METHODS: The PubMed, Scopus, and MEDLINE databases were systematically searched up to December 2019 to identify relevant studies. Random-effects model was used to calculate summary ORs and 95%CI for I 2 >50%. If the heterogeneity is not significant, the fixed-effects model was used. Overall analysis of the studies, inverse variance weighting after transforming the estimates of each study into log OR and its standard error were used.
RESULTS: 21 studies were included in this meta-analysis. Results showed that aspirin significantly reduced the GC risk (OR=0.64, 95%CI=0.54-0.76) with substantial heterogeneity (I 2 =96%). Effect of GC risk reduction in low dose (OR=0.80, 95%CI=0.59-1.09) is slightly greater than high dose aspirin (OR=1.08, 95%CI=0.77-1.52). Protective effect of aspirin uses >5 years (OR=0.67, 95%CI=0.34-1.31) was greater than <5 years (OR=1.01, 95%CI=0.72-1.43) Conclusion: In conclusion, this meta-analysis showed that low dose aspirin with longer duration of more than 5 years were associated with a statistically significant reduction in GC risk. However, due to possible confounding variables and bias, these results should be cautiously treated.
METHODS: This paper presents two hybrid methodologies that combines optimal control theory with multi-objective swarm and evolutionary algorithms and compares the performance of these methodologies with multi-objective swarm intelligence algorithms such as MOEAD, MODE, MOPSO and M-MOPSO. The hybrid and conventional methodologies are compared by addressing CMOOP.
RESULTS: The minimized tumor and drug concentration results obtained by the hybrid methodologies demonstrate that they are not only superior to pure swarm intelligence or evolutionary algorithm methodologies but also consumes far less computational time. Further, Second Order Sufficient Condition (SSC) is also used to verify and validate the optimality condition of the constrained multi-objective problem.
CONCLUSION: The proposed methodologies reduce chemo-medicine administration while maintaining effective tumor killing. This will be helpful for oncologist to discover and find the optimum dose schedule of the chemotherapy that reduces the tumor cells while maintaining the patients' health at a safe level.