Patient Decision Aids for Breast Cancer Reconstruction: A Systematic Review and Network Meta-Analysis of Randomized Controlled Trials.
Plast Reconstr Surg
; 2024 Jan 15.
Article
en En
| MEDLINE
| ID: mdl-38232225
ABSTRACT
BACKGROUND:
Breast cancer has surpassed lung cancer to become the most frequently diagnosed cancer in women. There has been a dramatic increase in the use of breast reconstruction after mastectomy. However, struggle in making decisions regarding breast reconstruction has existed. Thus, decision aid (DA) is necessary to be conducted, and further studies are needed to promote better decision aid. This review discussed how DAs can be used to help women make decisions about breast reconstruction after mastectomy. Additionally, the review was the first to compare different DA formats to determine which one is most effective.METHODS:
We searched for relevant studies published before October 2022 in PubMed and Embase using the medical subject headings "breast reconstruction" and "decision aid." Demographic data as well as decision, outcomes and instruments used for assessment were also collected. Risk of bias was measured by the Cochrane Risk-of-Bias 2 (RoB 2) tool.RESULTS:
A network meta-analysis of 14 RCTs with a total of 1401 patients wereincluded. 90.9% participants presented usable results for evaluation of decisional conflict, and web-based DA (-0.3, 95% CI -0.56 to -0.05) showed significant improvement. 50.3% participants provided results of decisional regret, and no subgroups showed significant reduction. 60.3% participants contributed to results for knowledge, and web-based DA (0.61, 95% CI 0.01 to 1.21) showed the most positive effect. 44.5% participants were included for evaluation of satisfaction, and web-based DA (0.44, 95% CI 0.15 to 0.72) revealed significant increase.CONCLUSION:
The review concluded that web-based decision aids are the favorable format of decision aid.
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Base de datos:
MEDLINE
Tipo de estudio:
Clinical_trials
/
Systematic_reviews
Idioma:
En
Revista:
Plast Reconstr Surg
Año:
2024
Tipo del documento:
Article