SLE Biomarker Risk Scoring for Anti-dsDNA-Negative Diagnosis
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Solution Overview
Problem
Current diagnostic methods for systemic lupus erythematosus (SLE) are inaccurate and lack sensitivity, particularly in patients who test negative for anti-dsDNA antibodies, leading to misdiagnosis and inadequate monitoring of disease activity.
Innovation Solution
The method involves determining levels of biomarkers such as BC4d, EC4d, PC4d, ECR1, anti-MCV antibody, and anti-nuclear antibody (ANA) in a biological sample, calculating an SLE risk score through logistic regression analysis, and comparing it to a standard to diagnose or monitor SLE.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional diagnostic criteria (11 ACR criteria) are used for SLE diagnosis, then the diagnostic process is simple and widely applicable, but the diagnostic accuracy and sensitivity are insufficient, especially for patients negative for anti-dsDNA antibodies
Solution Approach 1:
The patent combines multiple diagnostic markers (anti-dsDNA antibodies, BC4d, EC4d, PC4d, ECR1, anti-MCV antibodies, and ANA) into an integrated diagnostic approach. This merging of multiple detection targets allows for improved diagnostic accuracy by capturing a broader range of SLE manifestations, particularly in patients who are negative for anti-dsDNA antibodies alone.
Solution Approach 2:
The patent introduces a multivariate logistic regression model that transforms multiple marker levels into a composite SLE risk score. This parameter transformation approach allows for quantitative assessment of disease probability, converting qualitative marker presence/absence into a continuous risk metric that improves diagnostic precision.
2Reliability
If multiple biomarkers are measured and logistic regression analysis is performed, then the sensitivity and specificity of diagnosis improve, but the complexity of the diagnostic process increases
Solution Approach 1:
The patent introduces a computational algorithm (multivariate logistic regression model) as an intermediary between the measured biomarker levels and the final diagnostic conclusion. This intermediary processes the raw marker data through mathematical transformation, producing a standardized SLE risk score that is easier to interpret and apply clinically, thereby managing the complexity of handling multiple biomarkers.
3Measurement precision
If conventional criteria require 4 or more of 11 criteria for diagnosis, then the diagnostic threshold is clear, but many patients never accumulate enough criteria for definite diagnosis leading to delayed or missed diagnosis
Solution Approach 1:
The patent enables preliminary diagnosis by calculating an SLE risk score based on the measured biomarker levels before patients can accumulate 4 of the 11 conventional criteria. The logistic regression model provides a probabilistic assessment that can identify SLE cases early in the disease course, allowing for earlier intervention and treatment initiation.
4Measurement precision
If liberal standards are applied for determining presence or absence of criteria, then more patients can be diagnosed, but misdiagnosis increases
Solution Approach 1:
The patent transforms the binary presence/absence assessment of diagnostic criteria into a continuous SLE risk score through logistic regression analysis. This parameter change allows for nuanced interpretation of diagnostic probability, enabling clinicians to adjust diagnostic thresholds based on pre-test probability and clinical context, thereby improving both sensitivity and specificity simultaneously.
Data Source
AI summary
Methods of detecting biomarkers in a blood sample obtained from a human subject include detecting an erythrocyte-bound C4d (EC4d) marker, a B-lymphocyte-bound C4d (BC4d) marker, and an anti-nuclear antibody (ANA) in the blood sample; and detecting a level of double-stranded DNA antibody in the blood sample, wherein the human subject is negative for systemic lupus erythematosus based on the level of double-stranded DNA antibody. The methods optionally further include determining a systemic lupus erythematosus risk score by: (a) adjusting the level of EC4d marker by a weighting coefficient to produce a weighted score for EC4d marker; (b) adjusting the level of BC4d marker by a weighting coefficient to produce a weighted score for BC4d marker; (c) adjusting the level of ANA by a weighting coefficient to produce a weighted score for ANA; and (d) combining the weighted score for EC4d marker, the weighted score for BC4d marker, and the weighted score for ANA to generate the systemic lupus erythematosus risk score; wherein the systemic lupus erythematosus risk score does not include a score for double-stranded DNA antibody.