Breast Cancer in Afghan Women: A Systematic Review of Awareness, Screening Practices, and Risk Factors
Bibliographic record
Abstract
BACKGROUND: Breast cancer is the most prevalent and diagnosed tumor among women globally. There is limited data regarding its incidence and prevention in Afghanistan and among Afghan refugees. Sociopolitical instability, low awareness, and restricted access to healthcare may all lead to late-stage diagnosis and adverse results of breast cancer among Afghan women. AIM: This systematic study intends to analyze the available studies on breast cancer awareness, sociocultural, screening practices, and risk factors among Afghan women. METHODS: A systematic search was conducted in PubMed, Google Scholar, Scopus, Web of Science, and institutional repositories for studies published from 2013 to 2024. The keywords included “breast cancer,” “Afghanistan,” “Afghan women,” “awareness,” “screening,” “sociocultural,” and “risk factors.” Studies were chosen according to specified inclusion and exclusion criteria. Data were extracted using a standardized form and assessed for quality with the JBI and Newcastle-Ottawa tools. Due to the variety in study designs and outcomes, an exploratory approach was used. RESULTS: From 50 articles, nine studies met the inclusion criteria, including a total sample of over 3,085 Afghan women. Most studies were cross-sectional, with a few qualitative and case-control designs. Breast cancer awareness was generally low, with less than 40% of participants aware of breast clinical screening methods or self-examination (BSE). Screening rates were low, delayed menstruation, family history of cancer, obesity, sociocultural practices, religious reasons, low health literacy, and lack of female health professionals were found to be the main risk factors among Afghan and refugee women. Barriers to timely diagnosis and treatment included conflict-related infrastructure gaps, stigma, and gender norms restricting women’s participation in making healthcare decisions. CONCLUSION: Breast cancer in Afghan women has been under-studied and poorly addressed by the national public health system. Low awareness of breast cancer, low screening practice, or lack of information, and cultural and systemic barriers to delayed diagnosis and treatment are the main reasons. Since the political changes in Afghanistan after 2021, women’s access to public awareness about breast cancer, educational centers, and health facilities have been significantly limited. To reduce the incidence of disease in this society, public health interventions should be implemented to enhance access to female-led healthcare services and treatment.
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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 | 0.008 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".