Factors Associated with Health-Related Quality of Life in Women with Breast Cancer in the Middle East: A Systematic Review
Bibliographic record
Abstract
OBJECTIVES: The aim of the present systematic review was to identify the factors that potentially influence health-related quality of life (HRQoL) in women with breast cancer (BC) in the Middle East. METHODS: A systematic search of the PubMed, Ovid Medline, Cochrane, Embase, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Scopus, and Ebscohost databases was conducted to identify all relevant articles published in peer-reviewed journals up to April 2018. The keywords were "Health related quality of life", "Breast Cancer", and "Middle East countries". The Newcastle-Ottawa (NOS) scale was used to evaluate the methodological quality of the included studies. Due to the methodological heterogeneity of the identified studies, no statistical pooling of the individual effect estimates was carried out; instead, the results were summarized descriptively. RESULTS: A total of 5668 articles were screened and 33 studies were retained. The vast majority of these studies were cross-sectional and only two were longitudinal prospective studies. Concerning the methodological quality, only 39% were of high quality. Our comprehensive literature review identified several modifiable and non-modifiable risk factors associated with HRQoL, including sociodemographic, clinical, and treatment-related factors as well as behavioral and psychosocial factors. CONCLUSION: This study has many implications for clinical practice and may provide a framework for establishing policy interventions to improve HRQoL among women with BC. Healthcare systems in the Middle East are encouraged to develop interventional programs targeting modifiable factors, particularly socio-demographic, behavioral, and psychosocial factors.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".