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

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Abstract

Purpose

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

Methods

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).

Results

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).

Conclusions

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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Acknowledgments

The authors thank the reviewers and the associate editor for their thoughtful and constructive feedback, which improved the quality of the manuscript.

Author information

Authors and Affiliations

  1. Pfizer Inc, Groton, CT, USA

    Joseph C. Cappelleri

  2. Eliassen Group, New London, CT, USA

    Vijaya Koduru

  3. Outcomes Research Consultant, New York, NY, USA

    E. Jay Bienen

  4. Pfizer Inc., 235 East 42nd Street, New York, NY, 10017, USA

    Alesia Sadosky

Authors
  1. Joseph C. Cappelleri
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  4. Alesia Sadosky
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Corresponding author

Correspondence to Alesia Sadosky.

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Conflict of interest

This study was funded by Pfizer Inc. Joseph C. Cappelleri and Alesia Sadosky are employees and stockholders of Pfizer, the sponsor of this study; Vijaya Koduru is an employee of the Eliassen Group and paid consultant to Pfizer in connection with the analysis described in this study; E. Jay Bienen is an independent scientific consultant who was funded by Pfizer in connection with manuscript development.

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This article was based data from a study that received approval from a central institutional review board and required that subjects provide written informed consent.

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Cappelleri, J.C., Koduru, V., Bienen, E.J. et al. Mapping painDETECT, a neuropathic pain screening tool, to the EuroQol (EQ-5D-3L). Qual Life Res 26, 467–477 (2017). https://doi.org/10.1007/s11136-016-1379-2

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