scholarly journals Application of Neutrosophic Logic to Evaluate Correlation between Prostate Cancer Mortality and Dietary Fat Assumption

Symmetry ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 330 ◽  
Author(s):  
Muhammad Aslam ◽  
Mohammed Albassam
Keyword(s):  
Prostate Cancer ◽  
Dietary Fat ◽  
Death Rate ◽  
Prostate Cancer Risk ◽  
Cancer Death ◽  
Classical Statistics ◽  
Cancer Death Rate ◽  
Prostate Cancer Death ◽  
Fat Level ◽  
Uncertainty Environment

This paper presents an epidemiological study on the dietary fat that causes prostate cancer in an uncertainty environment. To study this relationship under the indeterminate environment, data from 30 countries are selected for the prostate cancer death rate and dietary fat level in the food. The neutrosophic correlation and regression line are fitted on the data. We note from the neutrosophic analysis that the prostate cancer death rate increases as the dietary fat level in the people increases. The neutrosophic regression coefficient also confirms this claim. From this study, we conclude that neutrosophic regression is a more effective model under uncertainty than the regression model under classical statistics. We also found a statistical correlation between dietary fat and prostate cancer risk.

State rurality does not increase risk of prostate cancer death.

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 119-119
Author(s):  
Alexander Geoffrey Shaw Anderson ◽  
Katie Murray
Keyword(s):  
Prostate Cancer ◽  
Cancer Screening ◽  
Rural Communities ◽  
Death Rate ◽  
Prostate Cancer Screening ◽  
Cancer Death ◽  
Psa Screening ◽  
The Us ◽  
Cancer Death Rate ◽  
Prostate Cancer Death

119 Background: Prostate cancer is the third most common cancer among men. PSA based screening for prostate cancer was introduced in the 1980s and resulted in a significant decline in prostate cancer mortality. Current AUA guidelines recommend PSA screening in average risk patients between the ages of 55 and 69. There are public health concerns in rural areas of the United States (US) potentially due to decreased access of care. In this study, we sought to evaluate the prevalence of prostate cancer screening and death rate in rural communities within the US. Methods: After IRB approval, data was collected from several different sources. Annual prostate cancer death rate (2011-2015) was obtained from the American Cancer Society. Data from the Behavioral Risk Factor Surveillance System regarding prostate cancer screening during this time interval was acquired. Data regarding populations was obtained from the US Census. Descriptive analyses were used to describe the population and Pearson Correlation Coefficient to determine screened, death rates and rurality correlations. All analyses were completed using SPSS. Results: The median percent of US population residing in rural and urban areas was 25.8% (IQR 22.1%) and 73.8% (IQR 22.1%), respectively. The median percent of male patients screened using PSA 50 years and older was 56.2% (IQR 7.0%). The median death rate (per 100,000) from prostate cancer per state was 19.5 (IQR 1.7%). Prostate cancer death rate was found to have no correlation to percent of population screened (p = 0.29) and percent rurality (p = 0.98). The percent rural population versus percent of screened men over the age of 50 was also not significant (p = 0.20). Conclusions: Neither death rate nor screening rate for prostate cancer using PSA demonstrated a significant association with the percent of patient’s living in rural communities. This is evidence that within the US, rural communities are following guidelines for PSA screening for prostate cancer and therefore there is no discrepancy in prostate cancer death in these areas compared to urban. This study is evidence that the barriers that may be associated with living in rural communities, such as decreased access to healthcare do not translate into worse outcomes related to prostate cancer.

scholarly journals Common genetic and clinical risk factors: Association with fatal prostate cancer in the Cohort of Swedish Men

2020 ◽  
Author(s):  
Minh-Phuong Huynh-Le ◽  
Roshan Karunamuni ◽  
Chun Chieh Fan ◽  
Wesley K Thompson ◽  
Kenneth Muir ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Risk Factors ◽  
Family History ◽  
Cancer Risk ◽  
Risk Stratification ◽  
Prostate Cancer Risk ◽  
Cancer Death ◽  
Clinical Variables ◽  
Prostate Cancer Death ◽  
Fatal Prostate Cancer

Background: Clinical variables--age, family history, genetics--are used for prostate cancer risk stratification. Recently, polygenic hazard scores (PHS46, PHS166) were validated as associated with age at prostate cancer diagnosis. While polygenic scores are associated with all prostate cancer (not specific for fatal cancers), PHS46 was also associated with age at prostate cancer death. We evaluated if adding PHS to clinical variables improves associations with prostate cancer death. Methods: Genotype/phenotype data were obtained from a nested case-control Cohort of Swedish Men (n=3,279; 2,163 with prostate cancer, 278 prostate cancer deaths). PHS and clinical variables (family history, alcohol intake, smoking, heart disease, hypertension, diabetes, body mass index) were tested via univariable Cox proportional hazards models for association with age at prostate cancer death. Multivariable Cox models with/without PHS were compared with log-likelihood tests. Results: Median age at last follow-up/prostate cancer death were 78.0 (IQR: 72.3-84.1) and 81.4 (75.4-86.3) years, respectively. On univariable analysis, PHS46 (HR 3.41 [95%CI 2.78-4.17]), family history (HR 1.72 [1.46-2.03]), alcohol (HR 1.74 [1.40-2.15]), diabetes (HR 0.53 [0.37-0.75]) were each associated with prostate cancer death. On multivariable analysis, PHS46 (HR 2.45 [1.99-2.97]), family history (HR 1.73 [1.48-2.03]), alcohol (HR 1.45 [1.19-1.76]), diabetes (HR 0.62 [0.42-0.90]) all remained associated with fatal disease. Including PHS46 or PHS166 improved multivariable models for fatal prostate cancer (p<10-15). Conclusions: PHS had the most robust association with fatal prostate cancer in a multivariable model with common risk factors, including family history. Impact: Adding PHS to clinical variables may improve prostate cancer risk stratification strategies.

scholarly journals Common genetic and clinical risk factors: Association with fatal prostate cancer in the Cohort of Swedish Men.

2021 ◽  
Vol 39 (6_suppl) ◽  
pp. 65-65
Author(s):  
Minh-Phuong Huynh-Le ◽  
Roshan Karunamuni ◽  
Chun Chieh Fan ◽  
Wesley K Thompson ◽  
Kenneth Muir ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Risk Factors ◽  
Family History ◽  
Cancer Risk ◽  
Alcohol Intake ◽  
Prostate Cancer Risk ◽  
Cancer Death ◽  
Clinical Variables ◽  
Prostate Cancer Death ◽  
Fatal Prostate Cancer

65 Background: Clinical variables (age, family history, and genetics) are commonly used for prostate cancer risk stratification. Recently, polygenic hazard scores (PHS46, PHS166) were validated as associated with age at prostate cancer diagnosis. While polygenic scores, including PHS, are associated with all prostate cancer and are not specific for fatal cancers, PHS46 was also associated with age at prostate cancer death. We evaluated if adding PHS to available clinical variables improves associations with prostate cancer death. Methods: Genotype and phenotype data were obtained from a nested case-control subset (n=3,279; 2,163 were diagnosed with prostate cancer, 278 died of prostate cancer) of the longitudinal, population-based Cohort of Swedish Men. PHS and clinical variables (family history, alcohol intake, smoking, heart disease, hypertension, diabetes history, and body mass index) were independently tested via univariable Cox proportional hazards models for association with age at prostate cancer death. Multivariable Cox models were constructed with clinical variables and PHS. Log-likelihood tests compared models. Results: Median age at last follow-up and at prostate cancer death were 78.0 (IQR: 72.3-84.1) and 81.4 (75.4-86.3) years, respectively. On univariable analysis, PHS46 (HR 3.41 [95% CI 2.78-4.17]), family history (HR 1.72 [1.46-2.03]), alcohol intake (HR 1.74 [1.40-2.15]), and diabetes (HR 0.53 [0.37-0.75]) were each associated with prostate cancer death. A multivariable clinical model including PHS46 improved associations for fatal disease ( p<10−15). On multivariable analysis, PHS46 (HR 2.45 [1.99-2.97]), family history (HR 1.73 [1.48-2.03]), alcohol intake (HR 1.45 [1.19-1.76]), and diabetes (HR 0.62 [0.42-0.90]) all remained associated with prostate cancer death. Similar results were found using the newer PHS166. Conclusions: PHS had the most robust association with fatal prostate cancer in a multivariable model with common clinical risk factors, including family history. Adding PHS to clinical variables may improve individualized prostate cancer risk stratification strategies.

2243 COMBINED VALUE OF GENOMIC BIOMARKERS AND CAPRA-S IN PREDICTING PROSTATE CANCER DEATH IN A HIGH-RISK SURGICAL COHORT

2013 ◽  
Vol 189 (4S) ◽  
Author(s):  
Matthew Cooperberg ◽  
Anamaria Crisan ◽  
Anirban Mitra ◽  
Mercedeh Ghadessi ◽  
Christine Buerki ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
High Risk ◽  
Cancer Death ◽  
Genomic Biomarkers ◽  
Prostate Cancer Death

scholarly journals Prostate cancer prognosis after initiation of androgen deprivation therapy among statin users. A population-based cohort study

2021 ◽  
Author(s):  
A. I. Peltomaa ◽  
P. Raittinen ◽  
K. Talala ◽  
K. Taari ◽  
T. L. J. Tammela ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Androgen Deprivation Therapy ◽  
Cancer Prognosis ◽  
Cancer Death ◽  
Psa Relapse ◽  
Prostate Cancer Death ◽  
Study Population ◽  
Statin Use ◽  
Prostate Cancer Prognosis

Abstract Purpose Statins’ cholesterol-lowering efficacy is well-known. Recent epidemiological studies have found that inhibition of cholesterol synthesis may have beneficial effects on prostate cancer (PCa) patients, especially patients treated with androgen deprivation therapy (ADT). We evaluated statins’ effect on prostate cancer prognosis among patients treated with ADT. Materials and methods Our study population consisted of 8253 PCa patients detected among the study population of the Finnish randomized study of screening for prostate cancer. These were limited to 4428 men who initiated ADT during the follow-up. Cox proportional regression model adjusted for tumor clinical characteristics and comorbidities was used to estimate hazard ratios for risk of PSA relapse after ADT initiation and prostate cancer death. Results During the median follow-up of 6.3 years after the ADT initiation, there were 834 PCa deaths and 1565 PSA relapses in a study cohort. Statin use after ADT was associated with a decreased risk of PSA relapse (HR 0.73, 95% CI 0.65–0.82) and prostate cancer death (HR 0.82; 95% CI 0.69–0.96). In contrast, statin use defined with a one-year lag (HR 0.89, 95% CI 0.76–1.04), statin use before ADT initiation (HR 1.12, 95% CI 0.96–1.31), and use in the first year on ADT (HR 1.02, 95% CI 0.85–1.24) were not associated with prostate cancer death, without dose dependency. Conclusion Statin use after initiation of ADT, but not before, was associated with improved prostate cancer prognosis.

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