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10.1371/journal.pntd.0005439 http://scihub22266oqcxt.onion/10.1371/journal.pntd.0005439 C5360336!5360336!28278301     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       PLoS+Negl+Trop+Dis 2017 ; 11 (3): ä Nephropedia Template TP {{tp|p=28278301|t=2017. GOST: A generic ordinal sequential trial design for a treatment trial in an emerging pandemic |pdf=|usr=}}{{28278301}} gab.com Text GOST: A generic ordinal sequential trial design for a treatment trial in an emerging pandemic JO: PLoS Negl Trop Dis http://www.kidney.de/pget.php?&tw=1&pmid=28278301 #FOAvip Background: Conducting clinical trials to assess experimental treatments for potentially pandemic infectious diseases is challenging. Since many outbreaks of infectious diseases last only six to eight weeks, there is a need for trial designs that can be implemented rapidly in the face of uncertainty. Outbreaks are sudden and unpredictable and so it is essential that as much planning as possible takes place in advance. Statistical aspects of such trial designs should be evaluated and discussed in readiness for implementation. Methodology/Principal findings: This paper proposes a generic ordinal sequential trial design (GOST) for a randomised clinical trial comparing an experimental treatment for an emerging infectious disease with standard care. The design is intended as an off-the-shelf, ready-to-use robust and flexible option. The primary endpoint is a categorisation of patient outcome according to an ordinal scale. A sequential approach is adopted, stopping as soon as it is clear that the experimental treatment has an advantage or that sufficient advantage is unlikely to be detected. The properties of the design are evaluated using large-sample theory and verified for moderate sized samples using simulation. The trial is powered to detect a generic clinically relevant difference: namely an odds ratio of 2 for better rather than worse outcomes. Total sample sizes (across both treatments) of between 150 and 300 patients prove to be adequate in many cases, but the precise value depends on both the magnitude of the treatment advantage and the nature of the ordinal scale. An advantage of the approach is that any erroneous assumptions made at the design stage about the proportion of patients falling into each outcome category have little effect on the error probabilities of the study, although they can lead to inaccurate forecasts of sample size. Conclusions/Significance: It is important and feasible to pre-determine many of the statistical aspects of an efficient trial design in advance of a disease outbreak. The design can then be tailored to the specific disease under study once its nature is better understood. Twit Text FOAVip GOST: A generic ordinal sequential trial design for a treatment trial in an emerging pandemic ????PLoS Negl Trop Dis http://www.kidney.de/pget.php?&tw=1&pmid=28278301 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28278301 #FOAvip English Wikipedia <ref>{{Cite pmid|28278301}}</ref> GOST: A generic ordinal sequential trial design for a treatment trial in an emerging pandemic #MMPMID28278301 Whitehead J; Horby P PLoS Negl Trop Dis 2017[Mar]; 11 (3): ä PMID28278301show ga Background: Conducting clinical trials to assess experimental treatments for potentially pandemic infectious diseases is challenging. Since many outbreaks of infectious diseases last only six to eight weeks, there is a need for trial designs that can be implemented rapidly in the face of uncertainty. Outbreaks are sudden and unpredictable and so it is essential that as much planning as possible takes place in advance. Statistical aspects of such trial designs should be evaluated and discussed in readiness for implementation. Methodology/Principal findings: This paper proposes a generic ordinal sequential trial design (GOST) for a randomised clinical trial comparing an experimental treatment for an emerging infectious disease with standard care. The design is intended as an off-the-shelf, ready-to-use robust and flexible option. The primary endpoint is a categorisation of patient outcome according to an ordinal scale. A sequential approach is adopted, stopping as soon as it is clear that the experimental treatment has an advantage or that sufficient advantage is unlikely to be detected. The properties of the design are evaluated using large-sample theory and verified for moderate sized samples using simulation. The trial is powered to detect a generic clinically relevant difference: namely an odds ratio of 2 for better rather than worse outcomes. Total sample sizes (across both treatments) of between 150 and 300 patients prove to be adequate in many cases, but the precise value depends on both the magnitude of the treatment advantage and the nature of the ordinal scale. An advantage of the approach is that any erroneous assumptions made at the design stage about the proportion of patients falling into each outcome category have little effect on the error probabilities of the study, although they can lead to inaccurate forecasts of sample size. Conclusions/Significance: It is important and feasible to pre-determine many of the statistical aspects of an efficient trial design in advance of a disease outbreak. The design can then be tailored to the specific disease under study once its nature is better understood. äGOST: A generic ordinal sequential trial design for a treatment trial (epmc).pdf DeepDyve Pubget Overpricing