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...

This analysis provides suggestions for future recruitment efforts and research. Translational studies with limited funds could consider multi-modal recruitment approaches including in-person presentations to practice groups and exploitation of previous relationships, which require the providers to opt-out, and interactive opt-in approaches which rely on borrowed networks. These approaches can be supplemented with non-relationship-based opt-out strategies such as cold calls strategically targeted to underrepresented provider groups.

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Background Few community urologists offer cancer patients the opportunity to participate in cancer clinical trials, despite national guidelines that recommend it, depriving an estimated 260,000 urological cancer patients of guideline-concordant care each year. Existing strategies to increase urologists’ offer of clinical trials are designed for resource-rich environments and are not feasible for many community urologists. We sought to design an implementation intervention for dissemination in under-resourced community urology practices and to compare its acceptability, appropriateness and adoption appeal among trial-naïve and trial-experienced urologists. Methods We used a design-for-dissemination approach, informed by the Theoretical Domains Framework and Behavior Change Wheel, to match determinants of the clinical trial offer to theoretically informed implementation strategies. We described the implementation intervention in evaluation workshops offered at urology professional society meetings. We surveyed participants to assess the implementation intervention’s acceptability and appropriateness using validated instruments. We also measured adoption appeal, intention to adopt and previous trial offer. Results Our design process resulted in a multi-modal implementation intervention, comprised of multiple implementation strategies designed to address six domains from the Theoretical Domains Framework. Evaluation workshops delivered at four meetings, convened five separate professional societies. Sixty-one percent of those offered an opportunity to participate in the implementation intervention indicated intention to adopt. Average implementation intervention acceptability and appropriateness ratings were 4.4 and 4.4 (out of 5), respectively. Acceptability scores were statistically significantly higher among those offering trials compared to those not (p = 0.03). Appropriateness scores did not differ between those offering trials and those not (p = 0.24). After urologists ranked their top three innovation attributes, 43% of urologists included practice reputation in their top three reasons for offering clinical trials; 30% listed practice differentiation among their top three reasons. No statistically significant differences were found between those who offered trials and those who did not among any of the innovation attributes. Conclusions LEARN|INFORM|RECRUIT is a promising implementation intervention to address low accrual to clinical trials, poised for implementation and effectiveness testing. The implementation intervention is appealing to its target audience and may have equal uptake among trial-naïve and trial-experienced practices.