Summary Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest—namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial—ENTHUSE M1—in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0·791; Bayes factor >5) and surpassed the reference model (iAUC 0·743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3·32, 95% CI 2·39–4·62, p<0·0001; reference model: 2·56, 1·85–3·53, p<0·0001). The new model was validated further on the ENTHUSE M1 cohort with similarly high performance (iAUC 0·768). Meta-analysis across all methods confirmed previously identified...

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Aims: Assess the antibacterial and antioxidant effects of ethanol extracts of Portuguese propolis samples when combined with gentamicin, a widely used aminoglycoside antibiotic, or with honey, collected from the same apiary as propolis. Methods and Results:Using the agar dilution method and DPPH free radical scavenging assay, antimicrobial and antioxidant synergistic effects between propolis and gentamicin or honey were assessed. Synergism between propolis and gentamicin was observed for all the tested extracts and against all the indicator bacteria, with particular interest against the Methicillin-Resistant Staphylococcus aureus (MRSA) with a threefold decrease of the gentamicin MIC if mixed with 25 µg ml −1 propolis.Likely to propolis and gentamicin, mixtures of sub-MIC concentrations of propolis and honey enhanced the antibacterial action of each individual natural product against the majority of the strains. However, propolis antioxidant capacity decreased along with higher honey content in the mixture.Conclusions: Propolis has a strong synergistic effect when combined with gentamicin, allowing the reduction of the therapeutic dose of this drug. Propolis and honey mixtures also display a stronger antibacterial effect than the activity exhibited by each sample when tested individually, whereas the high antioxidant capacity of propolis seems to be not affected when in combination with honey. Significance and Impact of Study: When mixed with honey, propolis antioxidant potential is maintained, or just slightly reduced up to 1:1 dilution, and show synergistic antibacterial effects, allowing to optimize the use of this usually scarce natural resource. Also, considering the antibiotic resistance problem, natural beehive products, alone or in the mixture, are promising alternatives to retard the outbreak of microbial resistance.

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