R).

A mathematical model of aortic aneurysm formation.

Abdominal aortic aneurysm (AAA) is a localized enlargement of the abdominal aorta, such that the diameter exceeds 3 cm. The natural history of AAA is progressive growth leading to rupture, an event that carries up to 90% risk of mortality. Hence there is a need to predict the growth of the diameter of the aorta based on the diameter of a patient's aneurysm at initial screening and aided by non-invasive biomarkers. IL-6 is overexpressed in AAA and was suggested as a prognostic marker for the risk in AAA. The present paper develops a mathematical model which relates the growth of the abdominal aorta to the serum concentration of IL-6. Given the initial diameter of the aorta and the serum concentration of IL-6, the model predicts the growth of the diameter at subsequent times. Such a prediction can provide guidance to how closely the patient's abdominal aorta should be monitored. The mathematical model is represented by a system of partial differential equations taking place in the aortic wall, where the media is assumed to have the constituency of an hyperelastic material.