General discussion 523 13 Open data, open methodology In this final paragraph of this discussion, I briefly address the importance of open data and open methodology in cancer research, especially concerning valuable techniques in relatively rare diseases such as differentiated thyroid cancer. In general, the sharing of research data has increasingly become the norm in investigator-driven as well as industry-driven research [778]. Yet, during the conduction of the systematic review and meta-analysis included in the supplementary data of Chapter 2, we encountered that the published data in several papers was incomplete, not available from public repositories and/or the involved researchers did not reply to e-mailed data requests. This also concerned well-received papers published in renowned, peer-reviewed journals. For example, for the main molecular marker panels that are used in the diagnosis of indeterminate thyroid nodules, the described methodology is not completely transparent and crucial elements of the applied diagnostic algorithms are omitted from the papers and their respective supplemental data. Although I recognise the commercial motivations that aided the development of these expensive tests in the first place, such non-transparency does impede the reproducibility and validation of study results as well as the global spread of knowledge [160, 683]. To endorse our position on open data and aid the global development of MD for indeterminate thyroid nodules, in Chapter 11 we described a method for the molecular assessment of oncocytic indeterminate nodules. We used a 1,500 SNP NGS panel that is suitable for daily practice and illustrated the observed CNA patterns and the differences between benign and malignant oncocytic lesions in detail [695]. These methods were subsequently successfully externally validated for the first time in the EfFECTS study cohort in Chapter 12 [725]. We hope that other research groups will be able to validate our methods in other cohorts, too. In the complicated balance between higher common scientific goals, business interests, and any more personal motivations, I would like to encourage researchers to share their methodology and data with each other more in order to optimize scientific progress in medical research. It advances validation studies, meta-analysis, and/or secondary use of data, guards your fellow researchers from having to reinvent the wheel, saves valuable research time, resources, and funds (especially concerning charity or collection box funds), and – perhaps most importantly – may inspire for new research projects and multidisciplinary, interinstitutional cooperation.
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