
==== Front
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rmdopen
RMD Open
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BMJ Publishing Group BMA House, Tavistock Square, London, WC1H 9JR

39117446
10.1136/rmdopen-2024-004631
rmdopen-2024-004631
Original Research
Psoriatic Arthritis
1506
Impact of initiation of targeted therapy on the use of psoriatic arthritis-related treatments and healthcare consumption: a cohort study of 9793 patients from the French health insurance database (SNDS)
https://twitter.com/LauraPnVg
http://orcid.org/0000-0002-2735-1148
Pina Vegas Laura 12LauraPinaVegas@live.fr

Iggui Siham 1siham.iggui@aphp.fr

Sbidian Emilie 34emilie.sbidian@aphp.fr

http://orcid.org/0000-0003-1911-0544
Claudepierre Pascal 12pascal.claudepierre@aphp.fr

1 Service de Rhumatologie, Hôpital Henri Mondor, Créteil, Île-de-France, France
2 EpiDermE, Université Paris-Est Créteil Val de Marne, Créteil, Île-de-France, France
3 Inserm, Centre d’investigation clinique 1430, Hôpital Henri Mondor, Créteil, Île-de-France, France
4 Service de Dermatologie, Hôpital Henri Mondor, Créteil, Île-de-France, France
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

LPV received a subsidy from Novartis to attend a congress. SI and ES have no conflict of interest to declare. PC has received consulting fees from AbbVie, Amgen, Biogen, Celltrion, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer and UCB (less than US$10 000 each) and has been an investigator for Abbvie, Janssen, Lilly, MSD, Novartis and Pfizer.

Additional supplemental material is published online only. To view, please visit the journal online (https://doi.org/10.1136/rmdopen-2024-004631).

Professor; pascal.claudepierre@aphp.fr
2024
7 8 2024
10 3 e00463106 6 2024
16 7 2024
Copyright © Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

Abstract

Objectives

To assess the potential impact of targeted therapies for psoriatic arthritis (PsA) on symptomatic treatments (non-steroidal anti-inflammatory drugs (NSAIDs), corticosteroids, opioid analgesics), methotrexate and mood disorder treatments and on hospitalisation and sick leave.

Methods

Using the French health insurance database, this nationwide cohort study included adults with PsA who were new users (not in the year before the index date) of targeted therapies for ≥9 months during 2015–2021. Main endpoints were difference in proportion of users of associated treatments, hospitalisations and sick leaves between 3 and 9 months after and 6 months before targeted therapy initiation. Logistic regression models adjusted for sex, age, psoriasis, inflammatory bowel disease and Charlson Comorbidity Index compared the impact of biologics initiation (tumour necrosis factor inhibitor (TNFi)/interleukin 17 inhibitor (IL17i)/IL12/23i) on associated treatment discontinuation.

Results

Among 9793 patients initiating targeted therapy for PsA (mean age: 51±13 years, 47% men), 62% initiated TNFi, 14% IL17i, 10% IL12/23i, 1% Janus kinase inhibitor, 12% phosphodiesterase-4 inhibitor. After treatment initiation, the proportion of treatment users was significantly reduced for NSAIDs (−15%), opioid analgesics (−9%), prednisone (−9%), methotrexate (−15%) and mood disorder treatments (−2%), along with decreased hospitalisations (−12%) and sick leaves (−4%). TNFi had a greater sparing effect on NSAIDs and prednisone use than IL17i (ORa=1.04, 95% CI=1.01 to 1.07; 1.04, 1.02 to 1.06) and IL12/23i (1.07, 1.04 to 1.10; 1.06, 1.04 to 1.09). Odds of methotrexate discontinuation was reduced with TNFi versus IL17i (0.96, 0.94 to 0.98) and IL12/23i (0.94, 0.92 to 0.97).

Conclusions

Targeted therapy initiation for PsA reduced the use of associated treatment and healthcare, with TNFi having a slightly greater effect than IL17i and IL12/23i, except for methotrexate discontinuation.

Antirheumatic Agents
Arthritis, Psoriatic
Epidemiology
==== Body
pmcWHAT IS ALREADY KNOWN ON THIS TOPIC

While targeted therapies are widely recognised for their efficacy in treating psoriatic arthritis (PsA), concerns over their safety profile and cost persist. Emerging data suggest a potential to reduce the need for other drugs, especially symptomatic ones, and certain costly cares. This potential beneficial impact still needs to be specifically studied.

WHAT THIS STUDY ADDS

We observed a significant sparing effect of targeted therapies on symptomatic treatments, and in particular on the use of non-steroidal anti-inflammatory drugs and prednisone (reduction in both the prevalence of users and the mean dosage), as well as lower rates of hospitalisations and sick leave. This effect was slightly more pronounced with tumour necrosis factor inhibitor than interleukin 17 inhibitor (IL17i) and IL12/23i.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

These results underscore the potential for optimising treatment strategies for PsA, suggesting that targeted therapies reduce the burden of associated treatments and healthcare utilisation, which can be particularly interesting given the potential for side effects and cost overruns.

Introduction

Psoriatic arthritis (PsA) is a complex chronic inflammatory rheumatic disease characterised by articular and periarticular involvement as well as extramusculoskeletal manifestations. This condition can be severe, potentially leading to irreversible joint damage and impaired quality of life.1 Over the past decades, the availability of biologic and targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) has rapidly expanded, resulting in substantial advancements in the treatment landscape for PsA. Inhibitors of not only tumour necrosis factor (TNFi) but also interleukin 12/23 (IL12/23i), IL23i, IL17i and Janus kinase (JAKi) are now recommended for moderate-to-severe PsA when conventional synthetic DMARDs (csDMARDs) fail to adequately control disease or are not tolerated.25 In patients with mild disease and an inadequate response to at least one csDMARD, in whom neither a bDMARD nor a JAKi is appropriate, apremilast, a phosphodiesterase-4 inhibitor (PDE4i), may be considered.2

The efficacy of these therapies is widely acknowledged, but is often contrasted by their safety profile and cost.6 Nonetheless, some emerging evidence suggests that they may reduce the consumption of other drugs, particularly symptomatic treatments, which are frequently poorly tolerated. For instance, although non-steroidal anti-inflammatory drugs (NSAIDs) effectively alleviate pain and stiffness in PsA, their daily use can be problematic because of potential adverse effects on the digestive, cardiovascular and renal systems.7 Therefore, they should be used at the minimum effective dose and for the shortest possible duration.2 8 9 Similarly, systemic corticosteroid therapy has undeniable symptomatic efficacy but should be used cautiously to mitigate adverse effects and the risk of dermatosis rebound on abrupt discontinuation or dose reduction.2 10 Although analgesics are useful as adjunct therapy in chronic inflammatory rheumatism, their chronic use must be limited because of serious risks.1113 Thus, as part of comprehensive patient management, a decrease or even discontinuation of those treatments can be considered as an objective in itself. Such a ‘sparing effect’ of targeted therapies seems to be common practice but has been little evaluated, and to our knowledge, no specific studies have been performed in PsA.14 The introduction of these second-line therapies also seems promising in reducing sick leaves and the frequency of certain costly care, such as hospitalisations.15 However, these potential benefits require validation in real-world settings. Furthermore, whether these effects are uniform across all targeted therapies or are preferentially observed with certain classes remains uncertain.

Thus, the main objective of this study was to assess the potential impact of targeted therapies in PsA on the consumption of symptomatic treatments (NSAIDs, opioid analgesics, prednisone, corticosteroids injections), methotrexate and mood disorder treatments as well as their influence on the need for hospitalisation or sick leave.

Methods

Data source and study design

This nationwide cohort study was based on analysis of the French national health insurance database (Système National des Données de Santé (SNDS)).16 The database contains individualised anonymous health data and covers 99% of the French population (>67 million people). As previously described,17 the SNDS contains exhaustive data on all reimbursements for health-related expenditures and outpatient medical and nursing cares prescribed/performed by healthcare professionals, together with sociodemographic data. The data on all pharmacy-dispensed medications include the date of prescription delivery, the type of formulation and the quantity delivered. The database also contains information on the date and nature of medical/paramedical interventions and information on patient eligibility for fully reimbursed care related to severe, costly chronic diseases, such as moderate-to-severe PsA, encoded according to the International Classification of Diseases, 10th Revision (ICD-10). It provides detailed medical information concerning all admissions to French hospitals, including the dates of hospital admission and discharge, the ICD-10 code at discharge, the medical procedures performed in the hospital and costly drugs (such as targeted therapies) administered in the hospital.16 18 This large database has been used for several pharmacoepidemiological studies.1922

This study followed the Strengthening the Reporting of Observational Studies in Epidemiology guidelines.

Study population and exposure definition

All adults (≥18 years old) with PsA who were registered in the SNDS from 1 January 2015 to 31 March 2021 were eligible for inclusion. Adults with PsA were identified by a specific ICD-10 code (M07, except M07.4 and M07.5) according to a previously published algorithm.23 Then, patients with at least one prescription for a targeted therapy were identified. Targeted therapies studied were adalimumab, certolizumab, etanercept, golimumab and infliximab as TNFi; ustekinumab as an IL12/23i; ixekizumab and secukinumab as IL17i; tofacitinib and upadacitinib as JAKi; and apremilast as a PDE4i. We did not evaluate abatacept, brodalumab or IL23i because they had not received marketing authorisation and/or reimbursement for PsA in France before the end of the study. Next, we selected previously targeted therapy-naive patients (ie, ‘new users’), defined as those who had not filled a prescription for one of these drugs for 1 year. Finally, we excluded patients who did not maintain treatment for at least 9 months, during which outcomes were assessed. We defined discontinuation of treatment as (1) a period of more than 60 days after the period of coverage (28 days for all targeted therapies, except infliximab (56 days) and ustekinumab (84 days)) by the last delivery of the molecule or (2) the date of delivery of a new targeted therapy in case of a therapeutic switch.

Outcomes

The primary endpoints were the difference between the proportion of patients (1) using symptomatic treatment, (2) using methotrexate, (3) using mood disorder treatments, (4) being hospitalised and (5) requiring a sick leave during the 3–9 months after initiation of the first line of targeted therapy (ie, the ‘index date’) as compared with the 6 months before initiation of the first line of targeted therapy. Thus, we considered a neutral period’ of 3 months after the initiation of the specific molecule. The symptomatic treatments studied were NSAIDs, opioid analgesics (weak and strong), prednisone and corticosteroids injections. Hospitalisations (excluding scheduled hospitalisations, lasting <24 hours) included those (1) for all causes, (2) specifically in a rheumatology department and (3) for PsA relapse (defined as a hospitalisation with an ICD-10 for PsA as the main diagnosis). We assessed all sick leaves, excluding maternity and paternity leaves. Mood disorder treatments included antidepressants and anxiolytics.

The difference in consumption of symptomatic treatments and methotrexate before and after targeted therapy initiation was estimated for each patient. Specifically, we calculated the following. (1) The difference in Assessment of SpondyloArthritis international Society-NSAID (ASAS-NSAID) scores, which reflects overall NSAID consumption, considering the type of NSAID, the average daily dose and the proportion of days with intake over the period considered.24 We also report the proportion of patients achieving a 50% reduction in ASAS-NSAID Score after targeted therapy initiation and the proportion attaining an ASAS-NSAID Score≤10 after targeted therapy initiation among those with a score>10 before therapy initiation. (2) The difference between total doses of weak/strong opioid analgesics (calculated using the dosage of each tablet, number of tablets per box and number of boxes dispensed), after conversion of doses to an oral morphine equivalent.25 26 (3) The difference in total prednisone doses and average daily dose between the two periods. (4) The difference in total methotrexate doses and average weekly doses between the two periods (using similar methods as above). Additionally, we evaluated the time to methotrexate discontinuation after targeted therapy initiation among patients with previous methotrexate treatment. The period of methotrexate exposure was estimated with a methodology similar to that used for defining exposure to targeted therapies.

Similarly, we determined the difference in proportion of hospitalisations and sick leaves between the two periods and reported the most frequent causes of hospitalisation (after grouping ICD-10 codes for main diagnoses by specialty).

Covariates

We collected basic demographics, including age, sex, French Deprivation Index (a geographic indicator of social disadvantage specifically adapted for population health studies in France)17 and complementary universal health coverage. We identified inflammatory diseases associated with PsA (active skin psoriasis, defined by at least four deliveries of topical vitamin D derivatives or topical corticosteroids in the 2 years before the index date, and inflammatory bowel disease (IBD)) and variables used to calculate the Charlson Comorbidity Index.27 These covariates are defined in online supplemental table S1. Furthermore, we also collected data on treatments of interest other than targeted therapies (csDMARDs, NSAIDs or prednisone) at the index date and during the 2 years before the index date. The combination of an add-on therapy and a targeted therapy at baseline was defined as a 30-day period between reimbursements for the two treatments. Vital status was also recorded during follow-up.

Statistical analysis

Patient characteristics at baseline are described overall and for each targeted therapy class. Categorical variables are reported with frequencies and quantitative variables with mean and SD. Percentages before and after targeted therapy initiation were compared with the McNemar test and mean score/doses with a paired Student’s t-test for quantitative variables. Given the multiplicity of tests performed, we applied a Bonferroni correction for these analyses: p<0.008 (=0.05/6 corresponding to the five therapeutic classes plus the overall cohort) was considered significant. Kaplan-Meier survival curves were used to model the time to discontinuation of methotrexate in patients with previous treatment.

We then compared the effect of first-line bDMARDs (TNFi/IL17i/IL12/23i) on the possibility of discontinuing symptomatic treatment or methotrexate and limiting the number of hospitalisations or sick leaves by using logistic regression models adjusted for age, sex, active psoriasis, IBD and Charlson Comorbidity Index to estimate the adjusted OR (ORa) and 95% CIs. We did not include apremilast, given its different place in the recommendations as compared with other treatments, and JAKi, the most recent molecules introduced, with a limited number of patients in the cohort, in the subsequent analyses.2 We performed predefined subgroup analyses among patients with and without active psoriasis and among women and men. To assess the robustness of our results, we conducted the following sensitivity analyses: (1) modifying the ‘new user’ definition to include patients who had not filled a prescription for a targeted therapy for 5 years before the index date; (2) defining treatment discontinuation as >90 days without filling a prescription for the same treatment after the period covered by the previous prescription; and (3) extending the ‘neutral period’ to 6 months.

Results

Description of the cohort population

During the study period, we identified 15 889 patients initiating targeted therapy for PsA. After excluding 6096 patients who had not maintained treatment for at least 9 months, we finally included 9793 patients in the cohort (mean age 51±13 years, 47% men, 37% with active skin psoriasis): 8537 in the bDMARDs cohort, including 6107 (62%) initiating TNFi, 1408 (14%) IL17i, and 1022 (10%) IL12/23i, and 1256 in the tsDMARDs cohort including 99 (1%) initiating JAKi and 1157 (12%) PDE4i (table 1 and figure 1). Details by molecule are given in online supplemental table S2.

Figure 1 Flow chart of the patients included in the analysis. bDMARDs, biologic disease-modifying antirheumatic drugs; IL, interleukin; JAKi, Janus kinase inhibitor; PDE4i, phosphodiesterase-4 inhibitor; PsA, psoriatic arthritis; TNFi, tumour necrosis factor inhibitors; tsDMARDs, targeted synthetic disease-modifying antirheumatic drugs.

Table 1 Characteristics of the included patients

	Alln=9793	bDMARDs cohortn=8537 (87%)	tsDMARDs cohortn=1256 (13%)	
TNFin=6107(62%)	IL17in=1408(14%)	IL12/23in=1022(10%)	JAKin=99(1%)	PDE4in=1157(12%)	
Sociodemographic characteristics	
 Age, mean±SD	51.0±13.1	48.7±13.1	51.3±12.1	51.5±13.2	58.3±11.8	56.7±11.6	
 Men, n (%)	4592 (47%)	2841 (47%)	668 (47%)	478 (47%)	28 (29%)	577 (47%)	
 Deprivation index, n (%)      	9440 (96%)	5938 (97%)	1309 (93%)	959 (94%)	85 (86%)	1149 (99%)	
  First quantile (least disadvantaged)	708 (8%)	478 (8%)	83 (6%)	71 (7%)	4 (5%)	72 (6%)	
  Second quantile	2101 (22%)	1346 (23%)	281 (21%)	217 (23%)	21 (25%)	236 (20%)	
  Third quantile	2983 (32%)	1783 (30%)	447 (34%)	340 (35%)	39 (46%)	374 (32%)	
  Fourth quantile	3188 (34%)	2047 (34%)	426 (32%)	296 (31%)	18 (21%)	401 (35%)	
  Fifth quantile (most disadvantaged)	460 (5%)	284 (5%)	72 (5%)	35 (4%)	3 (3%)	66 (6%)	
  Not available	353 (4%)	169 (7%)	99 (7%)	63 (7%)	14 (7%)	8 (7%)	
 Complementary universal health coverage, n (%)	1286 (13%)	777 (13%)	235 (17%)	137 (13%)	9 (9%)	128 (11%)	
Associated inflammatory diseases (within 2 years), n (%)	
 Active psoriasis	3600 (37%)	1847 (30%)	638 (45%)	558 (55%)	14 (14%)	543 (47%)	
 Inflammatory bowel disease	522 (5%)	423 (7%)	12 (1%)	72 (7%)	5 (5%)	10 (1%)	
Charlson Comorbidity Index, n (%)	
 0 point (least comorbid)   	6068 (62%)	3836 (63%)	891 (63%)	627 (61%)	49 (50%)	665 (57%)	
 1–2 points	3144 (32%)	1969 (32%)	429 (30%)	326 (32%)	38 (38%)	382 (33%)	
 3–4 points	422 (4%)	223 (4%)	63 (5%)	46 (4%)	11 (11%)	79 (7%)	
 ≥5 points (more comorbid)	159 (2%)	79 (1%)	25 (2%)	23 (2%)	1 (1%)	31 (3%)	
Therapies within 2 years, n (%)	
 csDMARDs	7081 (72%)	4548 (74%)	929 (66%)	672 (66%)	75 (76%)	857 (74%)	
  Methotrexate	6485 (66%)	4168 (68%)	846 (60%)	628 (61%)	66 (67%)	777 (67%)	
 NSAIDs (on at least three occasions)	7146 (73%)	4703 (77%)	957 (68%)	639 (62%)	54 (54%)	793 (68%)	
 prednisone (on at least three occasions)	2796 (29%)	1940 (32%)	328 (23%)	232 (23%)	42 (42%)	254 (22%)	
Associated therapies at index date, n (%)	
 csDMARDs	4200 (43%)	2888 (47%)	481 (34%)	315 (31%)	51 (51%)	465 (40%)	
  Methotrexate	3653 (37%)	2533 (41%)	415 (29%)	279 (27%)	47 (47%)	379 (33%)	
 NSAIDs	3300 (34%)	2244 (37%)	431 (31%)	261 (25%)	18 (18%)	346 (30%)	
 Prednisone	1524 (16%)	1066 (17%)	184 (13%)	109 (11%)	29 (29%)	136 (12%)	
bDMARDbiologic disease-modifying antirheumatic drugcsDMARD, conventional synthetic disease-modifying antirheumatic drug; ILi, interleukin inhibitor; JAKi, Janus kinase inhibitor; NSAID, non-steroidal anti-inflammatory drug; PDE4i, phosphodiesterase-4 inhibitor; TNFi, tumour necrosis factor inhibitortsDMARDtargeted synthetic disease-modifying antirheumatic drug

At the time of targeted therapy initiation, 4200 (43%) patients had a coprescription of a csDMARD, and 3300 (34%) and 1524 (16%) had a coprescription of an NSAID or prednisone, respectively. Characteristics of the overall cohort and by therapeutic class are presented in table 1. The proportion of patients with active skin psoriasis was higher in the IL12/23i group (55%) than JAKi group (14%). Additionally, patients initiating a JAKi or PDE4i were older than those initiating a bDMARD (mean 58 and 57 vs 49–51 years) and had a higher prevalence of comorbidities (50% and 43% vs 37%–39% with Charlson Comorbidity Index≥1).

Use of associated treatments and healthcare resources before/after initiation of targeted therapy

After targeted therapy initiation, the proportion of users significantly decreased for NSAIDs (−15%; decrease in mean ASAS-NSAID Score among users: 25 vs 14, p<10−4), weak (−9%) and strong (−1%) opioid analgesics (p<10−4), prednisone (−9%; reduction in mean daily dose among users: 11 vs 5 mg/day, p<10−4), corticosteroids injections (−1%, p<10−3) and methotrexate (−15%; decrease in mean weekly dose among users=12 vs 9 mg, p<10−4) (table 2). However, we found variations in the magnitude of effect among therapeutic classes. The reduction in NSAID users after targeted therapy initiation ranged from −18% for TNFi to −6% for PDE4i new users, with a corresponding mean reduction in ASAS-NSAID Score of 50% and 13%, respectively (for detailed effects of targeted therapy initiation on ASAS-NSAID Score, see online supplemental table S3. Similarly, the reduction in opioid analgesic users varied: −11% for TNFi to −2% for PDE4i new users. Moreover, we found a more substantial decrease in prednisone consumption after TNFi initiation as compared with other therapeutic classes (other bDMARDs and tsDMARDs), both in number of users (−11% vs −4% for IL12/23i to −6% for IL17i) and average daily dose (−56% vs −29% to −47%, respectively). Conversely, methotrexate discontinuation and dose reduction among users were more frequent after the initiation of IL12/23i (−22%; mean dose reduction: 45%) than TNFi (−12% and −20%, respectively). The time to discontinuation of methotrexate after the initiation of each targeted therapy class is provided in online supplemental figure S1.

Table 2 Use of symptomatic treatments and methotrexate by targeted therapy initiation (before and after initiation)

	Alln=9793	TNFin=6107	IL17in=1408	IL12/23in=1022	JAKin=99	PDE4in=1157	
Before	After	Before	After	Before	After	Before	After	Before	After	Before	After	
Difference	Difference	Difference	Difference	Difference	Difference	
NSAIDs	
Users, n (%)	5251 (54%)	3818 (39%)	3490 (57%)	2383 (39%)	739 (52%)	563 (40%)	455 (45%)	383 (38%)	43 (43%)	31 (31%)	524 (45%)	458 (40%)	
−1433 (−15%***)	−1107 (−18%***)	−176 (−13%***)	−72 (−7%***)	−12 (−12%)	−66 (−6%***)	
Mean ASAS-NSAID Score (±SD)	24.5 (±29)	13.9 (±28)	26.6 (±30)	13.4 (±28)	23.0 (±30)	14.0 (±25)	18.2 (±27)	15.0 (±32)	16.8 (±23)	9.9 (±16)	19.0 (±26)	16.5 (±28)	
−10.6 (±1) (−43%***)	−13.2 (±2) (−50%***)	−9.0 (±5) (−39%**)	−3.2 (±5) (−40%**)	−6.9 (±7) (−41%)	−2.5 (±2) (−13%***)	
Opioid analgesics	
Users of opioid analgesics (weak or strong), n (%)	4180 (43%)	3310 (34%)	2698 (44%)	2009 (33%)	623 (44%)	490 (35%)	389 (38%)	359 (35%)	40 (40%)	45 (45%)	430 (37%)	407 (35%)	
−870 (−9%***)	−689 (−11%***)	−133 (−9%***)	−30 (−3%)	−5 (−5%)	−23 (−2%)	
Mean dose difference (±SD) (mg)	−215.4 (±289.6)***	−236.4 (±418.6)***	−339.6 (±444.2)	−102.9 (±476.3)	−463.2 (±566.6)	−6.6 (±178.8)	
Weak opioid analgesics	
Users, n (%)	3956 (40%)	3093 (32%)	2573 (42%)	1885 (31%)	585 (42%)	454 (32%)	354 (35%)	327 (32%)	36 (36%)	39 (39%)	408 (35%)	388 (34%)	
−863 (−9%***)	−688 (−11%***)	−131 (−9%***)	−27 (−3%)	+3 (+3%)	−20 (−2%)	
Mean dose difference (±SD) (mg)	−197.1 (±168.2)***	−253.2 (±60.4)***	−217.2 (±644.5)	+27.9 (±143.5)	−462.9 (±1082.9)	−13.2 (±121.1)	
Strong opioid analgesics	
Users, n (%)	520 (5%)	393 (4%)	333 (5%)	24 (3%)	80 (6%)	63 (5%)	53 (5%)	48 (5%)	9 (9%)	7 (7%)	45 (4%)	33 (3%)	
−127 (−1%***)	−309 (−2%***)	−17 (−1%)	−5 (−1%)	−2 (−2%)	−12 (−1%)	
Mean dose difference (±SD) (mg)	−204.1 (±779.1)	+62.1 (±1320.4)	−971.7 (±904.5)	−919.3 (±1260.8)	−116.7 (±832.4)	+61.8 (±858.3)	
Prednisone	
Users, n (%)	2303 (24%)	1444 (15%)	1609 (26%)	943 (15%)	291 (21%)	201 (14%)	170 (17%)	130 (13%)	45 (45%)	37 (37%)	188 (16%)	133 (12%)	
−859 (−9%***)	−666 (−11%***)	−90 (−6%***)	−40 (−4%***)	−8 (−5%)	−55 (−5%***)	
Mean dose difference (±SD) (mg)	−423.2 (±185.0***)	−484.8 (±219.2***)	−356.8 (±215.9***)	−207.9 (±44.5)	−366.6 (±7.3***)	−237.0 (±59.8***)	
Mean daily dose (±SD) (mg)	10.7 (±9.8)	5.1 (±8.0)	10.9 (±9.9)	4.7 (±7.5)	10.9 (±10.7)	5.8 (±8.2)	10.3 (±10.1)	7.3 (±10.2)	8.1 (±6.4)	4.8 (±5.5)	8.8 (±8.2)	5.2 (±8.9)	
−5.6 (±1.8) (−52%***)	−6.2 (±2.4) (−56%***)	−5.1 (±2.5) (−47%***)	−3.0 (±0.1) (−29%***)	−3.3 (±0.9) (−41%)	−3.6 (±0.7) (−41%***)	
Corticosteroids injections	
Users, n (%)	740 (8%)	659 (7%)	476 (8%)	371 (6%)	106 (8%)	106 (8%)	58 (6%)	67 (7%)	9 (9%)	8 (8%)	91 (8%)	107 (9%)	
−81 (−1%**)	−105 (−2%***)	0 (−0%)	+9 (+1%)	−1 (−1%)	+16 (+1%)	
Methotrexate	
Users, n (%)	4841 (49%)	3398 (35%)	3141 (51%)	2405 (39%)	641 (46%)	379 (27%)	455 (45%)	233 (23%)	62 (63%)	43 (43%)	542 (47%)	338 (29%)	
−1,443 (−15%***)	−736 (−12%***)	−262 (−19%***)	−222 (−22%***)	−19 (−19%***)	−204 (−18%***)	
Mean dose difference (±SD) (mg)	−80.3 (±30.1***)	−65.0 (±22.6***)	−114.1 (±34.8***)	−135.2 (±15.1***)	−91.9 (±83.7***)	−83.6 (±55.5***)	
Mean dose per week (±SD) (mg)	12.1 (±7.1)	9.0 (±8.3)	12.2 (±7.2)	9.7 (±8.0)	12.0 (±6.9)	7.6 (±8.2)	11.5 (±7.2)	6.3 (±7.8)	12.8 (±6.0)	9.3 (±9.2)	11.9 (±7.2)	8.8 (±9.3)	
−3.1 (±1.2) (−26%***)	−2.5 (±0.8) (−20%***)	−4.4 (±1.3) (−37%***)	−5.2 (±0.6) (−45%***)	−3.5 (±3.2) (−27%***)	−3.1 (±2.1) (−26%***)	
P values obtained with McNemar test for binary categorical variables and paired Student’s t-test for quantitative variables. Bonferroni correction applied: p<0.008 was considered significant.**p<10−3,***p<10−4.

ASASAssessment of SpondyloArthritis international SocietyILi, interleukin inhibitor; JAKi, Janus kinase inhibitor; NSAID, non-steroidal anti-inflammatory drug; PDE4i, phosphodiesterase-4 inhibitor; TNFi, tumour necrosis factor inhibitor

Additionally, we found a decrease in hospital admissions (−12%), sick leave (−4%) and users of mood disorder treatments (−2%) after targeted therapy initiation (table 3). Further details on hospitalisations specifically in rheumatology departments and related to PsA relapse are presented in online supplemental table S4.

Table 3 Care consumption (hospitalisations, stop working and consumption of treatments for mood disorders) by targeted therapy initiation (before and after initiation)

	Alln=9793	TNFin=6107	IL17in=1408	IL12/23in=1022	JAKin=99	PDE4in=1157	
Before	After	Before	After	Before	After	Before	After	Before	After	Before	After	
Difference	Difference	Difference	Difference	Difference	Difference	
Hospitalisations (all causes)	
n (%)	1856 (19%)	641 (7%)	1236 (20%)	347 (6%)	272 (19%)	96 (7%)	203 (20%)	92 (9%)	17 (17%)	9 (9%)	128 (11%)	97 (8%)	
−1215 (−12%***)	−889 (−14%***)	−176 (−12%)	−111 (−11%***)	−8 (−8%***)	−31 (−3%***)	
Mean number of hospitalisations (±SD)	1.1 (±0.8)	0.4 (±0,7)	1.1 (±0,7)	0.3 (±0,6)	1.1 (±0,8)	0.4 (±0,8)	0.9 (±0,8)	0.4 (±0,7)	0.9 (±0,6)	0.5 (±0,7)	0.9 (±0,9)	0.7 (±0,9)	
−0.7 (±0.1) (−63%***)	−0.8 (±0.1) (−72%***)	−0.7 (±0.0) (−64%***)	−0.5 (±0.1) (−55%***)	−0.4 (±0.1) (−44%***)	−0.2 (±0.1) (−22%***)	
Sick leaves	
n (%)	1950 (20%)	1577 (16%)	1313 (22%)	1068 (18%)	287 (20%)	217 (15%)	159 (16%)	132 (13%)	16 (16%)	13 (13%)	175 (15%)	147 (13%)	
−373 (−4%***)	−245 (−4%***)	−70 (−5%***)	−27 (−3%)	−3 (−3%)	−28 (−2%)	
Mean number of sick leaves (±SD)	6.9 (±7.2)	5.3 (±6.8)	7.3 (±7.4)	5.6 (±6.7)	7.0 (±7.2)	4.9 (±6.4)	5.3 (±6.5)	3.8 (±5.6)	7.5 (±7.8)	5.8 (±8.0)	5.9 (±6.7)	5.1 (±6.6)	
−1.6 (±0.4) (−23%***)	−1.7 (±0.7) (−23%***)	−2.1 (±0.8) (−30%***)	−1.5 (±0.9) (−28%***)	−1.7 (±0.2) (−23%)	−0.8 (±0.1) (−14%)	
Use of mood disorder treatments	
Use of mood disorder treatments, n (%)	445 (5%)	298 (3%)	294 (5%)	187 (3%)	51 (4%)	46 (3%)	68 (7%)	36 (3%)	1 (1%)	7 (7%)	37 (3%)	23 (2%)	
−147 (−2%***)	−107 (−2%***)	−5 (−1%)	−32 (−4%***)	+6 (−6%)	−14 (−1%)	
Users of antidepressants, n (%)	426 (4%)	291 (3%)	275 (4%)	181 (3%)	49 (4%)	44 (3%)	65 (6%)	36 (3%)	1 (1%)	7 (7%)	36 (3%)	23 (2%)	
−135 (−1%***)	−94 (−1%***)	−5 (−1%)	−29 (−3%***)	+6 (+6%)	−13 (−1%)	
Users of other mood disorder treatments, n (%)	25 (0%)	8 (0%)	19 (0%)	6 (0%)	2 (0%)	2 (0%)	3 (0.3)	0 (0.0)	0 (0%)	0 (0%)	1 (0%)	0(0%)	
−15 (−0%)	−13 (−0%)	0 (0%)	−3 (−0%)	0 (0%)	−1 (−0%)	
pP -values obtained with McNemar test for binary categorical variables and paired Student’s t -test for quantitative variables. Bonferroni correction applied: pp<0.008 was considered significant. **p<10−3,***p<10−4.

ILi, interleukin inhibitor; JAKi, Janus kinase inhibitor; PDE4i, phosphodiesterase-4 inhibitorTNFi, tumour necrosis factor inhibitor

Possibility of discontinuing symptomatic treatment/methotrexate and limiting the number of hospitalisations/sick leaves by bDMARD class initiation

The sparing effect of NSAIDs and prednisone was slightly more pronounced after the initiation of TNFi than IL17i (ORa=1.04, 95% CI=1.01 to 1.07 and 1.04, 1.02 to 1.06) and IL12/23i (1.07, 1.04 to 1.10; 1.06, 1.04 to 1.09) (table 4). Conversely, the odds of methotrexate discontinuation were reduced after the initiation of TNFi versus IL17i (0.96, 0.94 to 0.98) and IL12/23i (0.94, 0.92 to 0.97). The odds of discontinuation of weak opioid analgesics were marginally increased after the initiation of TNFi (1.07, 1.04 to 1.10) and IL17i (1.05, 1.02 to 1.09) versus IL12/23i. We found no statistically significant differences in other outcomes after initiation of IL17i versus IL12/23i, except for discontinuation of mood disorder treatments, which was slightly less frequent with IL17i (0.97, 0.96 to 0.99).

Table 4 Odds of discontinuing symptomatic treatments, methotrexate and mood disorder treatments and limiting the number of hospitalisations and sick leaves after initiation of a biologic disease-modifying antirheumatic drug

	TNFi versus IL17i	TNFi versus IL12/23i	IL17i versus IL12/23i	
ORc (95% CI)	ORa* (95% CI)	ORc (95% CI)	ORa* (95% CI)	ORc (95% CI)	ORa* (95% CI)	
NSAID	1.04 (1.01 to 1.07)	1.04 (1.01 to 1.07)	1.09 (1.05 to 1.11)	1.07 (1.04 to 1.10)	1.05 (1.02 to 1.09)	1.03 (1.00 to 1.07)	
Weak opioid analgesics	1.03 (1.01 to 1.05)	1.02 (1.00 to 1.04)	1.07 (1.04 to 1.10)	1.07 (1.04 to 1.10)	1.05 (1.02 to 1.09)	1.05 (1.02 to 1.09)	
Strong opioid analgesics	1.00 (0.99 to 1.01)	1.00 (0.99 to 1.01)	1.01 (1 to 1.02)	1.01 (1.00 to 1.02)	1.01 (1.00 to 1.02)	1.01 (0.99 to 1.02)	
Prednisone	1.04 (1.02 to 1.06)	1.04 (1.02 to 1.06)	1.07 (1.05 to 1.10)	1.06 (1.04 to 1.09)	1.03 (1.00 to 1.06)	1.03 (1.00 to 1.06)	
Methotrexate	0.95 (0.93 to 0.97)	0.96 (0.94 to 0.98)	0.92 (0.90 to 0.95)	0.94 (0.92 to 0.97)	0.97 (0.94 to 1.00)	0.97 (0.94 to 1.00)	
Hospitalisations	1.02 (1.00 to 1.04)	1.01 (0.99 to 1.03)	1.02 (0.99 to 1.05)	1.02 (0.99 to 1.05)	1.00 (0.97 to 1.03)	1.01 (0.98 to 1.04)	
Sick leave	0.99 (0.98 to 1.02)	0.99 (0.97 to 1.01)	1.01 (0.99 to 1.03)	1.01 (0.98 to 1.02)	1.01 (0.99 to 1.03)	1.01 (0.99 to 1.03)	
Use of mood disorder treatments	1.01 (1.00 to 1.02)	1.01 (0.99 to 1.02)	0.98 (0.97 to 0.99)	0.98 (0.97 to 0.99)	0.97 (0.96 to 0.99)	0.97 (0.96 to 0.99)	
* Multivariate logistic regression with adjustment for sex, age, active psoriasis, inflammatory bowel disease and Charlson Comorbidity Index.

ILi, interleukin inhibitor; NSAID, non-steroidal anti-inflammatory drugORa, adjusted OR; ORc, crude OR; TNFi, tumour necrosis factor inhibitor

Increasing age was significantly associated with a reduction in use of associated treatments. Further factors associated with the discontinuation of each coprescription are presented in online supplemental table S5. Subgroup analyses of patients with and without psoriasis (online supplemental table S6) and women and men (online supplemental table S7) yielded results similar to those of the main analysis. Sensitivity analyses supported the robustness of our findings (online supplemental table S8).

Discussion

In this nationwide study involving 9793 new users of targeted therapies for PsA, we investigated the impact of each therapeutic class on the use of symptomatic treatments, methotrexate and mood disorder treatments as well as the need for hospitalisation or sick leave. After the introduction of targeted therapy, we found a significant overall decrease in the use of NSAIDs, opioid analgesics, corticosteroids, methotrexate and mood disorder treatments as well as hospitalisations and sick leaves. However, the magnitude of these effects varied among certain therapeutic classes. The odds of discontinuation of NSAIDs and prednisone were slightly increased with TNFi versus IL17i or IL12/23i initiation. Conversely, the odds of methotrexate discontinuation were increased with ILi versus TNFi initiation. Finally, reduction in the use of associated treatments was more pronounced with advancing age.

Our study is important because it is the first to investigate the sparing effect of the different classes of targeted therapies specifically in PsA. Previous research has predominantly focused on demonstrating the effect of TNFi on NSAIDs consumption in axial spondyloarthritis (axSpA). Consistent with our findings, NSAID consumption was reduced with TNFi treatment in both dedicated clinical trials and analyses of axSpA cohorts.14 28 29 Of note, the baseline ASAS-NSAID Score was higher in these studies (median 55 in the DESIR (DEvenir des Spondylarthropathies Indifférenciées Récentes) cohort; mean 98 in the SPARSE trial (NSAIDs sparing effect of etanercept in axial spondyloarthritis)) than in our study (mean 27). This difference can be attributed in part to disparities in study populations (studies of axSpA populations, involving younger patients with a known propensity for increased NSAID consumption).30 However, our results remained consistent with previously documented trends, such as the 50% reduction in ASAS-NSAID Score observed in 57%–67% of patients receiving TNFi (69% in our study) and the achievement of an NSAID Score≤10 observed in 46%–58% of cases (62% in our study). These effects have also been reported from studies of secukinumab, an IL17i, and IL12/23i in axSpA.31 32

Targeted therapies used in PsA also demonstrated a significant sparing effect on other treatments, including analgesics, corticosteroids and methotrexate. Of note, the introduction of targeted therapies led to a substantial reduction in corticosteroids use, with an average decrease of 6 mg/day over 6 months post initiation. Furthermore, hospital admissions and sick leaves declined in general after targeted therapy initiation. Although the extent of the reduction varies across studies (in particular because of differences in study populations and assessment time points) and treatment modalities, our findings align with those from other studies of chronic inflammatory diseases3336 and agree with those observed in daily practice. As expected, the maintenance of methotrexate in association with TNFi was more prevalent and continued over a longer duration than with the other molecules, which reflects common practice in rheumatology aimed at preventing the development of antidrug antibodies particularly against infliximab and adalimumab.37 In addition, it is important to note that tofacitinib, unlike upadacitinib (both JAKi), requires coprescription with methotrexate as part of its European marketing authorisation. This requirement may affect the proportion of patients using methotrexate at initiation of treatment and the number of patients discontinuing it after starting tofacitinib. These sparing effects hold significant promise, both from the perspective of the patient and society because they offer the prospect of enhanced tolerance, with fewer adverse events, and a potential long-term reduction in healthcare costs.

TNFi had a slightly higher sparing effect in PsA than other classes of biologics, particularly concerning the use of NSAIDs and prednisone, with no difference between ILi agents. Although direct comparisons between molecules are lacking, the literature suggests that, in line with our results, sparing effects may be slightly less pronounced with other therapies than with TNFi.31 32 36 Of note, IL17i seemed to facilitate more frequent discontinuation of weak opioid analgesics as compared with IL12/23i.38 Neutralisation of IL17 may lead to a reduction in hyperalgesia and somatic signs induced by opioids discontinuation. Although several studies suggest a pivotal role for TNF and IL agents in the pathogenesis and treatment of depression, we noted a significant reduction in the use of mood disorder treatments in our study within 6 months of targeted therapy initiation.39 This effect seemed more pronounced with IL12/23i agents and among patients with active skin psoriasis, as shown in some studies,4042 which supports the hypothesis of a major psychological impact of psoriasis in certain patients with PsA. However, it should be borne in mind that the overall magnitude of the effect of biologics on some studied outcomes, such as the treatment of mood disorders (reduction of around 2%), remains limited during this 6 month observation period and would require longer-term observation. Additionally, age seemed to play a role in the discontinuation of coprescribed drugs. This finding could be attributed to a heightened concern regarding adverse events associated with these prescriptions in older patients, for whom targeted therapies have been found to have comparable efficacy and safety profiles as in a younger population in PsA.43 44

The limitations of this study include the lack of availability of certain data, particularly concerning disease activity/severity and phenotype. Although we used ‘proxies’, such as therapies of interest for PsA in the 2 years preceding the index date, to approximate these parameters and reduce confounding bias, some residual bias may still remain. Moreover, because of the different profiles of treated patients, especially between bDMARDs and tsDMARDs, and the low number of patients exposed to certain first-line therapeutic classes (especially JAKi), direct comparison of the effect of these targeted therapies on healthcare consumption must be considered with caution. However, we adjusted our analyses for several confounders to accurately estimate the differential impact of bDMARD classes. We defined drug exposure based on healthcare reimbursement data, which are not necessarily equivalent to days of use, and the drugs within each class were not separated on analysis. The definition of PsA population was based on either ICD-10 diagnostic codes for PsA (M07 except M07.4 and M07.5, which correspond to arthropathy in Crohn’s disease and ulcerative colitis, respectively) applied to in-patients or out-patients with fully reimbursed PsA-related care procedures.23 We did not exclude patients with ICD-10 code M07.6. However, within the total population included, we found only 6 (<0.1%) patients identified solely via an ICD-10 code M07.6. As this study was based on real-life data, variations in sample size across different treatment groups were to be expected. Indeed, due to the greater use experience, the majority of patients initiate a TNFi. Although unequal sample sizes may affect statistical power and precision under certain conditions (smaller groups may reduce power, and larger groups may dominate comparative analyses), the use of logistic regressions to compare effects of biologics generally allows these imbalances to be managed effectively. Moreover, this risk is considerably reduced when sample sizes exceed 500, which was the case in our study where the smallest group (IL12/23i) included 1022 patients.45 46 Finally, the sparing effect emphasised in this study was demonstrated only in the short-term/medium-term, and its long-term validity still requires confirmation. Previous findings indicated a moderate persistence of first-line targeted therapies, decreasing from 73% at 1 year to 36% at 3 years, which raises concerns about a possible reduction in effect over time.47 Nevertheless, even in the short-term/medium-term, the effect remains of significant interest both for the patient and society.

This study has several strengths. Our cohort included a large number of patients in real world settings from a national exhaustive database providing health insurance data with a quality and consistency plan ensuring homogeneous data processing.16 This framework minimises selection bias. To mitigate channelling bias (ie, a result of confusion in assessing certain treatments in specific subgroups) and confounding by indication bias, we focused exclusively our analyses on patients who were naïve to targeted therapy. It is important to note that the targeted therapies studied are all recommended treatments for moderate-to-severe PsA, and that in France, each physician is free to choose the treatment labelled for PsA.3 Except in a minority of cases where an extramusculoskeletal manifestation (very active psoriasis, IBD, severe or repeated acute anterior uveitis) guides the prescriber’s choice, no factor is today likely to influence this prescription at the population level. In addition, outcomes were based on prospectively collected data, thus eliminating the risk of information bias, and involved standardised and validated tools such as the ASAS-NSAID Score, developed to evaluate the magnitude of NSAID intake and the NSAID-sparing effect of treatments. At last, to test the robustness of the results, we performed sensitivity analyses, which supported the integrity of our findings.

Conclusion

First-line targeted therapy for PsA resulted in a significant sparing effect for symptomatic treatments and methotrexate, leading to reductions in both the prevalence of users and the mean dosage, along with decreased rates of hospitalisations and sick leave. This effect seemed slightly more pronounced with TNFi than IL17i and IL12/23i, except for methotrexate, with odds of discontinuation greater with ILi agents. These findings highlight the potential for optimising PsA treatment strategies, suggesting that targeted therapies also reduce the burden of associated treatments and healthcare utilisation, which can be particularly of interest given the potential for side effects and cost overruns.

supplementary material

10.1136/rmdopen-2024-004631 online supplemental file 1

Acknowledgements

We thank Mrs. Laura Smales for English editing.

Data availability statement

Data are available on reasonable request.

Funding: The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Provenance and peer review: Not commissioned; externally peer reviewed.

Patient consent for publication: Not applicable.

Data availability free text: All relevant data are reported in the article. Additional details can be provided by the corresponding author on reasonable request.

Ethics approval: Specific approval was obtained to conduct this study from the French data protection agency (Commission nationale de l’informatique et des libertés: MLD/MFI/AR2010413), and patients were collectively informed about the use of pseudonymised data.

Patient and public involvement statement: Patients or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
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References

1 Gudu T Kiltz U de Wit M et al Mapping the effect of psoriatic arthritis using the international classification of functioning, disability and health J Rheumatol 2017 44 193 200 10.3899/jrheum.160180 27980011
2 Gossec L Kerschbaumer A Ferreira RJO et al EULAR recommendations for the management of psoriatic arthritis with pharmacological therapies: 2023 update Ann Rheum Dis 2024 83 706 19 10.1136/ard-2024-225531 38499325
3 Wendling D Hecquet S Fogel O et al 2022 French society for rheumatology (SFR) recommendations on the everyday management of patients with spondyloarthritis, including psoriatic arthritis Joint Bone Spine 2022 89 105344 10.1016/j.jbspin.2022.105344 35038574
4 Coates LC Soriano ER Corp N et al Group for research and assessment of psoriasis and psoriatic arthritis (GRAPPA): updated treatment recommendations for psoriatic arthritis 2021 Nat Rev Rheumatol 2022 18 465 79 10.1038/s41584-022-00798-0 35761070
5 Singh JA Guyatt G Ogdie A et al Special article: 2018 American college of rheumatology/national psoriasis foundation guideline for the treatment of psoriatic arthritis Arthritis Rheumatol 2019 71 5 32 10.1002/art.40726 30499246
6 Burgos-Pol R Martínez-Sesmero JM Ventura-Cerdá JM et al The cost of psoriasis and psoriatic arthritis in 5 European countries: a systematic review Actas Dermosifiliogr 2016 107 577 90 10.1016/j.ad.2016.04.018 27316590
7 Fine M Quantifying the impact of NSAID-associated adverse events Am J Manag Care 2013 19 s267 72 24494609
8 National Agency for the Safety of Medicines and Health Products (ANSM) Acetaminophen and non-steroidal anti-inflammatory drugs (nsaids) 2019 Available https://ansm.sante.fr/actualites/bon-usage-du-paracetamol-et-des-anti-inflammatoires-non-steroidiens-ains-ces-medicaments-ne-pourront-plus-etre-presentes-en-libre-acces#:~:text=Afin%20de%20favoriser%20le%20bon,souhaitent%20en%20disposer%20sans%20ordonnance
9 Ramiro S Nikiphorou E Sepriano A et al ASAS-EULAR recommendations for the management of axial spondyloarthritis: 2022 update Ann Rheum Dis 2023 82 19 34 10.1136/ard-2022-223296 36270658
10 Vincken NLA Balak DMW Knulst AC et al Systemic glucocorticoid use and the occurrence of flares in psoriatic arthritis and psoriasis: a systematic review Rheumatol (Oxford) 2022 61 4232 44 10.1093/rheumatology/keac129
11 Dowell D Haegerich TM Chou R CDC guideline for prescribing opioids for chronic pain--United States, 2016 JAMA 2016 315 1624 45 10.1001/jama.2016.1464 26977696
12 Mercadante S Arcuri E Santoni A Opioid-induced tolerance and hyperalgesia CNS Drugs 2019 33 943 55 10.1007/s40263-019-00660-0 31578704
13 Baldo BA Toxicities of opioid analgesics: respiratory depression, histamine release, hemodynamic changes, hypersensitivity, serotonin toxicity Arch Toxicol 2021 95 2627 42 10.1007/s00204-021-03068-2 33974096
14 Carbo MJG Spoorenberg A Maas F et al Ankylosing spondylitis disease activity score is related to NSAID use, especially in patients treated with TNF-α inhibitors PLoS One 2018 13 e0196281 10.1371/journal.pone.0196281 29689112
15 Momohara S Inoue E Ikari K et al Decrease in orthopaedic operations, including total joint replacements, in patients with rheumatoid arthritis between 2001 and 2007: data from Japanese outpatients in a single institute-based large observational cohort (IORRA) Ann Rheum Dis 2010 69 312 3 10.1136/ard.2009.107599 20007622
16 Tuppin P Rudant J Constantinou P et al Value of a national administrative database to guide public decisions: From the système 18 national d’information interrégimes de l’Assurance Maladie (SNIIRAM) to the système national des données de santé (SNDS) in France. Rev Epidemiol Sante Publique 2017 65 S149 67 10.1016/j.respe.2017.05.004 28756037
17 Rey G Jougla E Fouillet A et al Ecological association between a deprivation index and mortality in France over the period 1997 - 2001: variations with spatial scale, degree of urbanicity, age, gender and cause of death BMC Public Health 2009 9 33 10.1186/1471-2458-9-33 19161613
18 Moulis G Lapeyre-Mestre M Palmaro A et al French health insurance databases: what interest for medical research? Rev Med Interne 2015 36 411 7 10.1016/j.revmed.2014.11.009 25547954
19 Jabagi M-J Bertrand M Botton J et al Stroke, myocardial infarction, and pulmonary embolism after bivalent booster N Engl J Med 2023 388 1431 2 10.1056/NEJMc2302134 36988584
20 Hoisnard L Pina Vegas L Dray-Spira R et al Risk of major adverse cardiovascular and venous thromboembolism events in patients with rheumatoid arthritis exposed to JAK inhibitors versus adalimumab: a nationwide cohort study Ann Rheum Dis 2023 82 182 8 10.1136/ard-2022-222824 36198438
21 Roland N Baricault B Weill A et al Association between doses of levonorgestrel intrauterine systems and subsequent use of psychotropic drugs in France JAMA 2023 329 257 9 10.1001/jama.2022.21471 36548007
22 Pina Vegas L Penso L Sbidian E et al Influence of sex on the persistence of different classes of targeted therapies for psoriatic arthritis: a cohort study of 14 778 patients from the French health insurance database (SNDS) RMD Open 2023 9 e003570 10.1136/rmdopen-2023-003570 38114199
23 Pina Vegas L Sbidian E Penso L et al Epidemiologic study of patients with psoriatic arthritis in a real-world analysis: a cohort study of the French health insurance database Rheumatol (Oxford) 2021 60 1243 51 10.1093/rheumatology/keaa448
24 Dougados M Paternotte S Braun J et al ASAS recommendations for collecting, analysing and reporting NSAID intake in clinical trials/epidemiological studies in axial spondyloarthritis Ann Rheum Dis 2011 70 249 51 10.1136/ard.2010.133488 20829199
25 Webster LR Fine PG Review and critique of opioid rotation practices and associated risks of toxicity Pain Med 2012 13 562 70 10.1111/j.1526-4637.2012.01357.x 22458884
26 Faculty of Pain Medicine Dose equivalents and changing opioids 2020 Available https://fpm.ac.uk/opioids-aware-structured-approach-opioid-prescribing/dose-equivalents-and-changing-opioids
27 Bannay A Chaignot C Blotière P-O et al The best use of the charlson comorbidity index with electronic health care database to predict mortality Med Care 2016 54 188 94 10.1097/MLR.0000000000000471 26683778
28 Dougados M Wood E Combe B et al Evaluation of the nonsteroidal anti-inflammatory drug-sparing effect of etanercept in axial spondyloarthritis: results of the multicenter, randomized, double-blind, placebo-controlled SPARSE study Arthritis Res Ther 2014 16 481 10.1186/s13075-014-0481-5 25428762
29 Moltó A Granger B Wendling D et al Brief report: nonsteroidal antiinflammatory drug-sparing effect of tumor necrosis factor inhibitors in early axial spondyloarthritis: results from the DESIR cohort Arthritis Rheumatol 2015 67 2363 8 10.1002/art.39208 26109532
30 Ciurea A Götschi A Kissling S et al Characterisation of patients with axial psoriatic arthritis and patients with axial spondyloarthritis and concomitant psoriasis in the SCQM registry RMD Open 2023 9 e002956 10.1136/rmdopen-2022-002956 37277211
31 Dougados M Kiltz U Kivitz A et al Nonsteroidal anti-inflammatory drug-sparing effect of secukinumab in patients with radiographic axial spondyloarthritis: 4-year results from the measure 2, 3 and 4 phase III trials Rheumatol Int 2022 42 205 13 10.1007/s00296-021-05044-6 34773130
32 Poddubnyy D Hermann K-GA Callhoff J et al Ustekinumab for the treatment of patients with active ankylosing spondylitis: results of a 28-week, prospective, open-label, proof-of-concept study (TOPAS) Ann Rheum Dis 2014 73 817 23 10.1136/annrheumdis-2013-204248 24389297
33 Seror R Dougados M Gossec L Glucocorticoid sparing effect of tumour necrosis factor alpha inhibitors in rheumatoid arthritis in real life practice Clin Exp Rheumatol 2009 27 807 13 19917164
34 Khraishi M Millson B Woolcott J et al Reduction in the utilization of prednisone or methotrexate in Canadian claims data following initiation of etanercept in pediatric patients with juvenile idiopathic arthritis Pediatr Rheumatol Online J 2019 17 64 10.1186/s12969-019-0358-x 31500631
35 Shimizu Y Tanaka E Inoue E et al Reduction of methotrexate and glucocorticoids use after the introduction of biological disease-modifying anti-rheumatic drugs in patients with rheumatoid arthritis in daily practice based on the IORRA cohort Mod Rheumatol 2018 28 461 7 10.1080/14397595.2017.1369926 28880684
36 Galíndez-Agirregoikoa E Prieto-Peña D Martín-Varillas JL et al Treatment with tofacitinib in refractory psoriatic arthritis: a national multicenter study of the first 87 patients in clinical practice J Rheumatol 2021 48 1552 8 10.3899/jrheum.201204 33795330
37 Pizano-Martinez O Mendieta-Condado E Vázquez-Del Mercado M et al Anti-drug antibodies in the biological therapy of autoimmune rheumatic diseases J Clin Med 2023 12 3271 10.3390/jcm12093271 37176711
38 Inan S Meissler JJ Bessho S et al Blocking IL-17A prevents oxycodone-induced depression-like effects and elevation of IL-6 levels in the ventral tegmental area and reduces oxycodone-derived physical dependence in rats Brain Behav Immun 2024 117 100 11 10.1016/j.bbi.2024.01.001 38199516
39 Rani T Behl T Sharma N et al Exploring the role of biologics in depression Cell Signal 2022 98 110409 10.1016/j.cellsig.2022.110409 35843573
40 Langley RG Feldman SR Han C et al Ustekinumab significantly improves symptoms of anxiety, depression, and skin-related quality of life in patients with moderate-to-severe psoriasis: results from a randomized, double-blind, placebo-controlled phase III trial J Am Acad Dermatol 2010 63 457 65 10.1016/j.jaad.2009.09.014 20462664
41 Gordon KB Armstrong AW Han C et al Anxiety and depression in patients with moderate‐to‐severe psoriasis and comparison of change from baseline after treatment with guselkumab vs. adalimumab: results from the phase 3 VOYAGE 2 study Acad Dermatol Venereol 2018 32 1940 9 10.1111/jdv.15012
42 Timis T-L Beni L Mocan T et al Biologic therapies decrease disease severity and improve depression and anxiety symptoms in psoriasis patients Life (Basel) 2023 13 1219 10.3390/life13051219 37240864
43 Costa L Lubrano E Ramonda R et al Elderly psoriatic arthritis patients on TNF-α blockers: results of an Italian multicenter study on minimal disease activity and drug discontinuation rate Clin Rheumatol 2017 36 1797 802 10.1007/s10067-017-3697-3 28589323
44 Queiro R Pardo E Charca L et al Analysis by age group of disease outcomes in patients with psoriatic arthritis: a cross-sectional multicentre study Drugs Aging 2020 37 99 104 10.1007/s40266-019-00724-2 31745833
45 Nemes S Jonasson JM Genell A et al Bias in odds ratios by logistic regression modelling and sample size BMC Med Res Methodol 2009 9 56 10.1186/1471-2288-9-56 19635144
46 Herrera AN Gómez J Influence of equal or unequal comparison group sample sizes on the detection of differential item functioning using the mantel–haenszel and logistic regression techniques Qual Quant 2008 42 739 55 10.1007/s11135-006-9065-z
47 Pina Vegas L Penso L Claudepierre P et al Long-term persistence of first-line biologics for patients with psoriasis and psoriatic arthritis in the French health insurance database JAMA Dermatol 2022 158 513 22 10.1001/jamadermatol.2022.0364 35319735
