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Study identifies potential model for diagnosing, differentiating between types of back pain
Through serum sample analysis, researchers were able to develop models for distinguishing between causes of chronic low back pain and identify biomarkers that may be useful in diagnosing causes of discogenic low back pain.
The researchers collected serum samples from patients with discogenic low back pain (DLBP), chronic lumbar disc herniation (LDH), chronic low back pain (CLBP) of unknown origin and healthy controls; participants were then randomly divided into a training set and a blind test set.
Using scatter plots, the researchers assessed the discriminative ability of the two most significantly differential peptide peaks from each group. Classifications models were then developed through the use of differential peptide peaks to evaluate diagnostic accuracy.
The researchers identified the fewest statistically significant differential peaks between DLBP and CLBP.
The two most significantly differential peaks had poor discriminative ability in classifying DLBP from CLBP, but good discriminative ability for differentiating between DLBP and LDH, according to the researchers.
In the blind test group, accuracy of models for classification of DLBP vs. CLBP was not very high; however, the researchers noted a higher accuracy for classification of DLBP vs. LDH and LDH vs. healthy controls.
Disclosure: The authors have no relevant financial disclosures.