{"paper_id":"bef9dab6-6072-4ff2-b868-553748b8516c","body_text":"RESEARCH Open Access\n© The Author(s) 2025. Open Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, \nsharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and \nthe source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this \narticle are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included \nin the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will \nneed to obtain permission directly from the copyright holder. To view a copy of this licence, visit  h t t p  : / /  c r e a  t i  v e c  o m m  o n s .  o r  g / l i c e n s e s / b y / 4 . 0 /.\nLindner et al. Arthritis Research & Therapy          (2025) 27:188 \nhttps://doi.org/10.1186/s13075-025-03650-4\nArthritis Research & Therapy\n*Correspondence:\nLisa Lindner\nlisa.lindner@drfz.de\nFull list of author information is available at the end of the article\nAbstract\nBackground In psoriatic arthritis (PsA), growing evidence indicates sex-specific differences regarding clinical \nmanifestation and treatment outcomes. Research has highlighted that females may be less likely to achieve treatment \ntargets and are more prone to discontinuing therapy, though data on sex-specific adverse events is limited. This \nanalysis investigates sex differences in treatment outcomes, persistence, discontinuation reasons, and adverse events \nduring first-line b/tsDMARD therapy.\nMethods In this analysis bionaïve patients with PsA from the RABBIT-SpA register were included at the start of their \nfirst b/tsDMARD. Therapy persistence was estimated using the Cox-regression adjusted for age. Descriptive analyses \nwere used to examine and compare sex–specific differences on reasons for therapy discontinuation.\nResults A total of 457 female patients and 343 male patients were included. Females exhibited more severe joint \ninvolvement and poorer patient-reported parameters, such as higher disease activity, more pain, and greater \nfunctional limitations. In contrast, males showed more pronounced skin involvement and a higher prevalence of \nnail psoriasis. Females had lower treatment persistence rates, both in the overall analysis of all first-line b/tsDMARDs \nand in subgroup analyses restricted to TNFi and IL17i therapies. At 12 months, 52% of females and 68% of males \nremained on their initial b/tsDMARD therapy. Notable sex differences were also observed in the reasons for therapy \ndiscontinuation: males more frequently discontinued due to lack of efficacy or remission, while females more often \nstopped treatment due to adverse events. Our safety analysis indicated that although female patients experienced a \ngreater number of overall adverse events, males reported serious adverse events at twice the rate.\nConclusions Our findings underscore the need for sex-specific treatment strategies and more comprehensive \nresearch into biological and sociocultural factors influencing therapy persistence and reasons for discontinuation \nin real-world settings. Tailored treatment strategies are needed with regard to biologic therapy to overcome worse \ntherapeutic outcomes in female patients with PsA.\nReal-world sex differences in treatment \npersistence and reasons for discontinuation \nin psoriatic arthritis patients: results from the \nGerman RABBIT-SpA register\nLisa Lindner1* , Anja Weiß1 , Andreas Reich1 , Christine Baumann2, Frank Behrens3 , Xenofon Baraliakos4  and \nAnne C. Regierer1\n\nPage 2 of 11\nLindner et al. Arthritis Research & Therapy           (2025) 27:188 \nBackground\nPsoriatic-Arthritis (PsA) is a chronic inflammatory dis -\nease that not only affects the joints but can also affect the \nskin, and entheses, with overall prevalence considered \nrelatively equal between females and males [ 1]. However, \nseveral factors including hormonal influences, environ -\nmental and sociocultural factors, and genetic predisposi -\ntions contribute to differences in disease expression and \nprogression between the sexes [2].\nStudies on PsA patients have shown sex-specific dif -\nferences regarding clinical manifestation, disease impact \nand therapy response [ 3, 4]. Males typically have more \naxial and oligoarticular involvement, along with more \nsevere skin manifestations and rapid radiographic dam -\nage. Females, on the other hand, are more likely to have \npolyarticular involvement, enthesitis and a higher disease \nburden including more functional limitations [5, 6].\nInitial treatment of PsA includes conventional synthetic \ndisease-modifying anti-rheumatic drugs (csDMARDs), \nwhile biologic and targeted synthetic DMARDs (b/tsD -\nMARDs) such as tumor necrosis factor inhibitors (TNFi) \nand Interleukin-17 inhibitors (IL17i) are considered \nfor patients who do not respond adequately to first-line \noptions. The primary treatment objective is to achieve \nremission or at least minimal disease activity (MDA), \naiming to prevent further joint damage and enhance \npatients’ overall well-being. The current EULAR (Euro -\npean Alliance of Associations for Rheumatology) recom -\nmendations stress the importance of a tailored treatment \nstrategy, taking into account individual patients’ needs, \ncomorbidities and preferences. To optimize individual -\nized therapy, it is essential to recognize the influence of \nsex on these factors. Accordingly, research on the effect \nof sex on treatment choices, treatment efficacy, and treat-\nment maintenance was prioritized in the recommenda -\ntions for future research in PsA [7].\nCurrent studies suggest that male sex may have a favor-\nable impact on therapy persistence and outcome, with \nfemales less likely to achieve MDA [ 7– 9]. Reasons for \nthis disparity are multifaceted and may involve a combi -\nnation of hormonal, biological, disease presentation and \ntreatment-related factors. The specific mechanisms and \nreasons remain unclear.\nThe most common reasons for early therapy discon -\ntinuation in longitudinal observational studies include \nremission, lack of efficacy, and serious and non-serious \nadverse events (SAEs and AE) [ 10, 11]. However, a nota -\nble gap exists in sex-stratified data, particularly concern -\ning adverse events during first-line b/tsDMARD therapy. \nAlthough some randomized trials have provided sex-\nstratified data on AEs [ 12], comprehensive observational \nstudies with sex stratification remain limited.\nThe objectives of our analyses were to examine sex-\nspecific differences in clinical parameters and first-line \ntherapy persistence, as well as reasons for discontinua -\ntion. Additionally, we provide sex-stratified data on fre -\nquencies of SAEs and AEs occurring during the first-line \nb/tsDMARD therapy and leading to discontinuation.\nPatients and methods\nData source\nThe RABBIT-SpA register is a German longitudinal \nobservational cohort study focused on monitoring and \nevaluating the safety and effectiveness of b/tsDMARDs in \npatients with PsA in a real-world setting. Patients can be \nincluded by a rheumatologist with the start of a new b/\ntsDMARD or with a conventional systemic treatment e.g. \ncsDMARD or NSAID (nonsteroidal anti-inflammatory \ndrugs) [ 13]. Physicians and patients enter data using a \nweb-based documentation system. Clinical and patient-\nreported data is collected through an electronic case \nreport form (eCRF) at baseline, at three and six months \npost-enrolment, and subsequently at six-month intervals \nfor a follow-up period of up to ten years [14].\nPatients\nAll PsA patients enrolled between October 2017 and \ndatabase closure in March 2024 were included. For these \nanalyses, only b/tsDMARD-naïve patients with PsA who \ninitiated their first-line b/tsDMARD and who have a fol -\nlow-up time of at least one year were selected (Supple -\nmentary Figure S1).\nIn our register, sex was reported as “female” , “male” , or \n“other” . Since no patient’s sex was reported as “other” , this \nstudy only refers to female and male patients.\nWhile the distinction between sex and gender is well \nestablished in the social sciences, it remains a complex \nand evolving issue in medical research [ 15]. In this study, \nwe use the term sex acknowledging that both biological \nand sociocultural factors may influence treatment out -\ncomes, although the documentation of these variables \nmay vary across study sites and may not consistently \nreflect this distinction.\nStatistical analyses and variables\nDefinition of variables\nCharacteristics at the beginning of first-line therapy \nof female and male participants were compared using \nClinical trial number Not applicable.\nKeywords Observational study, Psoriatic arthritis, Gender, Sex, Women, Men, First-line therapy, bDMARD, tsDMARD, \nBiologics, Therapy outcome, Patient-reported outcome\n\nPage 3 of 11\nLindner et al. Arthritis Research & Therapy           (2025) 27:188 \nappropriate descriptive statistics, including means, stan -\ndard deviations, and percentages.\nThe physician eCRF contains data on treatment history \nand the current disease activity status and treatment reg -\nimen. Physicians record the onset of symptoms and the \ntime of diagnosis. Disease duration is calculated in years \nsince diagnosis, while diagnostic delay represents the \ntime in years between onset of symptoms and diagnosis. \nAdditional clinical parameters reported by the physician \ninclude dactylitis, axial involvement, and nail psoriasis, \nwhich are assessed using a binary yes or no response, \nenthesitis (SPARCC score including 16 entheses), swollen \njoint counts (66 joints, SJC-66), and tender joint counts \n(68 joints, TJC-68). The affected body surface area (BSA) \nis noted as a percentage and the C-Reactive Protein \n(CRP) value is provided as continuous value in mg/l. The \nDAS-28-CRP is calculated using 28 swollen and tender \njoint counts, CRP (mg/l), and patient global assessment. \nPhysician global assessment is rated on a numeric rating \nscale (NRS 0–10). The DAPSA is a continuous measure \nfocusing on joint involvement and providing granular \ninformation about disease activity [16]. Comorbidity data \nwere obtained from the physician’s CRF, where comor -\nbidities are documented using a checklist of predefined \nconditions (e.g., cardiovascular disease, renal disease, \nmalignancies, depression) with the option to add further \nconditions in free-text fields. The Rheumatic Disease \nComorbidity Index (RDCI) is used to quantify the bur -\nden of comorbid conditions in patients with rheumatic \ndiseases [ 17] including PsA [ 18]. The index incorporates \nten comorbidities (lung disease, myocardial infarction, \nstroke or other cardiovascular diseases, hypertension, \nfracture, depression, diabetes, cancer, and ulcers or stom-\nach symptoms). These comorbidities, as documented by \nthe physician, are assigned specific weights to generate \na composite score ranging from 0 to 9. A higher value \nreflects a higher burden of comorbid conditions.\nPatients provide data on sociodemographic charac -\nteristics and a variety of patient-reported outcome mea -\nsures. The patient global assessment, pain, and sleep \ndisturbance are rated on NRS 0–10. The WHO-5 Well-\nBeing Index (WHO-5) is a widely used five-item instru -\nment for screening depressive symptoms, yielding a total \nscore from 0 to 100, with scores below 29 indicating \nmoderate to severe depressive symptoms. Higher scores \nreflect greater well-being [ 19, 20]. The Dermatology Life \nQuality Index (DLQI) is reported annually by the patients \nto assess the impact of dermatological conditions on their \nquality of life. The Health Assessment Questionnaire \n(HAQ) is administered at each time point to evaluate \nthe patients’ functional ability and the extent of disability \nrelated to their condition.\nTherapy persistence rate\nThe Kaplan-Meier method was utilized to estimate ther -\napy persistence to visualize the time-to-treatment dis -\ncontinuation of the first-line b/tsDMARD therapy for the \ntwo groups of interest. One therapy episode was defined \nas an episode of the same active substance that has not \nbeen paused for more than 90 days. Patients who contin -\nued therapy after database close or were lost-to-follow up \nwere censored.\nTo analyze the direct effect of sex on therapy persis -\ntence, we used a minimally adjusted model. Age was \nincluded as covariate, as it may influence therapy per -\nsistence independently, through factors such as comor -\nbidities, treatment tolerability, or healthcare-seeking \nbehavior, but is not considered a mediator in the rela -\ntionship between sex and therapy persistence. Additional \ncovariates that could potentially act as mediators, such as \ndisease severity or other sociodemographic factors, were \ndeliberately excluded to avoid attenuating or obscuring \nthe direct effect of sex [ 21, 22]. By adjusting for age only, \nwe aimed to isolate the specific contribution of sex to \ntherapy persistence, without introducing other variables \nthat might blur this relationship. The age-adjusted analy -\nsis was performed using a Cox Regression model.\nReasons for discontinuation\nPhysician-reported reasons for discontinuation were cat -\negorized into adverse events, lack of efficacy, remission \nand other reasons. For all patients who stopped their \nfirst-line therapy during observation proportion of rea -\nsons for discontinuation were analyzed.\nAdverse events analysis\nTo enhance clarity, SAEs and AEs are collectively referred \nto as events unless otherwise specified and needed.\nIn this event analysis we only included patients for \nwhom the reason to discontinue was reported as “(seri -\nous) adverse event” . The specific event(s) that led to ther-\napy discontinuation cannot definitively be identified, due \nto the way events are reported in the register, because \nphysicians are not explicitly asked to specify which spe -\ncific event or a combination of events was the reason for \ndiscontinuation.\nTherefore, to identify an event as a treatment-related \nreason for discontinuation, we used the following \nassumptions: The primary criterion to classify an event, \nas either treatment-related or non-treatment-related, was \nthe causal relationship to the therapy indicated by the \nphysician as ‘definite, ’ ‘probable, ’ or ‘possible’ . Secondly, if \nno information on the causal relationship was provided \nor it was indicating an ‘unlikely’ , ‘no causal’ or ‘unknown’ \nrelationship, the event was selected time-based. This \nmeans if the event occurred no more than 90 days before \nand 14 days after the date of therapy discontinuation, it \n\nPage 4 of 11\nLindner et al. Arthritis Research & Therapy           (2025) 27:188 \nwas eligible for selection and therefore matching to the \ntherapy episode. The risk windows for neoplasms and \nmalignancies were extended to the end of observation \ntime. If an event could not be classified as either having a \ncausal or time-based relationship to the first-line therapy, \nit was considered out of range and excluded from further \nevent analysis.\nResults\nPatients characteristics: demographics, disease variables \nand patient-reported outcomes\nTable 1 presents the characteristics at start of first-line \ntherapy of 800 patients with PsA, stratified by female \nsex ( n = 457) and male sex ( n = 343). The mean age was \n52.3 years in females, while males were slightly younger. \nA higher proportion of females reported being current \nsmokers and they were more frequently obese. Disease \nduration for joints and skin involvement was similar for \nboth sexes. Females exhibited a longer diagnostic delay \nfor joint and skin involvement compared to males. And \nthey had less BSA affected. Nail psoriasis and dactyli -\ntis were more common among males. The proportion \nof patients with ≥ 5  mg/l CRP was similar between the \nsexes.\nThe average number of SJC-66 and TJC-68 was higher \nin females, as well as the proportion of patients with \n≥ 5 affected joints. Females also had a higher propor -\ntion of enthesitis and more enthesitis sites. Females had \na slightly higher mean physician global disease activity \nscore, DAPSA and DAS-28-CRP compared to males.\nFemale patients reported higher values in most patient-\nrelated outcome measures including patient global, pain, \nsleep disturbance, functional status, and well-being. The \nmean DLQI score was comparable for both sexes.\nTreatments\nTable  2 presents the proportion of first-line b/tsD -\nMARDs, concomitant treatments, and therapy continu -\nation after one year, stratified by sex. Among first-line b/\ntsDMARD therapies, TNFi was the most commonly used \ntreatment in both females and males, prescribed to 54% \nof females and 57% of males. The second most frequently \nprescribed therapy was IL17i, administered to 26% of \nfemales and 31% of males.\nNSAID use was reported for 43% of females compared \nto 35% of males. Glucocorticoids were prescribed in \n32% of the overall population, with a higher use among \nfemales. Additionally, both non-opioid and opioid anal -\ngesics were more commonly used in females.\nPersistence rates\nFigure 1 presents the age-adjusted therapy persistence \nrates across all therapies (1a) (including TNFi, IL17i and \nother modes of action) as well as specifically for TNFi \n(1b) and IL17i (1c). Overall, 59% of patients remained \non their first-line b/tsDMARD therapy after one year \nof observation, with 52% of females and 68% of males \ncontinuing their initial treatment (HR: 0.62 [0.50–0.76], \np = 0.000). Males demonstrated higher persistence rates \nacross all therapies after adjustment, as well as for TNFi \n(HR: 0.56 [0.42–0.76], p = 0.000) and IL17i (HR: 0.63 \n[0.42–0.96], p = 0.030) in particular.\nReason for therapy discontinuation\nOf 800 patients, 328 patients discontinued their first-\nline treatment during follow-up within 12 months. The \nreason for discontinuation was reported in 213 patients \n(65%) (Table 3). The most common reasons were lack of \nefficacy and AEs. A higher proportion of males discon -\ntinued therapy due to lack of efficacy. In contrast, more \nfemales discontinued due to AEs (22%) compared to \nmales (13%). Remission was reported as a reason for dis -\ncontinuation in 2% of patients. Both sexes discontinued \ntherapy for other unspecified reasons at an equal rate, \nincluding for example non-compliance, patient decision, \nand other medical interventions unrelated to the rheu -\nmatic disease.\nSerious and non-serious adverse events\nIn total, 171 events occurred in 63 patients for whom the \nreason to discontinue was reported as “(serious) adverse \nevent” (Table 4). The overall number of events was 127 \nin females and 44 in male patients. Out of 127 events, 10 \nwere classified as SAE and 117 as AE in females. In male \npatients, 11 were SAEs and 33 were AEs. For females 91 \nand for males 30 events could either be related to a causal \nor time-based relationship. A total of fifty events could \nnot be identified as causal or time-based relationship and \nwere excluded from further analysis. Out of all treatment \nrelated events, more events were reported as serious in \nmales (20%) than in females (8%).\nIn Table  5, the treatment related events are further \nclassified. The most common events were infections, \nneurologic events, and other events, which were not \nspecifically categorized. A list of preferred terms (within \nthe MEdDRA hierarchy) can be found in the supplement \n(Supplementary Table S2).\nIn fifteen females (14 had AEs and 1 had a SAE) twenty-\ntwo infections (21 AEs and 1 SAE) and in 3 males (2 had \nAEs and 1 had a SAE) four infections (3 AEs and 1 SAE) \noccurred. The most common infections were influenza, \noral herpes, nasopharyngitis, and cystitis. One serious \nflare event occurred in one female. One serious cardio -\nlogic event was reported for one male patient, which was \nan intracardiac thrombus. Neurologic/psychiatric events \nwere reported in nine females (12 AEs) and three males \n(3 AEs) but no serious adverse events occurred in this \ncategory. Neurologic/psychiatric events include, among \n\nPage 5 of 11\nLindner et al. Arthritis Research & Therapy           (2025) 27:188 \nTable 1 Sex-Stratified Patient Characteristics in RABBIT-SpA\nPatient Characteristics Females (n = 457) Males\n(n = 343)\nTotal\n(n = 800)\nMissings\nIn %\nSociodemographic Factors\nAge, years, Mean (SD) 52.3 (12.7) 49.9 (13) 51.3 (12.9) 0\nBMI, kg/m2, Mean (SD) 28.8 (6.5) 28.4 (4.7) 28.7 (5.8) 1\nBMI > 30, kg/m2, Yes, n (%) 166 (37) 109 (32) 275 (35)\nCurrent Smoker, Yes, n (%) 144 (36) 71 (24) 215 (31) 14\nPhysician-Reported Measure\nDisease Duration, years\n Joints, Mean (SD) 4.9 (7.0) 4.5 (6.3) 4.7 (6.7) 10\n Skin, Mean (SD) 12.9 (14.5) 12.8 (13.8) 12.9 (14.2) 33\nDiagnostic Delay, years\n Joints, Mean (SD) 3.1 (6.0) 2.1 (4.4) 2.6 (5.4) 10\n Skin, Mean (SD) 3.5 (8.4) 2.2 (6.3) 2.9 (7.6) 36\nDactylitis, Yes, n (%) 76 (17) 70 (21) 146 (18) 1\nAxial Involvement, Yes, n (%) 89 (20) 63 (19) 152 (19) 1\nNail Psoriasis, Yes, n (%) 152 (34) 160 (47) 312 (39) 1\nBSA, Mean (SD) 6.1 (11.6) 10.7 (16) 8 (13.8) 3\nCRP , mg/L 6\n Mean (SD) 6.3 (10.2) 7 (12.5) 6.6 (11.2)\n ≥ 5 mg/l, n (%) 162 (38) 128 (39) 290 (39)\nHLA-B27, Positive, n (%) 45 (16) 46 (19) 91 (17) 35\nEnthesitis, Yes, n (%) 122 (27) 69 (20) 191 (24) 1\n Mean (SD) 0.8 (2.0) 0.5 (1.3) 0.7 (1.7)\nTender Joints (TJC-68), Yes, n (%) 387 (85) 270 (79) 657 (82) 0\n Mean (SD) 6.8 (7.2) 5.3 (7.0) 6.1 (7.1)\n No Affected Joints, n (%) 69 (15) 72 (21) 141 (18)\n ≥ 5 affected joints, n (%) 226 (50) 122 (36) 348 (44)\nSwollen Joints (SJC-66), Yes, n (%) 315 (69) 216 (63) 531 (67) 0\n Mean (SD) 3.3 (4.3) 2.8 (3.9) 3.1 (4.2)\n No affected joints, n (%) 141 (31) 126 (37) 267 (33)\n ≥ 5 affected joints, n (%) 107 (23) 67 (20) 174 (22)\nPhysician Global Disease Activity*, Mean (SD) 5.1 (1.9) 4.7 (2) 4.9 (2) 2\nDAPSA, Mean (SD) 22.9 (12.7) 19 (12.3) 21.2 (12.6) 16\n REM (0–4), n (%) 11 (3) 18 (6) 29 (4)\n LDA (5–14), n (%) 82 (21) 93 (32) 175 (26)\n MoDA (15–28), n (%) 182 (48) 135 (46) 317 (47)\n HDA (> 28), n (%) 108 (28) 46 (16) 154 (23)\nDAS-28-CRP , Mean (SD) 3.6 (1.1) 3.2 (1.1) 3.4 (1.1) 16\nNo. of comorbidities (0–47), Mean (SD) 1.9 (2.0) 1.7 (2.2) 1.8 (2.1)\n ≥ 3 comorbidities, n (%) 138 (30) 78 (23) 216 (27)\nRDCI (0–9), Mean (SD) 0.9 (1.1) 0.7 (1.0) 0.8 (1.1) 0\nDepression as comorbidity, n (%) 61 (13) 19 (6) 80 (10)\nFibromyalgia as comorbidity, n (%) 23 (5) 2 (1) 25 (3)\nPatient-Reported Outcomes\nPatient Global*, Mean (SD) 5.8 (2.3) 5.0 (2.5) 5.5 (2.5) 10\nPatient Pain*, Mean (SD) 5.8 (2.3) 4.7 (2.5) 5.3 (2.4) 10\nPatient Sleep Disturbance*, Mean (SD) 5.5 (3) 3.9 (2.9) 4.8 (3) 12\nWHO5 (0-100), Mean (SD) 42.0 (22.1) 52.1 (22.3) 46.3 (22.8) 13\n Moderate/Severe (< 29), n (%) 133 (33) 56 (19) 189 (27)\nDLQI, Mean (SD) 5.2 (6.2) 5.1 (5.7) 5.1 (6) 13\nHAQ, Mean (SD) 1.0 (0.6) 0.6 (0.6) 0.9 (0.6) 11\nBSA: Body surface area; DAPSA: Disease Activity in Psoriatic Arthritis; REM: Remission; LDA: Low Disease Activity; MoDA: Moderate Disease Activity, HDA: High \nDisease Activity; RDCI: Rheumatic Disease Comorbidity Index; WHO-5: World Health Organization-Five Well-Being Index; DLQI: Dermatology Life Quality Index; \nHAQ: Health Assessment Questionnaire. *NRS-Scale (0–10)\n\nPage 6 of 11\nLindner et al. Arthritis Research & Therapy           (2025) 27:188 \nothers, depression, headache, dizziness, and mood \nswings. One female had a haematologic AE, which was \nleucopenia. A benign neoplasia event was documented \nin three females. These were pulmonary mass, papilloma \nand uterine leiomyoma.\nThe most frequently documented events were labeled \nas “other events” , and included for example allergic condi-\ntions, diarrhea, skin disorders, alopecia, other musculo -\nskeletal disorders, and pruritus.\nDiscussion\nThis study investigated the differences between female \nand male patients with PsA, regarding variations in dis -\nease characteristics, therapy persistence, and reasons for \ndiscontinuation. Furthermore, we placed a special focus \non sex differences in treatment-related adverse events in \na real-world setting.\nWe analyzed 800 patients starting their first b/tsD -\nMARD therapy. We had a higher number of female \npatients in the cohort, and they were, on average, two \nyears older than males. Females had a one year longer \ndiagnostic delay, exhibited worse health-related out -\ncomes, and showed higher musculoskeletal disease activ -\nity at the start of treatment while males presented more \nsevere skin involvement. These findings align with previ -\nously presented data from systematic reviews on obser -\nvational studies and randomized clinical trials [ 3, 23]. \nWhile males had a higher mean BSA affected by psoria -\nsis, the disease burden, as measured by the DLQI, was \nsimilar for both sexes, which is consistent with the find -\nings of a scoping review by dermatologists [24].\nTNFi was the most frequently prescribed b/tsDMARD \namong both sexes, followed by IL17i, which were more \ncommonly prescribed to males, while females more \noften received IL23i. As IL17i are particularly effective \nin treating skin manifestations [ 25], the more frequent \nprescription of IL17i in males may be due to the greater \nskin involvement at start of the first line therapy in our \ncohort. Other modes of action were comparable in fre -\nquency. The frequent use of glucocorticoids, even more \ncommon in females than in males, does not correspond \nto current treatment recommendations [26].\nRegarding treatment, females had lower persistence \nrates for both TNFi and IL17i in our study. This corre -\nsponds to results from the Danish DANBIO register, \nwhere males also remained on TNFi first-line therapy for \na longer duration [ 27]. Another recent study analyzing \npooled data from 13 European registries within the Euro-\nSpA collaboration found that females were more likely \nto discontinue TNFi therapy within a two-year period \nwith a higher likelihood of discontinuation due to insuf -\nficient efficacy or side effects [ 10]. Further supporting \nthis, an Italian cohort study observed that females were \nmore likely to discontinue anti-TNFi treatments earlier \nthan males, although smaller sex differences were noted \nfor IL17i and IL12/23i therapies. However, the smaller \nsample sizes in these groups limit the generalizability of \nthese findings [ 28]. Similarly, a multinational prospec -\ntive cohort study by Van Kuijl et al. demonstrated that \nfemales who started ustekinumab, regardless of the ther -\napy line, showed lower persistence [29].\nA trend observed across multiple studies suggests that \nfemales experience higher rates of discontinuation due to \nside effects, particularly with TNFi and IL17i therapies. \nThis observation is further supported by a meta-analy -\nsis of randomized controlled trials (RCTs), which found \nlower response rates and higher discontinuation rates \nwhen treated with TNFi and IL17i in females. On the \nother hand, for Janus kinase inhibitors (JAKi), the effi -\ncacy between the sexes was similar, but females experi -\nenced a higher incidence of adverse events, which could \ncontribute to their lower therapy persistence [23].\nThese sex-based differences in therapy persistence may \nbe further elucidated by examining the reason for therapy \ndiscontinuation, where we found notable differences.\nWhile the most common reason for discontinuation \namong both sexes was lack of efficacy, interestingly, males \nwere three times more likely to discontinue therapy due \nto remission, further supporting the findings related to \ntreatment response and effectiveness. Females, on the \nother hand, were more likely to discontinue treatment \nbecause of safety events. Our safety data showed that, \nduring the initial b/tsDMARD intervention, females had \nmore safety events overall, but SAEs were reported twice \nas often in males. This finding aligns with a worldwide \nTable 2 First-Line Therapies and Concomitant Therapies at \nTreatment Initiation in Females and Males with PsA\nFemales\n(n = 457)\nMales\n(n = 343)\nTotal\n(n = 800)\nFirst-Line Therapy, n (%)\nFirst-Line TNFi 247 (54) 197 (57) 444 (56)\nFirst-Line IL17i 119 (26) 107 (31) 226 (28)\nFirst-Line Other Modes of Action 91 (20) 39 (11) 130 (16)\n IL23i 13 (14) 3 (8) 16 (12)\n IL12i/IL23i 13 (14) 9 (23) 22 (17)\n IL6i 1 (1) 0 (0) 1 (1)\n JAKi 19 (21) 8 (21) 27 (21)\n PDE4-Inhibitor 44 (48) 19 (49) 63 (48)\n T-Cell Costimulation Inhibitors 1 (1) 0 (0) 1 (1)\nConcomitant Therapies, n (%)\nCurrent Glucocorticoids, n (%) 156 (34) 99 (29) 255 (32)\n Glucocorticoid Dose, mean (SD) 7 (4.8) 8.8 (7.2) 7.7 (5.9)\nCurrent Non-Opioid Analgesics \nTherapy\n87 (26) 47 (19) 134 (23)\nCurrent Opioid Therapy 30 (11) 17 (8) 47 (9)\nCurrent NSAID Therapy 194 (43) 119 (35) 313 (39)\nCurrent csDMARD Therapy 197 (43) 154 (45) 351 (44)\n\nPage 7 of 11\nLindner et al. Arthritis Research & Therapy           (2025) 27:188 \nFig. 1 Therapy Persistence Rates per Group Across All Therapies, TNFi and IL17i\n \n\nPage 8 of 11\nLindner et al. Arthritis Research & Therapy           (2025) 27:188 \nstudy on differences in reporting drug events in which \nmale reports were more frequently classified as SAE [ 30]. \nThe reasons are mainly unclear and could be related to \nactual physiological differences in therapy response or \ngendered reporting practices and healthcare-seeking \nbehaviors. For example, women utilize healthcare pro -\ngram offerings more regularly [ 31]. They also tend to \nreport more events than men, which can possibly lead to \nan earlier detection and intervention on these potential \nserious impairments.\nAs expected, the most common treatment-related \nevents overall were infections, neurologic/psychiatric \nand other events, with more non-serious events reported \nin females. Most of the infectious events were attribut -\nable to flu-like infections. In a study on patients with \npsoriasis receiving bDMARDs, females had significantly \nmore fungal and herpes simplex infections compared to \nmales [32]. In this study, the authors report that females \nexperienced more side effects and had a lower overall sat-\nisfaction rate, which they suggest may explain the lower \ntherapy persistence rates observed in females. A post-\nhoc analysis of a phase 3 trial with tofacitinib showed \nsimilar proportions among both sexes who experienced \nAEs. However, females treated for up to 12 months had \na higher incidence of SAEs [ 23]. Gosselt et al. also found \nthat compared to men, women report more and a wider \nvariety of adverse drug reactions (ADR) in patients \nreceiving adalimumab and etanercept [ 33]. They also \nTable 3 Reasons for Therapy Discontinuation as Recorded by \nthe Treating Physician\nFemales\n(n = 218)\nMales\n(n = 110)\nTotal\n(n = 328)\nReason for Therapy Discontinuation\n(Serious) Adverse Events, n (%) 49 (22) 14 (13) 63 (19)\nLack of Efficacy, n (%) 83 (38) 45 (41) 128 (39)\nRemission, n (%) 1 (0) 4 (4) 5 (2)\nOther Reasona, n (%) 12 (6) 5 (5) 17 (5)\nUnknown (%) 73 (33) 42 (38) 115 (35)\nae.g. non-compliance, patient decision, other medical interventions\nTable 4 Identification of Events as Treatment-Related Reasons for Therapy Discontinuation\nFemales Males Total\nPatients Who Discontinued Due to an Event and Had (S)AE Reported 49 14 63\nIdentification of Events as Treatment-Related Reasons for Discontinuation\nOverall No. of Events Occurred, n 127 44 171\n Causal relationship to therapya 61 (48) 17 (39) 78 (45)\n Time-based relationshipb 30 (24) 13 (29) 43 (25)\n Event out of range or missingc 36 (28) 14 (32) 50 (30)\nNo. of Treatment-Related Events, n 91 30 121\n Thereof SAEs 7 (8) 6 (20) 13 (11)\n Thereof AEs 84 (92) 24 (80) 108 (89)\nAll data presented as n (%)\naIndicated by physician as ‘definite,’ ‘probable,’ or ‘possible’\nbEvents occurring no more than 90 days before or 14 days after the date of therapy discontinuation where eligible for selection and therefore matching to the \ntherapy episode\ncIf an event could not be classified as either having a causal or time-based relationship to the first-line therapy or was missing, it was considered out of range and \nexcluded from further analysis\nTable 5 Treatment-Related Serious (SAE) and Non-Serious Adverse Events (AE)\nFemales\n(n = 49)\nMales\n(n = 14)\nn event / n patient* Non-serious adverse events \n(AE)\nSerious adverse events\n(SAE)\nNon-serious adverse events \n(AE)\nSerious \nadverse \nevents\n(SAE)\nInfection 21/14 1/1 3/2 1/1\nFlare 0/0 1/1 0/0 0/0\nCardiologic Events 0/0 0/0 0/0 1/1\nNeurologic/Psychiatric Events 12/9 0/0 3/3 0/0\nHematologic Events 1/1 0/0 0/0 0/0\nNeoplasia 3/3 0/0 0/0 0/0\nOther Events 47/29 5/3 18/11 4/2\nTotal 84/56 7/5 24/16 6/4\n*n event / n patient: represents the ratio of the number of events that occurred and the number of patients who experienced an event. Patients may be represented \nin multiple categories\n\nPage 9 of 11\nLindner et al. Arthritis Research & Therapy           (2025) 27:188 \nexamined the burden of ADR and found that there is no \ndifference in reported burden between women and men. \nThis could indicate, that although women are more likely \nto report events, they do not necessarily experience them \nin a more severe or burdensome way than men, which \nmight simply reflect more frequent reporting rather than \nactual differences in severity or overall experience of \nADR.\nOur findings underscore significant sex-specific differ -\nences among patients with PsA in terms of baseline char-\nacteristics, treatment outcomes, and persistence with \ntherapy. Moreover, we provide novel insights into the \nunderlying reasons for treatment discontinuation, reveal-\ning distinct patterns between female and male patients. \nAdditionally, our analysis highlights sex-based disparities \nin the nature and incidence of adverse events.\nStrengths and limitations\nA strength of our study is the large prospective, observa -\ntional, real-world data source providing a close monitor -\ning of efficacy and safety under all approved b/tsDMARD \nstrategies within predefined follow up intervals. The \nsample size enabled sex-stratified analyses on reasons for \ntherapy discontinuation, along with detailed information \non adverse events.\nLimitations: Due to the observational nature of the \nregistry, causal inferences cannot be drawn from our \nfindings. As we only capture sex as a simple variable, we \ncannot separate sex and gender but recognize that both \nbiological processes and gender roles likely influence \noutcomes.\nDue to the design of the questionnaires, we could not \ndetermine the exact event that led to therapy discontinu -\nation, but had to make assumptions and assigned the \nevents primarily via temporal context. In 35% of therapy \ndiscontinuations, the reason for discontinuation was not \ndocumented. This proportion of missing information \nmay have influenced the observed distribution of discon -\ntinuation causes between sexes and should be considered \nwhen interpreting these results. While we adjusted only \nfor age to retain the total observed effect of sex, other \npotential confounders (e.g., comorbidities, smoking, con-\ncomitant drugs) were not included in the models. Thus, \nresidual confounding may contribute to the observed \nsex differences and our findings should be interpreted \naccordingly. Differences in reporting behavior between \nsexes may have influenced our findings. In particular, \nfemales may be more likely to report less severe AE, \npotentially inflating AE-related discontinuation rates \ncompared to males. This possible reporting bias could \npartly explain the observed sex differences and should be \nconsidered when interpreting the results.\nConclusion\nThis study observed sex differences in PsA, with women \nshowing higher baseline disease activity and muscu -\nloskeletal burden, but lower therapy persistence, par -\nticularly with TNFi and IL17i therapies. Male patients \nwere more likely to discontinue treatment due to remis -\nsion, while females discontinued more often due to side \neffects, highlighting a key difference in treatment-related \nadverse events.\nThese findings emphasize the need for sex-specific \nstrategies in managing PsA to improve therapeutic out -\ncomes and patient satisfaction.\nMore nuanced research into both biological and socio -\ncultural factors influencing therapy outcomes in PsA is \nneeded, especially in real-world settings. Observational \nstudies provide valuable insights but the lack of stan -\ndardized reporting of sex data limits the ability to draw \ndefinitive conclusions. Capturing sex-related variables \nacross all types of studies is an important future direction \nto broaden our knowledge and deepen our understand -\ning of the underlying factors contributing to observed \ndisparities.\nSupplementary Information\nThe online version contains supplementary material available at  h t t p s :   /  / d o  i .  o r  \ng  /  1 0  . 1 1   8 6  / s 1 3  0 7 5 -  0 2 5 - 0  3 6 5 0 - 4.\nSupplementary Material 1\nAcknowledgements\nThe authors acknowledge the invaluable contributions of all participating \nconsultant rheumatologists and their patients. In particular, we would like to \nthank those rheumatologists who enrolled the highest numbers of patients.\nAuthor contributions\nLL: Lisa Lindner; AW: Anja Weiß; AR: Andreas Reich; CB: Christine Baumann; \nFB: Frank Behrens; XB: Xenofon Baraliakos; ACR: Anne C. Regierer; N/A: \nNot applicable. Term; Definition; Author(s)• Conceptualization; Ideas; \nformulation or evolution of overarching research goals and aims; LL, ACR, \nAW, AR•Methodology; Development or design of methodology; creation \nof models; LL, AW, AR• Software; Programming, software development; \ndesigning computer programs; implementation of the computer code and \nsupporting algorithms; testing of existing code components; LL, AW, AR• \nValidation; Verification, whether as a part of the activity or separate, of the \noverall replication/ reproducibility of results/experiments and other research \noutputs; LL, AR• Formal analysis; Application of statistical, mathematical, \ncomputational, or other formal techniques to analyze or synthesize study \ndata; LL, AW, AR• Investigation; Conducting a research and investigation \nprocess, specifically performing the experiments, or data/evidence collection; \nLL, AW, AR, ACR• Resources; Provision of study materials, reagents, materials, \npatients, laboratory samples, animals, instrumentation, computing resources, \nor other analysis tools; N/A• Data Curation; Management activities to annotate \n(produce metadata), scrub data and maintain research data (including \nsoftware code, where it is necessary for interpreting the data itself ) for initial \nuse and later reuse; LL, AW• Writing - Original Draft; Preparation, creation \nand/or presentation of the published work, specifically writing the initial \ndraft (including substantive translation); LL, ACR• Writing - Review & Editing; \nPreparation, creation and/or presentation of the published work by those \nfrom the original research group, specifically critical review, commentary \nor revision – including pre-or postpublication stages; LL, AW, AR, CB, FB, XB, \nACR• Visualization; Preparation, creation and/or presentation of the published \nwork, specifically visualization/ data presentation; LL• Supervision; Oversight \n\nPage 10 of 11\nLindner et al. Arthritis Research & Therapy           (2025) 27:188 \nand leadership responsibility for the research activity planning and execution, \nincluding mentorship external to the core team; FB, XB•Project administration; \nManagement and coordination responsibility for the research activity \nplanning and execution; ACR• Funding acquisition; Acquisition of the financial \nsupport for the project leading to this publication; N/A.\nFunding\nOpen Access funding enabled and organized by Projekt DEAL. RABBIT-SpA \nis supported by a joint, unconditional grant from AbbVie, Amgen, Biocon \nBiologics, Biogen, Celltrion, Johnson & Johnson, Lilly, Novartis, Pfizer, and UCB.\nData availability\nThe data that support the findings of this study are available from German \nRheumatology Research Center but restrictions apply to the availability of \nthese data, which were used under license for the current study, and so are \nnot publicly available. Data are however available from the authors upon \nreasonable request and with permission of the German Rheumatology \nResearch Center.\nDeclarations\nEthics approval and consent to participate\nRABBIT-SpA is approved by the Ethics Committee of Charité University \nMedicine, Berlin (#EA1/246/16). Participants have to consent to participate in \nthe study.\nConsent for publication\nNot applicable.\nCompeting interests\nLL: The author declares that they have no competing interests. AW: The author \ndeclares that they have no competing interests. AR: The author declares that \nthey have no competing interests. CB: The author declares that they have \nno competing interests. FB: grants/research support from Bionorica, Bristol \nMyers Squibb, Chugai, Iron4u, Janssen-Cilag, LEO Pharma, Novartis, Pfizer, \nand Roche andmeeting support, honoraria, or fees for serving as a speaker, \nconsultant, and/or advisory board member from AbbVie, Affibody, Amgen, \nBristol Myers Squibb, Boehringer Ingelheim, Eli Lilly, Galapagos, GSK, Janssen-\nCilag, MoonLake, Merck Sharp & Dohme, Novartis, Pfizer, Sandoz, Sanofi , \nand UCB. XB: Consultant, Scientific Advisory Board: Abbvie, Advanz, Alexion, \nAlphasigma, Amgen, AstraZeneca, BMS, Cesas, Celltrion, Clarivate, Galapagos, \nJ&J, Lilly, Moonlake, Novartis, Peervoice, Pfizer, Roche, Sandoz, Springer, Stada, \nTakeda, UCB, Zuellig. Research Grants: Abbvie, Celltrion, Janssen, Moonlake, \nNovartis. Non-commercial disclosures: ASAS Past President, EULAR President-\nElect. ACR: Speaker fees from Amgen, BMS, Novartis.\nAuthor details\n1German Rheumatology Research Center (DRFZ Berlin), Epidemiology \nand Health Services Research, Research Charitéplatz 1, 10117 Berlin, \nGermany\n2Private Practice for Rheumatology, Plauen, Germany\n3Fraunhofer Institute for Translational Medicine and Pharmacology ITMP , \nFrankfurt am Main, Germany\n4Rheumatology Center Ruhrgebiet, Ruhr University Bochum, Herne, \nGermany\nReceived: 9 July 2025 / Accepted: 11 September 2025\nReferences\n1. Ogdie A, Langan S, Love T, Haynes K, Shin D, Seminara N, et al. Prevalence and \ntreatment patterns of psoriatic arthritis in the UK. Rheumatology (Oxford). \n2013;52(3):568–75.\n2. Bragazzi NL, Bridgewood C, Watad A, Damiani G, McGonagle D. Sex-Based \nmedicine Meets psoriatic arthritis: lessons learned and to learn. Front Immu-\nnol. 2022;13:849560.\n3. Coates LC, van der Horst-Bruinsma IE, Lubrano E, Beaver S, Drane E, Ufuktepe \nB, et al. 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