87 citations · 557 across the 33 of their papers we have counts for
33 papers
Communicating results in trials with multiple hypotheses or adaptive design features
Elina Asikanius, Marcel Wolbers, Mouna Akacha +8
Over time, clinical trials have increasingly incorporated complex design and analysis elements such as interim analyses, adaptations, multiple endpoints, and sophisticated multipli…
Statistical Methodology Groups in the Pharmaceutical Industry
Jenny Devenport, Tobias Mielke, Mouna Akacha +10
Research and Development is the largest budget position in the pharmaceutical industry, with clinical trials being a critical, yet costly and time-consuming component to inform dec…
Exhausting the type I error level in event-driven group-sequential designs with a closed testing procedure for progression-free and overall survival
Moritz Fabian Danzer, Kaspar Rufibach, Jan Beyersmann +1
In oncological clinical trials, overall survival (OS) is the gold-standard endpoint, but long follow-up and treatment switching can delay or dilute detectable effects. Progression-…
"6 choose 4": A framework to understand and facilitate discussion of strategies for overall survival safety monitoring
Godwin Yung, Kaspar Rufibach, Marcel Wolbers +2
Advances in anticancer therapies have significantly contributed to declining death rates in certain disease and clinical settings. However, they have also made it difficult to powe…
Clinical trials with interim analyses: Standardizing Terminology to increase clarity
Elina Asikanius, Benjamin Hofner, Lisa V. Hampson +5
Interim analyses for group-sequential decision making are prevalent in clinical trials. Methodology is well established and has been routinely implemented over the last decades. St…
Using shrinkage methods to estimate treatment effects in overlapping subgroups in randomized clinical trials with a time-to-event endpoint
Marcel Wolbers, Mar Vázquez Rabuñal, Ke Li +2
In randomized controlled trials, forest plots are frequently used to investigate the homogeneity of treatment effect estimates in subgroups. However, the interpretation of subgroup…
Balancing events, not patients, maximizes power of the logrank test: and other insights on unequal randomization in survival trials
Godwin Yung, Kaspar Rufibach, Marcel Wolbers +2
We revisit the question of what randomization ratio (RR) maximizes power of the logrank test in event-driven survival trials under proportional hazards (PH). By comparing three app…
Survival analysis for AdVerse events with VarYing follow-up times (SAVVY): summary of findings and a roadmap for the future of safety analyses in clinical trials
Kaspar Rufibach, Jan Beyersmann, Tim Friede +2
The SAVVY project aims to improve the analyses of adverse events (AEs) in clinical trials through the use of survival techniques appropriately dealing with varying follow-up times…
Oncology clinical trial design planning based on a multistate model that jointly models progression-free and overall survival endpoints
Alexandra Erdmann, Jan Beyersmann, Kaspar Rufibach
When planning an oncology clinical trial, the usual approach is to assume proportional hazards and even an exponential distribution for time-to-event endpoints. Often, besides the…
Applying the Estimand and Target Trial frameworks to external control analyses using observational data: a case study in the solid tumor setting
Letizia Polito, Qixing Liang, Navdeep Pal +5
In causal inference, the correct formulation of the scientific question of interest is a crucial step. Here we apply the estimand framework to a comparison of the outcomes of patie…
Quantification of follow-up time in oncology clinical trials with a time-to-event endpoint: Asking the right questions
Kaspar Rufibach, Lynda Grinsted, Jiang Li +3
For the analysis of a time-to-event endpoint in a single-arm or randomized clinical trial it is generally perceived that interpretation of a given estimate of the survival function…
Conditional Power and Friends: The Why and How of (Un)planned, Unblinded Sample Size Recalculations in Confirmatory Trials
Kevin Kunzmann, Michael J. Grayling, Kim M. Lee +3
Adapting the final sample size of a trial to the evidence accruing during the trial is a natural way to address planning uncertainty. Designs with adaptive sample size need to acco…
Estimands in Hematologic Oncology Trials
Steven Sun, Hans-Jochen Weber, Emily Butler +2
The estimand framework included in the addendum to the ICH E9 guideline facilitates discussions to ensure alignment between the key question of interest, the analysis, and interpre…
Survival analysis for AdVerse events with VarYing follow-up times (SAVVY) -- estimation of adverse event risks
Regina Stegherr, Claudia Schmoor, Jan Beyersmann +12
The SAVVY project aims to improve the analyses of adverse event (AE) data in clinical trials through the use of survival techniques appropriately dealing with varying follow-up tim…
Survival analysis for AdVerse events with VarYing follow-up times (SAVVY) -- comparison of adverse event risks in randomized controlled trials
Kaspar Rufibach, Regina Stegherr, Claudia Schmoor +12
Analyses of adverse events (AEs) are an important aspect of the evaluation of experimental therapies. The SAVVY (Survival analysis for AdVerse events with Varying follow-up times)…
Principal Stratum Strategy: Potential Role in Drug Development
Björn Bornkamp, Kaspar Rufibach, Jianchang Lin +6
A randomized trial allows estimation of the causal effect of an intervention compared to a control in the overall population and in subpopulations defined by baseline characteristi…
A review of Bayesian perspectives on sample size derivation for confirmatory trials
Kevin Kunzmann, Michael J. Grayling, Kim May Lee +3
Sample size derivation is a crucial element of the planning phase of any confirmatory trial. A sample size is typically derived based on constraints on the maximal acceptable type…
Assessing the Impact of COVID-19 on the Objective and Analysis of Oncology Clinical Trials -- Application of the Estimand Framework
Evgeny Degtyarev, Kaspar Rufibach, Yue Shentu +10
COVID-19 outbreak has rapidly evolved into a global pandemic. The impact of COVID-19 on patient journeys in oncology represents a new risk to interpretation of trial results and it…
Survival analysis for AdVerse events with VarYing follow-up times (SAVVY): Rationale and statistical concept of a meta-analytic study
Regina Stegherr, Jan Beyersmann, Valentine Jehl +4
The assessment of safety is an important aspect of the evaluation of new therapies in clinical trials, with analyses of adverse events being an essential part of this. Standard met…
Integrating Phase 2 into Phase 3 based on an Intermediate Endpoint While Accounting for a Cure Proportion -- with an Application to the Design of a Clinical Trial in Acute Myeloid Leukemia
Kaspar Rufibach, Dominik Heinzmann, Annabelle Monnet
For a trial with primary endpoint overall survival for a molecule with curative potential, statistical methods that rely on the proportional hazards assumption may underestimate th…
Joint modelling of progression-free and overall survival and computation of correlation measures
Matthias Meller, Jan Beyersmann, Kaspar Rufibach
In this paper, we derive the joint distribution of progression-free and overall survival as a function of transition probabilities in a multistate model. No assumptions on copulae…
A multistate model for early decision making in oncology
Ulrich Beyer, David Dejardin, Matthias Meller +2
The development of oncology drugs progresses through multiple phases, where after each phase a decision is made about whether to move a molecule forward. Early phase efficacy decis…
Treatment Effect Quantification for Time-to-event Endpoints -- Estimands, Analysis Strategies, and beyond
Kaspar Rufibach
A draft addendum to ICH E9 has been released for public consultation in August 2017. The addendum focuses on two topics particularly relevant for randomized confirmatory clinical t…
SurvRegCensCov: Weibull Regression for a Right-Censored Endpoint with a Censored Covariate
Stanislas Hubeaux, Kaspar Rufibach
Biomarker data is often subject to limits of quantification and/or limits of detection. Statistically, this corresponds to left- or interval-censoring. To be able to associate a ce…