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Project Results

Ondra, T., Jobjörnsson, S., Beckman, R.A., Burman, C.-F., König, F., Stallard, N. and Posch, M. (2019) Optimized adaptive enrichment designs. Statistical Methods in Medical Research, 28, 2096-2111.

Ursino, M., Ying, Y., Alberti, C., Favrais, G., Friede, T., Lentz, F., Stallard, N. and Zohar, S. (2019) A dose-finding design for seizure reduction in neonates. Journal of the Royal Statistical Society Series C, 68, 427-444.

Shing, L.M., Ursino, M., Cheung, Y.K. and Zohar, S. (2019). Dose-finding designs for cumulative toxicities using multiple constraints. Biostatistics, 20, 17-29. Doi: 10.1093/biostatistics/kxx059

Thall, P.F., Ursino, M., Baudouin, V., Alberti, C. and Zohar, S. (2019). Bayesian Treatment Comparison Using Parametric Mixture Priors Computed from Elicited Histograms. Statistical Methods in Medical Research, 28, 404-418. Doi: 10.1177/0962280217726803

Day, S., Jonker, A.H., Lau, l.P.L., Hilgers, R.-D., Irony, I., Larsson, K., Roes, K. and Stallard, N. (2018) Recommendations for the design of small population clinical trials. Orphanet Journal of Rare Diseases, 13: 195.

Friede, T., Posch, M., Zohar, S., Alberti, C., Benda, N., Comets, E., Day, S., Dmitrienko, A., Graf, A., Günhan, B.K., Hee, S.W., Lentz, F., Madan, J., Miller, F., Ondra, T., Pearce, M., Röver, C., Toumazi, A., Unkel, S., Ursino, M., Wassmer, G. and Stallard, N. (2018) Recent advances in methodology for clinical trials in small populations: the InSPiRe project. Orphanet Journal of Rare Diseases, 13, 186.

Miller, F., Zohar, S., Stallard, N., Madan, J., Posch, M., Hee, S.W., Pearce, M., Vagero, M. and Day, S. (2018) Approaches to sample size calculation for clinical trials in rare diseases. Pharmaceutical Statistics, 17, 214-230.

Hee, S.W., Parsons, N. and Stallard, N. (2018) Decision-theoretic designs for a series of trials with correlated treatment effects using the Sarmanov multivariate beta-binomial distribution. Biometrical Journal, 60, 232-245. doi:10.1002/bimj.201600202

Pearce, M., Hee, S.W., Madan, J., Posch, M., Day, S., Miller, F., Zohar, S. and Stallard, N. (2018) Value of information methods to design a clinical trial in a small population to optimize a health economic utility function. Medical Research Methodology, 18, 20.

Toumazi, A., Comets, E., Alberti, C., Friede, T., Lentz, F., Stallard, N., Zohar, S. and Ursino, M. (2018) dfpk: an R-package for Bayesian Dose-Finding Designs using Pharmacokinetics (PK) for Phase I Clinical Trials. Computer Methods and Programs in Biomedicine, 157, 163-177.

Petit C, Samson A, Satoshi M, Ursino M, Guedj J, Jullien V, Comets E, Zohar S (2018) Unified approach for extrapolation and bridging of adult information in early-phase dose-finding paediatric studies Stat Methods Med Res, 27, 1860-1877. Doi: 10.1177/0962280216671348

Ursino, M., Zohar, S., Lentz, F., Alberti, C., Friede, T., Stallard, N., Comets, E. (2017) Dose-finding methods using pharmacokinetics in small populations. Biometrical Journal, 59, 804-825. doi:10.1002/bimj.201600084

Wandel S, B Neuenschwander B, Röver C, Friede T (2017) Using phase II data for the analysis of phase III studies: an application in rare diseases. Clinical Trials, 14, 277-285. Doi: 10.1177/1740774517699409

Daniel R. Messroghli , Thomas Pickardt , Marcus Fischer , Bernd Opgen-Rhein , Konstantin Papakostas , D Boecker , A Jakob , Markus Khalil , Goetz C. Mueller , Florian Schmidt , Michael Kaestner , Floris E.A. Udink ten Cate , Robert Wagner , Bettina Ruf , Daniela Kiski , Gesa Wiegand , Franziska Degener , Ulrike M.M. Bauer , Tim Friede , Stephan Schubert (2017) Toward evidence-based diagnosis of

myocarditis in children and adolescents: Rationale, design, and first baseline data of MYKKE, a multicenter registry and study platform. American Heart Journal, 187:133-144. doi: 10.1016/j.ahj.2017.02.027.

Hee SW, Willis A, Smith CT, Day S, Miller F, Madan J, Posch M, Zohar S, Stallard N (2017) Does the low prevalence rate affect the sample size of interventional clinical trials of rare diseases? An analysis of data from the Aggregate Analysis of Orphanet Journal of Rare Diseases 12:44 Doi: 10.1186/s13023-017-0597-1

Röver C, Friede T (2017) Discrete approximation of a mixture distribution via restricted divergence Journal of Computational and Graphical Statistics, 26, 271-222. Doi: 10.1080/10618600.2016.1276840

Kunz, CU, Stallard N, Parsons N, Todd S, FriedeT (2016) Blinded versus unblinded estimation of a correlation coefficient to inform interim design adaptations. Biometrical Journal, 59, 344-357. Doi: 10.1002/bimj.201500233

Chataway J , Friede T (2016) The N-MOmentum trial: Building momentum to advance trial methodology in a rare disease Mult Scler June 2016 22: 852-853, doi:10.1177/1352458516643399

Friede, T., Röver, C., Wandel, S., and Neuenschwander, B. (2016) Meta-analysis of few small studies in orphan diseases. Res. Syn. Meth., doi: 10.1002/jrsm.1217

Friede T, Röver C , Wandel S and Neuenschwander B (2016) Meta-analysis of two studies in the presence of heterogeneity with applications in rare diseases, Biometrical Journal 2016 doi: 10.1002/bimj.201500236

Varges D, Manthey H, Heinemann U, Ponto C, Schmitz M, Schulz-Schaeffer WJ, Krasnianski A, Breithaupt M, Fincke F, Kramer K, Friede T, Zerr (Published online before print 2 November 2016) Doxycycline in early CJD: a double-blinded randomised phase II and observational study, Journal of Neurology, Neurosurgery and Psychiatry 2016 doi: 10.1136/jnnp-2016-313541

Ondra, T, Jobjörnsson, S, Beckman, R A, Burman, C-F, König, F, Stallard, N and Posch, M (2016) Optimizing trial designs for targeted therapies. PLoS One, 11: e0163726

Hilgers, R.-D., Roes, K. and Stallard, N. (2016) Directions for new developments on statistical design and analysis of small population group trials. Orphanet Journal of Rare Diseases, 11, 78.

Unkel S, Röver C, Stallard N, Benda N, Posch M, Zohar S and Friede S, (20 Feb 2016) Systematic reviews in paediatric multiple sclerosis and Creutzfeldt-Jakob disease exemplify shortcomings in methods used to evaluate therapies in rare conditions. Orphanet Journal of Rare Diseases, 201611:16, doi: 10.1186/s13023-016-0402-6

Ondra T, Dmitrienko A, Friede T, Graf A, Miller F, Stallard N, Posch M. (2016), Methods for identification and confirmation of targeted subgroups in clinical trials: a systematic review. Journal of Biopharmaceutical Statistics, 26, 99-119

Petit C, Jullien V, Samson A, Guedj J, Kiechel J-R, Zohar S, Comets E (2015) Designing a Pediatric Study for an Antimalarial Drug by Using Information from Adults. Antimicrob Agents Chemotherapy, 2015 Dec 28;60(3):1481-91 doi:10.1128/AAC.01125-15

Röver, C, Knapp, G and Friede (2015), Hartung-Knapp Sidik Jonkman Approach and its modification for random-effects meta-analysis with few studies. BMC Medical Research Methodology, Vol 15:99. doi: 10.1186/s12874-015-0091-1

Hee, S W, Hamborg, T, Day, S, Madan, J, Miller, F, Posch, M, Zohar S and Stallard, N (2015), Decision theoretic designs for small trials and pilot studies: a review. doi: 10.1177/0962280215588245 (Published online before print June 5, 2015)

Graf, A. C., Posch, M. and Koenig, F. (2014), Adaptive designs for subpopulation analysis optimizing utility functions. Biom. J.. doi: 10.1002/bimj.201300257 (Published 14 November 2014)

Koenig, F., Slattery, J., Groves, T., Lang, T., Benjamini, Y., Day, S., Bauer, P. and Posch, M. (2014), Sharing clinical trial data on patient level: Opportunities and challenges. Biom. J.. doi: 10.1002/bimj.201300283 (Published 18 June 2014)



Artemis Toumazi , Moreno Ursino and Sarah Zohar, INSERM, Paris. (10 August 2016). R package dfpk "A Bayesian Dose-Finding Design using Pharmacokinetics (PK) for Phase I Clinical Trials". Available at: 

Christian Roever, University Medical Centre, Gottingen. (16 December 2015). Available at: The bayesmeta package provides a collection of functions to facilitate easy Bayesian inference in the generic random-effects meta-analysis model. It allows to derive the posterior distribution of the two parameters (effect and heterogeneity), and provides the functionality to evaluate joint and marginal posterior probability distributions, predictive distributions, shrinkage, etc.

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