Diagnostic delay in women with cancer: What do we know and which factors contribute?

医学 癌症 肿瘤科 内科学
作者
Liza A. Hoveling,Melinda S. Schuurman,Sabine Siesling,Kristel M. van Asselt,Christina Bode
出处
期刊:The Breast [Elsevier BV]
卷期号:80: 104427-104427 被引量:9
标识
DOI:10.1016/j.breast.2025.104427
摘要

Timely cancer diagnosis is important, but delays are common, also among women. This study reviews recent literature on diagnostic delays in women with breast cancer, focusing on individual-level factors and their interaction with micro, meso, exo, and macrosystem factors. Following PRISMA-ScR guidelines, we conducted a scoping review on diagnostic delays in cancer among women, including qualitative and quantitative studies with oncological patients or healthcare professionals. We searched PubMed/MEDLINE and Scopus for publications from 2018 to November 28, 2023, excluding studies not meeting the inclusion criteria, not in English or Dutch, or focused solely on cancer screening. Titles and full texts were screened, with disagreements resolved through discussion. Two reviewers independently extracted study details, population characteristics, study design, and factors contributing to diagnostic delays. Initially, 9699 records were retrieved, resulting in 129 relevant studies after exclusions. We focused on women's health and breast cancer, narrowing our scope to 22 studies in high-income countries. Studies explored diagnostic delays and factors at various levels: microsystem (demographics, health behaviours, psychology, healthcare interactions), mesosystem (schedules, peer and support networks), exosystem (social, cultural, environmental, accessibility factors), and macrosystem (broader cultural, societal contexts, healthcare policies). In high-income countries, diagnostic delays in breast cancer care involve factors across various systems, affecting individuals, peers, healthcare, and policies. Enhancing awareness, communication, and access is important, requiring targeted campaigns and infrastructure upgrades. The Bronfenbrenner's ecological model effectively addresses the multifaceted factors influencing diagnostic delays. Future research can benefit from applying this model to various cancers and income settings.

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