scholarly journals 552P Reasons of screening failure during the 28-day screening period in patients identified for inclusion in phase I trials and their outcome

2021 ◽  
Vol 32 ◽  
pp. S612
Author(s):  
I. Korakis ◽  
T. Darbas ◽  
F. Mathevet ◽  
S. Clementei ◽  
L. Goubault ◽  
...  
Keyword(s):  
Phase I ◽  
2011 ◽  
Vol 2 (3) ◽  
pp. 449-455 ◽  
Author(s):  
CHIARA CARLOMAGNO ◽  
GENNARO DANIELE ◽  
ROBERTO BIANCO ◽  
ROBERTA MARCIANO ◽  
VINCENZO DAMIANO ◽  
...  

1999 ◽  
Vol 35 ◽  
pp. S283
Author(s):  
C. Twelves ◽  
J.L. Misset ◽  
M. Villalona-Calero ◽  
D. Ryan ◽  
J. Clark ◽  
...  

1996 ◽  
Vol 7 (7) ◽  
pp. 728-733 ◽  
Author(s):  
Richard Pazdur ◽  
Yvonne Lassere ◽  
Enrique Diaz-Canton ◽  
Beth Bready ◽  
Dah H Ho

PLoS ONE ◽  
2012 ◽  
Vol 7 (12) ◽  
pp. e51039 ◽  
Author(s):  
Christophe Le Tourneau ◽  
Hui K. Gan ◽  
Albiruni R. A. Razak ◽  
Xavier Paoletti

2016 ◽  
Vol 43 (4) ◽  
pp. E153-E160 ◽  
Author(s):  
Denise Weiss ◽  
Laurel Northouse ◽  
Sonia Duffy ◽  
Berit Ingersoll-Dayton ◽  
Maria Katapodi ◽  
...  

Author(s):  
Pavel Mozgunov ◽  
Rochelle Knight ◽  
Helen Barnett ◽  
Thomas Jaki

There is growing interest in Phase I dose-finding studies studying several doses of more than one agent simultaneously. A number of combination dose-finding designs were recently proposed to guide escalation/de-escalation decisions during the trials. The majority of these proposals are model-based: a parametric combination-toxicity relationship is fitted as data accumulates. Various parameter shapes were considered but the unifying theme for many of these is that typically between 4 and 6 parameters are to be estimated. While more parameters allow for more flexible modelling of the combination-toxicity relationship, this is a challenging estimation problem given the typically small sample size in Phase I trials of between 20 and 60 patients. These concerns gave raise to an ongoing debate whether including more parameters into combination-toxicity model leads to more accurate combination selection. In this work, we extensively study two variants of a 4-parameter logistic model with reduced number of parameters to investigate the effect of modelling assumptions. A framework to calibrate the prior distributions for a given parametric model is proposed to allow for fair comparisons. Via a comprehensive simulation study, we have found that the inclusion of the interaction parameter between two compounds does not provide any benefit in terms of the accuracy of selection, on average, but is found to result in fewer patients allocated to the target combination during the trial.


Author(s):  
Dixie-Lee W. Esseltine ◽  
David P. Schenkein
Keyword(s):  
Phase I ◽  

2011 ◽  
Vol 17 (3) ◽  
pp. 200-203 ◽  
Author(s):  
Matthew Macaluso ◽  
Michael Krams ◽  
Sheldon H. Preskorn
Keyword(s):  
Phase I ◽  

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