Health-related quality of life and its predictors among patients with breast cancer at Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia
Bibliographic record
Abstract
BACKGROUND: Breast cancer is the second most prevalent malignancy in Ethiopia and severely affects patients' health-related quality of life (HRQOL). We aimed to assess HRQoL, factors influencing HRQoL, and utilities among breast cancer patients at Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia. METHODS: A hospital-based cross-sectional study was conducted in Tikur Anbessa Specialized Hospital from December 2017 to February, 2018. A total of 404 breast cancer patients were interviewed using the validated Amharic version of the European Organization for Research and Treatment of Cancer module (EORTC QLQ-C30), EORTC QLQ-BR23, and Euro Quality of Life Group's 5-Domain Questionnaires 5 Levels (EQ-5D-5 L) instruments. Mean scores and mean differences of EORTC- QLQ-C30 and EORTC- QLQ-BR23 were calculated. One-way ANOVA test was employed to determine the significance of mean differences among dependent and independent variables while stepwise multivariate logistic regression was used to identify factors associated with the global quality of life (GQOL). Coefficients and level specific utility values obtained from a hybrid regression model for the Ethiopian population were used to compute utility values of each health state. Data was analyzed using SPSS version 23. RESULTS: The mean age of patients was 43.94 ± 11.72 years. The mean score for GQoL and visual analog scale was 59.32 ± 22.94 and 69.94 ± 20.36, respectively while the mean utility score was 0.8 ± 0.25. Predictors of GQoL were stage of cancer (AOR = 7.94; 95% CI: 1.83-34.54), cognitive functioning (AOR = 2.38; 95% CI: 1.32-4.31), pain (AOR = 7.99; 95% CI: 4.62-13.83), financial difficulties (AOR = 2.60; 95% CI: 1.56-4.35), and future perspective (AOR = 2.08; 95% CI: 1.24-3.49). CONCLUSIONS: The overall GQoL of breast cancer patients was moderate. Targeted approaches to improve patients' HRQoL should consider stage of cancer, cognitive functioning, pain, financial status and worries about the patient's future health. This study also provides estimates of EQ-5D utility scores that can be used in economic evaluations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".