Browsing by Author "Kravchenko, J"
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Item Open Access CARDIOVASCULAR COMORBIDITIES IN LUNG CANCER PATIENTS: TREATMENT-SPECIFIC EFFECTS ON SURVIVAL(GERONTOLOGIST, 2014-11) Kravchenko, J; Berry, MF; Arbeev, KG; Akushevich, IItem Open Access IMPACTS OF CEREBROVASCULAR AND NEURODEGENERATIVE DISEASES ON SURVIVAL OF LUNG CANCER PATIENTS(GERONTOLOGIST, 2015-11) Kravchenko, J; Berry, MF; Arbeev, KG; Lyerly, H; Yashin, AI; Akushevich, IItem Open Access Long-term dynamics of death rates of emphysema, asthma, and pneumonia and improving air quality.(Int J Chron Obstruct Pulmon Dis, 2014) Kravchenko, J; Akushevich, I; Abernathy, AP; Holman, S; Ross, WG; Lyerly, HKBACKGROUND: The respiratory tract is a major target of exposure to air pollutants, and respiratory diseases are associated with both short- and long-term exposures. We hypothesized that improved air quality in North Carolina was associated with reduced rates of death from respiratory diseases in local populations. MATERIALS AND METHODS: We analyzed the trends of emphysema, asthma, and pneumonia mortality and changes of the levels of ozone, sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and particulate matters (PM2.5 and PM10) using monthly data measurements from air-monitoring stations in North Carolina in 1993-2010. The log-linear model was used to evaluate associations between air-pollutant levels and age-adjusted death rates (per 100,000 of population) calculated for 5-year age-groups and for standard 2000 North Carolina population. The studied associations were adjusted by age group-specific smoking prevalence and seasonal fluctuations of disease-specific respiratory deaths. RESULTS: Decline in emphysema deaths was associated with decreasing levels of SO2 and CO in the air, decline in asthma deaths-with lower SO2, CO, and PM10 levels, and decline in pneumonia deaths-with lower levels of SO2. Sensitivity analyses were performed to study potential effects of the change from International Classification of Diseases (ICD)-9 to ICD-10 codes, the effects of air pollutants on mortality during summer and winter, the impact of approach when only the underlying causes of deaths were used, and when mortality and air-quality data were analyzed on the county level. In each case, the results of sensitivity analyses demonstrated stability. The importance of analysis of pneumonia as an underlying cause of death was also highlighted. CONCLUSION: Significant associations were observed between decreasing death rates of emphysema, asthma, and pneumonia and decreases in levels of ambient air pollutants in North Carolina.Item Open Access MEDICARE-BASED MULTIMORBIDITY INDEX FOR PROJECTING MORBIDITY AND MORTALITY AMONG OLDER ADULTS IN THE U.S(GERONTOLOGIST, 2012-11) Akushevich, I; Kravchenko, J; Whitson, H; Cohen, HJ; Ukraintseva, SV; Arbeev, KG; Yashin, AIItem Open Access PATTERNS OF AGING-RELATED DISEASES INCIDENCE AND RECOVERY IN US ELDERLY(GERONTOLOGIST, 2011-11) Akushevich, I; Kravchenko, J; Ukraintseva, SV; Arbeev, KG; Yashin, AIItem Open Access Predictive model of the treatment effect for patients with major depressive disorder(2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013, 2013-11-28) Akushevich, I; Kravchenko, J; Gersing, K; Mane, KKThe model to evaluate and predict the effectiveness of treatment of the Major Depressive Disorder (MDD) was developed and estimated using MindLinc data. The clinical global impression (CGI) scale with seven categories was used to measure the patient's state. The proportional odds model was selected because of ordinal nature of the outcome. The set of predictors included i) CGI score measured at preceded visit, ii) three groups of medications (antidepressants, atypical medicine, and augmentation medicine), all categorized for appropriate number of strata (from six to nine) and their daily doses, iii) psychiatric comorbidities, iv) type of the therapy used (talk vs. medications), v) demographic variables (e.g., age group, sex), and vi) the history of the efficiency of prior treatment. More than a half of a million records with measured CGI scores and their predictors were identified in the MindLinc database and used for model estimation. The predicted model of future CGI scales was developed and evaluated for single and recurrent episodes of MDD. Significant estimates were obtained for demographic factors, history of previous SGI scales, and for comorbidity and treatment indices. The methods of causal inferences based on the inverse probability weighting approach were applied to evaluate the treatment effects. The model extensions allowing for addressing the limitations of the proportional odds model are discussed. Copyright © 2007 by the Association for Computing Machinery.Item Open Access Survey of the potential environmental and health impacts in the immediate aftermath of the coal ash spill in Kingston, Tennessee.(Environ Sci Technol, 2009-08-15) Ruhl, L; Vengosh, A; Dwyer, GS; Hsu Kim, H; Deonarine, A; Bergin, M; Kravchenko, JAn investigation of the potential environmental and health impacts in the immediate aftermath of one of the largest coal ash spills in U.S. history at the Tennessee Valley Authority (TVA) Kingston coal-burning power plant has revealed three major findings. First the surface release of coal ash with high levels of toxic elements (As = 75 mg/kg; Hg = 150 microg/kg) and radioactivity (226Ra + 228Ra = 8 pCi/g) to the environment has the potential to generate resuspended ambient fine particles (< 10 microm) containing these toxics into the atmosphere that may pose a health risk to local communities. Second, leaching of contaminants from the coal ash caused contamination of surface waters in areas of restricted water exchange, but only trace levels were found in the downstream Emory and Clinch Rivers due to river dilution. Third, the accumulation of Hg- and As-rich coal ash in river sediments has the potential to have an impact on the ecological system in the downstream rivers by fish poisoning and methylmercury formation in anaerobic river sediments.Item Open Access Theory of partitioning of disease prevalence and mortality in observational data.(Theor Popul Biol, 2017-04) Akushevich, I; Yashkin, AP; Kravchenko, J; Fang, F; Arbeev, K; Sloan, F; Yashin, AIIn this study, we present a new theory of partitioning of disease prevalence and incidence-based mortality and demonstrate how this theory practically works for analyses of Medicare data. In the theory, the prevalence of a disease and incidence-based mortality are modeled in terms of disease incidence and survival after diagnosis supplemented by information on disease prevalence at the initial age and year available in a dataset. Partitioning of the trends of prevalence and mortality is calculated with minimal assumptions. The resulting expressions for the components of the trends are given by continuous functions of data. The estimator is consistent and stable. The developed methodology is applied for data on type 2 diabetes using individual records from a nationally representative 5% sample of Medicare beneficiaries age 65+. Numerical estimates show excellent concordance between empirical estimates and theoretical predictions. Evaluated partitioning model showed that both prevalence and mortality increase with time. The primary driving factors of the observed prevalence increase are improved survival and increased prevalence at age 65. The increase in diabetes-related mortality is driven by increased prevalence and unobserved trends in time-periods and age-groups outside of the range of the data used in the study. Finally, the properties of the new estimator, possible statistical and systematical uncertainties, and future practical applications of this methodology in epidemiology, demography, public health and health forecasting are discussed.Item Open Access Underlying mechanisms of change in cancer prevalence in older U.S. adults: contributions of incidence, survival, and ascertainment at early stages.(Cancer causes & control : CCC, 2022-09) Akushevich, I; Yashkin, A; Kovtun, M; Yashin, AI; Kravchenko, JPurpose
To quantitatively evaluate contributions of trends in incidence, relative survival, and stage at diagnosis to the dynamics in the prevalence of major cancers (lung, prostate, colon, breast, urinary bladder, ovaries, stomach, pancreas, esophagus, kidney, liver, and skin melanoma) among older U.S. adults age 65 +.Methods
Trend partitioning was applied to the Surveillance, Epidemiology, and End Results Program data for 1973-2016.Results
Growth of cancer prevalence in older adults decelerated or even decreased over time for all studied cancers due to decreasing incidence and improving survival for most of cancers, with a smaller contribution of the stage at cancer diagnosis. Changes in the prevalence of cancers of the lung, colon, stomach, and breast were predominantly due to decreasing incidence, increasing survival and more frequent diagnoses at earlier stages. Changes in prevalence of some other cancers demonstrated adverse trends such as decreasing survival in localized and regional stages (urinary bladder and ovarian) and growing impact of late-stage diagnoses (esophageal cancer).Conclusion
While decelerating or decreasing prevalence of many cancers were due to a beneficial combination of decreasing incidence and increasing survival, there are cancers for which decelerating prevalence is due to lack of improvement in their stage-specific survival and/or increasing frequency of diagnosis at advanced stages. Overall, if the observed trends persist, it is likely that the burden associated with cancer prevalence in older U.S. adults will be lower comparing to projections based on constant increasing prevalence have previously estimated.