BackgroundBreast cancer is the most common cancer affecting women in Ethiopia with increasing burden, and chemotherapy treatment produces a detrimental effect on individual wellbeing. Since last few years quality of life has been the primary goal of cancer treatment, yet little research has been conducted on quality of life of breast cancer patients under chemotherapy.ObjectiveTo determine the quality of life and associated factors among patients with breast cancer under chemotherapy at Tikur Anbessa specialized hospital, Addis Ababa, Ethiopia.MethodsInstitution based cross-sectional study was conducted on 404 patients with breast cancer, who took at least one cycle of chemotherapy treatment using face to face interview at oncology unit of Tikur Anbessa specialized hospital day care center from February to April 2018. The validated Amharic version of European organization for research and treatment of cancer core 30 (EORTC QLQ-C30) and quality of life questionnaire specific to breast (QLQ-BR23) was used to measure health related quality of life. Both descriptive and inferential statistics were used. For the purpose of interpretation quality of life score was dichotomized in to two using the calculated mean score, which is 53 as a cutoff point, then, bi-variable and multivariable logistic regression was used to describe association between dependent and independent variables. Hence, patients who score above 53 for quality of life were considered to have good quality of life.ResultOf the total sample, overall response rate was 99.77%. The average quality of life score of patients with breast cancer under chemotherapy treatment was 52.98 (SD = 25.61). Majority of patients had scored poor in emotional functioning, sexual functioning, and financial difficulties. Educational status of college and above, being divorced, higher household income, higher scores of physical and social functioning were associated with significantly improved (better) quality of life. Lower scores of fatigue, insomnia, financial difficulties and systemic therapy side effects all were associated with better scores of quality of life of breast cancer patients. Whereas, patients receiving < = 2 cycles of chemotherapy had significantly lower scores of quality of life.Conclusion and recommendationQuality of life of breast cancer patients under chemotherapy treatment is poor in comparison with the reference data and international findings. Therefore, quality of life assessment should be incorporated in patient’s treatment protocol. And financial aids may significantly improve the quality of life of breast cancer patients under chemotherapy treatment.
Genotype by environment (G×E) interaction is associated with the differential performance of genotypes tested at different locations and in different years, and influences selection and recommendation of cultivars. Wheat genotypes were evaluated in six environments to determine the G×E interactions and stability of the genotypes. Additive main effects and multiplicative interactions (AMMI) was conducted for grain yield of both year and it showed that grain yield variation due to environments, genotypes and (G×E) were highly significant (p <0.01). Stability for grain yield was determined using genotype plus genotype by environment interaction (GGE) biplot analysis. The first two principal components (PC1 and PC2) were used to create a 2-dimensional GGE biplot. Which-wonwhere pattern was based on six locations in the first and five locations in the second year for all the 20 genotypes. The resulting pattern is one realization among many possible outcomes, and its repeatability in the second was different and a future year is quite unknown. A repeatability of whichwon-where pattern over years is the necessary and sufficient condition for mega-environment delineations and genotype recommendation.
Selection of superior genotypes and measuring heritability are some of the basic objectives of plant breeding. For this purpose, plant breeders grow crops across environments. Understanding the pattern of response across environments is an integral component of selection of superior and stable genotypes. The objective of this study was to improve selection strategies in barley breeding of Ethiopia through modeling spatial field trend. A set of multi-environment trials (MET) data from the national variety trial series conducted over four years, was taken from the Ethiopian Barley Breeding Programme, spanning stages from early generation to national variety trial testing for yield, was used in this study. The trials were analysed in a linear mixed model framework. Then, fitting a one-stage model for MET data, including a correlated spatial process for field trend within each trial, and combining a factor analytic (FA) model for genotype by environment interaction was conducted. The genetic correlations from this MET analysis were then used to cluster the environments based on their similarity. Performance of genotypes across these environmental clusters indicate broad (Bekoji-2005 and Bekoji-2004) and specific adaptation (Sgonder-2007 and Sgonder-2006) of genotype to certain types of environments. In addition, analysis of this historical MET data shed light on how breeding programme design can be improved to capture responses across the target population of environments, as it can inform the adequacy of the current number of barley grown areas in Ethiopia and the improvement in measuring heritability.
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