Our Contributions to EHA 2026 in Stockholm

We’re excited to announce that our team contributed to six abstracts at this year’s EHA Congress, held right here in Stockholm. The contributions span both lymphoma and myeloma/MGUS research, including one oral presentation, and reflect our ongoing work in haematological malignancies. A big thank you to the entire team involved in these projects.

Lymphoma

Safety Data and Initial Pooled Efficacy Data from the Nordic Lymphoma Group Phase 3 POLAR BEAR Trial in Elderly or Frail Patients with Diffuse Large Cell Lymphoma – R-POLA-mini-CHP vs. R-mini-CHOP Oral Presentation — Abstract S238
Infection Rates in Patients Treated with CAR-T versus Autologous Stem Cell Transplant for Relapsed/Refractory Large B-Cell Lymphoma and in the General Population: A Swedish Population-Based Study Poster — Abstract PS2085
Treatment for Malignant Lymphomas and Risk of Therapy-Related Myeloid Neoplasms Overall and with High-Risk Features Poster — Abstract PS2096

Myeloma and MGUS

Significant Improvements in Survival Outcomes in Smoldering Multiple Myeloma: A Population-Based Study Poster — Abstract PF801
Patterns of MGUS in Men and Women Participating in the Screened Population-Based iStopMM Study: Earlier Onset or Accelerated M Protein Increase in Men? Poster — Abstract PS1900
Antidiabetic Medication Use and Monoclonal Gammopathy of Undetermined Significance: Associations with Prevalence and M-Protein Trajectories in the iStopMM Study Poster — Abstract PF835

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Clinical Trial Services

Clinical Trial Services Biostatistics services of RDA are the cornerstone of clinical trial design, execution, and interpretation. Biostatistical support by RDA will ensure that your clinical development programme and inherent studies are scientifically rigorous, appropriately powered, and capable of generating reliable evidence for regulatory approval and clinical use. RDA’s expertise for clinical development is focused […]

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Methods Development

Methods Development We provide expert guidance in finding the appropriate statistical approach to answer your question… and if there isn’t yet a method, well, we can develop one. While applying biostatistics to address your research question is essential, there may be times when existing methods fall short for your specific problem. In such cases, we’re […]

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Applied Biostatistics

Applied Biostatistics Biostatistics plays a crucial role in advancing medical research. Whether it’s clinical trials, epidemiological studies, or pre-clinical research, biostatistics is essential for drawing meaningful, impactful conclusions from complex data. Our team consists of internationally recognized experts in applied biostatistics, with deep experience in a wide range of areas such as survival analysis, multi-state […]

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Haematology

Haematological malignancies At Red Door Analytics, we have extensive experience in working with haematological malignancies, demonstrated through 18 publications in peer-reviewed journals. Our expertise spans epidemiological studies on prognosis and late effects, as well as randomised clinical trials. Based in Stockholm, we have unique experience in accessing and working with registry data from the Nordic […]

Videos

Introduction to Epidemiological Study Designs

This video offers a comprehensive introduction to epidemiological study designs, emphasising their classification, key definitions, strengths, limitations, and practical applications. We will dive into the most commonly used study designs, exploring their structure, purpose, and the contexts in which they are most effective. Throughout the video, real-world case studies of landmark research will be used […]

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Real-World Evidence (RWE)

Real-World Evidence Real-world evidence (RWE) refers to data and information that, unlike data generated in clinical trials conducted in controlled environments, has been obtained from everyday clinical practice, patient registers, or other sources outside the clinical trial setting. RWE plays a crucial role in complementing traditional clinical trial data, providing insights into the safety, effectiveness, […]

Videos

State-of-the-art statistical models for modern HTA

At @RedDoorAnalytics, we develop methodology and software for efficient modelling of biomarkers, measured repeatedly over time, jointly with survival outcomes, which are being increasingly used in cancer settings. We have also developed methods and software for general non-Markov multi-state survival analysis, allowing for the development of more plausible natural history models, where patient history can […]

Videos

Multilevel (hierarchical) survival models: Estimation, prediction, interpretation

Hierarchical time-to-event data is common across various research domains. In the medical field, for instance, patients are often nested within hospitals and regions, while in education, students are nested within schools. In these settings, the outcome is typically measured at the individual level, with covariates recorded at any level of the hierarchy. This hierarchical structure […]

Statistical Primers

What are competing risks?

Competing risks In survival analysis, competing risks refer to the situation when an individual is at risk of experiencing an event that precludes the event under study to occur. Competing risks commonly occur in studies of cause-specific mortality, as all other causes of death than the one under study might happen before the individuals “have […]

Statistical Primers

What is immortal time bias?

Immortal time bias Immortal time bias is a type of bias that can occur in observational research when the study design allows for a period of time during which the outcome of interest cannot occur, often referred to as “immortal time”. Simply put, immortal time bias occurs when information from a future event is incorporated into the […]

Statistical Primers

What is the proportional hazards assumption?

Proportional hazards Proportional hazards in survival analysis means that the rate at which an event of interest occurs over time for two or more groups or individuals is proportional over time. Specifically, it assumes that the hazard ratio, which represents the relative rate of an event occurring between two groups or individuals, is constant over […]

Statistical Primers

What is censoring?

Censoring refers to a situation in survival analysis where the event of interest is not observed for some of the individuals under study. In this Statistical Primer, we’ll define three types of censoring often seen in survival analysis studies. Censoring occurs when the information on the survival time is incomplete or only partially observed. Censoring […]