Abstract
BACKGROUND: 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). OBJECTIVE: 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). METHODS: 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. RESULTS: 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. CONCLUSION: The PR-Lasso offers a way to discriminate a SCD pain phenotype.