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The objective was to evaluate the association between serum carotenoid levels and respiratory morbidity and mortality in a nationally representative sample of US adults. We assessed the association of serum carotenoid levels with respiratory morbidity and mortality using logistic regression and proportional hazards regression models. Meanwhile, a series of confounders were controlled in regression models and restricted cubic spline, which included age, sex, race, marriage, education, income, drinking, smoking, regular exercise, BMI, daily energy intake, vitamin E, vitamin C, fruit intake, vegetable intake, diabetes, hypertension, asthma, emphysema and chronic bronchitis. Compared with participants in the lowest tertiles, participants in the highest tertiles of serum total carotenoids, β -cryptoxanthin and lutein/zeaxanthin levels had a significantly lower prevalence of emphysema (ORtotal carotenoids = 0·61, 95% CI: 0·41–0·89, OR β -cryptoxanthin = 0·67, 95% CI: 0·49–0·92), chronic bronchitis (OR β -cryptoxanthin = 0·66, 95% CI: 0·50–0·87) and asthma (Q2: ORlutein/zeaxanthin = 0·78, 95% CI: 0·62–0·97); participants in the highest tertiles of total carotenoids, α -carotene, lutein/zeaxanthin and lycopene had a lower risk of respiratory mortality (hazard ratio (HR)total carotenoids = 0·62, 95% CI: 0·42–0·90, HR α -carotene = 0·54, 95% CI: 0·36–0·82, HRlutein/zeaxanthin = 0·48, 95% CI: 0·33–0·71, HRlycopene = 0·66, 95% CI: 0·45–0·96) than those in the lowest tertiles. Higher serum total carotenoids and β -cryptoxanthin levels is associated with decreased prevalence of emphysema and chronic bronchitis, and higher serum total carotenoids, α -carotene, lutein/zeaxanthin and lycopene levels had a lower mortality of respiratory disease. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study is to investigate the trends in incidence and mortality, and explore any change in survival of penile cancer in the United States. Methods: We obtained data from the Surveillance, Epidemiology, and End Results (SEER) database (2000–2018) utilizing the SEER Stat software. The joinpoint regression was used to analyze the secular trend of incidence and incidence-based mortality (IBM) stratified by age, race, and summary stage. The 5-year relative survival rate was also calculated. Result: The age-adjusted rates of penile cancer patients were 0.38 (0.37–0.39) and 0.21 (0.2–0.21) for overall incidence and IBM, respectively. The 5-year relative survival rates were 67.7%, 66.99%, and 65.67% for the calendar periods of 2000–2004, 2005–2009, and 2010–2014, respectively. No significant changes in incidence by era were observed from 2000 to 2018 [annual percentage change (APC) = 0.5%, p = 0.064]. The IBM rate of penile cancer showed an initial significant increase from 2000 to 2002 (APC = 78.6%, 95% CI, −1.7–224.6) followed by a deceleration rate of 4.6% (95% CI, 3.9–5.3) during 2002 to 2018. No significant improvement in 5-year relative survival was observed. The trends by age, race, and summary stage in incidence and IBM were significantly different. Conclusion: This study, using population-level data from the SEER database, showed an increasing trend in IBM and no significant improvement in the 5-year relative survival rate. Meanwhile, the incidence of penile cancer exhibited a relatively stable trend during the study period. These results might be due to the lack of significant progress in the treatment and management of penile cancer patients in the United States in recent decades. More efforts, like increasing awareness among the general population and doctors, and centralized management, might be needed in the future to improve the survival of this rare disease. [ABSTRACT FROM AUTHOR]

Background: Penile squamous cell carcinoma (PSCC) survival had no significant improvement since 1990 in the United States. This study aims to get insight into the changing trend and distribution of death causes of PSCC. The epidemiology of PSCC is also investigated. Methods: The Surveillance, Epidemiology, and End Results (SEER) (1992–2018) database is utilized to get patients diagnosed with penile squamous cell carcinoma. The trend of incidence, distribution of age, changing trend and distribution of death cause, and survival outcome are analyzed for all PSCC patients and each race. Results: Three thousand four hundred and twenty‐three male patients with PSCC are enrolled in our study. The age‐adjusted incidence rate of the white has a slight increase (Annual percent change [APC] = 0.647%). American Indian/Alaska Native men have the highest average annual incidence, while Asian /Pacific Islander men have the lowest. PSCC patients aged 70–80 are the most common, and patients over 80 years have the highest 3‐year (50%) and 5‐year (63.93%) mortality rate. Non‐cancer disease, especially circulatory system disease, is the most common cause of death, whereas the proportion of patients who died of PSCC significantly increased from 21.17% (1992–2001) to 41.3% (2012–2017) in PSCC patients (p < 0.001). These results have not changed significantly when we only focus on primary PSCC without previous malignant tumors. Hispanics are shown better overall survival than non‐Hispanic White and non‐ Hispanic Black men. (p < 0.001) No statistical differences in cancer‐specific survival are observed (p = 0.15). Conclusion: The current study provides essential initial data regarding the presentation and clinical outcomes of PSCC patients. Notably, non‐cancer disease, especially circulatory system disease, is the more common cause of death than PSCC. However, the proportion of patients who died of penile squamous cell carcinoma has a relatively significant increase in recent years. The increasing trends in the advanced stage of PSCC patients might account for this change. [ABSTRACT FROM AUTHOR]

Background: Suicide in cancer survivors is a major public health concern, but its trends and risk factors are not well understood. This study aimed to investigate the standardized mortality rate (SMR) and trends in suicide among cancer survivors in the United States., Methods: Using data from the SEER-9 database and US Mortality data, we identified 3,684,040 cancer survivors diagnosed between 1975 and 2020. The SMR of suicide among cancer survivors was calculated, and Poisson regression analysis was used to evaluate trends in suicide risk. Subgroup analyses were performed based on age, gender, race, tumor site, and stage. A competing risk model was used to calculate the 10-year cumulative incidence of suicide., Results: Among cancer survivors, the overall SMR of suicide was 1.49 (95%CI: 1.46-1.53) times higher than that of the general population in the US. The risk of suicide varied significantly by cancer site, with the highest risk found in patients with malignant respiratory system cancer. Overall, we observed a significant downward trend in the suicide mortality rate among cancer patients. The cumulative incidence of suicide mortality among cancer survivors across four study periods exhibited significant statistical differences ( P <0.001)., Conclusions: Our study highlights the need for targeted suicide prevention efforts for cancer survivors, particularly those diagnosed with respiratory system cancer. The trend of declining suicide mortality rates among cancer survivors is promising, but continued efforts are needed to understand and address the underlying risk factors.

In this paper, we developed a feasible and efficient deep-learning-based framework to combine the United States (US) natality data for the last five decades, with changing variables and factors, into a consistent database. We constructed a graph based on the property and elements of databases, including variables, and conducted a graph convolutional network (GCN) to learn the embeddings of variables on the constructed graph, where the learned embeddings implied the similarity of variables. Specifically, we devised a loss function with a slack margin and a banlist mechanism (for a random walk) to learn the desired structure (two nodes sharing more information were more similar to each other.), and developed an active learning mechanism to conduct the harmonization. Toward a total of 9,321 variables from 49 databases (i.e., 783 stemmed variables, from 1970 to 2018), we applied our model iteratively together with human reviews for four rounds, then obtained 323 hyperchains of variables. During the harmonization, the first round of our model achieved recall and precision of 87.56%, 57.70%, respectively. Our harmonized graph neural network (HGNN) method provides a feasible and efficient way to connect relevant databases at a meta-level. Adapting to the database's property and characteristics, HGNN can learn patterns globally, which is powerful to discover the similarity between variables among databases. Our proposed method provides an effective way to reduce the manual effort in database harmonization and integration of fragmented data into useful databases for future research., (Copyright © 2021 Elsevier Inc. All rights reserved.)