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Patients with breast cancer can survive and live a long, cancer-free life; however, late complications of treatment, such as second primary malignancies (SPMs), have emerged as a competing cause of death and morbidity. We conducted a long-term population-based cohort study to identify the risk factors for SPMs and specific secondary cancer types after various latency periods of irradiated breast cancer. Cox proportional hazards regression was used to calculate the hazard ratio (HR) and 95% confidence interval (95% CI) for independent risk factors for SPM. We also calculated the HR of each specific cancer type and the latency time to specific SPMs. The risk of SPM was statistically significantly higher in patients with adjuvant RT than in patients without adjuvant RT (adjusted HR [aHR]: 1.105, 95% CI: 1.013-1.206). Compared with the control group, the case group had significantly increased risks of contralateral breast cancer (aHR: 1.268, 95% CI: 1.112-1.445), lung cancer (aHR: 1.218, 95% CI: 1.049-1.565), and urinary system cancer (aHR: 1.702, 95% CI: 1.140-2.543). Adjuvant RT for breast cancer increases the risk of SPM. Contralateral breast cancer, lung cancer, and bladder cancer were significant SPMs after breast RT, although the cumulative risk of SPM was low, at approximately 6, 10, and 13 cancers per 1000 women with irradiated breasts at latency periods of 5, 10, and 15 years, respectively, after breast RT., Competing Interests: None., (AJCR Copyright © 2022.)

Diseases can be interconnected. In the recent years, there has been a surge of multidisease studies. Among them, HDN (human disease network) analysis takes a system perspective, examines the interconnections among diseases along with their individual properties, and has demonstrated great potential. Most of the existing HDN analyses are based on either molecular information (which may be unreliable and have limited clinical relevance) or phenotypic measures (which may have limited implications for disease management and not directly reflect disease severity). In this study, we take advantage of the uniquely valuable Taiwan NHIRD (National Health Insurance Research Database) data and conduct an HDN analysis of disease treatment cost. Complementing the existing literature, treatment cost can serve as a surrogate of disease severity (and hence be clinically highly relevant) and also directly describe the financial burden of illness (and hence be uniquely informative for disease management). With inpatient and outpatient treatment data on close to 1 million randomly selected subjects and collected during the period of 2000 to 2013, the human disease cost network is constructed using a novel copula-based approach and the weighted correlation-based network construction technique. Extensive analysis is conducted, and the results are found to be biomedically sensible., (© 2020 John Wiley & Sons, Ltd.)

With accumulating research on the interconnections among different types of genomic regulations, researchers have found that multidimensional genomic studies outperform one-dimensional studies in multiple aspects. Among many sources of multidimensional genomic data, The Cancer Genome Atlas (TCGA) provides the public with comprehensive profiling data on >30 cancer types, making it an ideal test bed for conducting and comparing different analyses. In this article, the analysis goal is to apply several existing methods and associate multidimensional genomic measurements with cancer outcomes in particular prognosis, with special focus on the predictive power of genomic signatures. We exploit clinical data and four types of genomic measurement including mRNA gene expression, DNA methylation, microRNA and copy number alterations for breast invasive carcinoma, glioblastoma multiforme, acute myeloid leukemia and lung squamous cell carcinoma collected by TCGA. To accommodate the high dimensionality, we extract important features using Principal Component Analysis, Partial Least Squares and Least Absolute Shrinkage and Selection Operator (Lasso), which are representative of dimension reduction and variable selection techniques and have been extensively adopted, and fit Cox survival models with combined important features. We calibrate the predictive power of each type of genomic measurement for the prognosis of four cancer types and find that the results vary across cancers. Our analysis also suggests that for most of the cancers in our study and the adopted methods, there is no substantial improvement in prediction when adding other genomic measurement after gene expression and clinical covariates have been included in the model. This is consistent with the findings that molecular features measured at the transcription level affect clinical outcomes more directly than those measured at the DNA/epigenetic level., (© The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.)

Background: Illness and the medical expenditure that follows have a profound impact on the well-being of individuals and households. China is a huge country with significant regional differences. The goal of this study is to investigate the associations of illness and medical expenditure with other categories of household expenditures, with special attention paid to the differences in observations between the western and eastern regions., Methods: A survey was conducted in six major cities in China, three in the east and three in the west, in 2011. Data on demographics, illness conditions, and medical and other expenditures were collected from 12,515 households., Results: In the analysis of the associations of illness conditions and medical expenditure with demographics, multiple significant associations were observed, and there are differences between the eastern and western regions. In univariate analyses, illness conditions and medical expenditure were found as having significant associations with other categories of expenditures. In multivariate analyses adjusting for household and household head characteristics, few associations were observed, and there exist differences between the regions., Conclusions: This study has provided empirical evidence on the associations of illness/medical expenditure with demographics and with other categories of expenditures. Differences across regions were observed in multiple aspects. The reasons underlying such differences are worth investigating further.

In cancer studies with high-throughput genetic and genomic measurements, integrative analysis provides a way to effectively pool and analyze heterogeneous raw data from multiple independent studies and outperforms "classic" meta-analysis and single-dataset analysis. When marker selection is of interest, the genetic basis of multiple datasets can be described using the homogeneity model or the heterogeneity model. In this study, we consider marker selection under the heterogeneity model, which includes the homogeneity model as a special case and can be more flexible. Penalization methods have been developed in the literature for marker selection. This study advances from the published ones by introducing the contrast penalties, which can accommodate the within- and across-dataset structures of covariates/regression coefficients and, by doing so, further improve marker selection performance. Specifically, we develop a penalization method that accommodates the across-dataset structures by smoothing over regression coefficients. An effective iterative algorithm, which calls an inner coordinate descent iteration, is developed. Simulation shows that the proposed method outperforms the benchmark with more accurate marker identification. The analysis of breast cancer and lung cancer prognosis studies with gene expression measurements shows that the proposed method identifies genes different from those using the benchmark and has better prediction performance., (© 2014 WILEY PERIODICALS, INC.)

Background: Illness conditions lead to medical expenditure. Even with various types of medical insurance, there can still be considerable out-of-pocket costs. Medical expenditure can affect other categories of household consumptions. The goal of this study is to provide an updated empirical description of the distributions of illness conditions and medical expenditure and their associations with other categories of household consumptions., Methods: A phone-call survey was conducted in June and July of 2012. The study was approved by ethics review committees at Xiamen University and FuJen Catholic University. Data was collected using a Computer-Assisted Telephone Survey System (CATSS). "Household" was the unit for data collection and analysis. Univariate and multivariate analyses were conducted, examining the distributions of illness conditions and the associations of illness and medical expenditure with other household consumptions., Results: The presence of chronic disease and inpatient treatment was not significantly associated with household characteristics. The level of per capita medical expenditure was significantly associated with household size, income, and household head occupation. The presence of chronic disease was significantly associated with levels of education, insurance and durable goods consumption. After adjusting for confounders, the associations with education and durable goods consumption remained significant. The presence of inpatient treatment was not associated with consumption levels. In the univariate analysis, medical expenditure was significantly associated with all other consumption categories. After adjusting for confounding effects, the associations between medical expenditure and the actual amount of entertainment expenses and percentages of basic consumption, savings, and insurance (as of total consumption) remained significant., Conclusion: This study provided an updated description of the distributions of illness conditions and medical expenditure in Taiwan. The findings were mostly positive in that illness and medical expenditure were not observed to be significantly associated with other consumption categories. This observation differed from those made in some other Asian countries and could be explained by the higher economic status and universal basic health insurance coverage of Taiwan.

Background: The main goal of this study is to examine the distributions of illness conditions and resulting medical expenditures and their associated factors. To achieve this goal, an in-house survey was conducted in August of 2012 in rural Beijing, the capital city of China., Results: The survey was conducted in Nanjianchang and Beijianchang, which are two villages 20 KM away from Miyun, a satellite city of Beijing. Data was collected on 346 households, which included 834 members. Variables measured included household characteristics, household head characteristics, illness conditions, and medical expenditures. Illness conditions and corresponding expenditure were measured for inpatient treatment, outpatient treatment, and self-treatment separately. Multivariate analysis suggested that the presence of inpatient treatment was associated with household head characteristics including age, gender, and education. The presence of a high level of outpatient treatment was associated with household head characteristics including gender and education. The presence of a high level of self-treatment was significantly associated with household size. In the analysis of overall out-of-pocket (OOP) medical expenditure, only age of household head was borderline significant. In the analysis of OOP inpatient expenditure, age and gender of household head were borderline significant. The OOP outpatient expenditure was associated with household size, presence of members older than 60, household head's gender, marital status, and occupation. The OOP self-treatment expenditure was not associated with any household characteristic., Conclusions: For the surveyed households, medical expenditure made up a considerable proportion of the total consumption. This study suggested that the presence of illness conditions and resulting OOP medical expenditure were associated with certain household and household head characteristics. Such results may help identify the subgroup that is the most affected by illness conditions. As this study collected recent data on inpatient, outpatient, and self-treatment separately, it may provide a useful complement to the existing studies.

Background: The main goal of this study is to examine the associations between illness conditions and out-of-pocket medical expenditure with other types of household consumptions. In November and December of 2011, a survey was conducted in three cities in western China, namely Lan Zhou, Gui Lin and Xi An, and their surrounding rural areas., Results: Information on demographics, income and consumption was collected on 2,899 households. Data analysis suggested that the presence of household members with chronic diseases was not associated with characteristics of households or household heads. The presence of inpatient treatments was significantly associated with the age of household head (p-value 0.03). The level of per capita medical expense was significantly associated with household size, presence of members younger than 18, older than 65, basic health insurance coverage, per capita income, and household head occupation. Adjusting for confounding effects, the presence of chronic diseases was negatively associated with the amount of basic consumption (p-value 0.02) and the percentage of basic consumption (p-value 0.01), but positively associated with the percentage of insurance expense (p-value 0.02). Medical expenditure was positively associated with all other types of consumptions, including basic, education, saving and investment, entertainment, insurance, durable goods, and alcohol/tobacco. It was negatively associated with the percentage of basic consumption, saving and investment, and insurance., Conclusions: Early studies conducted in other Asian countries and rural China found negative associations between illness conditions and medical expenditure with other types of consumptions. This study was conducted in three major cities and surrounding areas in western China, which had not been well investigated in published literature. The observed consumption patterns were different from those in early studies, and the negative associations were not observed. This study may complement the existing rural studies and provide useful information on western Chinese cities.

Background: China has one of the world's largest health insurance systems, composed of government-run basic health insurance and commercial health insurance. The basic health insurance has undergone system-wide reform in recent years. Meanwhile, there is also significant development in the commercial health insurance sector. A phone call survey was conducted in three major cities in China in July and August, 2011. The goal was to provide an updated description of the effect of health insurance on the population covered. Of special interest were insurance coverage, gross and out-of-pocket medical cost and coping strategies., Results: Records on 5,097 households were collected. Analysis showed that smaller households, higher income, lower expense, presence of at least one inpatient treatment and living in rural areas were significantly associated with a lower overall coverage rate. In the separate analysis of basic and commercial health insurance, similar factors were found to have significant associations. Higher income, presence of chronic disease, presence of inpatient treatment, higher coverage rates and living in urban areas were significantly associated with higher gross medical cost. A similar set of factors were significantly associated with higher out-of-pocket cost. Households with lower income, inpatient treatment, higher commercial insurance coverage, and living in rural areas were significantly more likely to pursue coping strategies other than salary., Conclusions: The surveyed cities and surrounding rural areas had socioeconomic status far above China's average. However, there was still a need to further improve coverage. Even for households with coverage, there was considerable out-of-pocket medical cost, particularly for households with inpatient treatments and/or chronic diseases. A small percentage of households were unable to self-finance out-of-pocket medical cost. Such observations suggest possible targets for further improving the health insurance system.