Public Availability of Results of Trials Assessing Cancer Drugs in the United States

2013 ◽  
Vol 31 (24) ◽  
pp. 2998-3003 ◽  
Author(s):  
Thi-Anh-Hoa Nguyen ◽  
Agnes Dechartres ◽  
Soraya Belgherbi ◽  
Philippe Ravaud

Purpose To evaluate to what extent results of completed trials of cancer drugs conducted in the United States are publicly available at ClinicalTrials.gov, as required by the Food and Drug Administration Amendments Act (FDAAA), or are published in journals. Methods We searched ClinicalTrials.gov for cancer trials governed by the FDAAA: phase II to IV trials assessing drugs in the United States with a primary completion date between December 26, 2007, and May 31, 2010. For each trial, we also searched PubMed to identify the publication of results. We assessed the cumulative percentages of posted or published results over time by using the Kaplan-Meier method. Results We identified 646 trials, including 209 randomized controlled trials (RCTs). At 12 months after completion of the trials, the cumulative percentages of trials with results posted at ClinicalTrials.gov, published in journals, and available either at ClinicalTrials.gov or in journals were 9% (95% CI, 7% to 11%), 12% (95% CI, 10% to 15%), and 20% (95% CI, 17% to 23%), respectively, and for RCTs, the percentages were 12% (95% CI, 8% to 16%), 5% (95% CI, 2% to 8%), and 17% (95% CI, 12% to 22%), respectively. At 36 months, these percentages were 31% (95% CI, 28% to 35%), 35% (95% CI, 31% to 39%), and 55% (95% CI, 51% to 59%), respectively, and for RCTs, they were 38% (95% CI, 31% to 45%), 32% (95% CI, 25% to 39%), and 56% (95% CI, 48% to 62%), respectively. Public availability of phase III trials was 15% (95% CI, 7% to 23%) at 12 months, 39% (95% CI, 27% to 49%) at 24 months, and 64% (95% CI, 50% to 73%) at 36 months. Conclusion Despite the FDAAA, results for nearly half the trials of cancer drugs in the United States were not publicly available 3 years after completion of the trials.

2010 ◽  
Vol 9 (1) ◽  
pp. 59-60
Author(s):  
Edward Chu ◽  
David Cunningham ◽  
David Watkins

2007 ◽  
Author(s):  
Karen A. Fitzner ◽  
Charlie Bennett ◽  
June McKoy ◽  
Cara Tigue

Author(s):  
William W. Franko ◽  
Christopher Witko

The authors conclude the book by recapping their arguments and empirical results, and discussing the possibilities for the “new economic populism” to promote egalitarian economic outcomes in the face of continuing gridlock and the dominance of Washington, DC’s policymaking institutions by business and the wealthy, and a conservative Republican Party. Many states are actually addressing inequality now, and these policies are working. Admittedly, many states also continue to embrace the policies that have contributed to growing inequality, such as tax cuts for the wealthy or attempting to weaken labor unions. But as the public grows more concerned about inequality, the authors argue, policies that help to address these income disparities will become more popular, and policies that exacerbate inequality will become less so. Over time, if history is a guide, more egalitarian policies will spread across the states, and ultimately to the federal government.


2014 ◽  
Vol 35 (4) ◽  
pp. 423-425 ◽  
Author(s):  
Edwin C. Pereira ◽  
Kristin M. Shaw ◽  
Paula M. Snippes Vagnone ◽  
Jane E. Harper ◽  
Alexander J. Kallen ◽  
...  

Carbapenem-resistant Enterobacteriaceae (CRE) are a growing problem in the United States. We explored the feasibility of active laboratory-based surveillance of CRE in a metropolitan area not previously considered to be an area of CRE endemicity. We provide a framework to address CRE surveillance and to monitor changes in the incidence of CRE infection over time.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Di Zhu ◽  
Xinyue Ye ◽  
Steven Manson

AbstractWe describe the use of network modeling to capture the shifting spatiotemporal nature of the COVID-19 pandemic. The most common approach to tracking COVID-19 cases over time and space is to examine a series of maps that provide snapshots of the pandemic. A series of snapshots can convey the spatial nature of cases but often rely on subjective interpretation to assess how the pandemic is shifting in severity through time and space. We present a novel application of network optimization to a standard series of snapshots to better reveal how the spatial centres of the pandemic shifted spatially over time in the mainland United States under a mix of interventions. We find a global spatial shifting pattern with stable pandemic centres and both local and long-range interactions. Metrics derived from the daily nature of spatial shifts are introduced to help evaluate the pandemic situation at regional scales. We also highlight the value of reviewing pandemics through local spatial shifts to uncover dynamic relationships among and within regions, such as spillover and concentration among states. This new way of examining the COVID-19 pandemic in terms of network-based spatial shifts offers new story lines in understanding how the pandemic spread in geography.


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