Melanoma Diagnostic Practices of French-Speaking Belgian General Practitioners and the Prospective Study of Their Pigmented Skin Lesion Diagnostic Accuracy and Management

JOURNAL OF CANCER EDUCATION(2020)

引用 4|浏览6
暂无评分
摘要
General practitioners (GPs) are among the main actors involved in early melanoma diagnosis. However, melanoma diagnostic accuracy and management are reported to be insufficient among GPs in Europe. The primary aim of this observational prospective study was to shed light on melanoma diagnostic practices among French-speaking Belgian GPs. The second aim was to specifically analyse these GPs’ pigmented skin lesion diagnostic accuracy and management. GPs from the five French-speaking districts of Belgium were asked to complete a questionnaire, before taking part in a melanoma diagnostic training session. First, we assessed the GPs’ current melanoma diagnostic practices. Then, their pigmented skin lesion diagnostic accuracy and management were evaluated, through basic theoretical questions and clinical images. These results were subsequently analysed, according to the GPs’ sociodemographic characteristics and medical practice type. In total, 89 GPs completed the questionnaire. Almost half of the GPs (43%; CI = [33;54]) were confronted with a suspicious skin lesion as the main reason for consultation once every 3 months, while 33% (CI = [24;43]) were consulted for a suspicious lesion as a secondary reason once a month. Prior to training, one-third of the GPs exhibited suboptimal diagnostic accuracy in at least one of six “life-threatening” clinical cases among two sets of 10 clinical images of pigmented skin lesions, which can lead to inadequate patient management (i.e. incorrect treatment and/or inappropriate reinsurance). This study underlines the need to train GPs in melanoma diagnosis. GPs’ pigmented skin lesion diagnostic accuracy and management should be improved to increase early melanoma detection.
更多
查看译文
关键词
Observational study,Melanoma,Cancer early detection,Management,General practitioners
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要