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https://www.selleckchem.com/products/GDC-0449.html 427; p less then 0.01) in our sample. The analysis of the receiver-operating characteristic (ROC) curve revealed that the best cut-off value for LAP index to define MS was 59.4 (sensitivity 80%, specificity 79% and area under the curve (AUC) of 0.875. In female and male, analysis of the ROC curve revealed that the best cut-off value for LAP index to define MS was 56.3 (sensitivity 100%, specificity 82% and AUC of 0.929) and 52.0 (sensitivity 78%, specificity 74% and AUC of 0.838), respectively. CONCLUSION Despite the low prevalence of MS in our sample, the ROC curves analyzes demonstrated a good diagnostic accuracy as an additional screening tool of MS according to the IDF. © 2020 Marshfield Clinic.BACKGROUND The integrity of data in a clinical trial is essential, but the current data management process is too complex and highly labor-intensive. As a result, clinical trials are prone to consuming a lot of budget and time, and there is a risk for human-induced error and data falsification. Blockchain technology has the potential to address some of these challenges. OBJECTIVE The aim of the study was to validate the system, which enables the security of the medical data in clinical trial using blockchain technology. METHODS We have developed a blockchain-based data management system for clinical trials and tested the system through a clinical trial for breast cancer. The project was conducted to demonstrate clinical data management using blockchain technology under the regulatory sandbox enabled by the Japanese Cabinet Office. RESULTS We verified and validated the data in the clinical trial using the validation protocol and tested its resilience to data tampering. The robustness of the system was also proven by survival with zero downtime for clinical data registration during the AWS disruption event in the Tokyo region on August 23, 2019. CONCLUSIONS We show that our system can improve clinical trial data management

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