Methods for planning and analysis of clinical phase II trials in oncology

• Applicant: Professor Meinhard Kieser, Ph.D.
• Subject Area: Epidemiology and Medical Biometry/Statistics
• Term: from 2009 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 151327791

Within the current funding period of the project, two-stage adaptive designs were developed for clinical phase II studies in oncology that, during the course of the trial, allow for arbitrary (especially: data-driven) modifications of the initial sample size fixed in the planning phase while controlling the significance level. These designs allow for addressing unforeseen or unpredictable changes occurring during the study conduct without compromising the specified type I error rate. For example, assumptions regarding the treatment effect made in the planning stage might be put into question by the results of an interim analysis. It would then be a promising option either to reduce or to increase the sample size. Currently, however, it is still an open question which one of the various possible strategies for sample size recalculation is "optimal" in such a situation. This problem will be examined in the continuation phase of the project. Based on the results of these investigations, recommendations shall be provided about the choice of an appropriate design or sample size recalculation strategy in the respective situation at hand. Moreover, methods are to be developed that allow to adequately deal with over- or underrunning of the sample size planned for the interim analysis. Such a situation arises quiet often in practice, for example due to a too late or too early stop of patient recruitment. All currently available methods show serious deficits; amongst others, they do not control the pre-specified significance level.Furthermore, there are currently no methods available for calculating valid p-values, point estimates andconfidence intervals in phase II oncology trials with an adaptive design. It is well-known that an application of methods developed for the respective one-stage designs lead to distorted results and, consequently, to a biased interpretation of the study. When our project is being continued, it is our aim to develop analysis methods for phase II oncology trials with adaptive design that take into account the sequential and flexible nature of the study design leading to unbiased results. The characteristics of the created methods will be examined, and recommendations will be given about which of the methods are to be preferred.The developed methods will be implemented in an R software package with a user-friendly user interface. This will lead to a direct transfer of the project results into practice.

• DFG Programme: Research Grants
• Participating Institution: Deutsches Krebsforschungszentrum (DKFZ); Forschungsschwerpunkt Krebsrisikofaktoren und Prävention; Abteilung Biostatistik; Coventry University ; Faculty of Health and Life Sciences; Universitätsmedizin Göttingen; Institut für Medizinische Statistik; Nationales Centrum für Tumorerkrankungen (NCT) Heidelberg – DKFZ; Universitätsklinikum Heidelberg ; Radiologische Klinik