Su Yon Jung

Contagious Diseases in the United States from 1888 to the Present

Using data from digitized weekly surveillance reports of notifiable diseases for U.S. cities and states for 1888 through 2011, the authors derived a quantitative history of disease reduction in the United States, focusing particularly on the effects of vaccination programs.

Factors associated with mortality after breast cancer metastasis

BACKGROUND It is generally accepted that patients with breast cancer metastases have very poor survival. Metastatic breast cancer patients can be considered a heterogeneous population with a varied clinical course, which underscores the need for accurate prediction of survival based on prognostic factors. The purpose of the present study was to identify factors related to survival in breast cancer patients after diagnosis with metastatic disease. POPULATIONS AND METHODS A total of 557 patients with breast cancer metastasis diagnosis seen at one large urban practice have been followed up between 1 January, 1999 and 30 June, 2010. Demographic, tumor characteristics, clinical factors as predictors of survival were analyzed using log-rank test and Cox regression model. RESULTS The median survival length was 39 months (range 1-138 months) with 154 (27.7%) alive and 403 (72.3%) dead at the end of follow-up period. This study demonstrated that a history of hypertension, ER/PR status, HER2 status, metastasis-free interval, metastatic location (including brain, bone and liver), and BMI at diagnosis with metastatic breast cancer were the most relevant prognostic factors for survival after metastatic disease diagnosis. CONCLUSION Findings of this study may form a foundation for the growing corpus of knowledge explaining the outcome differences in treatment of patients with metastatic breast cancer, potentially helping to create tailored counseling and personalized treatment approaches for this vulnerable group.

Comorbidity as a Mediator of Survival Disparity Between Younger and Older Women Diagnosed With Metastatic Breast Cancer

The presence of comorbidity becomes increasingly important for its prognostic effect on survival in breast cancer patients with advancing age. This study aimed to evaluate the role of comorbidities including hypertension as a mediator of disparity in survival after metastasis diagnosis between younger (⩽51 years) and older (>51 years) patients. A total of 553 patients 26–88 years of age with breast cancer metastasis diagnosis from 1 large urban practice were followed between January 1, 1999, and June 30, 2008. Comorbidity variables and survival were analyzed using Cox regression model. To assess comorbidity variables as a mediator of age-survival relationship, 2 approaches have been applied: (1) Baron Kenny approach and (2) alternative assessment to compute the percentage change in the hazard ratios (HRs). The median survival was 40 months, with 265 (47.9%) alive and 288 (52.1%) dead. Older patients had worse survival than younger patients (HR, 1.43; 95% confidence interval [CI], 1.11–1.84). Hypertension was related to survival (HR, 1.45; 95% CI, 1.12–1.89) when age and other covariates were controlled. The effect of age on survival was no longer significant after adjustment for hypertension (HR, 1.26; 95%, CI 0.97–1.65) or hypertension-augmented Charlson comorbidity score (HR, 1.24; 95% CI, 0.95–1.63). Hypertension-augmented Charlson comorbidity score or hypertension was a strong mediator of age-survival relationship among metastatic breast cancer patients, explaining survival disparity between younger and older patients by 44% and 40%, respectively. The study findings suggest that hypertension should be included in the comorbidity information for decision-making support programs.

Risk profiles for weight gain among postmenopausal women: A classification and regression tree analysis approach

Purpose Risk factors for obesity and weight gain are typically evaluated individually while “adjusting for” the influence of other confounding factors, and few studies, if any, have created risk profiles by clustering risk factors. We identified subgroups of postmenopausal women homogeneous in their clustered modifiable and non-modifiable risk factors for gaining ≥ 3% weight. Methods This study included 612 postmenopausal women 50–79 years old, enrolled in an ancillary study of the Womens Health Initiative Observational Study between February 1995 and July 1998. Classification and regression tree and stepwise regression models were built and compared. Results Of 27 selected variables, the factors significantly related to ≥ 3% weight gain were weight change in the past 2 years, age at menopause, dietary fiber, fat, alcohol intake, and smoking. In women younger than 65 years, less than 4 kg weight change in the past 2 years sufficiently reduced risk of ≥ 3% weight gain. Different combinations of risk factors related to weight gain were reported for subgroups of women: women 65 years or older (essential factor: < 9.8 g/day dietary factor), African Americans (essential factor: currently smoking), and white women (essential factor: ≥ 5 kg weight change for the past 2 years). Conclusions Our findings suggest specific characteristics for particular subgroups of postmenopausal women that may be useful for identifying those at risk for weight gain. The study results may be useful for targeting efforts to promote strategies to reduce the risk of obesity and weight gain in subgroups of postmenopausal women and maximize the effect of weight control by decreasing obesity-relevant adverse health outcomes.

In cross-sectional observations, dietary quality is not associated with CVD risk in women; in men the positive association is accounted for by BMI.

The role that BMI plays in the association between dietary quality and CVD risk is not known. We aimed to better understand this relationship using statistical methods which correct for sex-specific underreporting of dietary intake. Overall, dietary quality was assessed using the Healthy Eating Index (HEI) on data from 9797 non-pregnant adults (aged >20 years) who participated in the National Health and Nutrition Examination Survey from 2005 to 2010. CVD risk factors included blood pressure, fasting glucose and insulin, homeostatic models of insulin resistance (HOMA-IR), HDL- and LDL-cholesterol (HDL-C and LDL-C), TAG and C-reactive protein (CRP). We controlled for demographic and lifestyle covariates, and we used the population ratio approach (which adjusts for the underreporting of intake) to compare mean HEI scores between the top and bottom quartiles of covariate-adjusted CVD risk factors. In women, the total HEI score was not associated with any CVD risk factors (all Q>0·11). In men, the total HEI score was associated with covariate-adjusted residuals for fasting insulin (Q<0.001), HOMA-IR (Q<0.001), HDL-C (Q=0.01) and CRP (Q<0.001). When we additionally adjusted for BMI, the association with total HEI score was not significant (all P>0.10). In the present analyses, dietary quality was associated with five CVD risk factors in a sex-specific manner. Moreover, the association of BMI with CVD risk attenuated the relationship between CVD risk and diet, which suggests that BMI is an important factor in heart disease prevention.

Associations between time spent sitting and cancer-related biomarkers in postmenopausal women: an exploration of effect modifiers.

PurposeDespite evidence that prolonged periods of sitting may influence biological mediators of cancer development, few studies have considered these relationships in a cancer-specific context.MethodsThis cross-sectional study included 755 postmenopausal women enrolled in an ancillary study of the Women’s Health Initiative. Plasma levels of Insulin-like growth factor-I (IGF-I), IGF-binding protein-3, leptin, insulin, C-peptide, C-reactive protein (CRP), and Interleukin (IL)-6 were measured. The time spent sitting per day was categorized as quartiles (Qs). The relationships between sedentary time and biomarkers were modified by race, physical activity, and exogenous estrogen use.ResultsIGF-I levels among African American (AA) women were higher than those of white women across the Qs of sedentary time. Likewise, IL-6 levels in AA women were higher than those in white women at Q3 and Q4 of sedentary time. IGFBP-3 levels were higher and insulin levels were lower across the Qs of sedentary time among women meeting guidelines for physical activity than women who were not. Additionally, CRP levels were higher among estrogen users than nonusers at Q1, Q2, and Q4 of sedentary time.ConclusionsThese results suggest that relationship between time spent sitting and cancer-related biomarkers may not be simply linear, but differ in the context of effect modifiers.

Obesity and associated lifestyles modify the effect of glucose metabolism-related genetic variants on impaired glucose homeostasis among postmenopausal women.

Impaired glucose metabolism‐related genetic variants likely interact with obesity‐modifiable factors in response to glucose intolerance, yet their interconnected pathways have not been fully characterized.

Genetic Variants in Metabolic Signaling Pathways and Their Interaction with Lifestyle Factors on Breast Cancer Risk: A Random Survival Forest Analysis

Genetic variants in the insulin-like growth factor-I (IGF-I)/insulin resistance axis may interact with lifestyle factors, influencing postmenopausal breast cancer risk, but these interrelated pathways are not fully understood. In this study, we examined 54 single-nucleotide polymorphisms (SNP) in genes related to IGF-I/insulin phenotypes and signaling pathways and lifestyle factors in relation to postmenopausal breast cancer, using data from 6,567 postmenopausal women in the Womens Health Initiative Harmonized and Imputed Genome-Wide Association Studies. We used a machine-learning method, two-stage random survival forest analysis. We identified three genetic variants (AKT1 rs2494740, AKT1 rs2494744, and AKT1 rs2498789) and two lifestyle factors [body mass index (BMI) and dietary alcohol intake] as the top five most influential predictors for breast cancer risk. The combination of the three SNPs, BMI, and alcohol consumption (≥1 g/day) significantly increased the risk of breast cancer in a gene and lifestyle dose-dependent manner. Our findings provide insight into gene–lifestyle interactions and will enable researchers to focus on individuals with risk genotypes to promote intervention strategies. These data also suggest potential genetic targets in future intervention/clinical trials for cancer prevention in order to reduce the risk for breast cancer in postmenopausal women. Cancer Prev Res; 11(1); 44–51. ©2017 AACR.

Bioavailable insulin-like growth factor-I as mediator of racial disparity in obesity-relevant breast and colorectal cancer risk Among postmenopausal women

Objective: Bioavailable insulin-like growth factor-I (IGF-I) interacts with obesity and exogenous estrogen (E) in a racial disparity in obesity-related cancer risk, yet their interconnected pathways are not fully characterized. We investigated whether circulating bioavailable IGF-I acted as a mediator of the racial disparity in obesity-related cancers such as breast and colorectal (CR) cancers and how obesity and E use regulate this relationship. Methods: A total of 2,425 white and 164 African American (AA) postmenopausal women from the Womens Health Initiative Observational Study were followed from October 1, 1993 through August 29, 2014. To assess bioactive IGF-I as a mediator of race-cancer relationship, we used the Baron-Kenny method and quantitative estimation of the mediation effect. Results: Compared with white women, AA women had higher IGF-I levels; their higher risk of CR cancer, after accounting for IGF-I, was no longer significant. IGF-I was associated with breast and CR cancers even after controlling for race. Among viscerally obese (waist/hip ratio >0.85) and overall nonobese women (body mass index <30), IGF-I was a strong mediator, reducing the racial disparity in both cancers by 30% and 60%, respectively. In E-only users and nonusers, IGF-I explained the racial disparity in CR cancer only modestly. Conclusions: Bioavailable IGF-I is potentially important in racial disparities in obesity-related breast and CR cancer risk between postmenopausal AA and white women. Body fat distribution and E use may be part of the interconnected hormonal pathways related to racial difference in IGF-I levels and obesity-related cancer risk.

Challenges in Epidemiological and Statistical Evaluations of Effect Modifiers and Confounders

In multiple adjusted regression models, researchers sometimes do not know when the interaction occurs and how to interpret the exposure effect estimate while adjusting for the interaction term, resulting in a misinterpretation of the results; this issue has been raised in previous epidemiologic studies. In addition, when the positions of exposure and outcome are switched in the multiple regression, interpreting covariates is challenging. Here, we present the epidemiological and statistical challenges in evaluating the effect modifier and confounding factor.