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Method-Hub ECU

Method-Hub ECU

Please feel free to contact us for a free initial consultation

The aim of the Methods Hub (Epidemiology Core Unit, ECU) is to ensure a high standard of methodological quality in clinical and clinical-epidemiological studies. We offer consultancy services covering every stage, from planning through to implementation and analysis. In doing so, we enable:

  • Ensuring robust study planning
  • High-quality implementation of studies
  • Methodologically sound analysis of study data
  • Effective reuse of study data

The focus here is on non-regulated trials / clinical-epidemiological studies. For enquiries regarding regulated trials, please contact the KKS network or your local KKS/ZKS. NUKLEUS (APT-SU) can provide support for adaptive trial designs.

Epidemiology Centre (ECU)

Expertise in core epidemiology

We support you with an interdisciplinary team comprising specialists in biometrics, epidemiology, medical informatics, health sciences/public health and paediatrics, with complementary expertise across several locations.

Expert reports

Patient-Reported Outcomes (PROs) & Patient-Reported Outcome Measures (PROMs)

Brief description: Establishment of a German registry infrastructure for rare diseases: linking disease-specific registries, clinical data and PROMs from patients with rare diseases

NUM-MB’s role: Methodological advice on the collection, harmonisation and use of PROMs within NUKLEUS

Num4Rare

The NUM Methods & Biosamples Hub (NUM-MB) recommends a standardised, modular system for collecting patient-reported outcomes (PROs) within the NUM. This is based on a cross-disease core module using the PROMIS metric, an internationally recognised measurement system founded on modern test theory. It is supplemented by additional modules specific to particular diseases, interventions and contexts. The recommendation is aimed at all NUM researchers who wish to collect PROs in studies, registries, cohorts or healthcare projects in future in a psychometrically robust manner and in a way that is harmonised across specialist fields.

Recommendation on the collection of PROs

NUM external partners & collaborations

Outputs from the external healthcare-related data (eVeDa)

Brief description: Establishment of a German registry infrastructure for rare diseases; linking the TREAT registry to NUM4Rare

NUM-MB’s role: Providing advice on linking external register data from the TREATgermany medical register with health insurance data

NUM4Rare

Role of NUM-MB: Methodological advice on linking data with health insurance data

Role NUM-MB: Providing advice on adapting patient information, consent and secondary use documents in relation to the linking of external data (health insurance funds, cancer registries, ePA)

Paediatric-specific methodological advice for researchers within the NUM

 

Methodology Toolbox:

A comprehensive toolkit of methods and instruments, comprising internationally standardised and established screening and diagnostic tools for assessing the health and clinical presentations of children and adolescents.

LLM-based classification

  • Generative AI enables effective, resource-efficient structuring and classification of unstructured data
  • Areas of application: data imputation, curation and augmentation; process automation; matching different data sets; metadata corrections

Data analysis using Machine Learning

  • Machine Learning enables the identification of non-linear and complex associations in complex models and, provided there is a sufficient volume of data, can be applied without prior knowledge (‘hypothesis-free’).
  • Areas of application: classification and predictive models, causal inference

Our services

  • Practical advice on the use of state-of-the-art Machine Learning and generative AI methods in relation to clinical and clinical-epidemiological data
  • Support in identifying suitable project partners

Outputs of Clinical Data Science (CDS)

Brief description: Investigation into the use of Large Language Models (LLMs) to support the partial automation of systematic reviews

NUM-MB’s role: CDSexpertise

Systematic Reviews with LLMs

Brief description: Support for the conduct of a systematic review (“Systematic Review on the Gender Gap in the Care of Patients with Impulse Control Disorders”) by Ruhr University Bochum using several large language models (LLMs)

NUM-MB’s role: CDS expertise

GENIOBA

Brief description: Investigation of the diagnostic potential of Large Language Models (LLMs) to support clinical differential diagnoses in infectious diseases

NUM-MB’s role: CDS expertise

Dr LLM

Brief description: AnLLM-based process escrow service to improve data minimisation in the process automation of agent-based workflows

NUM-MB role: CDS expertise