Enrollment of adolescents and young adults onto SWOG cancer research network clinical trials: A comparative analysis by treatment site and era.

BackgroundFew adolescents and young adults (AYAs, 15-39 years old) enroll onto cancer clinical trials, which hinders research otherwise having the potential to improve outcomes in this unique population. Prior studies have reported that AYAs are more likely to receive cancer care in community settings. The National Cancer Institute (NCI) has led efforts to increase trial enrollment through its network of NCI-designated cancer centers (NCICC) combined with community outreach through its Community Clinical Oncology Program (CCOP; replaced by the NCI Community Oncology Research Program in 2014).MethodsUsing AYA proportional enrollment (the proportion of total enrollments who were AYAs) as the primary outcome, we examined enrollment of AYAs onto SWOG therapeutic trials at NCICC, CCOP, and non-NCICC/non-CCOP sites from 2004 to 2013 by type of site, study period (2004-08 vs 2009-13), and patient demographics.ResultsOverall, AYA proportional enrollment was 10.1%. AYA proportional enrollment decreased between 2004-2008 and 2009-2013 (13.1% vs 8.5%, P < .001), and was higher at NCICCs than at CCOPs and non-NCICC/non-CCOPs (14.1% vs 8.3% and 9.2%, respectively; P < .001). AYA proportional enrollment declined significantly at all three site types. Proportional enrollment of AYAs who were Black or Hispanic was significantly higher at NCICCs compared with CCOPs or non-NCICC/non-CCOPs (11.5% vs 8.8, P = .048 and 11.5% vs 8.6%, P = .03, respectively).ConclusionNot only did community sites enroll a lower proportion of AYAs onto cancer clinical trials, but AYA enrollment decreased in all study settings. Initiatives aimed at increasing AYA enrollment, particularly in the community setting with attention to minority status, are needed

Translating research into evidence-based practice: The National Cancer Institute Community Clinical Oncology Program

The recent rapid acceleration of basic science is reshaping both our clinical research system and our health care delivery system. The pace and growing volume of medical discoveries are yielding exciting new opportunities, yet we continue to face old challenges to maintain research progress and effectively translate research into practice. The National Institutes of Health and individual government programs are increasingly emphasizing research agendas involving evidence development, comparative effectiveness research among heterogeneous populations, translational research, and accelerating the translation of research into evidence-based practice, as well as building successful research networks to support these efforts. For over 25 years, the National Cancer Institute's Community Clinical Oncology Program has successfully extended research into the community and facilitated the translation of research into evidence-based practice. By describing its keys to success, this article provides practical guidance to cancer-focused provider-based research networks as well as those in other disciplines

Validity and Reliability of the US National Cancer Institute’s Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE)

Symptomatic adverse events (AEs) in cancer trials are currently reported by clinicians using the National Cancer Institute's (NCI) Common Terminology Criteria for Adverse Events (CTCAE). To integrate the patient perspective, the NCI developed a patient-reported outcomes version of the CTCAE (PRO-CTCAE) to capture symptomatic AEs directly from patients

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure