Startseite Factors influencing quality of life in patients with osteoarthritis: analyses from the BISCUITS study
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Factors influencing quality of life in patients with osteoarthritis: analyses from the BISCUITS study

  • Patricia Schepman , Rebecca Robinson , Karin Hygge Blakeman , Stefan Wilhelm , Craig Beck , Sara Hallberg EMAIL logo , Johan Liseth-Hansen , Anna De Geer , Ola Rolfson und Lars Arendt-Nielsen
Veröffentlicht/Copyright: 6. Juli 2022
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Scandinavian Journal of Pain
Aus der Zeitschrift Scandinavian Journal of Pain Band 23 Heft 1

Abstract

Objectives

Osteoarthritis can have a profound effect on patients’ quality of life. The Burden of Disease and Management of Osteoarthritis and Chronic Low Back Pain: Health Care Utilization and Sick Leave in Sweden, Norway, Finland and Denmark (BISCUITS) study aimed to describe the impact of osteoarthritis on quality of life and determine the association with factors such as pain severity and pharmacological treatment.

Methods

An observational study was performed with a cross-sectional design including patients with a confirmed osteoarthritis diagnosis enrolled in the National Quality Register for Better management of patients with Osteoarthritis (BOA) between 2016 and 2017 in Sweden. Patient-reported information from BOA was linked to administrative data from three national health registers. The impact of osteoarthritis on quality of life was estimated using the EQ-5D-5L and the first developed experienced-based time-trade-off value set for Sweden to calculate the EQ-5D-5L index scores. EQ-5D-3L index scores were also estimated based on a UK hypothetical value set via a crosswalk method. Ordinary least squares regression models were used to analyse the association between quality of life and potential influencing factors.

Results

For the 34,254 patients evaluated, mean EQ-5D-5L index score was 0.792 (SD 0.126). Stratifications showed that the index score varied across different levels of pain severity. Increased pain severity and use of pain-relieving medications remained significantly associated with a lower quality of life index score when controlled for potential confounders. The mean EQ-5D-3L index score was 0.605 (SD 0.192).

Conclusions

This large population-based study from Sweden highlights the substantial impact of osteoarthritis on quality of life amongst different patient groups and that currently available treatment options for osteoarthritis pain do not appropriately address the needs for many osteoarthritis patients.

Keywords: cohort study; EQ-5D-5L; observational data; osteoarthritis; pain severity; real-world data

Introduction

Osteoarthritis (OA) is a chronic disease characterized by the deterioration of cartilage and joint inflammation impacting mobility and leading to chronic pain [1]. OA is a major public health problem affecting more than 300 million people worldwide, and it is estimated that one in 10 people over the age of 60 have health issues due to OA [2, 3]. The global prevalence of OA has increased by 30% during the last 10 years and it is described as the fastest growing disability given the aging population and increased rates of obesity [3, 4].

There is considerable evidence from the literature on the negative impact of OA on quality of life (QoL) for affected patients, indicating that this is a major contributor to the overall disease burden [5], [6], [7]. Prior research of population-based QoL studies has concluded that the effect OA have on QoL is one of the largest compared with other chronic conditions [8], [9], [10]. Predictive factors for lower QoL in OA patients include pain severity, with a strong link to the disabling effects of OA and decreased QoL [11, 12], and prescribed medication [13, 14]. However, there may be several important mediators such as pain severity and the number of pain locations which affect the association.

Management of OA aims to reduce pain and to improve function. Current treatment guidelines recommend a multimodal pain management approach including nonpharmacologic and pharmacologic therapies [15], [16], [17]. Non-pharmacological management includes life-styles alterations and physical exercise while short-term pharmacologic pain treatment consists of paracetamol and nonsteroidal anti-inflammatory drugs (NSAIDs) [16, 18]. Opioids have traditionally been considered an option for OA pain and are still prescribed to patients [19], although their use over longer periods is questioned and no longer recommended by certain guidelines [16, 20]. While joint replacement surgery is considered the end stage option for managing severe OA, it has been shown that one in five patients undergoing total knee arthroplasty continue to have persistent chronic pain. Furthermore, four in five of those who underwent revision surgery continued to have pain at an even higher level [21].

The impact of OA on QoL can have far reaching and complex effects on people’s lives [11, 22] and assessing predictors of QoL is important for understanding the effect of disease progression and pharmacological treatment in OA patients [7]. Furthermore, disease management can be better targeted with knowledge of the differential burden amongst OA subpopulations. The BISCUITS (Burden of Disease and Management of Chronic Low Back Pain and Osteoarthritis) study is a cross-sectional case-control cohort study of real-world observational data which aims to describe the multi-dimensional burden of OA and describe its many contributing factors. The aim of the present study was to describe the impact of OA on QoL and its association with potential predictive factors such as pain severity and pharmacological treatment, using Swedish national health registry data.

Methods

Study population

This study consisted of an observational cross-sectional cohort study of adult (≥18 years) OA patients based on their first registration (“index date”) in a self-management program in Sweden from January 1, 2016 to December 31, 2017. The study was a part of The Burden of Disease and Management of Osteoarthritis and Chronic Low Back Pain: Healthcare Utilization and Sick Leave in Sweden, Norway, Finland and Denmark (BISCUITS), an observational cohort study linking longitudinal healthcare and socioeconomic registers in the Nordics, which has been described in detail elsewhere [submitted/if accepted: reference to “sjpain-2021-0212”]. Individuals with a primary diagnosis of malignant cancer (ICD10: C00-C43; C45-C97) during the three years before index date were excluded from the study, focusing on non-malignant pain in accordance with other analyses within the BISCUITS study.

Data sources and study measures

This study used data from the National Quality Register for Better Management of Patients with Osteoarthritis (BOA) [23], with data on over 139,000 patients who have been referred to a nationwide self-management program after confirmed OA diagnosis. The register has been described in detail elsewhere [23]. Information from the BOA register include QoL (measured as EQ-5D-5L and EQ-5D-3L via crosswalk method), perceived pain variables and demographic variables (age, sex, body mass index [BMI], smoking, weekly physical activity). For further details, see appendixS1, online supplement. Since pain is strongly associated with OA outcomes, including QoL, results were stratified by self-reported pain severity using Numeric Rating Scale.

Additional data was retrieved from three national registers and linked together by the Swedish National Board of Health and Welfare using unique personal identifiers [24], [25], [26], [27]. Information on hospitalizations and outpatient physician specialist visits was collected from the National Patient Register and the Swedish Prescribed Drug Register provided data on pain relief medication (Table 1) filled at pharmacies for the complete observable period for each patient. Opioid use was estimated as dispensed oral morphine equivalents (OMEQ) (see appendixS2, online supplement). These national registers are mandatory to report to with a high degree of coverage [24, 25]. Socioeconomic variables were provided by Statistics Sweden’s Longitudinal integrated database for health insurance and labour market studies.

Table 1:

Pain relief medication – ATC-codes and definitions.

Medication ATC-code Definitions
Opioids N02A Non-persistent opioid users: <4,500 OMEQ

Persistent opioid use: ≥4,500 OMEQ

Persistent high opioid use: ≥8,100 OMEQ

Measured 1 year pre-index
Other analgesics and antipyretics N02B Active treatment: Supply of filled prescription lasting over the index date
Nonsteroidal anti-inflammatory drugs (NSAIDs) M01A Long-term NSAIDs user: ≥2 NSAIDs prescriptions measured 3 months pre-index

Active treatment: Supply of filled prescription lasting over the index date
Topical products for joint and muscular pain M02A Active treatment: Supply of filled prescription lasting over the index date
Tricyclic antidepressants N06AA
Serotonin-norepinephrine reuptake inhibitors N06AX
Gabapentin and pregabalin (anti-epileptics) N03AX12, N03AX16

  1. ATC, anatomical therapeutic chemical; OMEQ, oral morphine equivalents; NSAIDs, nonsteroidal anti-inflammatory drugs.

Statistical analysis

Continuous variables were presented with means and standard deviations (SDs), and categorical variables were shown as frequencies with percentages. To analyse the association between QoL and potential influencing factors, a cross-sectional ordinary least squares (OLS) regression model with robust standard errors was used. An OLS model was chosen as it is recommended as a simple and valid approach and may be less biased than alternative models [28]. The dependent variable was EQ-5D-5L and the independent variable of interest was the continuous pain intensity score. There were four OLS models that included different sets of covariates. Model 1 was unadjusted, with pain intensity as the only independent variable. In the other models 2–4, potential confounding factors (demographics, drug utilization and other pain severity measures) were added sequentially to evaluate whether these covariates had an impact on the effect of pain intensity on EQ-5D-5L. All tests were two-tailed and an alpha value of 0.05 was employed as the cut-off for statistical significance. All data management and statistical analyses were performed using RStudio v1.3 (RStudio Team, PBC, Boston, MA) and Stata version 16 (StataCorp, College Station, US).

Results

Characteristics

In total, 34,254 patients with OA during 2016 and 2017 were included in the study (Table 2). Most patients had moderate (40.0%) or severe (40.0%) pain relative to no/mild pain (20.0%). The mean age at time of registration in BOA was 67 years and 68% of the patients were female. Of those below 65 years of age (43% of total study sample), 80% were employed and the mean disposable income was 28,096 euro per year. Overall, 17% of the patient were educated beyond secondary school level. These socioeconomic variables decreased with increasing pain severity.

Table 2:

Study population characteristics for all and by pain severity category.

All No/Mild pain Moderate pain Severe pain
No/mean %/SD No/mean %/SD No/mean %/SD No/mean %/SD
Number of individuals 34,254 100% 6,548 19% 13,733 40% 13,824 40%
Age 66.81 9.68 66.86 9.55 67.46 9.65 66.10 9.71
Sex
 Females 23,441 68.4% 4,225 64.5% 9,449 68.8% 9,655 69.8%
 Males 10,813 31.6% 2,323 35.5% 4,284 31.2% 4,169 30.2%
BMI 28.08 4.90 26.94 4.40 27.88 4.78 28.83 5.12
Smoking
 Never smoked 17,089 49.9% 3,594 54.9% 6,882 50.1% 6,533 47.3%
 Stopped smoke before index 14,060 41.0% 2,557 39.1% 5,768 42.0% 5,682 41.1%
 Smoke regularly 2,892 8.4% 358 5.5% 998 7.3% 1,525 11.0%
Comorbidity profile
 Elixhauser comorbidity index 0.48 0.97 0.36 0.83 0.47 0.94 0.54 1.05
 Depressive episodes 1,362 4.0% 204 3.1% 498 3.6% 653 4.7%
 Anxiety disorders 1,428 4.2% 210 3.2% 504 3.7% 710 5.1%
Medication profile
 Non-persistent opioid users 5,129 15.0% 580 8.9% 1,845 13.4% 2,683 19.4%
 Persistent opioid usersa 436 1.3% 35 0.5% 112 0.8% 286 2.1%
 Persistent high opioid usersa 810 2.4% 57 0.9% 222 1.6% 527 3.8%
 Long-term NSAIDs usersb 475 1.4% 30 0.5% 123 0.9% 318 2.3%
Self-reported painc
 Recurrent pain 5,416 15.8% 2,814 43.0% 1,863 13.6% 716 5.2%
 Lasting pain 28,657 83.7% 3,680 56.2% 11,795 85.9% 13,081 94.6%
Pain intensity (continuous 0–10) 5.66 2.27 2.20 0.90 5.11  0.77 7.86  0.96
Number of pain locations
 1 12,886 37.6% 3,157 48.2% 5,186 37.8% 4,461 32.3%
 2–4 19,273 56.3% 3,262 49.8% 7,836 57.1% 8,110 58.7%
 5+ 2,095 6.1% 129 2.0% 711 5.2% 1,253 9.1%
Joint with most pain
 Hip 10,607 31.0% 1,766 27.0% 4,185 30.5% 4,616 33.4%
 Knee 21,956 64.1% 4,448 67.9% 8,874 64.6% 8,543 61.8%
 Hand 1,639 4.8% 324 4.9% 658 4.8% 639 4.6%
Walking difficulty due to pain
 No 7,354 21.5% 2,973 45.4% 2,942 21.4% 1,404 10.2%
 Yes 26,549 77.5% 3,496 53.4% 10,648 77.5% 12,297 89.0%
Physical activity per week
 0 min 8,544 24.9% 1,429 21.8% 3,305 24.1% 3,775 27.3%
 1–60 min 13,028 38.0% 2,291 35.0% 5,314 38.7% 5,376 38.9%
 60–150 min 7,079 20.7% 1,550 23.7% 2,916 21.2% 2,583 18.7%
 >150 min 5,407 15.8% 1,244 19.0% 2,117 15.4% 2,018 14.6%
Highest attained level of education
<upper secondary school 10,236 29.9% 1,486 22.7% 4,147 30.2% 4,552 32.9%
Upper secondary school 13,296 38.8% 2,325 35.5% 5,304 38.6% 5,611 40.6%
>upper secondary school 4,870 14.2% 1,108 16.9% 1,957 14.3% 1,788 12.9%
 First stage tertiary education (bachelor) 3,326 9.7% 878 13.4% 1,352 9.8% 1,079 7.8%
 First stage tertiary education (master) 2,161 6.3% 627 9.6% 839 6.1% 687 5.0%
 Second stage tertiary education (PhD) 231 0.7% 101 1.5% 78 0.6% 52 0.4%
Working age population (18–65 years) 14,693 42.9% 2,770 42.3% 5,444 39.6% 6,438 46.6%
Employment (in working age population)
 Not employed 2,912 19.8% 400 14.4% 1,005 18.4% 1,499 23.2%
 Employed 11,781 80.0% 2,370 85.4% 4,439 81.4% 4,939 76.5%
Disposable income (in working age population) 28,096 25,303 30,509 22,106 29,106 33,179 26,167 17,530

  1. aPersistent opioid use – defined as annual OMEQ pre-index: 4,500–8,100. Persistent high opioid use – defined as annual OMEQ pre-index: >8,100. bLong-term NSAID use – defined as ≥2 NSAIDs prescriptions within three months post-index. cSelf-reported pain: Either stated as Recurrent or as Lasting pain(defined as “daily and always”). OMEQ, oral morphine equivalents measured within one-year post-index, see appendixS2 in the online supplement; SD, standard deviation; BMI, body mass index; NSAIDs, nonsteroidal anti-inflammatory drugs.

The Elixhauser comorbidity index was 0.48 overall, and varied with pain severity, from 0.36 (SD 0.83) in no/mild pain patients to 0.54 (SD 1.05) in severe pain patients. In terms of depressive episodes and anxiety disorders, 3% of both no/mild and moderate pain groups were affected, compared to 5% of those reporting severe pain. An overall mean BMI of 28 was relatively stable across pain groups, but current smoking rates in the severe pain group were double (11%) compared to no/mild pain (6%). More patients with severe pain (27%) reported zero minutes of physical activity per week compared to patients with no/mild (22%) and moderate pain (24%).

Overall, 84% of the study sample reported lasting pain (defined as daily and always), which was most common among those in the severe pain group (95% compared to 57% with no/mild pain). A similar pattern of increased percentage across the pain severity groups was found for having more than one joint affected (no/mild: 52% – severe: 68%), overall pain intensity (2.36–7.64), and walking difficulty due to pain (55–92%). Across all three pain severity groups, the joint with most pain in our population was the knee (62–68%).

Within the study population, 19% had used opioids within the year prior to index date. Of these, 3.7% were classified as persistent or persistent high opioid users, having dispensed ≥4,500 OMEQ of opioids in the year before index date. Of the non-persistent opioid users (<4,500 OMEQ of opioids in the pre-index year), 11% reported no/mild pain, 36% moderate and 52% severe pain. This skewed distribution was also seen for persistent opioid users as 66% reported severe pain and 8% no/mild pain. Of the included patients, 1% had filled at least two NSAID prescriptions in the first quarter prior to the index date and were defined as long-term NSAID users. A higher share of patients with severe pain (2.3%) were long-term NSAID users compared to patients with no/mild pain (0.5%).

Quality of life (QoL)

Across this study sample of patients with OA, the mean EQ-5D-5L index score was 0.792 (SD 0.126) (Figure 1 and Table 3). The impact of pain severity on QoL was demonstrated by a drop in mean EQ-5D-5L index score of 0.170 between patients who reported no/mild vs. severe pain. The mean EQ-5D-3L index score, created via a crosswalk method, was 0.605 (SD 0.192).

Figure 1: Boxplot figure of EQ-5D-5L (mean, distribution) for all and by pain severity.
Figure 1:

Boxplot figure of EQ-5D-5L (mean, distribution) for all and by pain severity.

Table 3:

EQ-5D index scores, for all and by pain severity.

Mean Standard deviation Minimum 1st quartile 4th quartile Maximum
EQ-5D-5L index score – Experienced-based value set
All 0.792 0.126 0.243 0.726 0.881 0.975
No/Mild pain 0.888 0.076 0.408 0.849 0.939 0.975
Moderate pain 0.819 0.094 0.243 0.762 0.884 0.975
Severe pain 0.718 0.131 0.243 0.637 0.817 0.975
EQ-5D-3L index score – Hypothetical value set
All 0.605 0.192 −0.594 0.531 0.735 1.000
No/Mild pain 0.743 0.112 −0.163 0.691 0.836 1.000
Moderate pain 0.654 0.130 −0.594 0.612 0.735 1.000
Severe pain 0.491 0.209 −0.511 0.336 0.654 1.000

The impact of pain severity on each of the five sub-dimensions of EQ-5D-5L is shown in Figure 2. Almost all OA patients reported problems in the subdimension pain/discomfort and more patients with higher levels of pain severity reported problems as well as worse intensity of problems, a pattern that could be seen in all subdimensions. For example, 12% of patients with no/mild pain had moderate or worse problems performing usual activities while the corresponding proportion within the group of severe pain patients was 56%.

Figure 2: Percentage of people reporting subdimensions of EQ-5D-5L by pain severity.
Figure 2:

Percentage of people reporting subdimensions of EQ-5D-5L by pain severity.

Predictors of EQ-5D-5L

The results from the OLS regressions are presented in Table 4, displaying the associations between the included covariates and the EQ-5D-5L index score for the four models. The regression coefficient for pain severity was robust across the models, even with an increasing number of covariates. The adjusted R2 estimates increased as covariates were added to model, from 0.32 to 0.42 for the main model. When all factors were considered (model 4), the five main categorical factors that were associated with worsening QoL as shown by the EQ-5D-5L index scores were, in order of largest to smallest coefficient size: having walking difficulty due to pain, dispensed over 8100 OMEQ, dispensed between 4,500 and 8,100 OMEQ, having five or more pain locations and having an active treatment with serotonin-norepinephrine reuptake inhibitors (SNRIs) (p<0.05 for all). Of the four non-categorical covariates in the model, pain intensity had a large impact on the index score. One unit increase in the pain intensity scale being associated with a 0.025 decrease of the EQ-5D-5L index score. Having an additional disease category in the Elixhauser comorbidity index implied on average a 0.004 decrease of the EQ-5D-5L index score, while each additional year in age increased the score with 0.001.

Table 4:

OLS models comparing impact of factors on EQ-5D-5L index score.

OLS models Outcome: EQ-5D-5L index score
Model 1 Model 2 Model 3 Model 4
CE SE CE SE CE SE CE SE
Constant 0.969 0.001 0.949 0.008 0.953 0.008 0.945 0.008
Pain intensity (continuous) −0.031 0.000 −0.029 0.000 −0.025 0.000 −0.024 0.000
Age (continuous) 0.001 0.000 0.001 0.000 0.001 0.000
Male (ref: female) −0.014 0.001 −0.014 0.001 −0.016 0.001
Employment status (ref: employed)
 – Not employed −0.012 0.003 −0.012 0.003 −0.012 0.003
 – Disability pension −0.041 0.003 −0.034 0.003 −0.026 0.003
 – Retired (>66 years of age) 0.003a 0.002 0.003a 0.002 0.003a 0.002
Highest attained level of education (ref: <Upper secondary education)
 – Upper secondary education 0.006 0.001 0.007 0.001 0.006 0.001
 – >Upper secondary education 0.005 0.001 0.005 0.001 0.004 0.001
Elixhauser comorbidity index (continuous) −0.007 0.001 −0.006 0.001 −0.004 0.001
BMI (continuous) −0.002 0.000 −0.002 0.000 −0.001 0.000
Weekly physical activity (ref: nothing)
 – Between 1 and 60 min 0.013 0.001 0.011 0.001 0.011 0.001
 – Between 60 and 150 min 0.025 0.002 0.021 0.002 0.020 0.002
 – More than 150 min 0.032 0.002 0.026 0.002 0.025 0.002
Smoking (ref: never smoked)
 – Stopped before index −0.001a 0.001 0.000a 0.001 0.001a 0.001
 – Smoke regularly −0.020 0.002 −0.018 0.002 −0.014 0.002
Number of pain locations (ref: one)
 – Two to four pain locations −0.013 0.001 −0.012 0.001
 – Five or more pain locations −0.046 0.003 −0.043 0.003
Joint with most pain (ref: hip)
 – Most pain in knee 0.014 0.001 0.011 0.001
 – Most pain in hand 0.004a 0.003 0.001a 0.003
Walking difficulty due to pain (ref: no) −0.061 0.001 −0.059 0.001
Active treatment with NSAIDs (ref: no) −0.008 0.001
Active treatment with other analgesics (ref: no) −0.016 0.001
Active treatment with TCA (ref: no) −0.015a 0.006
Active treatment with topical products (ref: no) −0.019 0.005
Active treatment with SNRI (ref: no) −0.032 0.004
Active treatment with anti-epileptics (ref: no) −0.021 0.006
Opioid use (ref: no opioid use)
 – Non-persistent opioid use −0.028 0.002
 – Persistent opioid use −0.050 0.006
 – Persistent high opioid use −0.052 0.007
 Adjusted R2 0.32 0.36 0.40 0.42

  1. aNon-significant at p-value ≥0.05. All other p-values <0.05. Non-persistent opioid use – defined as annual OMEQ pre-index: 1–4,499. Persistent high opioid use – defined as annual OMEQ pre-index: >8,100. Persistent opioid use – defined as annual OMEQ pre-index: 4,500–8,100. Active treatment – defined as prescription covering index date. OLS, ordinary least squares; CE, coefficient; SE, standard error; BMI, body mass index; OMEQ, oral morphine equivalents; NSAIDs, nonsteroidal anti-inflammatory drugs; TCAs, tricyclic antidepressants; SNRIs, serotonin-norepinephrine reuptake inhibitors; anti-epileptics, Gabapentin and Pregabalin. For ATC-codes, see Table 1.

Discussion

This observational cross-sectional study of 34,254 patients with OA estimated the impact of the multidimensional aspects of the disease on QoL using the EQ-5D-5L. To our knowledge, this is one of the largest studies to date with EQ-5D-5L measures for OA patients.

A regional Swedish registry data study utilizing both primary and secondary care data found that one in four adults over 45 years old had physician-diagnosed OA [29]. Given the implications of this for the sheer number of affected patients, it is important to acknowledge the between patient variation and identify groups with OA that are disproportionally affected. Apart from presenting stratified QoL measures by pain severity, we reviewed the predictive ability of several pain characteristics and pharmacological treatment on QoL. It is known that the use of prescription medication rises when the severity of pain increases [30] and most patients classified as opioid- or long-term NSAID users in this study reported severe pain.

An association between prescribed medication and lower QoL for OA patients has been found in two recent studies [13, 14]. However, the methodology of those studies did not allow the results to be controlled for certain important possible mediators such as pain severity and the number of pain locations. In our study we were able to adjust for these covariates in an OLS model and active treatment with pain-relieving medications remained predictive of a lower EQ-5D-5L index score. However, the method of the study does not allow causality to be attributed to the results. Covariates capturing aspects of non-pharmacological treatment such as physical activity and lower BMI were on the contrary predictive of a higher QoL.

This study employs the first experience-based time-trade-off (TTO) value set available to calculate the EQ-5D-5L index score, meaning that patients with direct experience of the condition have valued their own health. This implies that the estimates used in the value set become more patient-centric rather than utilizing a societal view. As the study uses this more recent version of the EQ-5D questionnaire in conjunction with a newly developed value set to calculate the index score, there are currently no comparable EQ-5D-5L estimates in the literature to contrast our findings with. We therefore also generated EQ-5D-3L index scores via a crosswalk method [31] to allow for comparisons with estimates for the general population using the same UK hypothetical-based TTO value set [32]. The mean EQ-5D-3L index score of 0.61 is lower than the general Swedish population norm of 0.80 for ages 60–69 years (0.84 for all ages) [33]. Previous studies aiming to assess the predictive power of EQ-5D-3L for work ability have suggested a cut-off of 0.6 as for having sufficient capacity to be able to work [34, 35]. The study population mean is just above this cut-off, while patients with severe pain are well below, with a mean EQ-5D-3L of 0.49.

The observed inverse associations between pain severity and QoL seen in our study are consistent with previous results from several countries [6, 13, 14, 36–40]. Patients with moderate and severe pain were more likely to report walking difficulty and problems in the functional subdimensions of the EQ-5D (self-care, daily activities, and mobility) compared to patients with no/mild pain. These findings indicate that pain is a major contributing factor to the functional limitations associated with OA, as previously seen in other studies [14, 38].

A systematic review of patients’ experience of living with OA found that pain severity and its impact on functional capability were two key factors in the attitude the patient had towards the condition. Other studies exploring personal living experiences with OA, and how it affects the person’s life at many levels, have found a desire of patients with OA to remain active and independent [41–43] denoting the importance of retaining the functional capability of OA patients.

Demographic characteristics of the OA patients varied with pain severity classification. Generally, in comparison to patients with no/mild pain, patients with severe pain had lower socioeconomic status in terms of higher unemployment rate, lower income, and lower level of education. These descriptive results also showed that patients with severe pain had higher BMI and lower physical activity. These lifestyle factors and common social determinants of health have been found to have a negative impact on the QoL of OA patients [7, 36]. Furthermore, OA patients have been shown to have more comorbidities [44]. This is important from a treatment perspective as comorbidities may present contraindications to pharmacological treatment. This study shows that patients with higher pain severity have more comorbidities but also that OA patients with more comorbidities have a lower QoL.

Strengths/limitations

The major strength of this study is the large study population with a rich data set linking various data sources with information on patients treated in a real-world setting. This study utilizes a combination of survey-based data for patient-reported outcomes on pain and QoL, and administrative data which are known to have a high degree of completeness since reporting on health care visits and prescriptions used in this study is mandatory in Sweden.

However, there are some limitations that should be addressed. Patients in the BOA register are not necessarily representative of all Swedish OA patients. All BOA register patients are a part of self-management program after confirmed OA diagnosis and this group may be different to the OA patients not included in the self-management program. For instance, patients in the BOA register had achieved a higher level of education compared to the general population [45], despite a known association between OA and lower educational level [46, 47]. Furthermore, as the study only captured prescribed medication, exclusion of over-the-counter drugs may have led to an underestimation of NSAID usage in our results. Also, information on what condition the medications were prescribed for was not available. Lastly, this was a cross-sectional study and as such, the correlational nature of this research makes it unable to attribute any causality to the results.

Conclusions

In conclusion, this large population-based study on Swedish national health registry data describes the humanistic burden of OA in terms of its impact on QoL. The QoL of OA patients decreased considerably with increased pain severity. When controlling for potential confounders, pain severity and current pharmacological treatment with NSAIDs and opioids remained as independent explanatory factors for lower QoL in OA patients.

Corresponding author: Sara Hallberg, Quantify Research, Hantverkargatan 8, 112 21Stockholm, Sweden, Phone: +46 70 306 7110, E-mail:

Previous presentation of study data at scientific meeting: ISPOR 2020, Virtual, 18-05-2020, https://doi.org/10.1016/j.jval.2020.08.1160.

Acknowledgments

Christoph Varenhorst, Emilie Toresson Grip and Anders Gustavsson are acknowledged for their contributions to the study.

  1. Research funding: This study was sponsored by Pfizer and Eli Lilly & Company. Center for Neuroplasticity and Pain (CNAP) is supported by the Danish National Research Foundation (DNRF121).

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: Sara Hallberg and Johan Liseth Hansen are employees at Quantify Research, who were paid consultants to Pfizer and Eli Lilly & Company in connection with this research and the development of this manuscript. Rebecca Robinson and Stefan Wilhelm are employees and stockholder of Eli Lilly. Patricia Schepman, Karin Hygge Blakeman, Anna De Geer, and Craig Beck are employees at Pfizer with stock and/or stock options. Lars Arendt-Nielsen was a paid contractor to Pfizer and Eli Lilly & Company in connection with this study. Ola Rolfson is an employee of the Swedish Arthroplasty Register which received funding from Pfizer and Eli Lilly and Company to conduct this study. Medical writing support was provided by Sara Hallberg at Quantify Research and was funded by Pfizer and Eli Lilly & Company.

  4. Informed consent: Individual informed consent was not required for this study and was therefore not collected.

  5. Ethical approval: This study complied with all relevant national regulations, institutional policies and is in accordance with the tenets of the Helsinki Declaration (as amended in 2013). Ethical approval was granted for this work on September 12, 2018 (registration number: 2018/1634-31/2) from the ethical review board in Stockholm, Sweden.

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Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/sjpain-2021-0213).

Received: 2021-12-02
Accepted: 2022-06-14
Published Online: 2022-07-06
Published in Print: 2023-01-27

© 2022 Walter de Gruyter GmbH, Berlin/Boston

Artikel in diesem Heft

  1. Frontmatter
  2. Editorial Comment
  3. What do we mean by “mechanism” in pain medicine?
  4. Topical Reviews
  5. Topical review – salivary biomarkers in chronic muscle pain
  6. Tendon pain – what are the mechanisms behind it?
  7. Systematic Review
  8. Psychological management of patients with chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS): a systematic review
  9. Topical Review
  10. Predicting pain after standard pain therapy for knee osteoarthritis – the first steps towards personalized mechanistic-based pain medicine in osteoarthritis
  11. Clinical Pain Researches
  12. Neuropathy and pain after breast cancer treatment: a prospective observational study
  13. Neuropeptide Y and measures of stress in a longitudinal study of women with the fibromyalgia syndrome
  14. Nociceptive two-point discrimination acuity and body representation failure in polyneuropathy
  15. Pain sensitivity in relation to frequency of migraine and tension-type headache with or without coexistent neck pain: an exploratory secondary analysis of the population study
  16. Clinician experience of metaphor in chronic pain communication
  17. Observational studies
  18. Chronic vulvar pain in gynecological outpatients
  19. Male pelvic pain: the role of psychological factors and sexual dysfunction in a young sample
  20. A bidirectional study of the association between insomnia, high-sensitivity C-reactive protein, and comorbid low back pain and lower limb pain
  21. Burden of disease and management of osteoarthritis and chronic low back pain: healthcare utilization and sick leave in Sweden, Norway, Finland and Denmark (BISCUITS): study design and patient characteristics of a real world data study
  22. Factors influencing quality of life in patients with osteoarthritis: analyses from the BISCUITS study
  23. Prescription patterns and predictors of unmet pain relief in patients with difficult-to-treat osteoarthritis in the Nordics: analyses from the BISCUITS study
  24. Lifestyle factors, mental health, and incident and persistent intrusive pain among ageing adults in South Africa
  25. Inequalities and inequities in the types of chronic pain services available in areas of differing deprivation across England
  26. Original Experimentals
  27. Conditioned pain modulation is not associated with thermal pain illusion
  28. Association between systemic inflammation and experimental pain sensitivity in subjects with pain and painless neuropathy after traumatic nerve injuries
  29. Endometriosis diagnosis buffers reciprocal effects of emotional distress on pain experience
  30. Educational Case Reports
  31. Intermediate cervical plexus block in the management of treatment resistant chronic cluster headache following whiplash trauma in three patients: a case series
  32. Trigeminal neuralgia in patients with cerebellopontine angle tumors: should we always blame the tumor? A case report and review of literature
  33. Short Communication
  34. Less is more: reliability and measurement error for three versions of the Tampa Scale of Kinesiophobia (TSK-11, TSK-13, and TSK-17) in patients with high-impact chronic pain
https://doi.org/10.1515/sjpain-2021-0213
Schlagwörter für diesen Artikel
cohort study; EQ-5D-5L; observational data; osteoarthritis; pain severity; real-world data

Artikel in diesem Heft

  1. Frontmatter
  2. Editorial Comment
  3. What do we mean by “mechanism” in pain medicine?
  4. Topical Reviews
  5. Topical review – salivary biomarkers in chronic muscle pain
  6. Tendon pain – what are the mechanisms behind it?
  7. Systematic Review
  8. Psychological management of patients with chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS): a systematic review
  9. Topical Review
  10. Predicting pain after standard pain therapy for knee osteoarthritis – the first steps towards personalized mechanistic-based pain medicine in osteoarthritis
  11. Clinical Pain Researches
  12. Neuropathy and pain after breast cancer treatment: a prospective observational study
  13. Neuropeptide Y and measures of stress in a longitudinal study of women with the fibromyalgia syndrome
  14. Nociceptive two-point discrimination acuity and body representation failure in polyneuropathy
  15. Pain sensitivity in relation to frequency of migraine and tension-type headache with or without coexistent neck pain: an exploratory secondary analysis of the population study
  16. Clinician experience of metaphor in chronic pain communication
  17. Observational studies
  18. Chronic vulvar pain in gynecological outpatients
  19. Male pelvic pain: the role of psychological factors and sexual dysfunction in a young sample
  20. A bidirectional study of the association between insomnia, high-sensitivity C-reactive protein, and comorbid low back pain and lower limb pain
  21. Burden of disease and management of osteoarthritis and chronic low back pain: healthcare utilization and sick leave in Sweden, Norway, Finland and Denmark (BISCUITS): study design and patient characteristics of a real world data study
  22. Factors influencing quality of life in patients with osteoarthritis: analyses from the BISCUITS study
  23. Prescription patterns and predictors of unmet pain relief in patients with difficult-to-treat osteoarthritis in the Nordics: analyses from the BISCUITS study
  24. Lifestyle factors, mental health, and incident and persistent intrusive pain among ageing adults in South Africa
  25. Inequalities and inequities in the types of chronic pain services available in areas of differing deprivation across England
  26. Original Experimentals
  27. Conditioned pain modulation is not associated with thermal pain illusion
  28. Association between systemic inflammation and experimental pain sensitivity in subjects with pain and painless neuropathy after traumatic nerve injuries
  29. Endometriosis diagnosis buffers reciprocal effects of emotional distress on pain experience
  30. Educational Case Reports
  31. Intermediate cervical plexus block in the management of treatment resistant chronic cluster headache following whiplash trauma in three patients: a case series
  32. Trigeminal neuralgia in patients with cerebellopontine angle tumors: should we always blame the tumor? A case report and review of literature
  33. Short Communication
  34. Less is more: reliability and measurement error for three versions of the Tampa Scale of Kinesiophobia (TSK-11, TSK-13, and TSK-17) in patients with high-impact chronic pain
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