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Additional co-authors: Ivan Ropovik, Balazs Aczel, Lena F. Aeschbach, Luca Andrighetto, Jack D. Arnal, Holly Arrow, Peter Babincak, Bence E. Bakos, Gabriel Banik, Ernest Baskin, Radomir Belopavlovic, Michael H. Bernstein, Michal Bialek, Nicholas G. Bloxsom, Bojana Bodroža, Diane B. V. Bonfiglio, Leanne Boucher, Florian Bruhlmann, Claudia C. Brumbaugh, Erica Casini, Yiling Chen, Carlo Chiorri, William J. Chopik, Oliver Christ, Antonia M. Ciunci, Heather M. Claypool, Sean Coary, Marija V. Cˇolic, W. Matthew Collins, Paul G. Curran, Chris R. Day, Anna Dreber, John E. Edlund, Filipe Falcao, Anna Fedor, Lily Feinberg, Ian R. Ferguson, Maire Ford, Michael C. Frank, Emily Fryberger, Alexander Garinther, Katarzyna Gawryluk, Kayla Ashbaugh, Mauro Giacomantonio, Steffen R. Giessner, Jon E. Grahe, Rosanna E. Guadagno, Ewa Halasa, Rias A. Hilliard, Joachim Huffmeier, Sean Hughes, Katarzyna Idzikowska, Michael Inzlicht, Alan Jern, William Jimenez-Leal, Magnus Johannesson, Jennifer A. Joy-Gaba, Mathias Kauff, Danielle J. Kellier, Grecia Kessinger, Mallory C. Kidwell, Amanda M. Kimbrough, Josiah P. J. King, Vanessa S. Kolb, Sabina Kolodziej, Marton Kovacs, Karolina Krasuska, Sue Kraus, Lacy E. Krueger, Katarzyna Kuchno, Caio Ambrosio Lage, Eleanor V. Langford, Carmel A. Levitan, Tiago Jesse Souza de Lima, Hause Lin, Samuel Lins, Jia E. Loy, Dylan Manfredi, Łukasz Markiewicz, Madhavi Menon, Brett Mercier, Mitchell Metzger, Venus Meyet, Jeremy K. Miller, Andres Montealegre, Don A. Moore, Rafal Muda, Gideon Nave, Austin Lee Nichols, Sarah A. Novak, Christian Nunnally, Ana Orlic, Anna Palinkas, Angelo Panno, Kimberly P. Parks, Ivana Pedovic, Emilian Pekala, Matthew R. Penner, Sebastiaan Pessers, Boban Petrovic, Thomas Pfeiffer, Damian Pienkosz, Emanuele Preti, Danka Puric, Tiago Ramos, Jonathan Ravid, Timothy S. Razza, Katrin Rentzsch, Juliette Richetin, Sean C. Rife, Anna Dalla Rosa, Kaylis Hase Rudy, Janos Salamon, Blair Saunders, Przemyslaw Sawicki, Kathleen Schmidt, Kurt Schuepfer, Thomas Schultze, Stefan Schulz-Hardt, Astrid Schutz, Ani N. Shabazian, Rachel L. Shubella, Adam Siegel, Ruben Silva, Barbara Sioma, Lauren Skorb, Luana Elayne Cunha de Souza, Sara Steegen, L. A. R. Stein, R. Weylin Sternglanz, Darko Stojilovic, Daniel Storage, Gavin Brent Sullivan, Barnabas Szaszi, Peter Szecsi, Orsolya Szoke, Attila Szuts, Manuela Thomae, Natasha D. Tidwell, Carly Tocco, Ann-Kathrin Torka, Francis Tuerlinckx, Wolf Vanpaemel, Leigh Ann Vaughn, Michelangelo Vianello, Domenico Viganola, Maria Vlachou, Ryan J. Walker, Sophia C. Weissgerber, Aaron L. Wichman, Bradford J. Wiggins, Daniel Wolf, Michael J. Wood, David Zealley, Iris Žeželj, Mark Zrubka, and Brian A. Nosek

Background Recent literature suggests that living in a rural setting may be associated with adverse cancer outcomes. This study examines the burden of travel from home to cancer center for clinical trial (CT) enrollees. Materials and Methods Patients from the University of California San Francisco Clinical Trial Management System database who enrolled in a cancer CT for a breast, genitourinary, or gastrointestinal malignancy between 1993 and 2014 were included. Cancer type, household zip code, race/ethnicity, phase of study, study sponsor, and year of signed consent were exported. Distance traveled from home to center was calculated using a GoogleMaps application programming interface. The relationships of distance with phase of CT, household income, and race/ethnicity were examined. Results A total of 1,600 patients were enrolled in breast (55.8%), genitourinary (29.4%), or gastrointestinal (14.9%) cancer CTs. The overall median unidirectional distance traveled from home to study site was 25.8 miles (interquartile range [IQR] 11.5–75.3). Of the trial sponsors examined, principal investigator (56.4%), industry (22.2%), cooperative group (11.6%), and National Institutes of Health (NIH; 9.8%), the longest distance traveled was for NIH-sponsored trials, with a median of 39.4 miles (p Conclusion This study found that the burden of travel is highest among patients enrolled in NIH-sponsored trials, phase I studies, or living in low-income areas. These data suggest that travel burden for cancer CT participants may be significant. Implications for Practice This study is one of the first to measure travel distance for patients in cancer clinical trials using a real-world GoogleMaps calculator. Out-of-pocket expenses such as travel are not typically covered by health care payers; therefore, patients may face considerable cost to attend each study visit. Using a single-center clinical trials enrollment database, this study found that the burden of travel is highest for patients enrolled in National Institutes of Health-sponsored trials and phase I studies, as well as for patients living in low-income areas. Results suggest that a significant proportion of patients enrolled in clinical trials face a substantial travel burden.

Author(s): Kaplan, Celia P; Siegel, Adam; Leykin, Yan; Palmer, Nynikka R; Borno, Hala; Bielenberg, Jessica; Livaudais-Toman, Jennifer; Ryan, Charles; Small, Eric J | Abstract: BackgroundTo address limitations in recruitment and enrollment of diverse, low-literacy patients into prostate cancer clinical trials, we evaluated the feasibility, acceptability, and efficacy of an English and Spanish, Internet-based, multilevel recruitment intervention.MethodsIntervention components included (1) a low-literacy, bilingual, automated, Internet-based clinical trial matching tool; (2) a bilingual nurse who assisted individuals with questions and enrollment; and (3) a targeted, Internet-based advertising campaign. We evaluated (a) completion of matching tool, (b) expression of interest in a clinical trial, (c) number of patients who matched to clinical trials at a single institution, (d) discussion of risks and benefits of clinical trials (via follow-up interviews), and (e) effect of the advertising on completing the matching tool. Feasibility, acceptability, and preliminary estimates of efficacy were measured through user engagement with the matching tool and subsequent qualitative interviews with these same users.ResultsDuring the 28-week study period, 523 users provided demographic information, 263 were identified with prostate cancer, 192 (73%) matched to at least one clinical trial, and 29 (15.1%) of those who matched provided contact information. During the study period, 17 prostate cancer clinical trials were available for matching. We completed follow-up interviews with 14 of the 29 men who provided contact information. Of the 14, 85.7% discussed the risks and benefits of clinical trials with their physician, and 35.7% enrolled in a clinical trial. The Internet-based advertising campaign resulted in an increased number of matching tool completions.ConclusionsOur study demonstrates that an Internet-based clinical trial matching tool that is advertised using a targeted Internet-based campaign can provide an effective means to reach diverse, low-literacy patients. When implemented at scale and over a longer duration, such interventions may help increase trial participation among underrepresented populations.

There is evidence that prediction markets are useful tools to aggregate information on researchers' beliefs about scientific results including the outcome of replications. In this study, we use prediction markets to forecast the results of novel experimental designs that test established theories. We set up prediction markets for hypotheses tested in the Defense Advanced Research Projects Agency's (DARPA) Next Generation Social Science (NGS2) programme. Researchers were invited to bet on whether 22 hypotheses would be supported or not. We define support as a test result in the same direction as hypothesized, with a Bayes factor of at least 10 (i.e. a likelihood of the observed data being consistent with the tested hypothesis that is at least 10 times greater compared with the null hypothesis). In addition to betting on this binary outcome, we asked participants to bet on the expected effect size (in Cohen's d) for each hypothesis. Our goal was to recruit at least 50 participants that signed up to participate in these markets. While this was the case, only 39 participants ended up actually trading. Participants also completed a survey on both the binary result and the effect size. We find that neither prediction markets nor surveys performed well in predicting outcomes for NGS2.

Lessons LearnedIn abiraterone- and/or enzalutamide-refractory metastatic castration-resistant prostate cancer (mCRPC) patients, selinexor led to prostate-specific antigen and/or radiographic responses in a subset of patients, indicating clinical activity in this indication. Despite twice-a-week dosing and maximal symptomatic management, selinexor was associated with significant anorexia, nausea, and fatigue in mCRPC patients refractory to second-generation anti-androgen therapies, limiting further clinical development in this patient population. This study highlights the challenge of primary endpoint selection for phase II studies in the post-abiraterone and/or post-enzalutamide mCRPC space.BackgroundSelinexor is a first-in-class selective inhibitor of nuclear export compound that specifically inhibits the nuclear export protein Exportin-1 (XPO-1), leading to nuclear accumulation of tumor suppressor proteins.MethodsThis phase II study evaluated the efficacy and tolerability of selinexor in patients with metastatic castration-resistant prostate cancer (mCRPC) refractory to abiraterone and/or enzalutamide.ResultsFourteen patients were enrolled. Selinexor was initially administered at 65 mg/m2 twice a week (days 1 and 3) and was subsequently reduced to 60 mg flat dose twice a week (days 1 and 3), 3 weeks on, 1 week off, to improve tolerability. The median treatment duration was 13 weeks. At a median follow-up of 4 months, two patients (14%) had ≥50% prostate-specific antigen (PSA) decline, and seven patients (50%) had any PSA decline. Of eight patients with measurable disease at baseline, two (25%) had a partial response and four (50%) had stable disease as their best radiographic response. Five patients (36%) experienced serious adverse events (SAEs; all unrelated to selinexor), and five patients (36%) experienced treatment-related grade 3–4 AEs. The most common drug-related adverse events (AEs) of any severity were anorexia, nausea, weight loss, fatigue, and thrombocytopenia. Three patients (21%) came off study for unacceptable tolerability.ConclusionSelinexor demonstrated clinical activity and poor tolerability in mCRPC patients refractory to second-line anti-androgenic agents.