XGBG: A Novel Method for Identifying Ovarian Carcinoma Susceptible Genes Based on Deep Learning.

Ovarian carcinomas (OCs) represent a heterogeneous group of neoplasms consisting of several entities with pathogenesis, molecular profiles, multiple risk factors, and outcomes. OC has been regarded as the most lethal cancer among women all around the world. There are at least five main types of OCs classified by the fifth edition of the World Health Organization of tumors: high-/low-grade serous carcinoma, mucinous carcinoma, clear cell carcinoma, and endometrioid carcinoma. With the improved knowledge of genome-wide association study (GWAS) and expression quantitative trait locus (eQTL) analyses, the knowledge of genomic landscape of complex diseases has been uncovered in large measure. Moreover, pathway analyses also play an important role in exploring the underlying mechanism of complex diseases by providing curated pathway models and information about molecular dynamics and cellular processes. To investigate OCs deeper, we introduced a novel disease susceptible gene prediction method, XGBG, which could be used in identifying OC-related genes based on different omics data and deep learning methods. We first employed the graph convolutional network (GCN) to reconstruct the gene features based on both gene feature and network topological structure. Then, a boosting method is utilized to predict OC susceptible genes. As a result, our model achieved a high AUC of 0.7541 and an AUPR of 0.8051, which indicates the effectiveness of the XGPG. Based on the newly predicted OC susceptible genes, we gathered and researched related literatures to provide strong support to the results, which may help in understanding the pathogenesis and mechanisms of the disease.

Adjuvant radiotherapy did not increase the risk of coronary heart disease in patients with non-metastatic breast cancer.

OBJECTIVE: Adjuvant radiotherapy (RT) in patients with breast cancer can adversely cause the heart to receive some radiation doses, which may lead to cardiovascular diseases. The results of previous research regarding this issue are not consistent. Therefore, we conducted a nationwide population-based study in Taiwan to evaluate whether adjuvant RT for breast cancer patients increased the risk of developing coronary heart disease (CHD). METHODS: This retrospective cohort study examined data from the National Health Insurance Research Database, Registry for Catastrophic Illness Patients, and Taiwan Cancer Registry Database. We identified 83,733 patients with breast cancer between 1 January 2000 and 31 December 2017. Individuals without breast cancer from the general population were frequency-matched by age and index year with individuals with breast cancer. Participants were followed until the occurrence of a CHD event, the end of follow-up, or patient record removal due to death or withdrawal from the NHI. A Cox proportional hazards regression analysis was conducted to compare the risk of CHD in breast cancer patients with that in patients in the comparison cohort. RESULTS: Compared to breast cancer patients without RT, those who underwent RT had a similar risk of subsequently developing CHD (adjusted hazard ratio, 0.94; 95% confidence interval, 0.87-1.02). Similar results were observed in a subgroup of patients with left-sided breast cancer. However, among patients who received adjuvant RT, those with left-sided breast cancer had a significantly higher risk of CHD than did those with right-sided breast cancer (adjusted hazard ratio, 1.17; 95% confidence interval, 1.04-1.30). Patients who received RT in 2010 or later had a significantly lower risk of CHD compared with those who received RT before 2010 (adjusted hazard ratio, 0.64; 95% confidence interval, 0.45-0.91). Higher prescribed doses of RT to the left-sided breast did not correspond to a higher risk of CHD. CONCLUSION: This large, nationwide cohort study suggests that adjuvant RT in patients with breast cancer did not increase the risk of CHD.

Uterine myoma is associated with an increased risk of lung cancer: A nationwide population-based cohort study.

OBJECTIVE: The rate of lung cancer in female patients is increasing, with different features from male patients being displayed. Hormonal factors could play a role. The association between the development of uterine myoma (UM) and female hormones has also been reported. The relationship between female lung cancer and UM may be due to the effect of female hormones. METHODS: Data from 50 711 Taiwanese women with UM were retrieved from the National Health Insurance Research Database between 2000 and 2012. They were propensity-score matched with 50 711 women without UM (control group). A multivariate Cox proportional hazard regression model was used to compare the incidence of lung cancer between groups and to determine the hazard ratio of lung cancer in the UM group. RESULTS: The risk of lung cancer was significantly higher in women with myoma (adjusted hazard ratio: 1.62, 95% confidence ratio = 1.24-2.12). Stratified analyses demonstrated that the significantly increased risk of lung cancer was more likely to be found in certain groups, such as women who (a) are of younger age, (b) have a mid-level income, (c) have the highest urbanisation level, (d) are office workers and (e) with a longer follow-up period of myoma. Furthermore, myomectomy did not affect the risk pattern. CONCLUSION: The results from this nationwide population-based cohort study suggested that UM is associated with a higher risk of developing lung cancer. However, the exact underlying mechanism accounted for this remains unclear, and our findings still need to be verified by further comprehensive studies elsewhere.

Uterine Fibroids Increase the Risk of Thyroid Cancer.

OBJECTIVES: The formation of uterine fibroids (UF) is potentially linked to the development of thyroid cancer through a common factor: female sex hormones. METHODS: We conducted a nationwide population-based cohort study to determine whether Taiwanese women with UF have an increased risk of thyroid cancer. The data of both the UF and control groups were derived from the National Health Insurance Research Database (NHIRD) of Taiwan. Groups were matched by the year of UF diagnosis, age, income, urbanization level, occupation, and comorbidities. A Cox proportional hazard regression model was used to compare the incidence of thyroid cancer between the UF and control groups. In addition, the model was used to determine the hazard ratio of thyroid cancer in the UF group in comparison with the control group. RESULTS: Women with UF had a statistically significantly increased risk of thyroid cancer compared with controls (adjusted hazard ratio (aHR): 1.64, 95% confidence interval (CI): 1.26-2.13). Stratified analyses showed that women with UF who had a significantly increased risk of thyroid cancer were more likely to be middle aged, have middle and higher income levels, and a medium follow-up period (1-5 years) of UF. No other UF patient characteristics and comorbidities showed association with the risk of thyroid cancer. In addition, UF patients had a significantly increased risk of thyroid cancer regardless of whether or not they underwent myomectomy. CONCLUSIONS: The results suggest that women with UF have an increased risk of subsequent thyroid cancer. Further research is needed to explore whether surveillance strategies for the early detection of thyroid cancer using ultrasonography should be implemented among patients with UF.

Suicide attempts in patients with head and neck cancer in Taiwan.

OBJECTIVE: We examined the risk of suicide attempts in patients with head and neck cancer (HNC) in comparison with that in the general population and in patients of other cancers (including all other cancers rather than HNC). METHODS: The definition of suicide attempt here is that an attempt of suicide with or without completed suicide. This retrospective cohort study consisted of 66 931 cases of HNC and individual without HNC from the general population assigned to the control group. Cox's proportion hazard regression analysis was conducted to compare the subsequent suicide attempt risk between patients with HNC and the control group. RESULTS: The suicide attempt rate for HNC and control groups were 7.44 and 1.98 per 10 000 person-year, respectively. A more than three-fold higher risk of suicide attempts was observed in the HNC group than in the control group (adjusted hazard ratio [HR]: 3.72; 95% confidence intervals: 2.85, 4.88). Patients of HNC also had a significantly 1.9-fold higher risk of suicide attempt than patients with other cancers. Subsequent stratified analyses revealed a significantly elevated risk of suicide attempts across every cancer anatomic subsite and almost all categories of various demographics, but the risk was limited to male patients and patients with no comorbidity. The suicide attempt rate was the highest among patients with oropharyngeal cancer, and chemotherapy was associated with an elevated risk of suicide attempt. CONCLUSIONS: Patients with HNC are vulnerable to an increased risk of suicide attempts than the general population and patients with other cancers.

The Performance of Different Artificial Intelligence Models in Predicting Breast Cancer among Individuals Having Type 2 Diabetes Mellitus.

Objective: Early reports indicate that individuals with type 2 diabetes mellitus (T2DM) may have a greater incidence of breast malignancy than patients without T2DM. The aim of this study was to investigate the effectiveness of three different models for predicting risk of breast cancer in patients with T2DM of different characteristics. Study design and methodology: From 2000 to 2012, data on 636,111 newly diagnosed female T2DM patients were available in the Taiwan's National Health Insurance Research Database. By applying their data, a risk prediction model of breast cancer in patients with T2DM was created. We also collected data on potential predictors of breast cancer so that adjustments for their effect could be made in the analysis. Synthetic Minority Oversampling Technology (SMOTE) was utilized to increase data for small population samples. Each datum was randomly assigned based on a ratio of about 39:1 into the training and test sets. Logistic Regression (LR), Artificial Neural Network (ANN) and Random Forest (RF) models were determined using recall, accuracy, F1 score and area under the receiver operating characteristic curve (AUC). Results: The AUC of the LR (0.834), ANN (0.865), and RF (0.959) models were found. The largest AUC among the three models was seen in the RF model. Conclusions: Although the LR, ANN, and RF models all showed high accuracy predicting the risk of breast cancer in Taiwanese with T2DM, the RF model performed best.

Long-Term Use of Tamoxifen Is Associated With a Decreased Subsequent Meningioma Risk in Patients With Breast Cancer: A Nationwide Population-Based Cohort Study.

Background: Earlier studies have indicated a relatively higher risk of occurring meningioma among female breast cancer survivors and have suggested that tamoxifen might decrease this risk. The present study evaluated whether tamoxifen use in breast cancer patients can reduce the risk of meningioma. Methods: We designed a population-based cohort study by using data from the National Health Insurance system of Taiwan to assess this issue. Between January 1, 2000, and December 31, 2008, women with breast cancer and of age ≥20 years were included. They were divided into two groups: those who had not received tamoxifen therapy and those who had. The Cox's proportion hazard regression analysis was conducted to estimate the effects of tamoxifen treatment and the subsequent meningioma risk. Results: We identified a total of 50,442 tamoxifen users and 30,929 non-tamoxifen users. Tamoxifen users had a borderline significantly lower overall risk of meningioma than non-tamoxifen users [adjusted hazard ratio (aHR) = 0.64, 95% confidence interval (95% CI) = 0.40-1.02]. A statistically significant difference was found in those patients with tamoxifen treatment duration longer than 1,500 days (aHR = 0.42, 95% CI = 0.19-0.91) or with cumulative dosage exceeding 26,320 mg (aHR = 0.44, 95% CI = 0.22-0.88). Furthermore, no statistically significant joint effect of aromatase inhibitors and tamoxifen on the occurrence of meningioma among breast cancer patients was seen. Conclusion: Tamoxifen users had a non-significantly (36%) lower risk of developing meningioma than did tamoxifen non-users; however, our data indicated that tamoxifen therapy is associated with a reduced meningioma risk for Taiwanese breast cancer patients receiving long duration or high cumulative dosage treatment with tamoxifen.

Development of a prediction model for pancreatic cancer in patients with type 2 diabetes using logistic regression and artificial neural network models.

OBJECTIVES: Patients with type 2 diabetes (T2DM) are suggested to have a higher risk of developing pancreatic cancer. We used two models to predict pancreatic cancer risk among patients with T2DM. METHODS: The original data used for this investigation were retrieved from the National Health Insurance Research Database of Taiwan. The prediction models included the available possible risk factors for pancreatic cancer. The data were split into training and test sets: 97.5% of the data were used as the training set and 2.5% of the data were used as the test set. Logistic regression (LR) and artificial neural network (ANN) models were implemented using Python (Version 3.7.0). The F 1, precision, and recall were compared between the LR and the ANN models. The areas under the receiver operating characteristic (ROC) curves of the prediction models were also compared. RESULTS: The metrics used in this study indicated that the LR model more accurately predicted pancreatic cancer than the ANN model. For the LR model, the area under the ROC curve in the prediction of pancreatic cancer was 0.727, indicating a good fit. CONCLUSION: Using this LR model, our results suggested that we could appropriately predict pancreatic cancer risk in patients with T2DM in Taiwan.

Risk of suicide attempts among colorectal cancer patients: A nationwide population-based matched cohort study.

OBJECTIVE: Patients with colorectal cancer (CRC) have been found to have a higher risk of suicide in limited-number studies. However, data on the actual incidence rate of suicide remain scarce. METHODS: Using Taiwan's National Health Insurance Research Database, we examined whether patients with CRC in Taiwan are at increased risk of suicide attempts. In this retrospective matched cohort study, data of 96 470 cases of CRC during 1 January 2000 to 31 December 2010 were collected. The control group was derived from general population by frequency matching 2 individuals without CRC for each individual with CRC by year of CRC diagnosis, age, and sex. The suicide risk in the CRC group compared with the control group was determined through Cox proportional hazard regression. We also compared the Kaplan-Meier analyses to competing risk cumulative incidence curves using the Aalen-Johansen estimator. RESULTS: A statistically significant 103% higher risk of suicide was observed in the CRC group compared with the control group (adjusted hazard ratio: 2.03; 95% confidence ratio: 1.60-2.56). Additional stratified analyses revealed a significantly elevated risk across almost all demographic groups but limited to rectum location, short follow-up time (<5 years), and without comorbidity. CONCLUSIONS: Our study suggested that patients with CRC in Taiwan have an elevated risk of suicide. Oncologists should pay attention to these patients and should consider referring them for psychological consultation to prevent suicide.

Development of a Prediction Model for Colorectal Cancer among Patients with Type 2 Diabetes Mellitus Using a Deep Neural Network.

OBJECTIVES: Observational studies suggested that patients with type 2 diabetes mellitus (T2DM) presented a higher risk of developing colorectal cancer (CRC). The current study aims to create a deep neural network (DNN) to predict the onset of CRC for patients with T2DM. METHODS: We employed the national health insurance database of Taiwan to create predictive models for detecting an increased risk of subsequent CRC development in T2DM patients in Taiwan. We identified a total of 1,349,640 patients between 2000 and 2012 with newly diagnosed T2DM. All the available possible risk factors for CRC were also included in the analyses. The data were split into training and test sets with 97.5% of the patients in the training set and 2.5% of the patients in the test set. The deep neural network (DNN) model was optimized using Adam with Nesterov's accelerated gradient descent. The recall, precision, F1 values, and the area under the receiver operating characteristic (ROC) curve were used to evaluate predictor performance. RESULTS: The F1, precision, and recall values of the DNN model across all data were 0.931, 0.982, and 0.889, respectively. The area under the ROC curve of the DNN model across all data was 0.738, compared to the ideal value of 1. The metrics indicate that the DNN model appropriately predicted CRC. In contrast, a single variable predictor using adapted the Diabetes Complication Severity Index showed poorer performance compared to the DNN model. CONCLUSIONS: Our results indicated that the DNN model is an appropriate tool to predict CRC risk in patients with T2DM in Taiwan.

Cancer risk in patients with candidiasis: a nationwide population-based cohort study.

BACKGROUND: Candidiasis and certain types of cancer are related to immunocompromised status. This study aimed to evaluate whether Candida infection (CI) is associated with subsequent cancer risk in Taiwan. METHODS: Data from the National Health Insurance system of Taiwan were used to evaluate the association between CI and cancer risk. The CI cohort comprised 34,829 patients. Each patient was randomly frequency matched with one person from the general population without CI on the basis of age, sex, year of index date of CI diagnosis, and other characteristics to generate the control group. We used Cox's proportional hazard regression analysis to estimate the effects of CI on subsequent cancer risk. RESULTS: Compared with the control group, patients with CI had a significantly higher risk of overall cancer (adjusted hazard ratio = 1.19, 95% confidence interval = 1.09-1.30). For subsite analysis, the risks of hematologic malignancy and head and neck, pancreatic, skin, and thyroid cancers were significantly higher in the CI group. Stratified analyses by sex, age, and follow-up time revealed different patterns. CONCLUSION: Our study suggested that CI can significantly increase overall and some individual cancer risks, which is partially compatible with previous findings.

Risk of mood disorders in patients with colorectal cancer.

BACKGROUND: To assess the risk of mood disorders among patients with colorectal cancer (CRC), a population-based cohort study was performed using the Taiwanese National Health Insurance Research Database. METHODS: The study cohort included 27242 patients diagnosed with CRC between January 1, 2000 and December 31, 2010. Four insurants from the general population without CRC were frequency matched to each case by age, sex, and index year/month to create the control group. Cox's proportional hazard regression model with hazard ratios (HRs) and 95% confidence intervals (CIs) was conducted to estimate the impact of CRC on the risk of mood disorders. RESULTS: Patients with CRC exhibited a significantly higher risk of developing mood disorders (adjusted HR=3.05, 95% CI=2.89-3.20) compared with the control group. This phenomenon was also observed for each type of mood disorder (depression, bipolar disease and anxiety), as well as across different subgroups by patient characteristics. However, a follow-up time longer than 1 year was more likely to have significantly increased risks, and we unexpectedly found that some treatments in CRC patients tended to have a decreased risk of anxiety compared to their counterparts. CONCLUSION: The findings of this population-based cohort study suggest that patients with CRC are at a higher risk of mood disorders, especially when follow-up time is longer than 1 year, but various treatments may inversely affect this association.

Cancer risk in patients with osteoporosis: a population-based cohort study.

BACKGROUND: Osteoporosis has been associated with cancer development. We conducted a nationwide population-based cohort study in Taiwan to evaluate this possible association of osteoporosis with subsequent cancer development. METHODS: A total of 35,979 patients diagnosed with osteoporosis between 2000 and 2010 identified from the National Health Insurance Research Database comprised the osteoporosis cohort, and each patient was randomly frequency matched with one individual from the general population (without osteoporosis) based on age, sex, and year of osteoporosis diagnosis to form the non-osteoporosis (control) cohort. Cox proportional hazard regression analysis was used to calculate adjusted hazard ratios and 95% confidence intervals and determine the effect of osteoporosis on cancer risk. RESULTS: Patients with osteoporosis showed a significantly higher risk of developing liver and thyroid cancers and lower risk of colorectal cancer than did individuals without osteoporosis. Male patients with osteoporosis had a significantly increased risk for liver cancer, whereas female patients with osteoporosis had a significantly increased risk for thyroid cancer, but a significantly decreased risk for overall and colorectal cancers. In addition, more significant findings were observed when age ≤64 years or the follow-up duration was ≤5 years; however, a significantly lower risk for colorectal cancer was observed when follow-up duration was >5 years. Study limits including lack of data for some health-related behaviors, inclusion criteria of osteoporosis and potential selection bias have been discussed. CONCLUSION: Patients with osteoporosis showed a higher risk for liver and thyroid cancers and a lower risk for colorectal cancer than did control individuals. Stratified analyses by sex, age, and follow-up duration showed various patterns in different cancers.

Evaluating the consistency of location of the most severe acute skin reaction and highest skin dose measured by thermoluminescent dosimeter during radiotherapy for breast cancer.

We conducted this prospective study to evaluate whether the location of the most severe acute skin reaction matches the highest skin dose measured by thermoluminescent dosimeter (TLD) during adjuvant radiotherapy (RT) for patients with breast cancer after breast conservative surgery. To determine whether TLD measurement can reflect the location of the most severe acute skin reaction, 80 consecutive patients were enrolled in this prospective study. We divided the irradiated field into breast, axillary, inframammary fold, and areola/nipple areas. In 1 treatment session when obvious skin reaction occurred, we placed the TLD chips onto the 4 areas and measured the skin dose. We determined whether the highest measured skin dose area is consistent with the location of the most severe skin reaction. The McNemar test revealed that the clinical skin reaction and TLD measurement are more consistent when the most severe skin reaction occurred at the axillary area, and the p = 0.0108. On the contrary, TLD measurement of skin dose is less likely consistent with clinical observation when the most severe skin reaction occurred at the inframammary fold, breast, and areola/nipple areas (all the p > 0.05). Considering the common site of severe skin reaction over the axillary area, TLD measurement may be an appropriate way to predict skin reaction during RT.

Infective Endocarditis and Cancer Risk: A Population-Based Cohort Study.

This study investigated the possible relationship between endocarditis and overall and individual cancer risk among study participants in Taiwan.We used data from the National Health Insurance program of Taiwan to conduct a population-based, observational, and retrospective cohort study. The case group consisted of 14,534 patients who were diagnosed with endocarditis between January 1, 2000 and December 31, 2010. For the control group, 4 patients without endocarditis were frequency matched to each endocarditis patient according to age, sex, and index year. Competing risks regression analysis was conducted to determine the effect of endocarditis on cancer risk.A large difference was noted in Charlson comorbidity index between endocarditis and nonendocarditis patients. In patients with endocarditis, the risk for developing overall cancer was significant and 119% higher than in patients without endocarditis (adjusted subhazard ratio = 2.19, 95% confidence interval = 1.98-2.42). Regarding individual cancers, in addition to head and neck, uterus, female breast and hematological malignancies, the risks of developing colorectal cancer, and some digestive tract cancers were significantly higher. Additional analyses determined that the association of cancer with endocarditis is stronger within the 1st 5 years after endocarditis diagnosis.This population-based cohort study found that patients with endocarditis are at a higher risk for colorectal cancer and other cancers in Taiwan. The risk was even higher within the 1st 5 years after endocarditis diagnosis. It suggested that endocarditis is an early marker of colorectal cancer and other cancers. The underlying mechanisms must still be explored and may account for a shared risk factor of infection in both endocarditis and malignancy.

Risk of Nongenitourinary Cancers in Patients With Spinal Cord Injury: A Population-based Cohort Study.

Little information is available regarding the risk of nongenitourinary (GU) cancers in patients with spinal cord injury (SCI). The authors conducted a nationwide population-based study to investigate whether a higher risk of non-GU cancer is seen among patients with SCI.Data retrieved from the National Health Insurance Research Database of Taiwan were used in this study. A total of 41,900 patients diagnosed with SCI between 2000 and 2011 were identified from the National Health Insurance Research Database and comprised the SCI cohort. Each of these patients was randomly frequency matched with 4 people from the general population (without SCI) according to age, sex, comorbidities, and index year. Cox proportional hazards regression analysis was used to calculate adjusted hazard ratios and 95% confidence intervals and determine how SCI affected non-GU cancer risk.No significant difference in overall non-GU cancer risk was observed between the SCI and control groups. The patients with SCI exhibited a significantly higher risk of developing esophageal, liver, and hematologic malignancies compared with those without SCI. By contrast, the SCI cohort had a significantly lower risk of colorectal cancer compared with the non-SCI cohort (adjusted hazard ratio = 0.80, 95% confidence interval = 0.69-0.93). Additional stratified analyses by sex, age, and follow-up duration revealed various correlations between SCI and non-GU cancer risk.The patients with SCI exhibited higher risk of esophageal, liver, and hematologic malignancies but a lower risk of colorectal cancer compared with those without SCI. The diverse patterns of cancer risk among the patients with SCI may be related to the complications of chronic SCI.

Nonalcoholic Cirrhosis Increased Risk of Digestive Tract Malignancies: A Population-Based Cohort Study.

Alcoholic cirrhosis is generally accepted as a risk factor for hepatocellular carcinoma (HCC) development; however, little research has examined the relationship between nonalcoholic cirrhosis (NAC) and HCC. Thus, the aim of this study was to investigate whether NAC is associated with the risk of HCC and extrahepatic malignancies in Taiwan.We conducted a populated-based retrospective cohort study by using data from the Taiwan National Health Insurance (NHI) program. A total of 2109 patients with NAC were identified from the NHI database between 2000 and 2011. For a control group, 4 patients without NAC were frequency-matched with each NAC patient according to sex, age, and index year. We used Cox proportional hazards regression analysis to calculate adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) and determine the effects of NAC on cancer risk.The overall cancer risk was significantly higher in patients with NAC compared with those without NAC, and this association was consistent among age, sex, and comorbidity groups. The risk of developing HCC was remarkably high in the NAC group compared with in the control cohort (aHR = 122.7, 95% CI = 68.4-220.1); significantly higher risks of extrahepatic malignancies were observed in patients with digestive tract cancers and hematological malignancies. Further analyses stratified according sex, age, and follow-up duration revealed various patterns among the cancer types.The results indicate that patients with NAC in Taiwan have higher risks of HCC, digestive tract cancers, and hematological malignancies.

Statin Use Reduces Prostate Cancer All-Cause Mortality: A Nationwide Population-Based Cohort Study.

Studies have suggested that statin use is related to cancer risk and prostate cancer mortality. We conducted a population-based cohort study to determine whether using statins in prostate cancer patients is associated with reduced all-cause mortality rates. Data were obtained from the Taiwan National Health Insurance Research Database. The study cohort comprised 5179 patients diagnosed with prostate cancer who used statins for at least 6 months between January 1, 1998 and December 31, 2010. To form a comparison group, each patient was randomly frequency-matched (according to age and index date) with a prostate cancer patient who did not use any type of statin-based drugs during the study period. The study endpoint was mortality. The hazard ratio (HR) and 95% confidence interval (CI) were estimated using Cox regression models. Among prostate cancer patients, statin use was associated with significantly decreased all-cause mortality (adjusted HR = 0.65; 95% CI = 0.60-0.71). This phenomenon was observed among various types of statin, age groups, and treatment methods. Analyzing the defined daily dose of statins indicated that both low- and high-dose groups exhibited significantly decreased death rates compared with nonusers, suggesting a dose-response relationship. The results of this population-based cohort study suggest that using statins reduces all-cause mortality among prostate cancer patients, and a dose-response relationship may exist.

Radiotherapy did not increase thyroid cancer risk among women with breast cancer: A nationwide population-based cohort study.

The aim of this study was to evaluate whether an increased risk of thyroid cancer exists among women with breast cancer in Taiwan, particularly among those receiving RT. We used data from the National Health Insurance system of Taiwan for the investigation. The breast cancer cohort contained 55,318 women (including 28,187 who received RT and 27,131 who received no RT), each of whom was randomly frequency matched according to age and index year with three women without breast cancer from the general population. Cox's proportion hazards regression analysis was conducted to estimate the effects of breast cancer with or without RT treatment on subsequent thyroid cancer risk. We found that women with breast cancer exhibited a significantly higher risk of subsequent thyroid cancer (adjusted hazard ratio [aHR] = 1.98, 95% confidence interval [CI] = 1.60-2.44). The two groups (with or without RT) in the breast cancer cohort exhibited significantly increased risks. However, in the breast cancer cohort, the risk of thyroid cancer among women who received RT was not significantly higher than that of women who received no RT (aHR = 1.28, 95% CI = 0.90-1.83). Stratified analysis according to age revealed that only younger women with breast cancer (20-54 y) had a significantly higher risk of developing thyroid cancer. This study determined that Taiwanese women with breast cancer had a higher risk of developing thyroid cancer; however, RT seems to not play a crucial role in this possible relationship.