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کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: Asian Pacific Journal of Cancer Prevention
- نوع مقاله: Journal Article
- کلمات کلیدی: fatty acids,Breast Neoplasms,Omega-3,fish consumption
- چکیده:
- چکیده انگلیسی: Objective: This systematic review and meta-analysis was performed to determine the protective effect of omega-3
fatty acids in fish consumption against breast cancer in Asian patients. Methods: The authors conducted a meta-analysis
of published research articles on protective effect of omega-3 fatty acids in fish consumption against breast cancer in
Asian patients published between January 2000 and July 2018 in online database of PubMed, ProQuest and EBSCO.
Pooled odds ratios (OR) were calculated by using fixed and random-effect models. Publication bias was visually
evaluated by using funnel plots and statistically assessed in Egger’s and Begg’s tests. Data were processed by Review
Manager 5.3 (RevMan 5.3) and Stata version 14.2 (Stata Corporation). Results: This study reviewed 913 articles.
There were 11 studies which conducted systematic review then continued by meta-analysis of relevant data with total
number of samples were 130,365 patients. The results showed there was protective effect of omega-3 fatty acids in fish
consumption against breast cancer in Asian patients (OR = 0.80 [95% CI 0.73-0.87, p <0.00001]). There was not any
study with significant publication bias included. Conclusion: This analysis confirmed the protective effect of omega-3
fatty acids in fish consumption against breast cancer in Asian patients.- انتشار مقاله: 31-05-1397
- نویسندگان: Ricvan Dana Nindrea,Teguh Aryandono,Lutfan Lazuardi,Iwan Dwiprahasto
- مشاهده
- جایگاه : پژوهشی
- مجله: Asian Pacific Journal of Cancer Prevention
- نوع مقاله: Journal Article
- کلمات کلیدی: Machine Learning,Breast cancer risk,calculation,algorithms
- چکیده:
- چکیده انگلیسی: Objective: The aim of this study was to determine the diagnostic accuracy of different machine learning algorithms
for breast cancer risk calculation. Methods: A meta-analysis was conducted of published research articles on diagnostic
test accuracy of different machine learning algorithms for breast cancer risk calculation published between January 2000
and May 2018 in the online article databases of PubMed, ProQuest and EBSCO. Paired forest plots were employed for
the analysis. Numerical values for sensitivity and specificity were obtained from false negative (FN), false positive (FP),
true negative (TN) and true positive (TP) rates, presented alongside graphical representations with boxes marking the
values and horizontal lines showing the confidence intervals (CIs). Summary receiver operating characteristic (SROC)
curves were applied to assess the performance of diagnostic tests. Data were processed using Review Manager 5.3
(RevMan 5.3). Results: A total of 1,879 articles were reviewed, of which 11 were selected for systematic review and
meta-analysis. Fve algorithms for machine learning able to predict breast cancer risk were identified: Super Vector
Machine (SVM); Artificial Neural Networks (ANN); Decision Tree (DT); Naive Bayes (NB); and K-Nearest Neighbor
(KNN). With the SVM, the Area Under Curve (AUC) from the SROC was > 90%, therefore classified into the excellent
category. Conclusion: The meta-analysis confirmed that the SVM algorithm is able to calculate breast cancer risk with
better accuracy value than other machine learning algorithms.- انتشار مقاله: 18-02-1397
- نویسندگان: Ricvan Dana Nindrea,Teguh Aryandono,Lutfan Lazuardi,Iwan Dwiprahasto
- مشاهده
- جایگاه : پژوهشی
- مجله: Asian Pacific Journal of Cancer Prevention
- نوع مقاله: Journal Article
- کلمات کلیدی: Breast cancer,methylation,BRCA1,Asia
- چکیده:
- چکیده انگلیسی: Objective: The aim of this study was to determine the degree of association of BRCA1 promoter methylation with
breast cancer in Asia. Methods: The study sample for the present meta-analysis was provided by published research
articles on associations of BRCA1 promoter methylation with breast cancer in Asia accessed through databases on
PubMed, ProQuest and EBSCO published between 1997 and November 2017. Pooled odds ratios (OR) were calculated
with fixed and random-effect models. Data were processed using Review Manager 5.3 (RevMan 5.3). Results: Of
a total of 475 articles, 11 studies were included in our systematic review with meta-analysis of relevant data. The
results showed a highly significant association between BRCA1 promoter methylation with breast cancer in Asia
(OR = 8.78 [95% CI 4.15-18.56, p < 0.00001]). Conclusion: This analysis confirmed association between BRCA1
promoter methylation and breast cancer in Asia. BRCA1 promoter assessment might be a predictive or diagnostic aid
for breast cancer prediction.- انتشار مقاله: 02-09-1396
- نویسندگان: Ricvan Dana Nindrea,Wirsma Arif Harahap,Teguh Aryandono,Lutfan Lazuardi
- مشاهده