Impact of Breast Cancer on Body Image: A Systematic Review and Meta-Analysis
Yazici Sarikaya, S.; Wang, R.; Kimmig, A.-C. S.; Brucker, S.; Hahn, M.; Wikman, A.; Derntl, B.
Show abstract
PurposeBreast cancer is the most common cancer among women worldwide. Although treatment is essential and often life-saving, it can have profound consequences beyond physical health, particularly for psychological well-being and body image. This study aimed to systematically review and synthesize the existing evidence on how breast cancer and its treatment affect body image in women. MethodsWe conducted a systematic search of four major electronic databases for peer-reviewed studies published up to 2025. In total, 41 studies met the inclusion criteria for the systematic review, and 24 were included in the meta-analysis. Standardized mean differences (SMDs) with 95% confidence intervals were calculated using a restricted maximum likelihood model. Analyses were performed in JAMOVI, and heterogeneity was assessed using Cochrans Q and I{superscript 2} statistics. The review was registered in PROSPERO (CRD42024503033). ResultsFemales with breast cancer reported significantly lower body image scores than healthy controls (ES = -1.02). Furthermore, body image scores declined from pre-treatment to during treatment (ES = -0.45). Mastectomy was associated with poorer body image compared to breast-conserving therapy (ES = -1-11). ConclusionAlthough medically essential, breast cancer treatment can adversely affect body image. Integrating body image support into treatment plans is crucial for promoting the overall health and quality of life of females diagnosed with breast cancer.
Matching journals
The top 1 journal accounts for 50% of the predicted probability mass.
Similar papers in this journal
- Factors associated with breast lesions among women attending select teaching and referral health facilities in Kenya: A cross-sectional study 94%
- Knowledge towards breast cancer, and breast self-examination practices and its barriers among university female students in Bangladesh: Findings from a cross-sectional study 94%
- Pre- and post-operative psychological interventions to prevent pain and fatigue after breast cancer surgery (PREVENT): a randomized controlled trial 94%
Similar papers in this journal
- Palliative care in the treatment of women with breast cancer: a scoping review protocol 96%
- Efficacy and safety of acupuncture for postpartum hypogalactia: Protocol for a systematic review and meta-analysis 91%
- Surgical candidacy and treatment uptake among women with cervical cancer at public referral hospitals in Kampala, Uganda 91%
Similar papers in this journal
- Impact of a natural disaster on access to care and biopsychosocial outcomes among Hispanic/Latino cancer survivors 91%
- Immediate effect of osteopathic techniques on human resting muscle tone in healthy subjects using myotonometry: A factorial randomized trial 89%
- Prevalence and Predictors of Depression among Training Physicians in China: A Comparison to the United States 89%
Similar papers in this journal
- Effectiveness of educational intervention on breast cancer knowledge and breast self-examination among female university students in Bangladesh: a pre-post quasi-experimental one group study 94%
- Assessing awareness of blood cancer symptoms and barriers to symptomatic presentation: Measure development and results from a population survey in the UK 91%
- Risk-Reducing Salpingectomy: Considerations from an OBGYN Perspective 91%
Similar papers in this journal
- Association between Hormonal Contraceptive Use and Lipedema: A Cross-Sectional Study with 637 Brazilian Women 90%
- The Impact of Fasting the Holy Month of Ramadan on Colorectal Cancer Patients and Two Tumor Biomarkers: A Tertiary-Care Hospital Experience 90%
- Non-Consensual Sex among Japanese Women in the COVID-19 Pandemic: A Large-Scale Nationwide Survey-Based Study 89%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.