Skip to main content

Pharmacological pain management in patients with rheumatoid arthritis: a narrative literature review

Abstract

Background

Pain is a major challenge for patients with rheumatoid arthritis (RA), with many people suffering chronic pain. Current RA management guidelines focus on assessing and reducing disease activity using disease-modifying anti-rheumatic drugs (DMARDs). Consequently, pain care is often suboptimal, with growing evidence that analgesics are widely prescribed to patients with RA, despite potential toxicities and limited evidence for efficacy. Our review provides an overview of pharmacological treatments for pain in patients with RA, summarising their efficacy and use.

Findings

Thirteen systematic reviews of drug efficacy for pain in patients with RA were included in this review. These showed moderate- to high-quality evidence from clinical trials in more contemporary time-periods (mainly 1990s/2000s for synthetic DMARDs and post-2000 for biological/targeted synthetic DMARDs) that, in patients with active RA, short-term glucocorticoids and synthetic, biologic, and targeted synthetic DMARDs have efficacy at reducing pain intensity relative to placebo. In contrast, they showed low-quality evidence from trials in more historical time-periods (mainly in the 1960s–1990s for opioids and paracetamol) that (aside from naproxen) analgesics/neuromodulators provide any improvements in pain relative to placebo, and no supportive evidence for gabapentinoids, or long-term opioids. Despite this evidence base, 21 studies of analgesic prescribing in patients with RA consistently showed substantial and sustained prescribing of analgesics, particularly opioids, with approximately one quarter and > 40% of patients receiving chronic opioid prescriptions in each year in England and North America, respectively. Whilst NSAID prescribing had fallen over time across countries, gabapentinoid prescribing in England had risen from < 1% of patients in 2004 to approximately 10% in 2020. Prescribing levels varied substantially between individual clinicians and groups of patients.

Conclusions

In patients with active RA, DMARDs have efficacy at reducing pain, supporting the role of treat-to-target strategies. Despite limited evidence that analgesics improve pain in patients with RA, these medicines are widely prescribed. The reasons for this are unclear. We consider that closing this evidence-to-practice gap requires qualitative research exploring the drivers of this practice, high-quality trials of analgesic efficacy in contemporary RA populations, alongside an increased focus on pain management (including pharmacological and non-pharmacological options) within RA guidelines.

Peer Review reports

Background

Rheumatoid arthritis (RA) is a common autoimmune-mediated condition, characterised by persistent synovial inflammation (particularly of the hand and feet small joints, although any synovial joint can be affected). Raised inflammatory markers and autoantibodies (rheumatoid factor and/or anti-cyclic citrullinated peptide antibodies) are common. Contemporary RA management focuses on treat-to-target strategies. These involve measuring disease activity regularly—often using the Disease Activity Score for 28-Joint Counts (DAS28), which represents a composite score combining information on swollen and tender joint counts, the patient global assessment of disease activity, and inflammatory markers—and increasing treatment with disease-modifying anti-rheumatic drugs (DMARDs) until the “target” of remission or low disease activity is achieved [1]. The high prevalence of RA (which affects approximately 0.8% of adults in England [2], and 17.6 million people globally [3], and is rising in both contexts) and far-reaching personal and economic impacts (including increased disability [4] and unemployment [5]) mean that optimising the care patients with RA receive is a clinical priority.

Despite key therapeutic advances in reducing synovitis and disease activity, pain remains a major challenge in RA. Surveys demonstrate that approximately two-thirds of patients have daily pain [6] with most rating pain to be the health area they most want improved [7], and longitudinal studies show that despite biologic therapies pain is often uncontrolled [8, 9] (with 79% of patients with RA receiving biologics in the British Society for Rheumatology Biologics Registry belonging to a “persistent pain” trajectory). Pain has detrimental impacts on the quality of life [10], function [11], mental health [12], and fatigue levels [13] of patients with RA. The mechanisms driving pain in RA are complex, and often involve multiple pain types and pathways [14], with fibromyalgia particularly common [15].

Contemporary RA guidelines focus on reducing disease activity using DMARDs [16,17,18], providing few/no pain-specific recommendations. To date, the only RA pain-specific guideline is from the European Alliance of Associations for Rheumatology (EULAR) [19]. Underpinned by an umbrella review of non-pharmacological treatments, it advocates biopsychosocial approaches involving reducing synovitis and non-drug care. In the absence of a pain-specific focus in most RA guidelines, there is increasing evidence that its management involves the substantial prescribing of analgesics (particularly opioids) [20, 21], despite known risks (including overdose, fractures, and myocardial infarction with opioids, upper gastrointestinal complications and cardiovascular events with NSAIDs [22,23,24]), emerging data about other potential harms (such as fractures with gabapentinoids [25]), and limited trial evidence for efficacy. Our narrative review summarises evidence for (a) the efficacy of pharmacological treatments for pain in RA and (b) how they are being prescribed/used, outlining potential future research directions to reduce evidence-to-practice gaps. It provides complementary but distinct information to recent RA therapeutic reviews describing the role of immunosuppressive medicines to reduce disease activity [26, 27].

Methods

Efficacy evidence

We searched Medline and EMBASE (using the Ovid Platform from inception until July 2024) alongside RA guidelines to identify systematic reviews evaluating the efficacy of the following drugs for pain in RA: analgesics (paracetamol/acetaminophen, opioids, NSAIDs); gabapentinoids, anti-depressants, cannabinoids, and other neuromodulators; and drugs for disease activity (corticosteroids, synthetic DMARDs, biologic DMARDs, targeted synthetic DMARDs). We considered corticosteroids/DMARDs because pain is integral to the concept of disease activity, being directly considered in two American College of Rheumatology-recommended disease activity measures [28], and indirectly in the remainder (with patient global assessment scores and pain intensity scores strongly correlated [29]).

Prescribing evidence

We searched Web of Science for observational studies (published from 2004 until July 2024) examining analgesic, gabapentinoid, DMARD, and corticosteroid prescribing using datasets with national/substantial regional coverage. We excluded studies of specific subpopulations only (e.g. pregnant women). As anti-depressants are usually prescribed for non-pain reasons, and literature on the use of cannabinoids in rheumatic diseases (including RA) has recently been systematically summarised [30], we did not consider these drug classes.

Search terms

Search terms are provided in supplementary data (Additional file 1: Tables S1 to S3) and an overview of the search strategy provided in Fig. 1. Database searching was conducted by one author (NC), with data extracted by two authors (ICS and NC). No language restrictions were applied.

Fig. 1
figure 1

Overview of search strategy to identify systematic reviews of drug efficacy and observational studies of drug prescribing

Systematic reviews of efficacy

Reviews identified

From 5915 citations, we identified 34 relevant systematic reviews (with a further review identified from RA guidelines). Key reviews (totalling 13) for each drug class are described below, with a summary of their findings provided in Table 1 and Fig. 2. Details of all identified reviews are provided in supplementary data (Additional file 1: Table S4) [16, 31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63].

Table 1 Key systematic reviews reporting the efficacy of drugs for pain in patients with RA
Fig. 2
figure 2

Summary of the evidence for efficacy and risk of bias from trials included in key systematic reviews of drugs for pain in patients with RA. Where efficacy is green, this indicates there is trial evidence indicating a favourable effect on pain (please see manuscript text and Table 1 for details on effect sizes). Where efficacy is orange, this indicates there is uncertain trial evidence for a favourable effect on pain. Where risk of bias is red, this indicates the trial evidence is at high risk of bias. Where risk of bias is orange, this indicates the trial evidence is at variable risk of bias. Where risk of bias is green, this indicates the trial evidence is at low risk of bias. Please see Table 1 for further details on each systematic review considered in this figure

Paracetamol

Hazlewood et al. summarised paracetamol efficacy in 9 trials using a narrative synthesis (Table 1) [31]. All trials were short-term, used atypical dosing (doses ranging 650 mg to 7.5 g/day), and had high-risk of bias. Three (conducted in the 1970s; 6-h duration) compared single paracetamol doses to placebo using crossover designs, showing small, statistically significant improvements in “pain relief” (e.g. mean pain relief scores over trial period on a 0–3 scale of 1.2 with paracetamol vs. 0.8 with placebo); these also compared paracetamol with weak opioids, with no differences in efficacy found [64, 65]. Four trials compared paracetamol to NSAIDs (duration 1–2 weeks) [66,67,68,69], indicating a benefit of NSAIDs over paracetamol, although the relevance of this was uncertain as three either did not report effect sizes or significance levels. Two trials compared paracetamol with NSAIDs vs. NSAIDs [70, 71]; one showed no difference and the other significantly lower mean rest pain scores with paracetamol-naproxen combined vs. naproxen. The review authors concluded there was weak evidence for paracetamol’s efficacy.

Opioids

A Cochrane review summarised opioid efficacy in 11 trials, all short duration (longest 6 weeks), in which the risk of bias was considered generally high [32]. Only two were published post-2000. Six studies with a duration of ≥ 1 week compared opioids to placebo; five reported superiority of opioids for at least one efficacy measure. Several studies could be included in meta-analyses for different outcomes. Three were included for the outcome of improvement in patient-reported global impression of clinical change of “good/very good”, with a pooled relative risk of 1.44 (95% CI 1.03, 2.03), equating to 18 more people out of 100 reporting a good/very good symptom improvement. Four were included for the outcome of adverse events, with the risk of experiencing at least one adverse event significantly more with opioids (pooled odds ratio 3.90; 95% CI 2.31, 6.56), equating to 30 more people out of 100 experiencing these. Evidence quality for these outcomes was “low”. The authors concluded there was limited evidence weak oral opioids may be effective for some patients, but adverse effects may offset benefits, with insufficient evidence to draw conclusions on opioids for > 6 weeks or strong opioids.

NSAIDs

A network meta-analysis evaluated NSAID efficacy, including 21 trials of various NSAIDs of treatment durations ranging 2–26 weeks [36]. Thirteen were included in the meta-analysis for pain. Naproxen (1000 mg/day) associated with a statistically significant greater reduction in pain vs. placebo (standardised mean difference − 10.28; 95% CI − 20.39, − 0.17), although evidence was considered “very low” quality. No other NSAIDs had significant differences in their effects on pain vs. placebo/each other. Within this systematic review, only one trial of NSAIDs was considered to be at low risk of bias [72]. This represented a phase III, 12-week, randomised, double-blind, parallel-group trial comparing oral meloxicam of varying doses to placebo (negative control arm) and diclofenac 75 mg twice daily (active comparator arm). Eight hundred ninety four patients were randomised to treatment, with baseline endpoint scores similar amongst treatment groups. Statistically significant reductions in pain levels were seen for all active treatment groups compared to placebo (P < 0.05) with a mean reduction in 100 mm pain intensity VAS of − 21.2 (standard error [SE] 2.1), − 25.1 (2.1), and − 24.3 (2.1) with meloxicam 7.5 mg, 15 mg, and 22.5 mg daily, respectively; − 25.4 (SE 2.1) with diclofenac; and − 14.4 (SE 2.1) with placebo. As with many trials of NSAIDs in RA, however, patients were required to have been taking an NSAID pre-trial, and have flared on stopping it; consequently, the trial population is likely to include people most likely to benefit from using NSAIDs.

Gabapentinoids

A National Institute for Health and Care Excellence (NICE) systematic review identified no trials examining gabapentin/pregabalin efficacy [16].

Anti-depressants

A Cochrane review summarised anti-depressant efficacy in 8 trials (seven at high-risk of bias) [39]. All evaluated tricyclic anti-depressants. Due to poor-quality, heterogeneous trials with mixed results meta-analysis were deemed unsuitable. Qualitative analyses found no evidence of an effect of antidepressants on pain in the short term (< 1 week), and conflicting evidence of a medium- (1–6 weeks) or long-term (> 6 weeks) benefit.

Cannabinoids

Fitzcharles et al. [40] examined the efficacy of cannabinoids in rheumatic diseases, identifying one trial (from 2006) of a cannabinoid administered as an oromucosal spray in RA [73]. It was considered at high risk of bias due to concerns regarding blinding of the outcome assessment, incomplete outcome data, and a small sample size (31 people randomised to active treatment). The primary outcome was pain on movement, measured using an 11-point numeric rating scale, with the baseline score (mean of last 4 days of 14-day baseline period) compared with endpoint score (mean of last 14 days of treatment). The median difference in change between baseline and endpoint scores was − 0.95 (95% CI − 1.83, − 0.02) with active vs. placebo treatment. More people receiving cannabinoids vs. placebo reported dizziness (26% vs. 4%) and light-headedness (10% vs 4%). A recent systematic review evaluated the association between cannabinoids and pain in people with “rheumatological conditions” more broadly, including both observational and trial data [30]. The authors conducted a meta-analysis of changes in pain scores before and after using cannabinoids, including six non-randomised studies (totalling 1079 patients). Four studies considered people with fibromyalgia, and two considered people with chronic pain related to a range of diagnoses. Whilst a statistically significant reduction in pain VAS scores was seen between baseline and follow-up assessments—pooled effect size of − 1.75 (95% CI − 2.75, − 0.76)—the non-randomised nature of included studies, alongside their consideration of non-RA populations, makes the relevance of their findings to RA pain management of uncertain significance.

Nefopam and topical capsaicin

A Cochrane review identified two trials evaluating oral nefopam in RA (52 participants) and one evaluating topical capsaicin in RA and osteoarthritis (31 participants) [38]. All were considered at high-risk of bias. Meta-analysis identified a significant reduction in pain favouring nefopam over placebo (weighted mean difference − 21.2; 95% CI − 35.6 to − 6.7 after 2 weeks); however, nefopam associated with significantly more adverse events (relative risk 4.1; 95% CI 1.58 to 10.69). A significantly greater reduction in pain favouring topical capsaicin over placebo at 2 weeks was seen (mean difference − 34.4; 95% CI − 54.7 to − 14.1); whilst no separate safety data were available for patients with RA, 44% developed application site burning.

Glucocorticoids

McWilliams et al. identified 33 trials examining systemic glucocorticoid efficacy at improving pain; 22 considered oral dosing [62]. Meta-analysis for the outcome of “spontaneous pain” at the earliest available timepoint showed a standardised mean difference of − 0.67 (95% CI − 0.84, − 0.50) for glucocorticoids vs. inactive comparators. Restricting analysis to 14 “high-quality” studies showed similar findings. Greatest improvement was seen in 100 mm pain visual analogue scale (VAS) at 0 to 3 months (mean difference − 15 mm; 95% CI − 20, − 9) followed by > 3 to 6 months (mean difference − 8 mm; 95% CI − 12, − 3), and > 6 months (mean difference − 7 mm; 95% CI − 13, 0). The authors concluded that systemic glucocorticoids are “analgesic in RA” with benefits greatest shortly after initiation.

Synthetic DMARDs

Cochrane reviews have summarised the efficacy of methotrexate (seven trials) [41], sulphasalazine (six trials) [46], and leflunomide (33 trials) [45]. With methotrexate, differences in pain scores compared to placebo were reported in four studies (assessed at timepoints varying 12–52 weeks); the pooled mean difference for pain scores was − 2.02 (95% CI − 2.41, − 1.63) with methotrexate (267 participants) vs. placebo (201 participants) on a 0 to 10 scale. Trial risk of bias was generally low. With sulphasalazine, differences in pain scores compared to placebo were reported in three studies (assessed at timepoints varying between 6 and 12 months); the pooled mean difference for pain scores was − 8.71 (95% CI − 14.80, − 2.62) with sulphasalazine (84 participants) vs. placebo (95 participants) on a 0 to 100 scale. Study quality was assessed using the Jadad scale, ranging from 0 (worst) to 5 (best); two scored 5; one scored 4. With leflunomide, differences in pain scores compared to placebo were reported in three trials at 6 months; the pooled mean difference for pain scores was − 13.81 (95% CI − 15.91, 11.71) on a 0 to 100 scale with leflunomide (413 participants) vs. placebo (311 participants). Study quality was rated high in all three trials. Overall, these reviews provide generally high-quality evidence that synthetic DMARDs reduce pain intensity in active RA.

Biologic DMARDs

A systematic review and network meta-analysis evaluated the efficacy of biologics for pain in RA [53]. This included 17 trials, all rated “good quality” (Jadad scores 3–5); 13 trials provided an outcome for pain. Relative to placebo, both anti-TNF (pooled estimate − 20.2; 95% CI − 17.4, − 0.37) and tocilizumab (pooled estimate − 31.3; 95% CI − 27.7, − 0.53) monotherapy demonstrated significantly greater reductions in pain over 24 weeks (on a 0 to 100 scale), which were considered larger than the minimal clinically important difference defined by the authors (10 units). Tocilizumab monotherapy associated with greater improvements in pain, compared to anti-TNF monotherapy (pooled estimate − 11.1; 95% CI − 21.3, − 0.1).

Targeted synthetic DMARDs

Tóth et al. evaluated the efficacy of Janus Kinase (JAK) Inhibitors at improving patient-reported outcome measures, including pain, in RA [61]. Twenty-one trials were included for the outcome of pain at < 6 months (assessed using a 0–100 VAS) for JAK inhibitors vs. placebo: weighted mean difference was 15.3 mm lower (95% CI 13.2, 17.3) with active treatment (“moderate” certainty of evidence). Four trials were included for this outcome for JAK inhibitors vs. biologic DMARDs; all compared tofacitinib/baricitinib to adalimumab. Whilst these indicated a small but statistically significant improvement in pain with JAK inhibitors relative to adalimumab—weighted mean difference 4.4 mm lower (95% CI 2.2, 6.5) with JAK inhibitors (“moderate” certainty of evidence)—they also showed statistically significant improvements for a range of other outcomes (including remission rates, ACR20 responses, and CRP reductions) suggesting small global (as opposed to analgesic-specific) benefits with JAK inhibitors relative to adalimumab. A post hoc analysis of the RA-BEAM trial by Taylor et al. has, however raised the possibility that the JAK inhibitor, baricitinib, may exert its effects on pain via alternative pathways to adalimumab [74]. This trial randomised patients with active RA to baricitinib (487 patients), adalimumab (330 patients), and placebo (488 patients) plus methotrexate for 24 weeks (with patients receiving placebo, switched to baricitinib thereafter, with the overall trial lasting 52 weeks). Pain was evaluated using a 100-m VAS. This analysis compared pain level reductions at week-24 between treatment arms, stratified by CRP status, using analysis of covariance. It also used a mediation analysis to evaluate the extent to which these drugs reduce pain via reductions in inflammation levels (represented by ESR levels, CRP levels, and SJCs) and the extent to which they reduce pain via other effects. At week 24, statistically significant reductions in pain levels from baseline were seen for baricitinib in all CRP level categories (≤ 3, ≤ 10, and > 10 mg/L), but only for adalimumab in the CRP level category ≤ 3 mg/L. In the mediation analysis, changes in inflammation levels accounted for approximately 40% of pain improvements observed with baricitinib vs 50% of those observed with adalimumab. Whilst this analysis suggests the difference in analgesia between baricitinib and adalimumab cannot be solely accounted for by their differential effects on inflammation, as it represents a post-hoc analysis, it requires interpretation within this context.

Summary

Systematic reviews show moderate- to high-quality trial evidence (from more contemporary time-periods) that, in patients with active RA, short-term systemic glucocorticoids and synthetic, biologic, and targeted synthetic DMARDs have efficacy at reducing pain relative to placebo. Conversely, they show low-quality evidence from trials in more historical time-periods that (aside from naproxen) analgesics and neuromodulators provide improvements in pain relative to placebo. No trials have evaluated gabapentinoids, serotonin and norepinephrine reuptake inhibitors, or long-term opioids, meaning that whilst no evidence exists to support their use for pain in RA, they cannot be entirely discounted as therapeutic options.

Prescribing practice

Studies identified

From 11,547 citations, our search identified 67 relevant observational studies. From these, we describe 21 key studies of analgesic prescribing and 6 of glucocorticoid and/or DMARD prescribing in this review (Table 2). For studies examining analgesic prescribing: 9 considered opioids, 5 NSAIDs, and 7 multiple analgesics. Geographically, they spanned North America, Australia, Columbia, Europe, Iceland, and Japan, with sizes ranging from 359 to 88,097 patients. For studies examining DMARD and glucocorticoid prescribing: 4 were conducted in North America, 1 in the UK, and 1 in Norway; study sizes ranged 829–71,411 patients. Details for the remaining observational studies are provided in supplementary data (Additional file 1: Tables S5 [20, 21, 75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106] and S6 [80, 83, 99, 102, 103, 107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134]).

Table 2 Key observational studies reporting analgesic prescribing levels or predictors in patients with RA

Analgesics

Prescribing levels

Substantial prescribing of all forms of analgesics across countries is seen (Table 2). For example, in a North American cohort study using health insurance data from 2006 to 2014 (involving 70,929 patients), regular opioid use (defined as ≥ 3 prescriptions or ≥ 90 days of cumulative use in each 12-month calendar interval) was observed in > 40% of patients every year [21]. In a Columbian cohort study, 84.9% of 1329 patients with RA used opioids for ≥ 1 month over 7 years [86]. In English electronic health record data (Clinical Practice Research Datalink Aurum) in each year from 2004 to 2020 approximately one in four received a long-term opioid prescription [20]. This study also demonstrated reductions in oral NSAID prescribing over 17 years, but rising gabapentinoid prescriptions (occurring in < 1% in 2004, and approximately 10% in 2020). Other studies in Japan and the UK also demonstrated declining NSAID prescriptions over time (although they remained common) with 25.1% receiving a long-term NSAID prescription in the UK in 2017 [83], and 80.9% of patients with incident RA in Japan receiving an NSAID as the main first line treatment in 2011 [99]. Figure 3 demonstrates the trends in chronic NSAID and opioid prescriptions/use (in studies containing extractable data from > one calendar year); substantial reductions in chronic NSAID prescriptions were observed in the UK and England, with chronic opioid prescriptions/use changing little.

Fig. 3
figure 3

Observational studies reporting the prevalence of chronic analgesic, DMARD, and corticosteroid prescriptions or use over time in patients with RA. Different studies used different definitions of chronic prescriptions. Scott et al.: the denominator is 100 person-years, and the population includes patients with RA, psoriatic arthritis, and axial spondyloarthritis (although RA was the commonest diagnosis). Crossfield et al.: DMARD and corticosteroid prescriptions are long-term. Navarro-Millan et al.: the population comprises beneficiaries of Social Security Disability Insurance (no longer working because they are considered disabled) and < 65 years old. Studies included in the figure are those reporting the prevalence of chronic NSAID, chronic opioid, DMARD, and corticosteroid prescriptions/use in > one calendar year that contain extractable data

Prescribing changes post-DMARD initiation

Several studies evaluated analgesic prescribing pre-/post-DMARD initiation, showing reductions, which were small for opioids. Park et al. reported that pre- and post-anti-TNF initiation, the proportion of 2330 patients receiving any opioid decreased from 54.0 to 51.0% [89], and Kawai et al. reported that amongst 32,476 patients initiating new DMARDs, in the 6–12 months afterwards the proportion receiving opioids decreased by 2.5% [101]. Larger reductions were reported for NSAIDs, with the study by Kawai et al. reporting a 12.9% reduction for NSAIDs, and another by Hunter et al. reporting that during the 12-month pre- and post-biologic DMARD initiation, NSAID prescriptions fell from 61.1 to 41.5% [82].

Prescribing variation

Analgesic prescribing varied substantially between groups of patients in England, with opioid and gabapentinoid prescriptions commoner in deprived areas and North England, older people, and females [20]. It also varied substantially between clinicians, with Curtis et al. reporting that patients cared for by the same physician were 25% (95% CI 18, 32) more likely to be regular opioid users or non-users, after controlling for other patient characteristics [21], and Lee et al. reporting that during follow-up, long-term opioid use occurred in 7.0% of patients of physicians with very low opioid prescribing rates, compared to 12.7% of patients of physicians with high prescribing rates [88].

Patient factors associating with prescriptions

Two longitudinal studies reported that more intense pain had significant associations with chronic opioid use. In North America, using survey data, amongst 26,288 individuals not taking opioids at baseline, cox proportional hazards models demonstrated that severe pain was a significant predictor of chronic opioid use (HR 2.53; 95% CI 2.19, 2.92) [92]. In a cohort study in the Australian biologics registry, within-patient opioid use associated with higher self-reported pain scores, which also associated with a higher probability of starting opioids and a lower probability of stopping them [90]. An increased body mass index (BMI) also has significant associations with opioid prescribing. In English primary care data, BMI at RA diagnosis had a significant association with the subsequent receipt of a chronic opioid prescription, with HRs (95% CI) of 1.66 (1.59, 1.73) and 1.24 (1.19, 1.29) for people categorised as overweight and obese, relative to those categorised as normal weight/underweight [20]. Baker et al. examined the association between BMI (at enrolment) and incident chronic opioid use in a longitudinal study using semi-annual surveys [84]. Severe obesity associated with a higher risk of overall (HR 1.74; 95% CI 1.72, 2.04) and strong (HR 2.11; 95% CI 1.64, 2.71) opioid use, compared to normal BMI. Other factors with significant associations with chronic opioid prescriptions include the presence of depression, anxiety, and fibromyalgia [20, 21].

Glucocorticoids and DMARDs

Studies showed consistent findings, with the prescribing of DMARD types increasing over time, but long-term glucocorticoid prescribing remaining similar (Table 3). In UK primary care electronic health record data, Crossfield et al. reported that the percentage with incident RA receiving a long-term synthetic DMARD in the 12 months post-diagnosis rose from 41.6% in 1998, peaking at 67.9% in 2009 then falling slightly in 2016 to 54.7% [83]. The percentage receiving long-term corticosteroids changed little (22.2% in 1998; 19.1% in 2016). In Canada, Hanly et al. reported that (in health administrative data from 8240 patients) between 1997 and 2017 the percentage prescribed synthetic and biologic DMARDs in each year rose from 33.8 to 64.9% and 0 to 20.4%, respectively, but the percentage prescribed corticosteroids changed little (from 34.3 to 32.5%) [111]. Similarly, in the USA (within pharmacy claims data from 40,373 patients) the percentage prescribed biologic DMARDs rose from 16% in 2004 to 39% in 2013 [118], and in Norway (within data from 10 centres) the percentage receiving a biologic or targeted synthetic DMARD increased from 39% of 4909 patients in 2010 to 45% of 9335 patients in 2019 [110]. Crowson et al. compared glucocorticoid use between two cohorts of patients with RA: those diagnosed in 1999–2008 and those in 2009–2018 [109]. Glucocorticoids were initiated within 6 months of RA diagnosis in 67% of patients in 1999–2008 and 71% of patients in 2009–2018. Jeong et al. reported trends in biologic and targeted synthetic DMARD prescribing in the 664 days before and after the January 2021 release of trial data showing an increased risk of major cardiovascular events/cancer with JAK inhibitors; significant reductions and increases in the prescribing of JAK inhibitors and anti-TNF biologics, respectively, were seen [108]. Figure 3 highlights these time trends in glucocorticoid/DMARD prescribing.

Table 3 Key observational studies reporting long-term glucocorticoid and DMARD prescribing levels in patients with RA

Summary

Many patients with RA receive analgesics (particularly long-term opioids), with prescribing levels varying substantially between clinicians and groups of patients. Whilst NSAID use has fallen over time, gabapentinoid prescribing has increased. DMARD prescribing levels have risen, but long-term glucocorticoid prescribing remains relatively static.

Research agenda

Data summarised in this review show that drug prescribing for pain in RA fails to align with research evidence for efficacy—despite limited evidence for analgesics (and no evidence for long-term opioids/gabapentinoids) they are widely prescribed. Closing this evidence-to-practice gap requires the following research: (1) qualitative studies exploring prescribing drivers; (2) high-quality contemporary trials of analgesic efficacy in RA; (3) an increased focus on pain management in RA guidelines, with an associated implementation strategy.

Qualitative research

In the context of opioids in chronic non-cancer pain, qualitative evidence syntheses using meta-ethnography show that key patient perspective themes are “reluctant users with little choice” (patients feeling there was no other choice available) and “understanding opioids” (patients reporting knowledge acquired gradually and ad hoc) [135], suggesting key drivers are a lack of available non-pharmacological treatment options and a lack of patient education on risks/benefits at opioid initiation. A key healthcare professional theme is “pain is pain” (people reporting a professional duty to resolve pain); this suggests a lack of prescriber knowledge on the relative inefficacy of opioids for chronic non-cancer pain is important [136]. Qualitative research in RA is urgently needed to explore the causes of widespread analgesic prescribing.

Clinical trials

The lack of contemporary high-quality trial evidence that analgesics have/do not have efficacy at improving pain in RA seems an important barrier to changing practice. This is recognised in UK RA guidelines, which recommend research into analgesic effectiveness. The design of such trials is complicated by several factors. First, the widespread use of analgesics in RA means a placebo-controlled trial is unlikely to be feasible, and a withdrawal trial/active comparator design needed. Second, the close relationship between pain and disease activity [29] means that the latter factor needs accounting for either in design, analysis, or both; this is challenging, with sustained remission rare and disease activity varying between appointments. Third, as pain has substantial day-to-day variation in RA [137], the traditional use of end-point pain scores will not sufficiently capture patients’ pain experiences over time. An additional barrier is obtaining funding, as recognised in RA NICE guideline research recommendations, which comment that pharmacological funding for a trial of analgesics “is unlikely due to the drugs being generic and widely available”.

Guidelines

Whist many RA guidelines exist, these focus on reducing disease activity using DMARDs, with the most recent American College of Rheumatology Guideline overlooking pain entirely [17]. Whilst these guidelines have been highly influential in facilitating treat-to-target care and high-cost biologic/targeted synthetic DMARD access, they fail to address the need of ensuring patients with RA receive evidence-based pain care. Within the UK, the British Society for Rheumatology is developing a pain management guideline for RA [138], which will be underpinned by an umbrella review of both pharmacological and non-pharmacological pain treatments (which was beyond the scope of this narrative review to undertake). There is a strong argument to address pain in either general RA guidelines or dedicated pain guidelines in other countries. To ensure these guidelines affect clinical practice, an associated implementation strategy is required, whose development is based on barriers/facilitators to changing practice at the level of patients, healthcare professionals, and organisations [139]. As detailed in a recent EULAR document on the implementation of recommendations in rheumatic diseases [139], effective implementation is complex, time-consuming, and difficult, with an umbrella review of complex intervention implementation strategies (most of which were clinical guidelines) reporting that whilst clinical champions, audit, and education were effective interventions, they had small effects [140].

Conclusions

In patients with active RA, there is substantial evidence that DMARDs and short-term glucocorticoids improve pain. However, in a real-world setting many patients receiving DMARDs have persistent pain and receive long-term opioids and gabapentinoids despite absent trial evidence for efficacy. The reasons for this divergence between practice and evidence are not fully understood; they may reflect patients’ and clinicians’ beliefs about analgesics, which need evaluating in new qualitative research. As an absence of evidence does not mean analgesics are invariably ineffective, new high-quality trials of analgesic efficacy in contemporary RA populations are needed to better understand their relative benefits. Finally, there should be a greater focus on pain management within RA guidelines. In contrast to synovitis and inflammation—which can be simply and objectively measured in routine practice—the subjective, multi-factorial, and multidimensional nature of pain makes this a substantially more challenging outcome to improve.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

BMI:

Body mass index

CI:

Confidence interval

DMARD:

Disease-modifying anti-rheumatic drug

EULAR:

European Alliance of Associations for Rheumatology

HR:

Hazard ratio

VAS:

Visual analogue scale

References

  1. Smolen JS, Aletaha D, Bijlsma JWJ, Breedveld FC, Boumpas D, Burmester G, et al. Treating rheumatoid arthritis to target: recommendations of an international task force. Ann Rheum Dis. 2010;69:631–7.

    Article  PubMed  Google Scholar 

  2. Scott IC, Whittle R, Bailey J, Twohig H, Hider SL, Mallen CD, et al. Rheumatoid arthritis, psoriatic arthritis, and axial spondyloarthritis epidemiology in England from 2004 to 2020: An observational study using primary care electronic health record data. Lancet Reg Health Eur. 2022;23:100519.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Black RJ, Cross M, Haile LM, Culbreth GT, Steinmetz JD, Hagins H, et al. Global, regional, and national burden of rheumatoid arthritis, 1990–2020, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021. Lancet Rheumatol. 2023;5:e594-610.

    Article  Google Scholar 

  4. Myasoedova E, Davis JM, Achenbach SJ, Matteson EL, Crowson CS. Trends in Prevalence of Functional Disability in Rheumatoid Arthritis Compared to the General Population. Mayo Clin Proc. 2019;94:1035–9.

    Article  PubMed  Google Scholar 

  5. Kirkeskov L, Bray K. Employment of patients with rheumatoid arthritis - a systematic review and meta-analysis. BMC Rheumatol. 2023;7:41.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Strand V, Wright GC, Bergman MJ, Tambiah J, Taylor PC. Patient Expectations and Perceptions of Goal-setting Strategies for Disease Management in Rheumatoid Arthritis. J Rheumatol. 2015;42:2046–54.

    Article  CAS  PubMed  Google Scholar 

  7. Heiberg T, Kvien TK. Preferences for improved health examined in 1,024 patients with rheumatoid arthritis: pain has highest priority. Arthritis Rheum. 2002;47:391–7.

    Article  PubMed  Google Scholar 

  8. McWilliams DF, Dawson O, Young A, Kiely PDW, Ferguson E, Walsh DA. Discrete trajectories of resolving and persistent pain in people with rheumatoid arthritis despite undergoing treatment for inflammation: results from three UK cohorts. J Pain. 2019;20:716–27.

    Article  PubMed  Google Scholar 

  9. Pisaniello HL, Lester S, Russell O, Black R, Tieu J, Richards B, et al. Trajectories of self-reported pain-related health outcomes and longitudinal effects on medication use in rheumatoid arthritis: a prospective cohort analysis using the Australian Rheumatology Association Database (ARAD). RMD Open. 2023;9:e002962.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Courvoisier DS, Agoritsas T, Glauser J, Michaud K, Wolfe F, Cantoni E, et al. Pain as an important predictor of psychosocial health in patients with rheumatoid arthritis. Arthritis Care Res. 2012;64:190–6.

    Article  Google Scholar 

  11. Ranzolin A, Brenol JCT, Bredemeier M, Guarienti J, Rizzatti M, Feldman D, et al. Association of concomitant fibromyalgia with worse disease activity score in 28 joints, health assessment questionnaire, and short form 36 scores in patients with rheumatoid arthritis. Arthritis Care Res. 2009;61:794–800.

    Article  Google Scholar 

  12. Euesden J, Matcham F, Hotopf M, Steer S, Cope AP, Lewis CM, et al. The relationship between mental health, disease severity, and genetic risk for depression in early rheumatoid arthritis. Psychosom Med. 2017;79:638–45.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Pollard LC, Choy EH, Gonzalez J, Khoshaba B, Scott DL. Fatigue in rheumatoid arthritis reflects pain, not disease activity. Rheumatology. 2006;45:885–9.

    Article  CAS  PubMed  Google Scholar 

  14. Sarzi-Puttini P, Pellegrino G, Giorgi V, Bongiovanni SF, Varrassi G, Di Lascio S, et al. Inflammatory or non-inflammatory pain in inflammatory arthritis - How to differentiate it? Best Pract Res Clin Rheumatol. 2024;38:101970.

  15. Duffield SJ, Miller N, Zhao S, Goodson NJ. Concomitant fibromyalgia complicating chronic inflammatory arthritis: a systematic review and meta-analysis. Rheumatology. 2018;57:1453–60.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Recommendations | Rheumatoid arthritis in adults: management | Guidance | NICE. 2018. https://www.nice.org.uk/guidance/ng100/chapter/Recommendations. Accessed 10 Dec 2024.

  17. Fraenkel L, Bathon JM, England BR, St. Clair EW, Arayssi T, Carandang K, et al. 2021 American college of rheumatology guideline for the treatment of rheumatoid arthritis. Arthritis Rheumatol. 2021;73:1108–23.

    Article  PubMed  Google Scholar 

  18. Smolen JS, Landewé RBM, Bergstra SA, Kerschbaumer A, Sepriano A, Aletaha D, et al. EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs: 2022 update. Ann Rheum Dis. 2023;82:3–18.

    Article  CAS  PubMed  Google Scholar 

  19. Geenen R, Overman CL, Christensen R, Åsenlöf P, Capela S, Huisinga KL, et al. EULAR recommendations for the health professional’s approach to pain management in inflammatory arthritis and osteoarthritis. Ann Rheum Dis. 2018;77:797–807.

    Article  PubMed  Google Scholar 

  20. Scott IC, Whittle R, Bailey J, Twohig H, Hider SL, Mallen CD, et al. Analgesic prescribing in patients with inflammatory arthritis in England: observational studies in the clinical practice research datalink. Rheumatol Oxf Engl. 2024;63:1672–81.

    Article  CAS  Google Scholar 

  21. Curtis JR, Xie F, Smith C, Saag KG, Chen L, Beukelman T, et al. Changing trends in opioid use among patients with rheumatoid arthritis in the United States. Arthritis Rheumatol. 2017;69:1733–40.

    Article  CAS  PubMed  Google Scholar 

  22. Chou R, Turner JA, Devine EB, Hansen RN, Sullivan SD, Blazina I, et al. The effectiveness and risks of long-term opioid therapy for chronic pain: a systematic review for a national institutes of health pathways to prevention workshop. Ann Intern Med. 2015;162:276–86.

    Article  PubMed  Google Scholar 

  23. Castellsague J, Riera-Guardia N, Calingaert B, Varas-Lorenzo C, Fourrier-Reglat A, Nicotra F, et al. Individual NSAIDs and upper gastrointestinal complications: a systematic review and meta-analysis of observational studies (the SOS project). Drug Saf. 2012;35:1127–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. McGettigan P, Henry D. Cardiovascular risk with non-steroidal anti-inflammatory drugs: systematic review of population-based controlled observational studies. PLoS Med. 2011;8:e1001098.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Scott IC, Daud N, Bailey J, Twohig H, Hider SL, Mallen CD, et al. Gabapentinoid use and the risk of fractures in patients with inflammatory arthritis: nested case-control study in the Clinical Practice Research Datalink Aurum. BMC Med. 2024;22:575.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Brown P, Pratt AG, Hyrich KL. Therapeutic advances in rheumatoid arthritis. BMJ. 2024;384:e070856.

    Article  PubMed  Google Scholar 

  27. Di Matteo A, Bathon JM, Emery P. Rheumatoid arthritis. The Lancet. 2023;402:2019–33.

    Article  Google Scholar 

  28. England BR, Tiong BK, Bergman MJ, Curtis JR, Kazi S, Mikuls TR, et al. 2019 Update of the American College of Rheumatology recommended rheumatoid arthritis disease activity measures. Arthritis Care Res. 2019;71:1540–55.

    Article  Google Scholar 

  29. Ibrahim F, Ma M, Scott DL, Scott IC. Defining the relationship between pain intensity and disease activity in patients with rheumatoid arthritis: a secondary analysis of six studies. Arthritis Res Ther. 2022;24:218.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Guillouard M, Authier N, Pereira B, Soubrier M, Mathieu S. Cannabis use assessment and its impact on pain in rheumatologic diseases: a systematic review and meta-analysis. Rheumatol Oxf Engl. 2021;60:549–56.

    Article  CAS  Google Scholar 

  31. Hazlewood G, van der Heijde DM, Bombardier C. Paracetamol for the management of pain in inflammatory arthritis: a systematic literature review. J Rheumatol Suppl. 2012;90:11–6.

    Article  CAS  PubMed  Google Scholar 

  32. Whittle SL, Richards BL, Husni E, Buchbinder R. Opioid therapy for treating rheumatoid arthritis pain. Cochrane Database Syst Rev. 2011;11:CD003113.

  33. Atzeni F, Masala IF, Bagnasco M, Lanata L, Mantelli F, Sarzi-Puttini P. Comparison of efficacy of ketoprofen and ibuprofen in treating pain in patients with rheumatoid arthritis: a systematic review and meta-analysis. Pain Ther. 2021;10:577–88.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Fidahic M, Jelicic Kadic A, Radic M, Puljak L. Celecoxib for rheumatoid arthritis. Cochrane Database Syst Rev. 2017;6:CD012095.

    PubMed  Google Scholar 

  35. Garner SE, Fidan D, Frankish RR, Judd M, Towheed T, Tugwell P, et al. Rofecoxib for rheumatoid arthritis. Cochrane Database Syst Rev. 2005;1:CD003685.

  36. Paglia MDG, Silva MT, Lopes LC, Barberato-Filho S, Mazzei LG, Abe FC, et al. Use of corticoids and non-steroidal anti-inflammatories in the treatment of rheumatoid arthritis: Systematic review and network meta-analysis. PLoS ONE. 2021;16:e0248866.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Ramiro S, Radner H, van der Heijde DM, Buchbinder R, Aletaha D, Landewé RB. Combination therapy for pain management in inflammatory arthritis: a Cochrane systematic review. J Rheumatol Suppl. 2012;90:47–55.

    Article  CAS  PubMed  Google Scholar 

  38. Richards BL, Whittle SL, Buchbinder R. Neuromodulators for pain management in rheumatoid arthritis. Cochrane Database Syst Rev. 2012;1:CD008921.

    PubMed  Google Scholar 

  39. Richards BL, Whittle SL, Buchbinder R. Antidepressants for pain management in rheumatoid arthritis. Cochrane Database Syst Rev. 2011;11:CD008920.

  40. Fitzcharles M-A, Ste-Marie PA, Häuser W, Clauw DJ, Jamal S, Karsh J, et al. Efficacy, tolerability, and safety of cannabinoid treatments in the rheumatic diseases: a systematic review of randomized controlled trials. Arthritis Care Res. 2016;68:681–8.

    Article  CAS  Google Scholar 

  41. Lopez-Olivo MA, Siddhanamatha HR, Shea B, Tugwell P, Wells GA, Suarez-Almazor ME. Methotrexate for treating rheumatoid arthritis. Cochrane Database Syst Rev. 2014;2014:CD000957.

    PubMed  PubMed Central  Google Scholar 

  42. Li J, Mao H, Liang Y, Lu Y, Chen S, Yang N, et al. Efficacy and safety of iguratimod for the treatment of rheumatoid arthritis. Clin Dev Immunol. 2013;2013:310628.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Steiman AJ, Pope JE, Thiessen-Philbrook H, Li L, Barnabe C, Kalache F, et al. Non-biologic disease-modifying antirheumatic drugs (DMARDs) improve pain in inflammatory arthritis (IA): a systematic literature review of randomized controlled trials. Rheumatol Int. 2013;33:1105–20.

    Article  CAS  PubMed  Google Scholar 

  44. Katchamart W, Trudeau J, Phumethum V, Bombardier C. Methotrexate monotherapy versus methotrexate combination therapy with non-biologic disease modifying anti-rheumatic drugs for rheumatoid arthritis. Cochrane Database Syst Rev. 2010;2010:CD008495.

    PubMed  PubMed Central  Google Scholar 

  45. Osiri M, Shea B, Robinson V, Suarez-Almazor M, Strand V, Tugwell P, et al. Leflunomide for treating rheumatoid arthritis. Cochrane Database Syst Rev. 2003;2002:CD002047.

    PubMed  Google Scholar 

  46. Suarez-Almazor ME, Belseck E, Shea B, Tugwell P, Wells GA. Sulfasalazine for treating rheumatoid arthritis. Cochrane Database Syst Rev. 1998;1998:CD000958.

    PubMed Central  Google Scholar 

  47. Suarez-Almazor ME, Spooner C, Belseck E. Penicillamine for treating rheumatoid arthritis. Cochrane Database Syst Rev. 2000;4:CD001460.

  48. Suarez‐Almazor ME, Spooner C, Belseck E, Shea B. Auranofin versus placebo in rheumatoid arthritis - Suarez‐Almazor, ME - 2000 | Cochrane Library.

  49. Suarez-Almazor ME, Spooner C, Belseck E. Azathioprine for treating rheumatoid arthritis. Cochrane Database Syst Rev. 2000;2000:CD001461.

    PubMed  PubMed Central  Google Scholar 

  50. Shrestha S, Zhao J, Yang C, Zhang J. Relative efficacy and safety of iguratimod monotherapy for the treatment of patients with rheumatoid arthritis: a systematic review and meta-analysis. Clin Rheumatol. 2020;39:2139–50.

    Article  PubMed  Google Scholar 

  51. Ma K, Li L, Liu C, Zhou L, Zhou X. Efficacy and safety of various anti-rheumatic treatments for patients with rheumatoid arthritis: a network meta-analysis. Arch Med Sci AMS. 2019;15:33–54.

    Article  CAS  PubMed  Google Scholar 

  52. Fleischmann R, Tongbram V, van Vollenhoven R, Tang DH, Chung J, Collier D, et al. Systematic review and network meta-analysis of the efficacy and safety of tumour necrosis factor inhibitor-methotrexate combination therapy versus triple therapy in rheumatoid arthritis. RMD Open. 2017;3:e000371.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Jansen JP, Buckley F, Dejonckheere F, Ogale S. Comparative efficacy of biologics as monotherapy and in combination with methotrexate on patient reported outcomes (PROs) in rheumatoid arthritis patients with an inadequate response to conventional DMARDs–a systematic review and network meta-analysis. Health Qual Life Outcomes. 2014;12:102.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Zhou Q, Zhou Y, Chen H, Wang Z, Tang Z, Liu J. The efficacy and safety of certolizumab pegol (CZP) in the treatment of active rheumatoid arthritis (RA): a meta-analysis from nine randomized controlled trials. Int J Clin Exp Med. 2014;7:3870–80.

    PubMed  PubMed Central  Google Scholar 

  55. Maxwell LJ, Singh JA. Abatacept for Rheumatoid Arthritis: A Cochrane Systematic Review. J Rheumatol. 2010;37:234–45.

    Article  CAS  PubMed  Google Scholar 

  56. Mertens M, Singh JA. Anakinra for rheumatoid arthritis: a systematic review. J Rheumatol. 2009;36:1118–25.

    Article  CAS  PubMed  Google Scholar 

  57. Blumenauer BB, Judd M, Wells GA, Burls A, Cranney A, Hochberg MC, et al. Infliximab for the treatment of rheumatoid arthritis. Cochrane Database Syst Rev. 2002;2002:CD003785.

    PubMed  PubMed Central  Google Scholar 

  58. Sparks JA, Harrold LR, Simon TA, Wittstock K, Kelly S, Lozenski K, et al. Comparative effectiveness of treatments for rheumatoid arthritis in clinical practice: A systematic review. Semin Arthritis Rheum. 2023;62:152249.

    Article  CAS  PubMed  Google Scholar 

  59. Hernández-Cruz B, Kiltz U, Avouac J, Treuer T, Haladyj E, Gerwien J, et al. Systematic literature review of real-world evidence on baricitinib for the treatment of rheumatoid arthritis. Rheumatol Ther. 2023;10:1417–57.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Song GG, Bae S-C, Lee YH. Efficacy and safety of tofacitinib for active rheumatoid arthritis with an inadequate response to methotrexate or disease-modifying antirheumatic drugs: a meta-analysis of randomized controlled trials. Korean J Intern Med. 2014;29:656–63.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Tóth L, Juhász MF, Szabó L, Abada A, Kiss F, Hegyi P, et al. Janus kinase inhibitors improve disease activity and patient-reported outcomes in rheumatoid arthritis: a systematic review and meta-analysis of 24,135 patients. Int J Mol Sci. 2022;23:1246.

    Article  PubMed  PubMed Central  Google Scholar 

  62. McWilliams DF, Thankaraj D, Jones-Diette J, Morgan R, Ifesemen OS, Shenker NG, et al. The efficacy of systemic glucocorticosteroids for pain in rheumatoid arthritis: a systematic literature review and meta-analysis. Rheumatology. 2021;61:76–89.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Gotzsche PC, Johansen HK. Short-term low-dose corticosteroids vs placebo and nonsteroidal antiinflammatory drugs in rheumatoid arthritis. Cochrane Database Syst Rev. 2004;2005:CD000189.

    PubMed  Google Scholar 

  64. Hardin JG, Kirk KA. Comparative effectiveness of five analgesics for the pain of rheumatoid synovitis. J Rheumatol. 1979;6:405–12.

    PubMed  Google Scholar 

  65. Huskisson EC. Simple analgesics for arthritis. Br Med J. 1974;4:196–200.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Hajnal J, Sharp J, Popert AJ. A method for testing analgesics in rheumatoid arthritis using a sequential procedure. Ann Rheum Dis. 1959;18:189–206.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Lee P, Watson M, Webb J, Anderson J, Buchanan W. Therapeutic effectiveness of paracetamol in rheumatoid arthritis. Int J Clin Pharmacol Biopharm. 1975;11:68–75.

    CAS  PubMed  Google Scholar 

  68. Solomon L, Abrams G. Voltaren in the treatment of rheumatoid arthritis. South Afr Med J Suid-Afr Tydskr Vir Geneeskd. 1974;48:949–52.

    CAS  Google Scholar 

  69. Solomon L, Abrams G. Bumadizone calcium in the treatment of rheumatoid arthritis. South Afr Med J Suid-Afr Tydskr Vir Geneeskd. 1977;52:391–3.

    CAS  Google Scholar 

  70. Seideman P. Additive effect of combined naproxen and paracetamol in rheumatoid arthritis. Br J Rheumatol. 1993;32:1077–82.

    Article  CAS  PubMed  Google Scholar 

  71. Seideman P, Melander A. Equianalgesic effects of paracetamol and indomethacin in rheumatoid arthritis. Rheumatology. 1988;27:117–22.

    Article  CAS  Google Scholar 

  72. Furst DE, Kolba KS, Fleischmann R, Silverfield J, Greenwald M, Roth S, et al. Dose response and safety study of meloxicam up to 22.5 mg daily in rheumatoid arthritis: a 12 week multicenter, double blind, dose response study versus placebo and diclofenac. J Rheumatol. 2002;29:436–46.

    CAS  PubMed  Google Scholar 

  73. Blake DR, Robson P, Ho M, Jubb RW, McCabe CS. Preliminary assessment of the efficacy, tolerability and safety of a cannabis-based medicine (Sativex) in the treatment of pain caused by rheumatoid arthritis. Rheumatology. 2006;45:50–2.

    Article  CAS  PubMed  Google Scholar 

  74. Taylor PC, Lee YC, Fleischmann R, Takeuchi T, Perkins EL, Fautrel B, et al. Achieving pain control in rheumatoid arthritis with baricitinib or adalimumab plus methotrexate: Results from the RA-BEAM Trial. J Clin Med. 2019;8:831.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Palsson O, Love TJ, Wallman JK, Kapetanovic MC, Gunnarsson PS, Gudbjornsson B. Prescription of non-steroidal anti-inflammatory drugs for patients with inflammatory arthritis decreases with the initiation of tumour necrosis factor inhibitor therapy: results from the ICEBIO registry. Scand J Rheumatol. 2024;53:402–8.

  76. Huang Y-T, Jenkins DA, Yimer BB, Benitez-Aurioles J, Peek N, Lunt M, et al. Trends for opioid prescribing and the impact of the COVID-19 pandemic in patients with rheumatic and musculoskeletal diseases between 2006 and 2021. Rheumatology. 2024;63:1093–103.

    Article  PubMed  Google Scholar 

  77. Gadzhanova S, Roughead E. Use of analgesic and anti-inflammatory medicines before and after initiation of biological disease-modifying antirheumatic drugs for rheumatoid arthritis. J Clin Pharm Ther. 2024;2024:8040681.

    Article  Google Scholar 

  78. Scott IC, Bailey J, White CR, Mallen CD, Muller S. Analgesic prescribing in patients with inflammatory arthritis in England: an observational study using electronic healthcare record data. Rheumatol Oxf Engl. 2022;61:3201–11.

    Article  CAS  Google Scholar 

  79. Lee Z-M, Yang Y-H, Kuo H-C, Shen Y-H, Yu H-R, Su Y-J. Comparison of glucocorticoids and painkiller prescribed days between rheumatoid arthritis patients receiving early and late treatment with a biological agent via a population-based cohort study. Medicine (Baltimore). 2022;101:e31986.

    Article  PubMed  Google Scholar 

  80. Hirata A, Ota R, Hata T, Hamada T, Nishihara M, Uchiyama K, et al. Prescribing trends of biologic disease-modifying anti-rheumatic drugs using a claims database from 6 million people in Japan. Clin Drug Investig. 2021;41:967–74.

    Article  PubMed  Google Scholar 

  81. Huang Y, Rege S, Chatterjee S, Aparasu RR. Opioid prescribing among outpatients with rheumatoid arthritis. Pain Med Malden Mass. 2021;22:2224–34.

    Google Scholar 

  82. Hunter T, Nguyen C, Birt J, Smith J, Shan M, Tan H, et al. Pain medication and corticosteroid use in ankylosing spondylitis, psoriatic arthritis, and rheumatoid arthritis in the United States: a retrospective observational study. Rheumatol Ther. 2021;8:1371–82.

    Article  PubMed  PubMed Central  Google Scholar 

  83. Crossfield SSR, Buch MH, Baxter P, Kingsbury SR, Pujades-Rodriguez M, Conaghan PG. Changes in the pharmacological management of rheumatoid arthritis over two decades. Rheumatol Oxf Engl. 2021;60:4141–51.

    Article  Google Scholar 

  84. Baker JF, Stokes A, Pedro S, Mikuls TR, George M, England BR, et al. Obesity and the risk of incident chronic opioid use in rheumatoid arthritis. Arthritis Care Res. 2021;73:1405–12.

    Article  Google Scholar 

  85. Albrecht K, Marschall U, Callhoff J. Prescription of analgesics in patients with rheumatic diseases in Germany: a claims data analysis. Z Rheumatol. 2021;80(Suppl 2):68–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Machado-Duque ME, Ramírez-Valencia DM, Murillo-Muñoz MM, Machado-Alba JE. Trends in opioid use in a cohort of patients with rheumatoid arthritis. Pain Res Manag. 2020;2020:3891436.

    Article  PubMed  PubMed Central  Google Scholar 

  87. Navarro-Millán I, Rajan M, Lui GE, Kern LM, Pinheiro LC, Safford MM, et al. Racial and ethnic differences in medication use among beneficiaries of social security disability insurance with rheumatoid arthritis. Semin Arthritis Rheum. 2020;50:988–95.

    Article  PubMed  PubMed Central  Google Scholar 

  88. Lee YC, Lu B, Guan H, Greenberg JD, Kremer J, Solomon DH. Physician prescribing patterns and risk of future long-term opioid use among patients with rheumatoid arthritis: a prospective observational cohort study. Arthritis Rheumatol Hoboken NJ. 2020;72:1082–90.

    Article  CAS  Google Scholar 

  89. Park S, Le TT, Slejko JF, Villalonga-Olives E, Onukwugha E. Changes in opioid utilization following tumor necrosis factor inhibitor initiation in patients with rheumatoid arthritis. Rheumatol Ther. 2019;6:611–6.

    Article  PubMed  PubMed Central  Google Scholar 

  90. Black RJ, Richards B, Lester S, Buchbinder R, Barrett C, Lassere M, et al. Factors associated with commencing and ceasing opioid therapy in patients with rheumatoid arthritis. Semin Arthritis Rheum. 2019. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.semarthrit.2019.06.003.

    Article  PubMed  Google Scholar 

  91. Bedene A, Lijfering WM, Niesters M, van Velzen M, Rosendaal FR, Bouvy ML, et al. Opioid prescription patterns and risk factors associated with opioid use in the Netherlands. JAMA Netw Open. 2019;2:e1910223.

    Article  PubMed  PubMed Central  Google Scholar 

  92. Lee YC, Kremer J, Guan H, Greenberg J, Solomon DH. Chronic opioid use in rheumatoid arthritis: prevalence and predictors. Arthritis Rheumatol. 2019;71:670–7.

  93. Chen SK, Feldman CH, Brill G, Lee YC, Desai RJ, Kim SC. Use of prescription opioids among patients with rheumatic diseases compared to patients with hypertension in the USA: a retrospective cohort study. BMJ Open. 2019;9:e027495.

    Article  PubMed  PubMed Central  Google Scholar 

  94. Kern DM, Chang L, Sonawane K, Larmore CJ, Boytsov NN, Quimbo RA, et al. Treatment patterns of newly diagnosed rheumatoid arthritis patients from a commercially insured population. Rheumatol Ther. 2018;5:355–69.

    Article  PubMed  PubMed Central  Google Scholar 

  95. Accortt NA, Schenfeld J, Chang E, Papoyan E, Broder MS. Changes in healthcare utilization after etanercept initiation in patients with rheumatoid arthritis: a retrospective claims analysis. Adv Ther. 2017;34:2093–103.

    Article  PubMed  PubMed Central  Google Scholar 

  96. Jobski K, Luque Ramos A, Albrecht K, Hoffmann F. Pain, depressive symptoms and medication in German patients with rheumatoid arthritis-results from the linking patient-reported outcomes with claims data for health services research in rheumatology (PROCLAIR) study. Pharmacoepidemiol Drug Saf. 2017;26:766–74.

    Article  PubMed  Google Scholar 

  97. Zamora-Legoff JA, Achenbach SJ, Crowson CS, Krause ML, Davis JM, Matteson EL. Opioid use in patients with rheumatoid arthritis 2005–2014: a population-based comparative study. Clin Rheumatol. 2016;35:1137–44.

    Article  PubMed  PubMed Central  Google Scholar 

  98. Kuo Y-F, Raji MA, Chen N-W, Hasan H, Goodwin JS. Trends in opioid prescriptions among part D medicare recipients from 2007 to 2012. Am J Med. 2016;129(221):e21-30.

    Google Scholar 

  99. Katada H, Yukawa N, Urushihara H, Tanaka S, Mimori T, Kawakami K. Prescription patterns and trends in anti-rheumatic drug use based on a large-scale claims database in Japan. Clin Rheumatol. 2015;34:949–56.

    Article  PubMed  Google Scholar 

  100. Baser O, Burkan A, Baser E, Koselerli R, Ertugay E, Altinbas A. Direct medical costs associated with rheumatoid arthritis in Turkey: analysis from National Claims Database. Rheumatol Int. 2013;33:2577–84.

    Article  PubMed  Google Scholar 

  101. Kawai VK, Grijalva CG, Arbogast PG, Curtis JR, Solomon DH, Delzell E, et al. Changes in cotherapies after initiation of disease-modifying antirheumatic drug therapy in patients with rheumatoid arthritis. Arthritis Care Res. 2011;63:1415–24.

    Article  CAS  Google Scholar 

  102. Grijalva CG, Chung CP, Stein CM, Mitchel EF, Griffin MR. Changing patterns of medication use in patients with rheumatoid arthritis in a medicaid population. Rheumatol Oxf Engl. 2008;47:1061–4.

    Article  CAS  Google Scholar 

  103. Goycochea-Robles MV, Arce-Salinas CA, Guzmán-Vázquez S, Cardiel-Ríos MH. Prescription rheumatology practices among Mexican specialists. Arch Med Res. 2007;38:354–9.

    Article  PubMed  Google Scholar 

  104. Solomon DH, Avorn J, Wang PS, Vaillant G, Cabral D, Mogun H, et al. Prescription opioid use among older adults with arthritis or low back pain. Arthritis Rheum. 2006;55:35–41.

    Article  PubMed  Google Scholar 

  105. Helin-Salmivaara A, Huupponen R, Virtanen A, Lammela J, Klaukka T. Frequent prescribing of drugs with potential gastrointestinal toxicity among continuous users of non-steroidal anti-inflammatory drugs. Eur J Clin Pharmacol. 2005;61:425–31.

    Article  PubMed  Google Scholar 

  106. Huang Y, Bruera S, Agarwal SK, Suarez-Almazor ME, Bazzazzadehgan S, Ramachandran S, et al. Opioid treatment for adults with and without systemic autoimmune/inflammatory rheumatic diseases: analysis of 2006–2019 United States national data. Arthritis Care Res. 2024;76:1427–35.

    Article  CAS  Google Scholar 

  107. Huang Y, Chatterjee S, Agarwal SK, Chen H, Johnson ML, Aparasu RR. Factors influencing prescribing the first add-on disease-modifying antirheumatic drugs in patients initiating methotrexate for rheumatoid arthritis. Explor Res Clin Soc Pharm. 2023;11:100296.

    PubMed  PubMed Central  Google Scholar 

  108. Jeong S, George MD, Mikuls TR, England BR, Sauer B, Cannon GW, et al. Changes in patterns of use of advanced therapies following emerging data about adverse events in patients with rheumatoid arthritis from the veterans affairs health system. ACR Open Rheumatol. 2023;5:563–7.

    Article  PubMed  PubMed Central  Google Scholar 

  109. Crowson LP, Davis JM, Hanson AC, Myasoedova E, Kronzer VL, Makol A, et al. Time trends in glucocorticoid use in rheumatoid arthritis during the biologics era: 1999–2018. Semin Arthritis Rheum. 2023;61:152219.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Brkic A, Diamantopoulos AP, Haavardsholm EA, Fevang BTS, Brekke LK, Loli L, et al. Exploring drug cost and disease outcome in rheumatoid arthritis patients treated with biologic and targeted synthetic DMARDs in Norway in 2010–2019 – a country with a national tender system for prescription of costly drugs. BMC Health Serv Res. 2022;22:48.

    Article  PubMed  PubMed Central  Google Scholar 

  111. Hanly JG, Lethbridge L. Use of disease-modifying antirheumatic drugs, biologics, and corticosteroids in older patients with rheumatoid arthritis over 20 years. J Rheumatol. 2021;48:977–84.

    Article  CAS  PubMed  Google Scholar 

  112. Perrone V, Losi S, Rogai V, Antonelli S, Fakhouri W, Giovannitti M, et al. Treatment patterns and pharmacoutilization in patients affected by rheumatoid arthritis in Italian settings. Int J Environ Res Public Health. 2021;18:5679.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. George MD, Baker JF, Wallace B, Chen L, Wu Q, Xie F, et al. Variability in glucocorticoid prescribing for rheumatoid arthritis and the influence of provider preference on long-term use of glucocorticoids. Arthritis Care Res. 2021;73:1597–605.

    Article  CAS  Google Scholar 

  114. Sánchez-Piedra C, Sueiro-Delgado D, García-González J, Ros-Vilamajo I, Prior-Español A, Moreno-Ramos MJ, et al. Changes in the use patterns of bDMARDs in patients with rheumatic diseases over the past 13 years. Sci Rep. 2021;11:15051.

    Article  PubMed  PubMed Central  Google Scholar 

  115. Park S-H, Jeon H-L, Kim SC, Hillen J, Gadzhanova S, Shin J-Y, et al. Utilization of targeted disease-modifying anti-rheumatic drugs (DMARDs) for managing rheumatoid arthritis in the last decade: A two-country comparison. Int J Clin Pharmacol Ther. 2021;59:639–44.

    Article  CAS  PubMed  Google Scholar 

  116. Steffen A, Holstiege J, Klimke K, Akmatov MK, Bätzing J. Patterns of the initiation of disease-modifying antirheumatic drugs in incident rheumatoid arthritis: a German perspective based on nationwide ambulatory drug prescription data. Rheumatol Int. 2018;38:2111–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Fakhouri W, Lopez-Romero P, Antonelli S, Losi S, Rogai V, Buda S, et al. Treatment patterns, health care resource utilization and costs of rheumatoid arthritis patients in Italy: findings from a retrospective administrative database analysis. Open Access Rheumatol Res Rev. 2018;10:103–11.

    CAS  Google Scholar 

  118. Atzinger CB, Guo JJ. Biologic disease-modifying antirheumatic drugs in a national, privately insured population: utilization, expenditures, and price trends. Am Health Drug Benefits. 2017;10:27–36.

  119. Donges E, Staatz CE, Benham H, Kubler P, Hollingworth SA. Patterns in use and costs of conventional and biologic disease-modifying anti-rheumatic drugs in Australia. Clin Exp Rheumatol. 2017;35:907–12.

    PubMed  Google Scholar 

  120. Desai RJ, Solomon DH, Jin Y, Liu J, Kim SC. temporal trends in use of biologic DMARDs for rheumatoid arthritis in the United States: a cohort study of publicly and privately insured patients. J Manag Care Spec Pharm. 2017;23:809–14.

    PubMed  Google Scholar 

  121. Kalkan A, Husberg M, Hallert E, Roback K, Thyberg I, Skogh T, et al. Physician preferences and variations in prescription of biologic drugs for rheumatoid arthritis: a register-based study of 4,010 patients in Sweden. Arthritis Care Res. 2015;67:1679–85.

    Article  Google Scholar 

  122. Yazdany J, Tonner C, Schmajuk G, Lin GA, Trivedi AN. Receipt of glucocorticoid monotherapy among medicare beneficiaries with rheumatoid arthritis. Arthritis Care Res. 2014;66:1447–55.

    Article  CAS  Google Scholar 

  123. Makol A, Davis JM, Crowson CS, Therneau TM, Gabriel SE, Matteson EL. Time trends in glucocorticoid use in rheumatoid arthritis: results from a population-based inception cohort, 1980–1994 versus 1995–2007. Arthritis Care Res. 2014;66:1482–8.

    Article  Google Scholar 

  124. Edwards CJ, Campbell J, van Staa T, Arden NK. Regional and temporal variation in the treatment of rheumatoid arthritis across the UK: a descriptive register-based cohort study. BMJ Open. 2012;2:e001603.

    Article  PubMed  PubMed Central  Google Scholar 

  125. Harrold LR, Harrington JT, Curtis JR, Furst DE, Bentley MJ, Shan Y, et al. Prescribing practices in a US cohort of rheumatoid arthritis patients before and after publication of the American College of Rheumatology treatment recommendations. Arthritis Rheum. 2012;64:630–8.

    Article  PubMed  PubMed Central  Google Scholar 

  126. Rantalaiho V, Kautiainen H, Virta L, Korpela M, Möttönen T, Puolakka K. Trends in treatment strategies and the usage of different disease-modifying anti-rheumatic drugs in early rheumatoid arthritis in Finland. Results from a nationwide register in 2000–2007. Scand J Rheumatol. 2011;40:16–21.

    Article  CAS  PubMed  Google Scholar 

  127. Nikolaisen C, Kvien TK, Mikkelsen K, Kaufmann C, Rødevand E, Nossent JC. Contemporary use of disease-modifying drugs in the management of patients with early rheumatoid arthritis in Norway. Scand J Rheumatol. 2009;38:240–5.

    Article  CAS  PubMed  Google Scholar 

  128. Söderlin MK, Geborek P. Changing pattern in the prescription of biological treatment in rheumatoid arthritis. A 7-year follow-up of 1839 patients in southern Sweden. Ann Rheum Dis. 2008;67:37–42.

    Article  PubMed  Google Scholar 

  129. Khanna R, Smith MJ. Utilization and costs of medical services and prescription medications for rheumatoid arthritis among recipients covered by a state Medicaid program: a retrospective, cross-sectional, descriptive, database analysis. Clin Ther. 2007;29:2456–67.

    Article  PubMed  Google Scholar 

  130. Carli C, Ehlin AGC, Klareskog L, Lindblad S, Montgomery SM. Trends in disease modifying antirheumatic drug prescription in early rheumatoid arthritis are influenced more by hospital setting than patient or disease characteristics. Ann Rheum Dis. 2006;65:1102–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Gibofsky A, Palmer WR, Goldman JA, Lautzenheiser RL, Markenson JA, Weaver A, et al. Real-world utilization of DMARDs and biologics in rheumatoid arthritis: the RADIUS (Rheumatoid Arthritis Disease-Modifying Anti-Rheumatic Drug Intervention and Utilization Study) study. Curr Med Res Opin. 2006;22:169–83.

    Article  CAS  PubMed  Google Scholar 

  132. Thiele K, Buttgereit F, Huscher D, German Collaborative Arthritis Centres. Zink A Current use of glucocorticoids in patients with rheumatoid arthritis in Germany. Arthritis Rheum. 2005;53:740–7.

    Article  CAS  PubMed  Google Scholar 

  133. Kvien TK, Heiberg, Lie E, Kaufmann C, Mikkelsen K, Nordvåg BY, et al. A Norwegian DMARD register: prescriptions of DMARDs and biological agents to patients with inflammatory rheumatic diseases. Clin Exp Rheumatol. 2005;23 5 Suppl 39:S188-194.

    Google Scholar 

  134. Edwards CJ, Arden NK, Fisher D, Saperia JC, Reading I, Van Staa TP, et al. The changing use of disease-modifying anti-rheumatic drugs in individuals with rheumatoid arthritis from the United Kingdom General Practice Research Database. Rheumatol Oxf Engl. 2005;44:1394–8.

    Article  CAS  Google Scholar 

  135. Nichols VP, Toye F, Eldabe S, Sandhu HK, Underwood M, Seers K. Experiences of people taking opioid medication for chronic non-malignant pain: a qualitative evidence synthesis using meta-ethnography. BMJ Open. 2020;10:e032988.

    Article  PubMed  PubMed Central  Google Scholar 

  136. Toye F, Seers K, Tierney S, Barker KL. A qualitative evidence synthesis to explore healthcare professionals’ experience of prescribing opioids to adults with chronic non-malignant pain. BMC Fam Pract. 2017;18:94.

    Article  PubMed  PubMed Central  Google Scholar 

  137. Mun CJ, Suk HW, Davis MC, Karoly P, Finan P, Tennen H, et al. Investigating intraindividual pain variability: methods, applications, issues, and directions. Pain. 2019;160:2415–29.

    Article  PubMed  Google Scholar 

  138. Scott IC, Babatunde O, Barker C, Beesley R, Beesley R, Birkinshaw H, et al. Pain management in people with inflammatory arthritis: British Society for Rheumatology guideline scope. Rheumatol Adv Pract. 2024;8:rkae128.

    Article  PubMed  PubMed Central  Google Scholar 

  139. Loza E, Carmona L, Woolf A, Fautrel B, Courvoisier DS, Verstappen S, et al. Implementation of recommendations in rheumatic and musculoskeletal diseases: considerations for development and uptake. Ann Rheum Dis. 2022;81:1344–7.

    Article  PubMed  Google Scholar 

  140. Lau R, Stevenson F, Ong BN, Dziedzic K, Treweek S, Eldridge S, et al. Achieving change in primary care—effectiveness of strategies for improving implementation of complex interventions: systematic review of reviews. BMJ Open. 2015;5:e009993.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

ICS is funded by the National Institute for Health and Care Research (NIHR) (Advanced Research Fellowship [NIHR300826]). CDM is funded by the NIHR Applied Research Collaboration and NIHR School for Primary Care Research. NC is funded by the Haywood Foundation and Keele Haywood Academic Rheumatology Group. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

NC conducted the literature search. ICS and NC extracted data from manuscripts included in the review. ICS drafted the manuscript, with contributions from NC and CDM. All authors read and approved the final manuscript version.

Corresponding author

Correspondence to Ian C. Scott.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

Keele University have received funding for CDM’s salary from the MRC, AHRC, Versus Arthritis, NIHR, and BMS.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

12916_2025_3870_MOESM1_ESM.docx

Additional file 1: Table S1. Search Terms used in Medline. Table S2. Search Terms used in EMBASE. Table S3. Search Terms used in Web of Science. Table S4. Systematic Reviews Examining Efficacy of Pharmacological Treatments for Pain in RA. Table S5. Observational Studies Examining Analgesic Prescribing/Use in Patients with RA. Table S6. Observational Studies Examining DMARD and Glucocorticoid Prescribing in Patients with RA.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cox, N., Mallen, C.D. & Scott, I.C. Pharmacological pain management in patients with rheumatoid arthritis: a narrative literature review. BMC Med 23, 54 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12916-025-03870-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12916-025-03870-0

Keywords