LF Common Case Report Form (CCRF)
Advancing Lipedema Research Through Standardization
The Lipedema Foundation’s Common Case Report Form (CCRF) represents an important step in strengthening the research infrastructure for Lipedema.
Developed through international collaboration and broad stakeholder engagement, the CCRF is a unified, publicly available framework designed to improve data quality, reproducibility, and comparability across studies. By supporting more consistent data collection, it helps researchers generate findings that can be meaningfully compared and evaluated.
The CCRF is organized into Core, Supplemental–Highly Recommended, Supplemental, and Exploratory classifications. This structure allows for standardization of essential data elements while maintaining flexibility for different research designs and clinical settings.
By enabling consistent and transparent data collection, the CCRF supports:
Assess the applicability of findings from individual studies
Compare results across studies
Conduct rigorous meta-analyses
Conduct retrospective analyses to understand which factors matter most for diagnosis
Identify and classify meaningful subtypes
As adoption grows, this shared framework will increasingly facilitate meta-analyses, support more consistent diagnostic research, and strengthen the evidence base informing future advances in treatment, policy, and patient care.
| CDE Classification | Definition | Number of CDEs |
|---|---|---|
| Exploratory | Core + Supplemental Highly Recommended + Supplemental + Data elements that are emerging, experimental, or do not yet have a clear link to Lipedema. These elements may represent novel assessments, biomarkers, or patient-reported outcomes not yet validated with Lipedema populations. Exploratory items can inform hypothesis generation and future standardization but are not yet recommended for routine use. |
Total CDEs: 682
|
| Supplemental | Core + Supplemental Highly Recommended + Data elements that may add scientific or clinical value but are not critical to diagnosis or characterization in all studies. These are useful in specific research aims or contexts, such as exploring specifics (such as triggers) for disease onset or worsening, treatment outcomes, quality of life, or comorbid conditions. |
Total CDEs: 618
|
| Supplemental Highly Recommended |
Core + Data elements that are not required for a basic diagnosis of Lipedema but are strongly recommended for comprehensive characterization of the condition and/or samples. These elements provide important context about subpopulations/subtypes and foundational understanding of disease onset, worsening (progression or exacerbation), severity, or impact and are widely applicable across most Lipedema studies. |
Total CDEs: 424
|
| Core | Common data elements related to the diagnosis of Lipedema include items essential for identifying, confirming, or differentiating Lipedema, as well as those providing clinically relevant information for diagnosis. Core elements include clinically assessed items such as Lipedema diagnosis for research purposes, Lipedema stage, anthropometric measurements, presence of edema, and palpable findings of nodularity or fibrosis. Participant-reported items that support diagnosis are also included, such as pain or discomfort in affected areas, common comorbidities, current medications and supplements, surgical history, menstrual status, family history, and basic demographics. This classification addresses areas of clinical disagreement and research gaps, facilitating data collection for cross-study and cross-geography comparisons to enhance understanding. |
Total CDEs: 288
|
The Exploratory version of the CCRF is the full CCRF and it is recommended that researchers use the most inclusive version of the CCRF as it feasible for their study design.
CCRF Data Dictionaries
The data dictionary versions of the CCRF are detailed references that defines each question on the form: what it means, how responses should be recorded, and how the data is structured behind the scenes. Data dictionaries serve as a “rulebook” to ensure every question is interpreted consistently and the data can be used reliably.