Clinical Trial Services

Biostatistics services of RDA is 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 on Hematology and Oncology.

The following list describes the services we provide out of RDA.

Study Design & Sample Size Calculation

Determining appropriate study endpoints and statistical methods.
Calculating sample size and power to ensure the trial can detect meaningful differences.
Supporting adaptive, Bayesian, or innovative trial designs where appropriate.
Defining estimands for analyses, which includes primary, secondary, exploratory endpoints for the protocol.
Specialist service of RDA includes longitudional and advanced survival analysis.

Randomization & Blinding

Developing randomization schemes to eliminate bias.
Ensuring proper stratification and allocation concealment.
Supporting blinding processes to maintain trial integrity.

Statistical Analysis Plan (SAP)

Creating detailed SAPs to predefine methods of data handling, analysis, and reporting.
Expanding on details for estimands for analyses, which includes primary, secondary, exploratory endpoints.
Outlining interim analysis and stopping rules.

Interim Analyses & Data Monitoring

Conducting planned interim analyses to assess efficacy, futility, or safety.
Supporting Data Monitoring Committees (DMCs) with independent statistical reporting.

Final Analysis & Reporting

Performing comprehensive statistical analyses of trial outcomes.
Generating tables, listings, and figures (TLFs) for regulatory submissions.
Supporting clinical study reports (CSRs) and scientific publications.

Advanced Analytics & Modeling

Applying advanced survival analysis, longitudinal modeling, and mixed-effects approaches.
Utilizing real-world data and external controls where applicable.
Leveraging cutting edge methodology and simulation techniques to optimize trial outcomes.
Services can be provided tailoring your needs, ie. by project, or allocation of resources to be utilised.

Clinical Trial Services

Clinical Trial Services Biostatistics services of RDA is 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 on […]

Specialist subjects

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 […]

Specialist subjects

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 […]

Specialist subjects

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 […]

Specialist subjects

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 […]