Validation and implementation of a mobile app decision support system for quality assurance of tumor boards: Analyzing the concordance rates for testis cancer at a multidisciplinary tumor board of a tertiary referral center.

Abstract

399 Background: Guideline-compliance in the management of GCT is suboptimal concerning and it results in significantly impaired long-term survival. To facilitating guideline concordant decisions even in less experienced MTD, we developed an algorithm-driven and validated mobile App to provide evidence-based recommendations. This App contains latest guideline versions and it is continuously updated to include practice changing clinical trials. It is the purpose of this study to analyse treatment decision made by MTD compared to guideline recommended therapy. Methods: 302 patients with GCT and MTD decision were randomly selected from our database. Concordance rates of MTD recommendations were compared to query results of the digital APP “Easy Oncology” performed by 2 independent, blinded reviewers. Descriptive statistics and data analysis included IBM´s statistics software SPSS Version 25. Correlation analysis of cancer case characteristics was performed by Kendalls Tau, Gamma, Pearson and Spearman tests. Results: Median age was 35 (18-82) years. Clinical stages I, IIA-C, and III were identified in 32%, 37%, and 31%, resp. According to IGCCCG 56%, 18%, and 25% demonstrated good, intermediate, and poor prognosis, resp. 56% were non-seminomas and 44% were seminomas. 60%, 16%, and 7% of MTD decisions were related to 1st-line, 2nd, and 3rd line therapy and 18% dealt with follow up. Overall concordance rate was 99% (301/302). Concordance rates in CS I, IIA-C, and III were 100%, 98% and 99%, resp. Concordance rates with regard to 1st, 2nd and 3rd line therapy were 99% (135/136), 100%, and 88% (13/14). Conclusions: Our validated expert-created mobile decision support system demonstrates easy and reliable application in daily routine in an expert tertiary referral centre. The APP relies on guideline and trial based information and avoids MTD decisions by expert opinions. It might improve the MTD decision in less experienced MTDs which is currently evaluated in a prospective study.