209 Summary and general discussion GENERAL DISCUSSION The outcomes of this thesis have provided innovative insights for the development of patient-friendly cancer detection methods. This chapter discusses the potential clinical value of this approach, together with upcoming challenges and implications for future research. 8.1 Toward implementation of patient-friendly cancer detection methods in routine clinical practice Patient-friendly cancer detection methods hold promise to advance cancer diagnostics and unlock self-collection from home, which could alleviate the burden on healthcare systems. While the use of urine and self-collected cervicovaginal material for cancer detection has the potential to partially replace tissue biopsies, it is more likely to serve as a complementary diagnostic method. Key applications of patient-friendly cancer detection methods include 1) cancer detection in high-risk individuals, 2) treatment selection and treatment response monitoring, and 3) disease monitoring after curative treatment (1). 8.1.1 Potential clinical value of patient-friendly cancer detection methods for endometrial, ovarian, and lung cancer The studies described in this thesis represent pioneering work and mark the starting point of patient-friendly cancer detection methods. While acknowledging that more research is needed to establish its clinical utility, it is compelling to discuss its potential clinical value in the context of endometrial, ovarian, and lung cancer. Gynecological cancers Endometrial cancer detection in urine and cervicovaginal self-samples, as investigated in Chapters 2 to 4, holds the potential to serve as a risk assessment tool and improve timely cancer detection. Risk assessment using home-collected samples could reduce hospital visits of women with postmenopausal blood loss or with an increased risk for endometrial cancer (e.g. Lynch syndrome) and aid in prioritizing healthcare resources. To this end, a high test sensitivity and positive predictive value are needed to decide which women can be safely followed up (i.e. without the need for an immediate diagnostic biopsy). Recent studies have utilized mutation analysis to classify endometrial cancers into four prognostically relevant molecular subgroups using urine and cervicovaginal self-samples (2-4), which could broaden the diagnostic use of these sample types. In collaboration, we are currently validating this approach in our urine sample cohort. 8
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