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1.
J Cancer Biol ; 2(1): 25-32, 2021.
Article in English | MEDLINE | ID: mdl-34447972

ABSTRACT

This study examines differences between patients with and without cancer in patient demographic and clinical characteristics and COVID-19 mortality and discusses the implications of these differences in relation to existing cancer disparities and COVID-19 vulnerabilities. Data was collected as a part of a retrospective study on a cohort of COVID-19 positive patients across Mount Sinai Health System from March 28, 2020 to April 26, 2020. Descriptive, comparative, and regression analyses were applied to examine differences between patients with and without cancer in demographic and clinical characteristics and COVID-19 mortality and whether cancer status predicts COVID-19 mortality controlling for these covariates using SAS 9.4. Results showed that, of 4641 patients who tested positive for COVID-19, 5.1% (N=236) had cancer. The median age of the total sample was 58 years (Q1-Q3: 41-71); 55.3% were male, 19.2% were current/former smokers, 6.1% were obese. The most commonly reported comorbidities were hypertension (22.6%) and diabetes (16.0%). Overall, the COVID-19 mortality rate was 8.3%. Examining differences between COVID-19 patients with and without cancer revealed significant differences (p<0.05) in COVID-19 mortality, hospitalization rates, age, gender, race, smoking status, obesity, and comorbidity indicators (e.g., diabetes) with cancer patients more likely to be older, male, black, obese, smokers, and with existing comorbidities. Controlling for these clinical, demographic, and behavioral characteristics, results of logistic regression analyses showed significant effects of older age and male gender on COVID-19 mortality (p<0.05). While cancer patients with COVID-19 were more likely to experience worse COVID-19 outcomes, these associations might be related to common cancer and COVID-19 vulnerability factors such as older age and gender. The coexistence of these vulnerability age and gender factors in both cancer and COVID-19 populations emphasizes the need for better understanding of their implications for cancer and COVID-19 disparities, both diseases prevention efforts, policies, and clinical management.

2.
Aging Male ; 15(3): 115-23, 2012 Sep.
Article in English | MEDLINE | ID: mdl-22201700

ABSTRACT

OBJECTIVE: Effective erectile dysfunction (ED) treatments and cardiovascular disease (CVD) and diabetes risk assessments are available, but require patient-provider communication. The present study explored this issue using 2010 National Social Life, Health and Aging Project data for males age 57 years and older (n = 1011). METHODS: Multinomial logistic regression was performed to compare factors associated with being without CVD/diabetes (39.9%), being diagnosed with CVD only (43.1%), and having comorbid CVD/diabetes (CVD 17.0%). Logistic regression compared factors associated with having ever discussed sexual issues with physicians. RESULTS: CVD-only participants were more likely to be ≥ 75 years (p = 0.004) and smoke (p = 0.019); CVD&D participants were more likely to report activity limitations (p < 0.001) and less likely to have sex within the previous year (p = 0.014). Compared to CVD-only, men with CVD&D were more likely to be minorities, obese, have daily activity limitations, and report erectile difficulties (all p < 0.05). Males discussing sexual issues with physicians were more likely to report higher education [OR = 1.68, p = 0.001], have sex in previous year [OR = 1.73, p = 0.006], and have erectile difficulties [OR = 2.26, p < 0.001]. DISCUSSION: Increased patient and provider awareness and communication are needed to lifestyle behaviors, promote self-care practices, and improve health care utilization among male patients affected by chronic disease and ED.


Subject(s)
Cardiovascular Diseases/complications , Communication , Diabetes Complications , Erectile Dysfunction/etiology , Physician-Patient Relations , Sexuality , Aged , Aging/psychology , Disclosure , Educational Status , Erectile Dysfunction/psychology , Humans , Life Style , Male , Middle Aged , Regression Analysis
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