From Data to Knowledge. Advancing Life Sciences: Editorial for the CEN2023 Special Issue

This Special Issue—From Data to Knowledge. Advancing Life Sciences—arose from the Fifth Conference of the Central European Network (CEN2023) of the International Biometric Society, which took place on September 3–7, 2023, in Basel, Switzerland (https://cen2023.github.io/home/). More than 500 colleagues registered for in-person attendance and a further 100 participated virtually, representing more than 30 countries. The scientific program began on Sunday with seven short courses. From Monday through Thursday, the main conference featured seven parallel tracks and nearly 400 oral and poster contributions, including keynote presentations by Ruth Keogh, Alicja Szabelska-Beręsewicz, and Peter Bühlmann.

This special issue consists of 14 peer-reviewed articles generated from research work presented at the symposium. The collection reflects the vibrancy and breadth of current research in biometrics, spanning areas such as clinical trials, epidemiology, genomics, and ecology. Von Felten et al. performed a simulation study comparing multiple approaches to estimating the survivor average causal effect in randomized trials with outcomes truncated by death. Carrozzo et al. compared the statistical efficiency of a two-arm crossover randomized controlled trial with that of a meta-analysis of N-of-1 studies, highlighting the potential of sequential aggregation. Burk et al. proposed a cooperative penalized regression approach for high-dimensional variable selection with competing risks, improving feature selection over traditional methods. Erdmann et al. demonstrated how multistate modeling of progression-free and overall survival endpoints can enhance oncology clinical trial design, especially in the presence of nonproportional hazards. Wünsch et al. investigated how the flexibility in gene set analysis can lead to overoptimistic findings, raising awareness of methodological uncertainty and offering practical guidance. Nassiri et al. proposed a Bayesian posterior probability adjustment method to mitigate class imbalance in classification tasks, improving predictive accuracy. Kim et al. introduced an inverse-weighted quantile regression approach tailored for partially interval-censored data, applicable to complex biomedical endpoints. Teschke et al. developed a method using cross-leverage scores to efficiently detect interaction effects in high-dimensional genetic data. Uno et al. proposed Firth-type penalized regression methods to improve the performance of modified Poisson and least-squares regression models in small or sparse binary outcome settings. Langthaler et al. developed a nonparametric inference method for assessing ecological niche overlap among multiple species, supporting biodiversity research. Kipruto and Sauerbrei revisited postestimation shrinkage in linear models, introducing a modified parameter-wise shrinkage method and assessing its performance in various settings. Röver and Friede explored the concept of “study twins” in meta-analysis, showing how limited information from two trials can complicate decisions about heterogeneity. Behning et al. extended random survival forests to competing risk settings by incorporating subdistribution-based imputation strategies, demonstrating improved prediction of cumulative incidence functions. Finally, Rousson and Locatelli developed mortality indicators derived from years of life lost and applied them to quantify the impact of COVID-19 in 30 countries.

We express our gratitude to the many colleagues who served as reviewers and provided thoughtful, high-quality assessments of the submitted articles. This issue would not have been possible without their generous and professional commitment. As is customary for the Biometrical Journal, the names of all reviewers will be acknowledged in a general year-end list to be published in a future issue. We also thank Matthias Schmid, Monika Kortenjann, and the entire editorial team of the Biometrical Journal for their continuous efforts in ensuring a smooth and timely production process. Finally, we gratefully acknowledge the generous support of the sponsors and funding bodies of the CEN2023 conference: Amgen, Basel City, BeiGene, Boehringer Ingelheim, Bristol-Myers Squibb, CRC Press, Cytel, Datamap, Denali, Janssen, Karger, Novartis, PHRT Network, Posit, Roche, Sanofi, Springer, and the Swiss National Science Foundation.

We look forward to the next CEN conference in Warsaw in 2026. See you there!