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Publications [#330870] of Francis J. Keefe

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Journal Articles

  1. Askew, RL; Cook, KF; Keefe, FJ; Nowinski, CJ; Cella, D; Revicki, DA; Morgan DeWitt, EM; Michaud, K; Trence, DL; Amtmann, D (2016). A PROMIS Measure of Neuropathic Pain Quality.. Value Health, 19(5), 623-630. [doi]
    (last updated on 2024/03/28)

    Abstract:
    OBJECTIVES: Neuropathic pain (NP) is a consequence of many chronic conditions. This study aimed to develop an unidimensional NP scale with scores that represent levels of NP and distinguish between individuals with NP and non-NP conditions. METHODS: A candidate item pool of 42 pain quality descriptors was administered to participants with osteoarthritis, rheumatoid arthritis, diabetic neuropathy, and cancer chemotherapy-induced peripheral neuropathy. A subset of pain quality descriptors (items) that best distinguished between participants with and those without NP conditions were identified. Dimensionality of pain descriptors was evaluated in a development sample and cross-validated in a holdout sample. Item responses were calibrated using an item response theory model, and scores were generated on a T-score metric. NP scale scores were evaluated in terms of the reliability, validity, and ability to distinguish between participants with and without conditions typically associated with NP. RESULTS: Of the 42 initial items, 5 were identified for the Patient-Reported Outcome Measurement Information System (PROMIS) Neuropathic Pain Quality Scale. T scores exhibited good discriminatory ability on the basis of receiver-operator characteristic analysis. Score thresholds that optimize sensitivity and specificity were identified. Construct, criterion, and discriminant validity, and reliability of scale scores were supported. CONCLUSIONS: The five-item Patient-Reported Outcome Measurement Information System (PROMIS PQ-Neuro) Neuropathic Pain Quality Scale is a short and practical measure that can be used to identify patients more likely to have NP and to distinguish levels of NP. The data collected will support future research that targets other unidimensional pain quality domains (e.g., nociceptive pain).


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