Immuno-IMDC Prognostic Algorithm for Metastatic Renal Carcinoma
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current prognostic classification systems for metastatic renal cell carcinoma (mRCC), such as the IMDC classification, fail to accurately stratify patients into risk classes due to heterogeneity within the c-Intermediate group, leading to inconsistent treatment responses and therapeutic inefficiencies.
Innovation Solution
A method integrating the IMDC classification with immunological parameters, specifically serum VEGF concentration and the percentage of circulating CD8+CD137+ T lymphocytes, to create an Immuno-IMDC prognostic algorithm that reclassifies patients into more precise risk categories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the IMDC classification system is used to stratify mRCC patients into risk classes, then the classification can be performed using standard clinical parameters, but the heterogeneity within the c-Intermediate group leads to poor prognostic stratification accuracy
Solution Approach 1:
The patent combines the IMDC classification system with immunological parameters (serum VEGF concentration and percentage of circulating CD8+CD137+ T lymphocytes) to create an integrated Immuno-IMDC prognostic algorithm. This merging of clinical and immunological data allows for more precise risk stratification while maintaining the ease of using standard clinical parameters, as the immunological tests are performed alongside routine clinical evaluations.
Solution Approach 2:
The patent adds a new dimension to the traditional IMDC classification by incorporating immunological parameters. Instead of relying solely on six clinical parameters (performance status, interval between diagnosis and treatment, absolute neutrophil count, platelet count, hemoglobin level, and tumor site), the system integrates serum VEGF concentration and CD8+CD137+ T lymphocyte percentage, thereby enhancing the prognostic stratification accuracy without compromising the ease of classification.
2Adaptability or versatility
If patients are classified into the c-Intermediate risk class based on IMDC criteria, then a large proportion of patients (up to 60%) can be grouped together, but this group exhibits great heterogeneity in IMDC parameters and very different prognoses
Solution Approach 1:
The patent segments the c-Intermediate risk class into more homogeneous subgroups by incorporating immunological parameters. Patients within the c-Intermediate group are further stratified based on their serum VEGF concentration and CD8+CD137+ T lymphocyte percentage, creating more reliable prognostic subcategories that reduce heterogeneity while maintaining the ability to group patients with similar clinical characteristics.
Solution Approach 2:
The patent applies local quality by tailoring the prognostic assessment to individual patients within the c-Intermediate group based on their specific immunological profiles. Instead of treating all c-Intermediate patients uniformly, the system evaluates and classifies patients according to their unique combinations of VEGF levels and T lymphocyte percentages, thereby improving prognostic prediction reliability for each patient while maintaining the overall grouping capability.
3Ease of operation
If the traditional IMDC classification is used, then the system remains simple and easy to apply, but it fails to effectively identify patients with the same clinical characteristics or significantly increase available therapies
Solution Approach 1:
The patent merges the simple IMDC classification system with immunological testing to create an enhanced prognostic algorithm that maintains ease of application while improving therapy optimization efficiency. The immunological parameters are integrated into the existing classification framework, allowing clinicians to apply the system without adding complex procedures, yet achieving better patient stratification and therapy selection.
Solution Approach 2:
The patent changes the parameters used in the prognostic classification by adding immunological measurements (serum VEGF concentration and CD8+CD137+ T lymphocyte percentage) to the traditional clinical parameters. This parameter expansion enhances the system's ability to identify patients with similar characteristics and optimize therapy selection, while the changes are implemented in a way that preserves ease of application through standardized testing protocols.
Data Source
AI summary
The present invention relates to a method for rapidly and accurately determining the prognostic score and subsequent division into risk classes, inpatients with metastatic renal carcinoma by acquiring and processing immunological analyses on the patients and combining those immunological analyses with the currently used IMDC classification.