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02-08-2016 | Uitgave 2/2017

Quality of Life Research 2/2017

Mapping painDETECT, a neuropathic pain screening tool, to the EuroQol (EQ-5D-3L)

Quality of Life Research > Uitgave 2/2017
Joseph C. Cappelleri, Vijaya Koduru, E. Jay Bienen, Alesia Sadosky
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Electronic supplementary material

The online version of this article (doi:10.​1007/​s11136-016-1379-2) contains supplementary material, which is available to authorized users.



To map relationships between painDETECT, a neuropathic pain (NeP) screening tool, and EQ-5D-3L health status in a real-world setting.


Patients with physician-confirmed NeP and painDETECT score classifications of nociceptive (n = 79), transitional (n = 141), and NeP (n = 386) completed the EuroQol (EQ-5D-3L), which evaluates Mobility, Self-Care, Usual Activities, Pain/Discomfort, and Anxiety/Depression with three ordinal response levels (“no problem,” “some problems,” or “extreme problems/unable to do”), and has a health status thermometer (0 = worst health, 100 = perfect health). Multiple linear and logistic regressions were performed (adjusted for age, gender, race, ethnicity, time since NeP diagnosis, number of comorbidities, NeP conditions).


Unadjusted mean (±SD) EQ-5D-3L thermometer scores showed poorer health status across painDETECT classifications from nociceptive (67.3 ± 22.1) to transitional (62.3 ± 20.9) to NeP (53.7 ± 21.8), as did utility scores, 0.695 ± 0.206, 0.615 ± 0.216, and 0.506 ± 0.216. In general, the highest odds of health problems were observed for NeP and the lowest for nociceptive, e.g., the NeP group was 6.2 (95 % confidence interval 3.4–11.4) times as likely to have a more severe problem of Usual Activities compared with the nociceptive group. Relative to nociceptive and transitional, NeP had lower adjusted mean thermometer scores, by 12.1 (P < 0.0001) and 7.8 (P = 0.0004) points, respectively, and lower mean utility scores by 0.157 (P < 0.0001) and 0.092 points (P < 0.0001).


This study, the first to map relationships between painDETECT and the EQ-5D-3L in a real-world setting, indicates that the patient burden with respect to pain classification can be characterized and quantified by decrements in health status overall and in specific domains. These data support the psychometric soundness of painDETECT, enhancing its use in pain management.

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Supplementary material 1 (PDF 133 kb)
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