Abstract
We sought to refine a screening measure for discriminating a sensitized or normal sensation pain phenotype among African American adults with sickle cell disease (SCD). To develop scoring schemes based on sensory pain quality descriptors; evaluate their performance on classifying patients with SCD who had sensitization or normal sensation, and compare with scores on the Self-report Leeds Assessment of Neuropathic Symptoms and Signs (S-LANSS) and the Neuropathic Pain Symptom Inventory (NPSI). Participants completed PAINReportIt, quantitative sensory testing (QST), S-LANSS, and NPSI. Conventional binary logistic regression and least absolute shrinkage and selection operator (lasso) regression were used to obtain 2 sets of weights resulting in 2 scores: the PR-Logistic (PAINReportIt score weighted by conventional binary logistic regression coefficients) and PR-Lasso (PAINReportIt score weighted by lasso regression coefficients). Performance of the proposed scores and the existing scores were evaluated. Lasso regression resulted in a parsimonious model with non-zero weights assigned to 2 neuropathic descriptors, cold and spreading. We found positive correlations between the PR-Lasso and other scores: S-LANSS (r=0.22, P<0.01), NPSI (r=0.22, P<0.01), and PR-Logistic (r=0.35, P<0.01). The NPSI and PR-Lasso performed similarly at different levels of required specificity and outperformed the S-LANSS and PR-Logistic at the various specificity points. The PR-Lasso offers a way to discriminate a SCD pain phenotype.
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