Race differences in mobility status among prostate cancer survivors: The role of socioeconomic status

Prognostic significance of surgery and radiotherapy in elderly patients with localized prostate cancer: establishing and time-based external validation a nomogram from SEER-based study

OBJECTIVE

Prostate cancer (PC) is a significant disease affecting men's health worldwide. More than 60% of patients over 65 years old and more than 80% are diagnosed with localized PC. The current choice of treatment modalities for localized PC and whether overtreatment is controversial. Therefore, we wanted to construct a nomogram to predict the risk factors associated with cancer-specific survival (CSS) and overall survival (OS) in elderly patients with localized PC while assessing the survival differences in surgery and radiotherapy for elderly patients with localized PC.

METHODS

Data of patients with localized PC over 65 years were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression models were used to determine independent risk factors for CSS and OS. Nomograms predicting CSS and OS were built using multivariate Cox regression models. The consistency index (C-index), the area under the subject operating characteristic curve (AUC), and the calibration curve were used to test the accuracy and discrimination of the prediction model. Decision curve analysis (DCA) was used to test the potential clinical value of this model.

RESULTS

A total of 90,434 patients over 65 years and diagnosed with localized PC from 2010 to 2018 were included in the study. All patients were randomly assigned to the training set (n = 63,328) and the validation set (n = 27,106). Univariate and multivariate Cox regression model analysis showed that age, race, marriage, T stage, surgical, radiotherapy, prostate-specific antigen (PSA), and Gleason score (GS) were independent risk factors for predicting CSS in elderly patients with localized PC. Age, race, marriage, surgery, radiotherapy, PSA, and GS were independent risk factors for predicting OS in elderly patients with localized PC. The c-index of the training and validation sets for the predicted CSS is 0.802(95%CI:0.788-0.816) and 0.798(95%CI:0.776-0.820, respectively). The c-index of the training and validation sets for predicting OS is 0.712(95%:0.704-0.720) and 0.724(95%:0.714-0.734). It shows that the nomograms have excellent discriminatory ability. The AUC and the calibration curves also show good accuracy and discriminability.

CONCLUSION

We have developed new nomograms to predict CSS and OS in elderly patients with localized PC. After internal validation and external temporal validation with reasonable accuracy, reliability and potential clinical value, the model can be used for clinically assisted decision-making.

Racial disparity in the genomics of precision oncology of prostate cancer

BACKGROUND

Significant racial disparities in prostate cancer incidence and mortality have been reported between African American Men (AAM), who are at increased risk for prostate cancer, and European American Men (EAM). In most of the studies carried out on prostate cancer, this population is underrepresented. With the advancement of genome-wide association studies, several genetic predictor models of prostate cancer risk have been elaborated, as well as numerous studies that identify both germline and somatic mutations with clinical utility.

RECENT FINDINGS

Despite significant advances, the AAM population continues to be underrepresented in genomic studies, which can limit generalizability and potentially widen disparities. Here we outline racial disparities in currently available genomic applications that are used to estimate the risk of individuals developing prostate cancer and to identify personalized oncology treatment strategies. While the incidence and mortality of prostate cancer are different between AAM and EAM, samples from AAM remain to be unrepresented in different studies.

CONCLUSION

This disparity impacts the available genomic data on prostate cancer. As a result, the disparity can limit the predictive utility of the genomic applications and may lead to the widening of the existing disparities. More studies with substantially higher recruitment and engagement of African American patients are necessary to overcome this disparity.

Health Burdens and SES in Alabama: Using Geographic Information System to Examine Prostate Cancer Health Disparity

Simple Summary

The focus of the research was to examine the relationship between Socioeconomic status and prostate cancer in Alabama’s Black Belt region. The cancer rate in Alabama is high, and the state has one of the highest rates of prostate cancer in the USA. The research aims to identify probable reasons, raise awareness, and propose cancer prevention policies. The Geographic Information System, a robust technology, has been adopted to understand Alabama’s county-level prostate cancer incidence and mortality and its association with socioeconomic and health disparities. The analysis indicated an apparent socioeconomic disparity between the Black Belt and Non-Black Belt counties of Alabama. The poverty rate is higher in Black Belt counties. The data revealed that the preexisting condition of diabetes and obesity is closely associated with prostate cancer. Also, incidence and mortality disparities strongly relate to socioeconomic status, and the preexisting condition of obesity and diabetes adds to prostate cancer incidences. Poverty is the root course of inequalities in education, income, and healthcare facilities, particularly among African Americans, contributing to Alabama’s health burden of prostate cancer. The study proposes effective health policy intervention to prevent and reduce prostate cases and mortality among underserved communities in Alabama.

Abstract

Socioeconomic disparities influence the risk of many diseases, including cancer. The cancer rate in Alabama is high, and the state has one of the highest rates of prostate cancer in the USA. Alabama’s counties are embedded with socioeconomic disparities, politics, race, ethnicity, and oppression, among which social equity and socioeconomic status (SES) been closely associated with prostate cancer. The Geographic Information System (GIS) has become a valuable technology in understanding public health in many applications, including cancer. This study integrates Alabama’s county-level prostate cancer incidence and mortality and its association with socioeconomic and health disparities. We conducted robust data mining from several data sources such as the Alabama State Cancer Profile data, Alabama Department of Health, American Cancer Society, Center for Disease Control, and National Cancer Institute. The research method is the Geographic Information System (GIS), and we employed prostate cancer data within GIS to understand Alabama’s prostate cancer prevalence regarding SES. The GIS analysis indicated an apparent socioeconomic disparity between the Black Belt and Non-Black Belt counties of Alabama. The Black Belt counties’ poverty rate is also remarkably higher than non-Black Belt counties. In addition, we analyzed the median household income by race. Our analysis demonstrates that the Asian background population in the state earned the highest median income compared to non-Hispanic whites and the African American population. Furthermore, the data revealed that the preexisting condition of diabetes and obesity is closely associated with prostate cancer. The GIS analysis suggests that prostate cancer incidence and mortality disparities are strongly related to SES. In addition, the preexisting condition of obesity and diabetes adds to prostate cancer incidences. Poverty also reflects inequalities in education, income, and healthcare facilities, particularly among African Americans, contributing to Alabama’s health burden of prostate cancer.

A Web-Based Prediction Model for Cancer-Specific Survival of Elderly Patients Undergoing Surgery With Prostate Cancer: A Population-Based Study

Objective

Prostate cancer (PC) is the second leading cause of cancer death in men in the United States after lung cancer in global incidence. Elderly male patients over 65 years old account for more than 60% of PC patients, and the impact of surgical treatment on the prognosis of PC patients is controversial. Moreover, there are currently no predictive models that can predict the prognosis of elderly PC patients undergoing surgical treatment. Therefore, we aimed to construct a new nomogram to predict cancer-specific survival (CSS) in elderly PC patients undergoing surgical treatment.

Methods

Data for surgically treated PC patients aged 65 years and older were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression models were used to identify independent risk factors for elderly PC patients undergoing surgical treatment. A nomogram of elderly PC patients undergoing surgical treatment was developed based on the multivariate Cox regression model. The consistency index (C-index), the area under the subject operating characteristic curve (AUC), and the calibration curve were used to test the accuracy and discrimination of the predictive model. Decision curve analysis (DCA) was used to examine the potential clinical value of this model.

Results

A total of 44,975 elderly PC patients undergoing surgery in 2010–2018 were randomly assigned to the training set (N = 31705) and validation set (N = 13270). the training set was used for nomogram development and the validation set was used for internal validation. Univariate and multivariate Cox regression model analysis showed that age, marriage, TNM stage, surgical style, chemotherapy, radiotherapy, Gleason score(GS), and prostate-specific antigen(PSA) were independent risk factors for CSS in elderly PC patients undergoing surgical treatment. The C index of the training set and validation indices are 0.911(95%CI: 0.899–0.923) and 0.913(95%CI: 0.893–0.933), respectively, indicating that the nomogram has a good discrimination ability. The AUC and the calibration curves also show good accuracy and discriminability.

Conclusions

To our knowledge, our nomogram is the first predictive model for elderly PC patients undergoing surgical treatment, filling the gap in current predictive models for this PC patient population. Our data comes from the SEER database, which is trustworthy and reliable. Moreover, our model has been internally validated in the validation set using the C-index,AUC and the and the calibration curve, showed that the model have good accuracy and reliability, which can help clinicians and patients make better clinical decision-making. Moreover, the DCA results show that our nomogram has a better potential clinical application value than the TNM staging system.

Church Attendance and Mobility Limitation Among Black and White Men With Prostate Cancer

Prostate cancer is a significant impediment that can reduce physical functional status. Mobility is fundamental for quality of life and church attendance to be associated with improved physical functioning. Few studies have examined how religious participation have implications for mobility limitation among men in general and among prostate cancer survivors in particular. The purpose of this study was to assess the association between church attendance and mobility limitation among Black and White prostate cancer patients and survivors. Data for this investigation were drawn from the Diagnosis and Decisions in Prostate Cancer Treatment Outcomes Study that consisted of 804 Black and White men with complete information on the primary outcome and predictor variables. Mobility limitation was the primary outcome variable, and church attendance was the main independent variable. The analytic sample was almost equally divided between Black (N = 382) and White men (N = 422). The proportion of Black men reporting mobility limitation (30.09%) more than doubled the corresponding percentage for White men (14.7%). Black men had a higher proportion of individuals who reported weekly church attendance (49.2% vs. 45.0%). Fully adjusted modified Poisson regression models produced results indicating that respondents attending church weekly had a lower mobility limitation prevalence (PR = 0.56, 95% CI [0.39, 0.81]) than those never attending church. Results from this study contribute to the body of evidence asserting the health benefits of church attendance. These findings suggest that health providers should consider how religion and spirituality can present opportunities for improved outcomes in prostate cancer patients and survivors.

Diabetic mortality risk among cancer patients in the United State SEER population, 1975-2016

BACKGROUND

The focus on diabetic mortality in cancer patients remains superficial. The objective of our study is to identify cancer patients with the highest risk of diabetic mortality compared with other cancer patients and the general US population.

METHODS

The representative data of cancer patients dying from diabetes between 1975 and 2016 was retrieved from the Surveillance, Epidemiology, and End Results program. Standardized mortality ratios (SMRs) and excess risks for multiple cancer sites were calculated. Cox regression analysis was performed to identify potential risk factors of death from diabetes.

RESULTS

Among 9,043,788 cancer patients diagnosed between 1975 and 2016, 51,611 patients died from diabetes. the SMR of diabetic death was 2.15 compared with the general population. Malignancies of pancreas, liver, and brain had the highest SMR (>15) compared with the general population. The risk of death from diabetes was increasing in more recent years. The majority of deaths from diabetes occurred in those >45 years of age diagnosed with prostate, breast, colorectum, lung, or bladder cancer. Patients with older age, male sex, black race, higher histologic grade, unmarried status, and not undergoing surgery are at higher risk compared with other cancer survivors.

CONCLUSIONS

Compared to the general population, cancer patients are at elevated risk of death from diabetes throughout the follow-up period. Elderly, black, unmarried males with distant metastases and without receiving surgery are recommended with earlier detection and more efficient diabetic care, especially for those with prostate, breast, colorectum, lung, or bladder cancer.

The Association Between Depressive Symptoms and Accumulation of Stress Among Black Men in the Health and Retirement Study

BACKGROUND AND OBJECTIVES

Among the multiple factors posited to drive the health inequities that black men experience, the fundamental role of stress in the production of poor health is a key component. Allostatic load (AL) is considered to be a byproduct of stressors related to cumulative disadvantage. Exposure to chronic stress is associated with poorer mental health including depressive symptoms. Few studies have investigated how AL contributes to depressive symptoms among black men. The purpose of the cross-sectional study was to examine the association between AL and depressive symptoms among middle- to old age black men.

RESEARCH DESIGN AND METHODS

This project used the 2010 and 2012 wave of the Health and Retirement Study enhanced face-to-face interview that included a biomarker assessment and psychosocial questionnaire. Depressive symptoms, assessed by the endorsement of 3 or more symptoms on the Center for Epidemiological Studies-Depression 8-item scale, was the outcome variable. The main independent variable, AL, score was calculated by summing the number values that were in the high range for that particular biomarker value scores ranging from 0 to 7. black men whose AL score was 3 or greater were considered to be in the high AL group. Modified Poisson regression was used to estimate prevalence ratios (PRs) and corresponding 95% confidence intervals (CIs).

RESULTS

There was a larger proportion of black men in the high AL group who reported depressive symptoms (30.0% vs. 20.0%) compared with black men in the low AL group. After adjusting for age, education, income, drinking, and smoking status, the prevalence of reporting 3 or more depressive symptoms was statistically significant among black men in the high AL group (PR = 1.61 [95% CI: 1.20-2.17]) than black men in the low AL group.

DISCUSSION AND IMPLICATIONS

Exposure to chronic stress is related to reporting 3 or more depressive symptoms among black men after controlling for potential confounders. Improving the social and economic conditions for which black men work, play, and pray is key to reducing stress, thereby potentially leading to the reporting of fewer depressive symptoms.

A novel prognostic model for Japanese patients with newly diagnosed bone‐metastatic hormone‐naïve prostate cancer

Objectives

To evaluate the prognosis of newly diagnosed patients with metastatic hormone‐naïve prostate cancer (mHNPC) and develop a novel prognostic model based on ChemoHormonal Therapy Versus Androgen Ablation Randomized Trial for Extensive Disease in Prostate Cancer (CHAARTED) risk classifications.

Patients and methods

We retrospectively analyzed the data of 578 newly diagnosed mHNPC patients initially treated with androgen deprivation therapy. We evaluated three clinical factors, namely, CHAARTED risk classifications (high‐volume disease [HVD] vs low‐volume disease [LVD]), Gleason scores (GS, 9‐10 vs ≤8), and hemoglobin (Hb, ≤13.0 g/dL vs >13.0 g/dL), for their prognostic potential in predicting time to castration‐resistant prostate cancer (TTC) and overall survival (OS) of mHNPC patients by multivariate analysis. Moreover, we developed a novel prognostic model that consisted of significant prognostic factors.

Results

Of the entire cohort, the median TTC and OS values were 18.3 and 67.5 months, respectively. HVD, GS 9‐10, and Hb ≤13.0 g/dL were independent poor prognostic factors for both TTC and OS. We developed a novel prognostic model which could stratify mHNPC patients into four risk groups according to the numbers of poor prognostic factors: group 1, LVD with low‐risk (LVD patients without GS 9‐10 and Hb ≤13.0 g/dL); group 2, LVD with high‐risk (LVD patients with GS 9‐10, Hb ≤13.0 g/dL, or both); group 3, HVD with low‐risk (HVD patients without GS 9‐10 with or without Hb ≤13.0 g/dL); and group 4, HVD with high‐risk (HVD patients with GS 9‐10 with or without Hb ≤13.0 g/dL). The median TTC and OS of groups 1, 2, 3, and 4 were 124.8, 36.4, 17.9, and 11.2 months, and 117.2, 94.2, 67.9, and 46.2 months, respectively. A significant difference in TCC and OS was found between all groups.

Conclusion

We developed a prognostic model for mHNPC patients that consisted of CHAARTED risk classifications, GS, and Hb. Our prognostic model could significantly stratify the prognosis of patients with LVD and HVD into two groups each. This model might be a good reference for shared decision making between patients and physicians on the initial treatment for mHNPC.