Results 11 to 20 of about 25,475 (182)

Estimation of the censoring distribution in clinical trials

Contemporary Clinical Trials Communications, 2021
Clinical studies with time to event endpoints typically report the median follow-up (i.e., censoring) time for the subjects in the trial, alongside the median time to event. The reason for this is to provide information about the opportunity for subjects
Shu Jiang, David Swanson, Rebecca A. Betensky   +2 more
doaj   +3 more sources

Problems in dealing with missing data and informative censoring in clinical trials [PDF]

Current Controlled Trials in Cardiovascular Medicine, 2002
A common problem in clinical trials is the missing data that occurs when patients do not complete the study and drop out without further measurements. Missing data cause the usual statistical analysis of complete or all available data to be subject to ...
Shih Weichung
doaj   +3 more sources

Censoring in clinical trials: Review of survival analysis techniques [PDF]

Indian Journal of Community Medicine, 2010
Medical and epidemiological studies are mostly conducted with an interest in measuring the occurrence of an outcome event. Studies conducting survival analysis, however, are focussed toward measuring time to event or outcome. Time to event could vary from time to fatal event i.e.
Prinja Shankar, Gupta Nidhi, Verma Ramesh   +2 more
doaj   +3 more sources

Benchmarking progression-free survival ratio as primary endpoint in precision oncology clinical trials [PDF]

npj Precision Oncology
Progression Free Survival Ratio (PFSratio), as defined as the ratio between PFS on investigational treatment (PFS2) and PFS on the last prior therapy (PFS1), is a popular endpoint in precision oncology (PO) studies.
Federico Nichetti, Jennifer Hüllein, Pauline du Rusquec, Erin Pleasance, Li Chen, Andreas Mock, Peter Horak, Paolo Ambrosini, Simone Rota, Monica Niger, Luca Agnelli, Gabriele Tinè, Dominic Edelmann, Christophe Le Tourneau, Janessa Laskin, Giancarlo Pruneri, Chi Wang, Daniel Hübschmann, Filippo de Braud, Stefan Fröhling, Luigi Mariani   +20 more
doaj   +2 more sources

The case against censoring of progression-free survival in cancer clinical trials – A pandemic shutdown as an illustration [PDF]

BMC Medical Research Methodology, 2022
Background Missing data may lead to loss of statistical power and introduce bias in clinical trials. The Covid-19 pandemic has had a profound impact on patient health care and on the conduct of cancer clinical trials.
Corinne Jamoul, Laurence Collette, Elisabeth Coart, Koenraad D’Hollander, Tomasz Burzykowski, Everardo D. Saad, Marc Buyse   +6 more
doaj   +4 more sources

Discovering heterogeneous treatment effects on slope-based endpoints in chronic kidney disease trials [PDF]

BMC Medical Research Methodology
Background Chronic kidney disease (CKD) is slowly progressive, with clinically-relevant end-points of interest (e.g. kidney failure, dialysis, transplantation, death due to kidney disease) occurring many years after diagnosis, making the design of trials
Tianyu Pan, Lu Tian, Manjula Kurella Tamura, Maria Montez-Rath, Vivek Charu   +4 more
doaj   +2 more sources

Responder identification in clinical trials with censored data [PDF]

Computational Statistics & Data Analysis, 2006
We present a newly developed technique for identification of positive and negative responders to a new treatment which was compared to a classical treatment (or placebo) in a randomized clinical trial. This bump-hunting-based method was developed for trials in which the two treatment arms do not differ in survival overall.
Kehl, Victoria, Ulm, Kurt
openaire   +2 more sources

Survival analysis for AdVerse events with VarYing follow-up times (SAVVY)—estimation of adverse event risks

Trials, 2021
Background The SAVVY project aims to improve the analyses of adverse events (AEs), whether prespecified or emerging, in clinical trials through the use of survival techniques appropriately dealing with varying follow-up times and competing events (CEs ...
Regina Stegherr, Claudia Schmoor, Jan Beyersmann, Kaspar Rufibach, Valentine Jehl, Andreas Brückner, Lewin Eisele, Thomas Künzel, Katrin Kupas, Frank Langer, Friedhelm Leverkus, Anja Loos, Christiane Norenberg, Florian Voss, Tim Friede   +14 more
doaj   +1 more source

Assessing the Course of Organ Dysfunction Using Joint Longitudinal and Time-to-Event Modeling in the Vasopressin and Septic Shock Trial

Critical Care Explorations, 2020
Objectives:. Non-mortality septic shock outcomes (e.g., Sequential Organ Failure Assessment score) are important clinical endpoints in pivotal sepsis trials. However, comparisons of observed longitudinal non-mortality outcomes between study groups can be
Michael O. Harhay, PhD, Alessandro Gasparini, PhD, Allan J. Walkey, MD, MS, Gary E. Weissman, MD, MSHP, Michael J. Crowther, PhD, Sarah J. Ratcliffe, PhD, James A. Russell, MD, on behalf of the Vasopressin and Septic Shock Trial (VASST) Investigators, J. A. Russell, K. R. Walley, C. L. Holmes Boulton, J. T. Granton, P. C. Hebert, D. J. Cooper, S. Mehta, J. Singer, A. C. Gordon, M. M. Storms, S. Jones, J. A. Russell, M. M. Storms, K. R. Walley, G. R. Bernard, A. S. Slutsky, G. A. Wells, A. Gasparini, B. Savage, D. Ayers, R. Woods, K. Wu, M. Maralit, L. Smith, K. Foley, A. Suri, M. Steinberg, B. Howe, P. Galt, A. Higgins, M. M. Storms, M. E. LeBlanc, A. M. Sutherland, A. Sham, A. McLeod, D. R. Dorscheid, M. Hameed, L. Lazosky, S. Helderweirt, C. Honeyman, T. Terins, D. Chittock, J. Ronco, L. Smith, S. Logie, G. Wood, F. Auld, V. Stedham, M. Mantle, L. Fox, G. D. McCauley, J. D. Rolf, C. Erbacher, G. Martinka, S. Goulding, S. Silverwood, L. Leung, S. Keenan, J. Murray, M. Van Osch, B. Light, M. Dominique, P. Gray, R. Stimpson, S. Rosser, D. Bell, W. Janz, P. C. Hebert, T. McArdle, I. Watpool, J. T. Granton, M. Steinberg, A. Matte-Martyn, D. J Cook, E. McDonald, F. Clarke, A. Tkaczyk, N. Zytaruk, T. Stewart, A. Suri, C. Martinez-Motta, R. MacDonald, V. Sivanantham, R. Hodder, J. Foxall, M. Lewis, M. Ward, C. Dos Santos, J. Friedrich, D. Scales, O. Smith, I. DeCampos, A. Richards, H. Michalopoulos, U. Bakshi, W. Sibbald, T. Smith, K. Code, B. Bojilov, C. Dale, M. Keogh, M. Meade, L. Hand, C. Martin, J. Kehoe, V. Binns, M. McGuire, G. Poirier, L. Provost, J. Muscedere, C. Diemer, D. J. Cooper, V. Pellegrino, A. Hilton, S. Morrison, C. Weatherburn, K. Moulden, C. Harry, J. J. Presneill, M. S Robertson, J. F. Cade, B. D. Howe, D. K. Barge, C. A. Boyce, F. Healy, C. Wright, D. Weyandt, J. Barrett, C. Walker, P. Galt, S. Burton, G. Dobb, S. Perryman, J. Chamberlain, L. Thomas, A. Bersten, L. Daly, T. Hunt, D. Wood, B. Patel, J. Larson, M. Rady, G. LeBrun, E. Boyd, R. Rush   +152 more
doaj   +1 more source

RECIST 1.1 and lesion selection: How to deal with ambiguity at baseline?

Insights into Imaging, 2021
Response Evaluation Criteria In Solid Tumors (RECIST) is still the predominant criteria base for assessing tumor burden in oncology clinical trials. Despite several improvements that followed its first publication, RECIST continues to allow readers a lot
Antoine Iannessi, Hubert Beaumont, Yan Liu, Anne-Sophie Bertrand   +3 more
doaj   +1 more source