Overall treatment recommendation concordance between a multidisciplinary tumor board and the application EasyOncology.

Overall treatment recommendation concordance between a multidisciplinary tumor board and the application EasyOncology.</p

Evaluation flow chart.

Testing results were categorized into 4 color-coded groups: greena represents “concordant treatment recommendation”; blueb represents “concordant, for consideration”; redc represents “non-concordant, not recommended” and greyd represents “non-concordant, not available” recommendations. In the second round of analysis, the mismatched pairs of responses were reviewed in detail in order to identify limitations in the query algorithm leading to non-concordancy and, subsequently, to improve the query. In summary, the evaluation method in this study involved comparing and analyzing the concordance rates between the tumor board recommendations of the urological multidisciplinary tumor board and the query results of the digital application "EasyOncology" and classifying the responses into different categories based on their agreement and compliance with best clinical practices.</p

Query algorithm.

The relevant information is requested by EO’s query algorithm depending on the selected initial clinical status. Abbreviations: TNM: Classification of Malignant Tumors; ECOG: Eastern Cooperative Oncology Group; PSA: Prostate-Specific Antigen; ISUP: International Society of Urological Pathology; PC: prostate cancer; mHSPC: metastatic Hormone-Sensitive Prostate Cancer; nmHSPC: non-metastatic Hormone-Sensitive Prostate Cancer; nmCRPC: non-metastatic Castration-Resistant Prostate Cancer; mCRPC: metastatic Castration-Resistant Prostate Cancer; TUR-P: Transurethral Resection of the Prostate; SPE: Suprapubic enucleation.</p

Flow chart of patient case selection process.

Certified Cancer Centers must present all patients in multidisciplinary tumor boards (MTB), including standard cases with well-established treatment strategies. Too many standard cases can absorb much of the available time, which can be unfavorable for the discussion of complex cases. In any case, this leads to a high quantity, but not necessarily a high quality of tumor boards. Our aim was to develop a partially algorithm-driven decision support system (DSS) for smart phones to provide evidence-based recommendations for first-line therapy of common urological cancers. To assure quality, we compared each single digital decision with recommendations of an experienced MTB and obtained the concordance.1873 prostate cancer patients presented in the MTB of the urological department of the University Hospital of Cologne from 2014 to 2018 have been evaluated. Patient characteristics included age, disease stage, Gleason Score, PSA and previous therapies. The questions addressed to MTB were again answered using DSS. All blinded pairs of answers were assessed for discrepancies by independent reviewers. Overall concordance rate was 99.1% (1856/1873). Stage specific concordance rates were 97.4% (stage I), 99.2% (stage II), 100% (stage III), and 99.2% (stage IV). Quality of concordance were independent of age and risk profile. The reliability of any DSS is the key feature before implementation in clinical routine. Although our system appears to provide this safety, we are now performing cross-validation with several clinics to further increase decision quality and avoid potential clinic bias.</div

Multivariate regression analyses of the concordance rate between EasyOncology and the multidisciplinary tumor board.

Multivariate regression analyses of the concordance rate between EasyOncology and the multidisciplinary tumor board.</p

Baseline clinical characteristics.

Certified Cancer Centers must present all patients in multidisciplinary tumor boards (MTB), including standard cases with well-established treatment strategies. Too many standard cases can absorb much of the available time, which can be unfavorable for the discussion of complex cases. In any case, this leads to a high quantity, but not necessarily a high quality of tumor boards. Our aim was to develop a partially algorithm-driven decision support system (DSS) for smart phones to provide evidence-based recommendations for first-line therapy of common urological cancers. To assure quality, we compared each single digital decision with recommendations of an experienced MTB and obtained the concordance.1873 prostate cancer patients presented in the MTB of the urological department of the University Hospital of Cologne from 2014 to 2018 have been evaluated. Patient characteristics included age, disease stage, Gleason Score, PSA and previous therapies. The questions addressed to MTB were again answered using DSS. All blinded pairs of answers were assessed for discrepancies by independent reviewers. Overall concordance rate was 99.1% (1856/1873). Stage specific concordance rates were 97.4% (stage I), 99.2% (stage II), 100% (stage III), and 99.2% (stage IV). Quality of concordance were independent of age and risk profile. The reliability of any DSS is the key feature before implementation in clinical routine. Although our system appears to provide this safety, we are now performing cross-validation with several clinics to further increase decision quality and avoid potential clinic bias.</div

Treatment concordance rates between a MTB and DSS according to prostate cancer tumor stage.

The queries of the APP on how many biopsy specimens were obtained, the patient’s wish against any active therapy and the presence of a neuroendocrine tumor could thus be identified as systematic errors for divergent treatment recommendations. These valuable insights can be used to optimize the APP in order to increase the reliability of its recommendations.</p

<i>OASIS/CREB3L1</i> is epigenetically silenced in human bladder cancer facilitating tumor cell spreading and migration <i>in vitro</i>

<div><p><i>CREB3L1</i> has been recently proposed as a novel metastasis suppressor gene in breast cancer. Our current study highlights CREB3L1 expression, regulation, and function in bladder cancer. We demonstrate a significant downregulation of <i>CREB3L1</i> mRNA expression (n = 64) in primary bladder cancer tissues caused by tumor-specific <i>CREB3L1</i> promoter hypermethylation (n = 51). Based on pyrosequencing <i>CREB3L1</i> methylation was shown to be potentially associated with a more aggressive phenotype of bladder cancer. These findings were verified by an independent public data set containing data from 184 bladder tumors. In addition, immunohistochemical evaluation showed that CREB3L1 protein expression is decreased in bladder cancer tissues as well. Interestingly, protein loss is predominately observed in the nuclei of aggressive tumor cells. Based on <i>in vitro</i> models we clearly show that CREB3L1 re-expression mediates suppression of tumor cell migration and colony growth of high grade and invasive bladder cancer cells. The candidate tumor suppressor and TGF-β signaling inhibitor HTRA3 was furthermore identified as putative target gene of CREB3L1 in both invasive J82 bladder cells and primary bladder tumors. Hence, our data provide for the first time evidence that the transcription factor CREB3L1 may have an important role as a putative tumor suppressor in bladder cancer.</p></div

Geolocation of users contributing to the #KidneyStones online discussion on Twitter.

<p>The colour tone reflects the number of users per country: the colour shifts from light tones (countries with few or no users) to dark tones (countries with many users).</p

Bubble chart visualising the 100 most frequently used words in tweets in the #KidneyStones online discussion on Twitter.

<p>The larger the bubble, the more a word is used. Colours only aid differentiation and have no other significance.</p