The burden of neuropathic pain A systematic review and meta-analysis

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PAIN 149 (2010) 338–344

The burden of neuropathic pain: A systematic review and meta-analysis of health utilities Alissa H. Doth a,b, Per T. Hansson c,d, Mark P. Jensen e, Rod S. Taylor f,*,1 a

Health Policy and Management, University of Minnesota, USA Medtronic Neuromodulation, Minneapolis, USA c Department of Molecular Medicine & Surgery, Karolinska Institute, Stockholm, Sweden d Department of Neurosurgery, Karolinska University Hospital, Stockholm, Sweden e University of Washington School of Medicine, Seattle, USA f Peninsula Medical School, Universities of Exeter & Plymouth, UK b

a r t i c l e

i n f o

Article history: Received 8 July 2009 Received in revised form 20 January 2010 Accepted 19 February 2010

Keywords: Neuropathic pain Utility Health-related quality of life Meta-analysis EQ-5D

a b s t r a c t Patients with neuropathic pain (NeuP) experience substantially lower health-related quality of life (HRQoL) than the general population. The aim of this systematic review and meta-analysis is to test the hypothesis that NeuP is associated with low levels of health utility. A structured search of electronic databases (MEDLINE, EMBASE, Cochrane Library and CINAHL) was undertaken. Reference lists of retrieved reports were also reviewed. Studies reporting utility single-index measures (preference based) in NeuP were included. Random effects meta-analysis was used to pool EQ-5D index utility estimates across NeuP conditions. The association of utilities and pre-defined factors (NeuP condition, patient age, sex, duration and severity of pain and method of utility scoring) was examined using meta-regression. Twenty-four studies reporting health utility values in patients with NeuP were included in the review. Weighted pooled utility score across the studies varied from a mean of 0.15 for failed back surgery syndrome to 0.61 for post-herpetic neuralgia and diabetic neuropathy. Although there was substantial heterogeneity (P < 0.0001) across studies, we found little variation in utility as a function of patient and study characteristics. The single exception was a significant relationship (P < 0.0001) between increasing neuropathic pain severity and a reduction in utility. This study confirms the hypothesis that patients with NeuP experience low utilities and therefore low HRQoL. However, the contribution of non-NeuP co-morbidity remains unclear. Neuropathic pain severity emerged as a primary predictor of the negative health impact of NeuP. Ó 2010 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

1. Introduction Patients with neuropathic pain (NeuP) report substantially lower levels of health-related quality of life (HRQoL) compared with the general population [18]. Furthermore there is strong evidence that the presence and severity of NeuP are associated with impairments in a number of important HRQoL domains [12]. Broadly HRQoL can be assessed in two ways: (1) by the use of a profile measure that assesses the health status of a patient over different generic (e.g., Short-Form 36) or disease-specific domains (e.g., Minnesota Living with Heart Failure Questionnaire), or (2) by use of a single-index health utility measure [5,10].

* Corresponding author. Address: Peninsula Medical School, Universities of Exeter & Plymouth, Noy Scott House, 3rd Floor, Barrack Rd., Exeter EX2 5DW, UK. Tel.: +44 1392 406980; fax: +44 1392 406401. E-mail address: [email protected] (R.S. Taylor). 1 The statistical analysis was conducted by Rod Taylor.

Generally, health utility measures evaluate patients’ subjective preferences on a scale where 0 represents death and 1 represents full health. Utility scores are frequently used to quantify the cost-effectiveness of therapies and are therefore often required by health policy makers. Preference-weighted (utility) measures also provide information on the desirability or value of a particular health state to a population. Based in economic theory, utility measures ‘‘reflect the preferences of groups of persons for particular treatment outcomes and disease states” and combine many different health domains into a single number, weighting the different domains with the values people have for the particular health states [5]. Utilities can be elicited directly, using the ‘standard gamble’ or ‘time trade off’ methods, or indirectly, using questionnaire-based measures (such as EuroQol [EQ-5D] or Health Utilities Index [HUI] for which population preference weights have previously been obtained). Either method results in an ability to weigh the score into a utility-based metric. Utility-based measures allow

0304-3959/$36.00 Ó 2010 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved. doi:10.1016/j.pain.2010.02.034



A.H. Doth et al. / PAIN 149 (2010) 338–344

for the direct comparison of health outcomes across different health conditions where the impact on varying morbidity effects and mortality may be different, but for which individuals or policy makers want to make comparisons. Although the impact of NeuP on HRQoL has been the subject of two recent reviews [12,20], the impact on health utility has not previously been the subject of a full systematic review. Such a review would add to our understanding of the effects of NeuP on HRQoL by providing a better sense of the effects of NeuP on HRQoL from the perspective of the patient, and as this relates to outcomes from a healthcare policy perspective. Overviews and meta-analyses of the utility literature have been undertaken in various disease areas including cancer, HIV/AIDS and multiple sclerosis [3,4,9,22,23]. Interestingly, studies, albeit anecdotal, are reporting what appear to be very low utility scores (i.e., 3.33 and 67.64) and severe (>7.64). b Pain VAS: mild 0/1–3; moderate: 4–6; severe: 7–10. c BPI-DPN average pain item: mild 0–3; moderate: 4–6; severe: 7–10.

baseline in a control group and one or more intervention groups. A total of 23 utility data sets were available for analysis across 3824 patients with NeuP. The pooled EQ-5D index utility scores across NeuP conditions are summarized in Table 1. There was evidence of a statistically non-significant difference in the utility across NeuP conditions (P = 0.362). Pooled utility ranged from a mean of 0.15 for FBSS to a mean of 0.61 for post-herpetic neuralgia and diabetic neuropathy. In the two studies that assessed utility in a mix of different NeuP conditions, the pooled mean utility score was 0.43 (95% confidence interval [CI]: 0.41–0.46) [v, viii]. Fig. 1 shows the variation in EQ-5D index scores across studies in diabetic neuropathy populations where there was evidence of significant statistical heterogeneity (P < 0.0001). 3.4. Exploration of potential predictors of utility In univariate study level analysis, a number of factors were found to be significantly associated with utility (see Table 2). However, in multivariate analysis and using a conservative P-value cut off (60.010), only pain severity showed a significant association with health utility in multivariate analyses; these analyses indicated that the higher the study mean pain NRS score, the lower the study mean health utility score (i.e., lower level of HRQoL). Seven studies (Currie (2006) [iii], Gordon (2006) [v], Gore (2005) [vi], Oster (2005) [x], Tölle (2006) [xiii], Tölle (2006) [xiv], van Seventer (2006) [xviiii]) undertook a within-study analysis of the relationship between the severity of neuropathic pain and utility score (see Table 3). These studies consistently reported a statistically significant reduction in utility with increasing severity of neuropathic pain as assessed by symptoms, in particular pain. 3.5. Change in utility values with NeuP treatment Five randomized controlled trials (RCTs) reported EQ-5D index data at follow up. Three trials compared differing doses of duloxetine to either placebo or usual care in patients with diabetic neuropathy [i, iv, xx], one trial compared spinal cord stimulation with usual care in patients with FBSS [vii], and one trial compared ketamine with placebo [xix]. An improvement in utility with treatment compared with control was seen in all studies. Mean utility was higher by 0.09 (95% CI: 0.07–0.10) with duloxetine, by 0.22 (95% CI: 0.09–0.35) with spinal cord stimulation and by 0.29 (95% CI: 0.10 to 0.77) with ketamine.

3.6. Comparison in utility values in NeuP with other medical conditions The utility scores in NeuP were generally lower than in other chronic medical conditions (see Fig. 2).

4. Discussion Our findings confirm the hypothesis that NeuP is associated with low levels of health utility. We found an average health utility of 0.43 in a mixed NeuP population. Two key drivers of health utility appear to be NeuP condition and disease severity. On average, EQ-5D index utility varied from 0.15 for failed back surgery to 0.61 for post-herpetic neuralgia and diabetic neuropathy. Between- and within-study analyses demonstrate that patients with more severe neuropathic pain experience lower utility values than more mildly affected patients. The utility scores seen in this study are considerably lower than EQ-5D scores in general population-based samples, which suggests a large impact of NeuP on HRQoL. For example, a population-based sample in the US reported a mean utility score of 0.87 [14]. Similarly, for individuals with no medical problems, a general population survey from Alberta reported a mean utility of 0.91 [13]. In addition, we found that NeuP utilities were generally lower (i.e., lower levels of HRQoL) than chronic conditions that include cancer, heart failure, chronic obstructive pulmonary disease, motor neurone disease, type 2 diabetes, Parkinson’s disease and stroke. The findings from this review have important clinical and research implications. First, the low level of utility seen in NeuP provides a clear indication of the health burden of neuropathic symptoms, in particular pain, in these patients. By providing a framework by which the health burden of diseases can be compared, utility scores offer a means by which healthcare managers, policy makers and industry can prioritize their resources for investment in healthcare interventions and potentially maximize future health gain. 4.1. Strengths and limitations A principal strength of the current review is its comprehensiveness. We used a broad search strategy across a number of bibliometric databases and included independent reviews of the title, abstract and full-text of papers identified by two researchers. This helped to



A.H. Doth et al. / PAIN 149 (2010) 338–344

Fig. 2. Comparison of EQ-5D index values for NeuP and common chronic diseases. Abbreviations: ALS, amyotrophic lateral sclerosis; DN, diabetic neuropathy; FBSS, failed back surgery syndrome; MND, motor neurone disease; NeuP, neuropathic pain; NYHA, New York Heart Association; PD, Parkinson’s disease; PHN, post-herpetic neuralgia [xxv, xxvi, xxvii, xxxi, xxviii, xxx].

minimize selection bias in the papers identified for this review and we include here a number of publications not identified by the two previous reviews in this field [12,20]. Furthermore, the problem of publication bias often seen in systematic reviews may be less important in this case as we were primarily interested in assessing health utility and not the efficacy of particular treatments.

We recognize there are limitations to this study, notably that the differences in NeuP utility across studies may not simply be due to variations in NeuP condition or neuropathic pain severity but instead due to other (unmeasured) factors. For example, the presence of non-NeuP co-morbid conditions (e.g., type 2 diabetes, heart disease) is likely to be an important driver of utility. Thus,


A.H. Doth et al. / PAIN 149 (2010) 338–344

the lower levels of HRQoL seen in patients with NeuP with more severe pain may simply be a reflection of their more advanced non-NeuP co-morbidities. Importantly, most studies were found to report little or no co-morbidity information, limiting us from estimating the contribution of non-NeuP morbidity to the variation in NeuP utility. Nevertheless, the one study that examined this issue found that severity of pain remained a significant predictor of EQ-5D score in patients with NeuP after adjusting for the number of concomitant co-morbid conditions [v]. Differences in study characteristics, including differing study designs and patient populations and substantial levels of statistical heterogeneity, could call some of the summary estimators obtained in the meta-analyses into question. To address this possible concern we pooled utilities according to specific NeuP conditions. Furthermore, our principal approach in this review was to use meta-analytic methods to explore heterogeneity rather than to derive a single estimate of overall NeuP utility. 4.2. Future research implications Studies that assessing the cost-effectiveness of treatments for NeuP need to carefully select health utility values to appropriately reflect both the NeuP condition and the severity of the pain in the particular patient subpopulations that they are modelling [8]. This review suggests some ways to improve HRQoL research in individuals with NeuP. Specifically, there is a need to describe more fully the population samples in HRQoL studies (e.g., assess and report co-morbid conditions) to allow ultimately a better understanding of the moderating effects of patient and disease factors on HRQoL burden. The choice and scoring of health utility instrument can affect the utility score [13,14]. While the majority of studies included in this review used the EQ-5D, some studies used the direct EQ-5D Visual Analogue Scale (VAS or ‘thermometer’) scoring method, and others used the EQ-5D index that uses population-specific preference weighting. Previous studies have shown that differences in utility score can result from the choice of EQ-5D index versus EQ-5D VAS systems [3,4,22,23]. However, in the NeuP studies included in this review that reported both scoring methods, there was no evidence of one consistently scoring lower or higher than the other. Nevertheless, current guidance on the conduct of cost-effectiveness studies would suggest that future NeuP studies use utility methods that incorporate public preferences, such as EQ-5D index [10]. 5. Conclusions This study confirms the hypothesis that patients with NeuP experience low utilities and therefore low HRQoL. However, the contribution of non-NeuP co-morbidity remains unclear. Severity of neuropathic pain emerged as a primary predictor of the negative health impact of NeuP and therefore needs to be considered in future economic evaluations of interventions for this patient population. Author disclosures This study was sponsored by Medtronic, Inc. The planning, conduct and conclusions of this report are those of the authors and not the company. Ms. Doth is an employee and stockholder of Medtronic Inc. Dr. Jensen has received research support, consulting fees, or honoraria in the past two years from Analgesic Research, Consultants in Behavioral Research, Endo Pharmaceuticals, Fralex Therapeutics, Inc., Medtronic, Inc., Merck & Co., Inc., National Multiple Sclerosis Society, Pfizer, Inc., the US Department of Education, the US Department of Veterans Affairs, and


the US National Institutes of Health. During this time, he has also served as an associate editor for the Clinical Journal of Pain, and has received royalties from the distribution of four measures: the Survey of Pain Attitudes and Chronic Pain Coping Inventory, which are published and distributed by Psychological Assessment Resources, and the Neuropathic Pain Scale and Pain Quality Assessment Scale, which are distributed by MAPI. Dr. Hansson has consulting fees for advisory boards for Pfizer and Boehringer. Ingelheim/Eli Lilly over the past 2 years. He is field editor for European Journal of Pain. Dr. Taylor presently holds a paid consultancy contract with Medtronic, Inc. He has received consultancy fees for advisory boards for Astra Zeneca, Eli Lily, Pfizer, Schering Plough and GlaxoSmithKline. Acknowledgements The authors wish to thank the following individuals for their support in the preparation of this paper – Anna Zawada and Elena Annoni for translation support and authors who provided data or additional information on their study – Michael Detke, Margaret Ferguson, Marius Kemler, Carrie Krueger, Garry Oster, Joel Raskin, Geert Spincemaille, Jean-Eric Tarride and Joachim Wernicke. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.pain.2010.02.034. References [1] Attal N, Cruccu G, Haanpää M, Hansson P, Jensen TS, Nurmikko T, Sampaio C, Sindrup S, Wiffen P. EFNS Task Force. EFNS guidelines on pharmacological treatment of neuropathic pain. Eur J Neurol 2006;13:1153–69. [2] Beverley C, Reese A. Quality of life – ongoing research Sample search filter InterTASC Information Specialists Sub-Group Search Filter Resource. ; 2009 [accessed 30.01.2009]. [3] Bremner KE, Chong CA, Tomlinson G, Alibhai SM, Krahn MD. A review and meta-analysis of prostate cancer utilities. Med Decis Making 2007;27:288–98. [4] Clayson DJ, Wild DJ, Quarterman P, Duprat-Lomon I, Kubin M, Coons SJ. A comparative review of health-related quality-of-life measures for use in HIV/ AIDS clinical trials. Pharmacoeconomics 2006;24:751–65. [5] Cramer JA, Spilker B. Quality of life and pharmacoeconomics: an introduction. Philadelphia: Lippincott-Raven Publishers; 1998. [6] Cruccu G, Aziz TZ, Garcia-Larrea L, Hansson P, Jensen TS, Lefaucheur JP, Simpson BA, Taylor RS. EFNS guidelines on neurostimulation therapy for neuropathic pain. Eur J Neurol 2007;14:952–70. [7] DerSimonsen R, Laird N. Meta analysis in clinical trials. Control Clin Trials 1986;7:177–88. [8] Detsky AS, Laupacis A. Relevance of cost-effectiveness analysis to clinicians and policy makers. JAMA 2007;298:221–4. [9] Efficace F, Kemmler G, Vignetti M, Mandelli F, Molica S, Holzner B. Healthrelated quality of life assessment and reported outcomes in leukaemia randomised controlled trials – a systematic review to evaluate the added value in supporting clinical decision making. Eur J Cancer 2008;44:1497–506. [10] Gold MR, Siegel JE, Russell LB, Weinstein MC. Cost effectiveness in health and medicine. Oxford: Oxford University Press; 1996. [11] Higgins JPT, Green S, editors. Cochrane Handbook for Systematic Reviews of Interventions Version 5.0.0 [updated February 2008]. The Cochrane Collaboration, 2008. ; 2008 [accessed 22.11.2008]. [12] Jensen MP, Chodroff MJ, Dworkin RH. The impact of neuropathic pain on health-related quality of life: review and implications. Neurology 2007;28:1178–82. [13] Johnson JA, Pickard AS. Comparison of the EQ-5D and SF-12 health surveys in a general population survey in Alberta Canada. Med Care 2000;38:115–21. [14] Luo N, Johnson JA, Shaw JW, Feeny D, Coons SJ. Self-reported health status of the general adult US population as assessed by the EQ-5D and health utilities index. Med Care 2005;43:1078–86. [15] McDermott AM, Toelle TR, Rowbotham DJ, Schaefer CP, Dukes EM. The burden of neuropathic pain: results from a cross-sectional survey. Eur J Pain 2006;10:127–35. [16] Manca A, Kumar K, Taylor RS, Jacques L, Eldabe S, Meglio M, Molet J, Thomson S, O’Callaghan J, Eisenberg E, Milbouw G, Buchser E, Fortini G, Richardson J, Taylor RJ, Goeree R, Sculpher MJ. Quality of life, resource consumption and costs of spinal cord simulation versus conventional medical management in neuropathic pain patients with failed back surgery syndrome (PROCESS trial). Eur J Pain 2008;12:1047–58.



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[17] Merskey H, Bogduk N. Classification of chronic pain. In: Merskey H, Bogduk N, editors. Descriptions of chronic pain syndromes and definition of pain terms. Seattle: IASP Press; 1994. p. 4142–54. [18] Meyer-Rosberg K, Burckhardt CS, Huizar K, Kvarnstrom A, Nordforsd L-O, Kristofferson A. A comparison of the SF-36 and Nottingham Health Profile in patients with chronic neuropathic pain. Eur J Pain 2001;5:391–403. [19] Moher D, Cook DJ, Eastwood S, Olkin I, Rennie D, Stroup DF. Improving the quality of reports of meta-analyses of randomised controlled trials: the QUOROM statement. Quality of Reporting of Meta-analyses. Lancet 1999;354:1896–900. [20] O’Connor AB. Neuropathic pain: quality-of-life impact, costs and cost effectiveness of therapy. Pharmacoeconomics 2009;2:95–112.

[21] Paisley S, Booth A, Mensinkai S. Chapter 12: Health-related Quality of Life Studies. In: Etext on Health Technology Assessment (HTA) Information Resources. National Library of Medicine.
The burden of neuropathic pain A systematic review and meta-analysis

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