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last five years, more attention has been paid to the correct recording of ICD-10 codes in rheumatic diseases in Finland. For example, peripheral spondyloarthritis, which does not fit into any specific disease criteria, might have previously been recorded as the ICD-10 code M46, but nowadays it is more frequently recorded as M13.9 (UA).
This may explain some differences in the incidences and drug usages of Finnish IA patients compared to those in other countries.
In the current study, women in group B seemed to be less responsive to bDMARDs than men, since their opioid use after bDMARD initiation was greater compared to men.
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than in RA, because of somewhat less aggressive DMARD initiation. Patients with seronegative RA have been shown to experience higher disease activity and delayed remission, partly due to changed diagnostics and the requirement for more joint involvement at diagnosis (Coffey et al. 2017), which may partly explain the differences in opioid use between the two RA serotypes. Furthermore, seronegative RA and UA patients may actually have another condition, such as crystal arthropathy, osteoarthrosis, or hemochromatosis, which may not respond to DMARDs; this explains why those groups had a greater need for pain medication than the seropositives.
Still, it seems that out of all IA patients, axSpA patients have the highest risk of becoming opioid users, although the mean age in this group is the lowest. This was seen especially among those axSpA patients who subsequently initiated a bDMARD.
Compared to the population controls, axSpA patients were 6.6 times, UA patients 3.5 times, seronegative RA patients 1.9 times, and seropositive RA patients 1.3 times more likely to be long-term opioid users a year after the ID. A similar finding was observed in a large US study where long-term opioid use among patients with different inflammatory rheumatic diseases (RA, SLE, PsA, and AS) was most common (RR 2.73) among AS patients compared to age- and sex-matched patients with hypertension (Chen et al. 2019a).
During the year after the ID, long-term opioid use was seen in 3-6% of RA and UA patients, 11% of those axSpA patients who initiated a bDMARD during the follow-up (group B), and 5% of those axSpA patients treated only with csDMARDs (group A). Although the definition of long-term opioid use varies between the studies, the previously reported numbers from the US range from 12% to 25% in RA (Zamora–Legoff et al. 2016, Lee et al. 2018, Curtis et al. 2017, Kern et al. 2018) and from 10% to 77% in AS (Dau et al. 2018, Sloan et al. 2019, Chen et al. 2019a), and are thus higher than the current results.
The differences in IA patients’ long-term opioid use frequencies between the years before and after the ID did not reach statistical significance in any of the diagnosis groups, thus these results suggest that those who end up being long-term users will continue to use opioids chronically still after DMARD initiation, and they are consequently at risk for opioid addiction. Likewise, patients with osteoarthritis who undergo joint replacement surgery, and thus should be pain free after some time postoperatively, are at risk of prolonged opioid use at least one year after surgery if they have used opioids preoperatively (Franklin et al. 2010). Even if opioids are
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initially prescribed for short-term pain, there is always a risk for opioid dependence, as has been shown among emergency department patients (Hoppe et al. 2015). Once started, the threshold for renewing opioid prescriptions may be lower. Thus, harmful long-term use of opioids may be a result of painful comorbidities, contraindications for NSAIDs, wrong diagnoses, or too liberal prescription habits by physicians.
AxSpA patients’ opioid consumption by dose (in DDDs) started to decline gradually once a bDMARD was initiated, and the trend was still declining at one year of bDMARD use. Recently presented but not yet published results from Iceland, however, showed that after the initiation of the first-line TNFi, IA (RA, axSpA, PsA, or UA) patients’ opioid consumption by dose [presented as morphine equivalent doses (MEDs)] did not decrease at the group level during two years of follow-up (Palsson et al. 2020).
In the present study, higher education level was associated with less opioid use in most IA diagnoses. Further, continuous oral GC use was a predictor of increased opioid use. Those IA patients using medications used to treat psychiatric or cardiovascular comorbidities were at a greater risk of being opioid users.
Since patients who receive an IA diagnosis and are started on DMARDs are usually monitored in rheumatologic clinics at least the first two years after diagnosis, they most likely get their drug (including opioid) prescriptions from there. Instead, the population controls as well as patients before IA diagnosis usually receive their drug prescriptions from primary care physicians. Thus, this study probably describes the physicians’ prescription patterns even more than their patients’ opioid need. A drop in opioid use was found after the ID when patients were presumably monitored by the rheumatologists, but the numbers did not reach population levels during the follow-up. Previous studies have shown that almost half of the RA patients using opioids receive their opioid prescriptions from a rheumatologist (Curtis et al. 2017), and the physician’s opioid prescription habits greatly affect the RA patient’s risk of later becoming a long-term opioid user (Lee et al. 2020). Thus, it is important that rheumatologists, especially in the early disease, carefully check the diagnostics and weigh up the treatment options before they renew the opioid prescription.
In all diagnoses, the purchases of NSAIDs and paracetamol showed similar trends as opioids (a peak before diagnosis and a reduction after that), even though the percentages of patients purchasing these medications were markedly higher, except in the axSpA group, in which both NSAIDs and opioids were purchased more often than paracetamol.
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