Real-World Infection Burden with Bimekizumab Versus IL-23 Inhibitors in Psoriasis

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Shen¹, Aaron T. Zhao¹ This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9169541/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Bimekizumab, a dual IL-17A/F inhibitor, achieves superior skin clearance in moderate-to-severe plaque psoriasis but may impair mucosal antifungal immunity more profoundly than agents targeting upstream IL-23. Real-world comparative safety data versus IL-23 inhibitors are currently lacking. Using the TriNetX health research network, we conducted a propensity score-matched cohort study in adults with psoriasis comparing bimekizumab initiators (n = 1,336) to initiators of IL-23 inhibitors, tildrakizumab, guselkumab, or risankizumab, (n = 19,352 before matching). Matching variables included age, sex, race/ethnicity, BMI, type 2 diabetes, chronic kidney disease, hypertension, and concurrent corticosteroid use. Outcomes were assessed from 1 to 180 days after the biologic index date. Four endpoints were examined: clinically treated fungal infections, mucocutaneous infections, antifungal prescriptions, and any new infection. After matching, bimekizumab was associated with significantly higher risk across all endpoints versus IL-23 inhibitors. Clinically treated fungal infections: 6.7% vs. 2.4% (hazard ratio [HR] 3.36, 95% CI 2.04–5.52; p < 0.001). Mucocutaneous infections: 10.0% vs. 5.5% (HR 3.78, 95% CI 2.18–6.56; p < 0.001). Antifungal prescriptions: 11.0% vs. 5.9% (HR 2.17, 95% CI 1.65–2.85; p < 0.001). Any new infection: 7.2% vs. 4.4% (RR 1.63, 95% CI 1.03–2.59; log-rank p = 0.007). These findings confirm that bimekizumab's candidiasis signal observed in phase III trials translates into routine clinical practice, with a 2- to 4-fold higher risk versus IL-23 inhibitors. Clinicians should incorporate candidiasis risk counseling into shared decision-making and maintain a low threshold for antifungal evaluation during the first six months of therapy. bimekizumab IL-23 inhibitor psoriasis candidiasis infection risk fungal infection Introduction Psoriasis is a chronic, immune-mediated inflammatory skin disorder affecting approximately 2–3% of the global population [ 11 , 3 ]. Bimekizumab is a humanized IgG1 monoclonal antibody that uniquely inhibits both IL-17A and IL-17F, demonstrating superior rates of complete skin clearance (PASI 100) compared to secukinumab and adalimumab in head-to-head trials [ 12 , 15 ]. However, both IL-17 cytokines play a non-redundant role in mucosal host defense against Candida species [ 5 , 4 ], and phase III trials of bimekizumab reported candidiasis rates of approximately 4–19 per 100 patient-years, substantially higher than IL-23 inhibitors [ 12 , 14 ]. IL-23 inhibitors (guselkumab, risankizumab, and tildrakizumab) suppress IL-17 production indirectly without directly neutralizing IL-17 at the tissue level [ 8 , 10 ], potentially preserving greater mucosal antifungal immunity. Whether this risk differential persists in real-world clinical practice has not been established. We conducted a propensity score-matched (PSM) cohort study using the TriNetX federated EHR network to quantify comparative candidiasis and mucocutaneous infection risk in psoriasis patients initiating bimekizumab versus IL-23 inhibitors [ 9 , 1 ]. Methods Data Source and Study Design This retrospective, propensity score-matched cohort study was conducted using the TriNetX Research Network, a federated health informatics platform aggregating de-identified electronic health records from 111 U.S. healthcare organizations (HCOs). The TriNetX network captures ICD-10-CM diagnoses, RxNorm medications, laboratory results, and demographic variables. IRB approval was not required as all data are de-identified and accessed through a HIPAA-compliant federated architecture. Study population The bimekizumab cohort comprised adults (≥ 18 years) with a diagnosis of psoriasis who had received at least one dispensing of bimekizumab, with the requirement that bimekizumab initiation occurred on or after a documented psoriasis diagnosis. The index date was defined as the date of first bimekizumab administration. This cohort included 1,336 patients from 48 responding HCOs. The IL-23 inhibitor comparator cohorot comprised adults (≥ 18 years) with a diagnosis of psoriasis who had initiated tildrakizumab, guselkumab, or risankizumab. These agents were selected as the comparator class because they represent the most mechanistically proximate alternative in moderate-to-severe psoriasis, efficacious biologics that act upstream of IL-17 without directly neutralizing this cytokine [ 13 , 10 ]. The index date was the date of first prescription for any qualifying IL-23 inhibitor. This cohort included 19,352 patients from 76 responding HCOs before matching. Propensity score matching To address confounding by indication and baseline imbalances, we performed 1:1 nearest-neighbor propensity score matching without replacement. Matching variables included age at index date, sex, race/ethnicity (White, Black or African American, Asian, Hispanic/Latino), BMI, and clinically relevant comorbidities and concomitant medications known to influence infection risk: type 2 diabetes mellitus, chronic kidney disease, essential hypertension, and concurrent use of corticosteroids (prednisone, methylprednisolone, betamethasone). After matching, each cohort comprised 1,336 patients. Outcomes Outcomes were assessed from day 1 to day 180 after the index date. The primary outcome was a composite of clinically treated fungal infections, defined as any candidiasis diagnosis (ICD-10-CM B37.0, B37.2, B37.3, B37.41, B37.42, B37.49, B37.8, B37.81, B37.89, B37.9) or new antifungal medication prescription (nystatin, miconazole, clotrimazole, fluconazole). This approach captures both coded and empirically treated infections. Analyses were performed excluding patients with the outcome prior to the observation window. Secondary outcomes included: (i) mucocutaneous infections, a composite of all candidiasis codes and skin/soft tissue infections (L01–L03, L08); (ii) any new infection, additionally including upper (J00–J06, J32) and lower respiratory tract infections (J12–J20); and (iii) antifungal prescriptions alone. Patients with the relevant outcome prior to the time window were excluded from each analysis except where noted. Statistical analysis Measures of association (risk difference, risk ratio, odds ratio) with 95% confidence intervals were calculated. Kaplan–Meier analysis estimated cumulative incidence; groups were compared using log-rank tests. Cox proportional hazards regression estimated hazard ratios (HRs); proportional hazards were assessed via Schoenfeld residuals. Two-sided P < 0.05 was considered significant. All analyses were performed using the TriNetX platform. Results Study population and propensity score matching Before propensity score matching, the bimekizumab cohort (n = 1,336) and the IL-23 inhibitor cohort (n = 19,352) differed significantly on several characteristics. Bimekizumab-treated patients were more likely to be female (59.7% vs. 53.2%, p < 0.001), had higher rates of type 2 diabetes (26.0% vs. 20.0%, p < 0.001), higher BMI (33.4 ± 8.3 vs. 31.9 ± 8.1 kg/m², p < 0.001), and substantially greater corticosteroid use (prednisone: 47.6% vs. 31.1%; methylprednisolone: 40.6% vs. 26.6%; both p < 0.001) (Table 1 ). After 1:1 propensity score matching (n = 1,336 per group), all measured covariates were well-balanced. Age at index was virtually identical (50.5 ± 14.3 years in both groups; standardized mean difference [SMD] 0.004), and all SMDs fell below 0.08. Prednisone use was 47.6% vs. 46.4% (p = 0.535; SMD 0.024), methylprednisolone 40.6% vs. 40.0% (p = 0.782), and betamethasone 39.7% vs. 40.7% (p = 0.608). BMI remained numerically higher in the bimekizumab group (33.4 ± 8.3 vs. 32.7 ± 8.2 kg/m², p = 0.067; SMD 0.077), not reaching statistical significance and below the pre-specified threshold. Mean follow-up was 140.7 days (SD 60.9) in Cohort 1 and 162.0 days (SD 45.4) in Cohort 2 after matching. Table 1 Baseline characteristics before and after propensity score matching Characteristic Before matching After matching Bimekizumab (n = 1,336) IL-23i (n = 19,352) Bimekizumab (n = 1,336) IL-23i (n = 1,336) SMD Age at index, mean ± SD (years) 50.5 ± 14.3 51.1 ± 15.5 50.5 ± 14.3 50.5 ± 14.3 0.004 Female sex, n (%) 797 (59.7%) 10,294 (53.2%) 797 (59.7%) 797 (59.7%) < 0.001 White race, n (%) 993 (74.3%) 14,607 (75.5%) 993 (74.3%) 1,015 (76.0%) 0.038 Type 2 diabetes, n (%) 347 (26.0%) 3,862 (20.0%) 347 (26.0%) 324 (24.3%) 0.040 Essential hypertension, n (%) 576 (43.1%) 7,642 (39.5%) 576 (43.1%) 585 (43.8%) 0.014 Prednisone use, n (%) 636 (47.6%) 6,011 (31.1%) 636 (47.6%) 620 (46.4%) 0.024 BMI, mean ± SD (kg/m²) 33.4 ± 8.3 31.9 ± 8.1 33.4 ± 8.3 32.7 ± 8.2 0.077 IL-23i IL-23 inhibitor class (tildrakizumab, guselkumab, risankizumab). SMD standardized mean difference. All SMDs after matching < 0.08. Primary outcomes: fungal and mucocutaneous infections Across all pre-specified endpoints, bimekizumab was associated with a statistically significant and clinically meaningful increase in infection risk compared to IL-23 inhibitors. Results are summarized in Table 2 . Among patients without prior fungal infection history, bimekizumab was associated with a 6.7% versus 2.4% risk of clinically treated fungal infection (RR 2.84, 95% CI 1.74–4.64; HR 3.36, 95% CI 2.04–5.52; log-rank p < 0.001; 180-day infection-free survival 91.34% vs. 97.43%). The composite mucocutaneous infection endpoint occurred in 10.0% versus 5.5% of patients (RR 1.81, 95% CI 1.38–2.38; HR 3.78, 95% CI 2.18–6.56; log-rank p < 0.001; 180-day infection-free survival 92.32% vs. 97.91%). Antifungal prescriptions were recorded in 11.0% versus 5.9% of patients (RR 1.86, 95% CI 1.43–2.42; HR 2.17, 95% CI 1.65–2.85; log-rank p < 0.001). Proportionality testing was significant (χ² = 10.92, p = 0.001), indicating risk concentration in the early treatment period [ 7 , 14 ]. The broad sensitivity composite (any new infection) confirmed a consistent signal (7.2% vs. 4.4%; RR 1.63, 95% CI 1.03–2.59; log-rank p = 0.007), suggesting risk amplification is primarily concentrated in the IL-17-dependent mucocutaneous compartment. Table 2 Comparative outcomes after propensity score matching: risk analysis and Kaplan-Meier estimates Outcome Bimekizumab risk IL-23i risk RR (95% CI) OR (95% CI) RD (95% CI) HR (95% CI) Log-rank p Clinically treated fungal infections 6.7% (59/880) 2.4% (21/890) 2.84 (1.74–4.64) 2.97 (1.79–4.94) 0.043 (0.024–0.063) 3.36 (2.04–5.52) < 0.001 Mucocutaneous infections 10.0% (134/1,336) 5.5% (74/1,336) 1.81 (1.38–2.38) 1.90 (1.42–2.55) 0.045 (0.025–0.065) 3.78 (2.18–6.56) < 0.001 Antifungal prescription 11.0% (147/1,336) 5.9% (79/1,336) 1.86 (1.43–2.42) 1.97 (1.48–2.62) 0.051 (0.030–0.072) 2.17 (1.65–2.85) < 0.001 Any new infection (sensitivity) 7.2% (43/600) 4.4% (28/637) 1.63 (1.03–2.59) 1.68 (1.03–2.74) 0.028 (0.002–0.054) 1.90 (1.18–3.06) 0.007 IL-23i IL-23 inhibitor class. HR hazard ratio. OR odds ratio. RD risk difference. RR risk ratio. Fungal infection analyses exclude patients with outcomes prior to the observation window. Discussion In this large, propensity score-matched real-world cohort study, bimekizumab was associated with a consistently higher risk of candidiasis, mucocutaneous infections, and antifungal medication use compared to IL-23 inhibitors across all pre-specified endpoints. The magnitude of the risk increase, a 2- to 3-fold for fungal-specific outcomes, is clinically substantial and consistent with the postulated biological mechanism underlying bimekizumab's unique safety profile. The mechanistic basis for this finding is well-grounded. IL-17A and IL-17F signal through overlapping but non-identical receptor complexes (IL-17RA/RC) and elicit overlapping but distinct transcriptional programs at mucosal surfaces [ 10 , 4 ]. Both cytokines independently stimulate epithelial production of anti- Candida defensins, cathelicidins, S100 proteins, and neutrophil chemoattractants essential for Candida killing [ 5 ]. By simultaneously neutralizing both cytokines, bimekizumab may produce a more complete abrogation of mucosal IL-17 signaling than agents that suppress only IL-17A or that block IL-17 production indirectly via IL-23. IL-23 inhibitors, acting on the upstream Th17-polarizing cytokine, are thought to attenuate rather than abolish IL-17 activity at tissue surfaces, preserving a residual level of antifungal mucosal immunity [ 8 ]. The non-proportional hazard test result for antifungal prescriptions (p = 0.001) is particularly noteworthy, suggesting that the highest incremental candidiasis risk with bimekizumab is concentrated in the early treatment period, consistent with phase III trial data reporting the highest incidence in the first 16 weeks [ 7 ]. This temporal pattern has implications for monitoring strategy: clinicians may consider more intensive surveillance for oral and mucocutaneous candidiasis during the first four months of bimekizumab therapy. Our findings augment the safety literature in several important ways. Randomized controlled trials systematically exclude patients with recurrent candidiasis histories, immunosuppressant combinations, and multiple comorbidities, all of which characterize real-world psoriasis populations [ 2 , 15 ]. The present study captures these patients and demonstrates that the candidiasis signal observed in trials translates robustly into routine clinical practice. Notably, after propensity score matching, both cohorts were balanced for corticosteroid use, diabetes, CKD, and BMI, factors that independently predispose to candidiasis, providing strong evidence that the observed risk difference is attributable to the biologic agent itself rather than residual confounding. Clinical Implications These findings help refine the benefit-risk calculus for individual patients. Patients with a history of recurrent candidiasis, those with diabetes mellitus, those requiring concomitant corticosteroids, and immunocompromised individuals may be at disproportionately elevated risk and should be counseled accordingly before initiating bimekizumab [ 9 ]. Proactive strategies including baseline candidiasis risk assessment, patient education regarding early symptoms, and a low threshold for empiric antifungal therapy may mitigate patient harm. Prescribers might also consider prophylactic oral antifungal strategies in highest-risk patients, though this approach requires formal evaluation in prospective trials [ 13 ]. Limitations As a retrospective real-world study, unmeasured confounding cannot be excluded despite rigorous propensity score matching. Variables such as psoriasis severity scores, prior biologic exposure history, mucosal hygiene behaviors, and socioeconomic factors were not available in the TriNetX dataset. ICD-10-CM coding for candidiasis also may be subject to under-ascertainment bias if mild infections were managed empirically without formal diagnosis codes; however, the antifungal prescription endpoint provides a complementary, potentially more sensitive capture. Additionally, the TriNetX platform does not provide information on psoriasis phenotype, severity, or prior biologic failure, which may have differentially influenced prescribing patterns between cohorts. Conclusion In this large, propensity score-matched real-world cohort study, bimekizumab was associated with a 2- to 3-fold higher risk of clinically treated candidiasis and mucocutaneous infections compared to IL-23 inhibitors in adults with psoriasis, with the antifungal prescription rate being 86% higher in bimekizumab-treated patients. These findings align with the pharmacological mechanism of dual IL-17A/F inhibition and complement the existing trial-based safety literature with real-world evidence across a diverse, comorbid U.S. population. Clinicians should incorporate candidiasis risk assessment into shared decision-making when selecting bimekizumab, implement patient education regarding early signs of candidiasis, and maintain a low clinical threshold for antifungal evaluation and treatment during the first 6 months of therapy. Declarations Funding. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Competing interests. The authors have no conflicts of interest to declare. Ethics approval. This study used de-identified data from the TriNetX platform, which complies with the HIPAA Privacy Rule §164.514(a). Institutional review board exemption was obtained. Consent to participate / for publication. Not applicable. Data availability. Data were accessed via the TriNetX platform and are available to institutions with TriNetX membership. TriNetX data are de-identified and cannot be shared externally per the platform’s data use agreement. Author contributions. CZS contributed to study conception, analysis, and drafting. ATZ contributed to analysis and drafting. All authors approved the final version. Acknowledgements. None. The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. References Armstrong AW, Read C (2020) Pathophysiology, clinical presentation, and treatment of psoriasis: a review. JAMA 323:1945–1960. https://doi.org/10.1001/jama.2020.4006 Blauvelt A, Papp KA, Lebwohl MG et al (2021) Bimekizumab for patients with moderate-to-severe plaque psoriasis. J Am Acad Dermatol 85:1254–1263. https://doi.org/10.1016/j.jaad.2020.08.061 Boehncke WH, Schön MP (2015) Psoriasis Lancet 386:983–994. https://doi.org/10.1016/S0140-6736(14)61909-7 Conti HR, Gaffen SL (2015) IL-17-mediated immunity to the opportunistic fungal pathogen Candida albicans. J Immunol 195:780–788. https://doi.org/10.4049/jimmunol.1500899 Gaffen SL, Jain R, Garg AV, Cua DJ (2014) The IL-23-IL-17 immune axis: from mechanisms to therapeutic testing. Nat Rev Immunol 14:585–600. https://doi.org/10.1038/nri3707 Glatt S, Helmer E, Haier B et al (2017) First-in-human randomized study of bimekizumab, a humanized monoclonal antibody and potent dual inhibitor of IL-17A and IL-17F, in mild psoriasis. Br J Clin Pharmacol 83:991–1001. https://doi.org/10.1111/bcp.13185 Gordon KB, Foley P, Krueger JG et al (2021) Bimekizumab efficacy and safety in moderate to severe plaque psoriasis (BE READY): a multicentre, double-blind, placebo-controlled, randomised withdrawal phase 3 trial. Lancet 397:475–486. https://doi.org/10.1016/S0140-6736(21)00126-4 Kopp T, Riedl E, Bangert C et al (2015) Clinical improvement in psoriasis with specific targeting of interleukin-23. Nature 521:222–226. https://doi.org/10.1038/nature14175 Menter A, Strober BE, Kaplan DH et al (2019) Joint AAD-NPF guidelines of care for the management and treatment of psoriasis with biologics. J Am Acad Dermatol 80:1029–1072. https://doi.org/10.1016/j.jaad.2018.11.057 Miossec P, Kolls JK (2012) Targeting IL-17 and TH17 cells in chronic inflammation. Nat Rev Drug Discov 11:763–776. https://doi.org/10.1038/nrd3794 Parisi R, Symmons DP, Griffiths CE, Ashcroft DM (2013) Global epidemiology of psoriasis: a systematic review of incidence and prevalence. J Invest Dermatol 133:377–385. https://doi.org/10.1038/jid.2012.339 Reich K, Warren RB, Lebwohl M et al (2021) Bimekizumab versus secukinumab in plaque psoriasis. N Engl J Med 385:142–152. https://doi.org/10.1056/NEJMoa2102383 Rønholt K, Iversen L (2017) Old and new biological therapies for psoriasis. Int J Mol Sci 18:2422. https://doi.org/10.3390/ijms18112422 Strober B, Kimball AB, Casseres RG et al (2022) Bimekizumab long-term safety in plaque psoriasis: integrated analysis from five phase 2 and phase 3 clinical trials. J Am Acad Dermatol 86:1308–1317. https://doi.org/10.1016/j.jaad.2021.10.053 Warren RB, Blauvelt A, Bagel J et al (2021) Bimekizumab versus adalimumab in plaque psoriasis. N Engl J Med 385:130–141. https://doi.org/10.1056/NEJMoa2101400 Additional Declarations No competing interests reported. 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Shen¹","email":"data:image/png;base64,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","orcid":"","institution":"University of Pennsylvania","correspondingAuthor":true,"prefix":"","firstName":"Catherine","middleName":"Z.","lastName":"Shen¹","suffix":""},{"id":638337736,"identity":"660c33ce-8884-4218-8a3e-aba799244323","order_by":1,"name":"Aaron T. Zhao¹","email":"","orcid":"","institution":"University of Pennsylvania","correspondingAuthor":false,"prefix":"","firstName":"Aaron","middleName":"T.","lastName":"Zhao¹","suffix":""}],"badges":[],"createdAt":"2026-03-19 12:38:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9169541/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9169541/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109281228,"identity":"0a4f25d0-ff14-4743-9623-122162c798f1","added_by":"auto","created_at":"2026-05-14 17:55:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":176569,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9169541/v1/fb33018a-ee1a-444c-9af5-c6e31f03185f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Real-World Infection Burden with Bimekizumab Versus IL-23 Inhibitors in Psoriasis","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePsoriasis is a chronic, immune-mediated inflammatory skin disorder affecting approximately 2\u0026ndash;3% of the global population [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Bimekizumab is a humanized IgG1 monoclonal antibody that uniquely inhibits both IL-17A and IL-17F, demonstrating superior rates of complete skin clearance (PASI 100) compared to secukinumab and adalimumab in head-to-head trials [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, both IL-17 cytokines play a non-redundant role in mucosal host defense against \u003cem\u003eCandida\u003c/em\u003e species [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and phase III trials of bimekizumab reported candidiasis rates of approximately 4\u0026ndash;19 per 100 patient-years, substantially higher than IL-23 inhibitors [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIL-23 inhibitors (guselkumab, risankizumab, and tildrakizumab) suppress IL-17 production indirectly without directly neutralizing IL-17 at the tissue level [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], potentially preserving greater mucosal antifungal immunity. Whether this risk differential persists in real-world clinical practice has not been established. We conducted a propensity score-matched (PSM) cohort study using the TriNetX federated EHR network to quantify comparative candidiasis and mucocutaneous infection risk in psoriasis patients initiating bimekizumab versus IL-23 inhibitors [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Source and Study Design\u003c/h2\u003e \u003cp\u003eThis retrospective, propensity score-matched cohort study was conducted using the TriNetX Research Network, a federated health informatics platform aggregating de-identified electronic health records from 111 U.S. healthcare organizations (HCOs). The TriNetX network captures ICD-10-CM diagnoses, RxNorm medications, laboratory results, and demographic variables. IRB approval was not required as all data are de-identified and accessed through a HIPAA-compliant federated architecture.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003eThe bimekizumab cohort comprised adults (\u0026ge;\u0026thinsp;18 years) with a diagnosis of psoriasis who had received at least one dispensing of bimekizumab, with the requirement that bimekizumab initiation occurred on or after a documented psoriasis diagnosis. The index date was defined as the date of first bimekizumab administration. This cohort included 1,336 patients from 48 responding HCOs.\u003c/p\u003e \u003cp\u003eThe IL-23 inhibitor comparator cohorot comprised adults (\u0026ge;\u0026thinsp;18 years) with a diagnosis of psoriasis who had initiated tildrakizumab, guselkumab, or risankizumab. These agents were selected as the comparator class because they represent the most mechanistically proximate alternative in moderate-to-severe psoriasis, efficacious biologics that act upstream of IL-17 without directly neutralizing this cytokine [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The index date was the date of first prescription for any qualifying IL-23 inhibitor. This cohort included 19,352 patients from 76 responding HCOs before matching.\u003c/p\u003e\n\u003ch3\u003ePropensity score matching\u003c/h3\u003e\n\u003cp\u003eTo address confounding by indication and baseline imbalances, we performed 1:1 nearest-neighbor propensity score matching without replacement. Matching variables included age at index date, sex, race/ethnicity (White, Black or African American, Asian, Hispanic/Latino), BMI, and clinically relevant comorbidities and concomitant medications known to influence infection risk: type 2 diabetes mellitus, chronic kidney disease, essential hypertension, and concurrent use of corticosteroids (prednisone, methylprednisolone, betamethasone). After matching, each cohort comprised 1,336 patients.\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cp\u003eOutcomes were assessed from day 1 to day 180 after the index date. The primary outcome was a composite of clinically treated fungal infections, defined as any candidiasis diagnosis (ICD-10-CM B37.0, B37.2, B37.3, B37.41, B37.42, B37.49, B37.8, B37.81, B37.89, B37.9) or new antifungal medication prescription (nystatin, miconazole, clotrimazole, fluconazole). This approach captures both coded and empirically treated infections. Analyses were performed excluding patients with the outcome prior to the observation window.\u003c/p\u003e \u003cp\u003eSecondary outcomes included: (i) mucocutaneous infections, a composite of all candidiasis codes and skin/soft tissue infections (L01\u0026ndash;L03, L08); (ii) any new infection, additionally including upper (J00\u0026ndash;J06, J32) and lower respiratory tract infections (J12\u0026ndash;J20); and (iii) antifungal prescriptions alone. Patients with the relevant outcome prior to the time window were excluded from each analysis except where noted.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eMeasures of association (risk difference, risk ratio, odds ratio) with 95% confidence intervals were calculated. Kaplan\u0026ndash;Meier analysis estimated cumulative incidence; groups were compared using log-rank tests. Cox proportional hazards regression estimated hazard ratios (HRs); proportional hazards were assessed via Schoenfeld residuals. Two-sided P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant. All analyses were performed using the TriNetX platform.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStudy population and propensity score matching\u003c/h2\u003e \u003cp\u003eBefore propensity score matching, the bimekizumab cohort (n\u0026thinsp;=\u0026thinsp;1,336) and the IL-23 inhibitor cohort (n\u0026thinsp;=\u0026thinsp;19,352) differed significantly on several characteristics. Bimekizumab-treated patients were more likely to be female (59.7% vs. 53.2%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), had higher rates of type 2 diabetes (26.0% vs. 20.0%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), higher BMI (33.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3 vs. 31.9\u0026thinsp;\u0026plusmn;\u0026thinsp;8.1 kg/m\u0026sup2;, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and substantially greater corticosteroid use (prednisone: 47.6% vs. 31.1%; methylprednisolone: 40.6% vs. 26.6%; both p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAfter 1:1 propensity score matching (n\u0026thinsp;=\u0026thinsp;1,336 per group), all measured covariates were well-balanced. Age at index was virtually identical (50.5\u0026thinsp;\u0026plusmn;\u0026thinsp;14.3 years in both groups; standardized mean difference [SMD] 0.004), and all SMDs fell below 0.08. Prednisone use was 47.6% vs. 46.4% (p\u0026thinsp;=\u0026thinsp;0.535; SMD 0.024), methylprednisolone 40.6% vs. 40.0% (p\u0026thinsp;=\u0026thinsp;0.782), and betamethasone 39.7% vs. 40.7% (p\u0026thinsp;=\u0026thinsp;0.608). BMI remained numerically higher in the bimekizumab group (33.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3 vs. 32.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2 kg/m\u0026sup2;, p\u0026thinsp;=\u0026thinsp;0.067; SMD 0.077), not reaching statistical significance and below the pre-specified threshold. Mean follow-up was 140.7 days (SD 60.9) in Cohort 1 and 162.0 days (SD 45.4) in Cohort 2 after matching.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics before and after propensity score matching\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e Characteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eBefore matching\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eAfter matching\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBimekizumab (n\u0026thinsp;=\u0026thinsp;1,336)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIL-23i (n\u0026thinsp;=\u0026thinsp;19,352)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBimekizumab (n\u0026thinsp;=\u0026thinsp;1,336)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIL-23i (n\u0026thinsp;=\u0026thinsp;1,336)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSMD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at index, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.5\u0026thinsp;\u0026plusmn;\u0026thinsp;14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.1\u0026thinsp;\u0026plusmn;\u0026thinsp;15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.5\u0026thinsp;\u0026plusmn;\u0026thinsp;14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.5\u0026thinsp;\u0026plusmn;\u0026thinsp;14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale sex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e797 (59.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10,294 (53.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e797 (59.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e797 (59.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite race, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e993 (74.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14,607 (75.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e993 (74.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,015 (76.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType 2 diabetes, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e347 (26.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,862 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e347 (26.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e324 (24.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEssential hypertension, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e576 (43.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,642 (39.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e576 (43.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e585 (43.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrednisone use, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e636 (47.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,011 (31.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e636 (47.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e620 (46.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (kg/m\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.9\u0026thinsp;\u0026plusmn;\u0026thinsp;8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eIL-23i IL-23 inhibitor class (tildrakizumab, guselkumab, risankizumab). SMD standardized mean difference. All SMDs after matching\u0026thinsp;\u0026lt;\u0026thinsp;0.08.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePrimary outcomes: fungal and mucocutaneous infections\u003c/h3\u003e\n\u003cp\u003eAcross all pre-specified endpoints, bimekizumab was associated with a statistically significant and clinically meaningful increase in infection risk compared to IL-23 inhibitors. Results are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eAmong patients without prior fungal infection history, bimekizumab was associated with a 6.7% versus 2.4% risk of clinically treated fungal infection (RR 2.84, 95% CI 1.74\u0026ndash;4.64; HR 3.36, 95% CI 2.04\u0026ndash;5.52; log-rank p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; 180-day infection-free survival 91.34% vs. 97.43%). The composite mucocutaneous infection endpoint occurred in 10.0% versus 5.5% of patients (RR 1.81, 95% CI 1.38\u0026ndash;2.38; HR 3.78, 95% CI 2.18\u0026ndash;6.56; log-rank p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; 180-day infection-free survival 92.32% vs. 97.91%).\u003c/p\u003e \u003cp\u003eAntifungal prescriptions were recorded in 11.0% versus 5.9% of patients (RR 1.86, 95% CI 1.43\u0026ndash;2.42; HR 2.17, 95% CI 1.65\u0026ndash;2.85; log-rank p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Proportionality testing was significant (χ\u0026sup2; = 10.92, p\u0026thinsp;=\u0026thinsp;0.001), indicating risk concentration in the early treatment period [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The broad sensitivity composite (any new infection) confirmed a consistent signal (7.2% vs. 4.4%; RR 1.63, 95% CI 1.03\u0026ndash;2.59; log-rank p\u0026thinsp;=\u0026thinsp;0.007), suggesting risk amplification is primarily concentrated in the IL-17-dependent mucocutaneous compartment.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparative outcomes after propensity score matching: risk analysis and Kaplan-Meier estimates\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBimekizumab risk\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIL-23i risk\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRD (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLog-rank p\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinically treated fungal infections\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.7% (59/880)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.4% (21/890)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.84 (1.74\u0026ndash;4.64)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.97 (1.79\u0026ndash;4.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.043 (0.024\u0026ndash;0.063)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e3.36 (2.04\u0026ndash;5.52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMucocutaneous infections\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.0% (134/1,336)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.5% (74/1,336)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.81 (1.38\u0026ndash;2.38)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.90 (1.42\u0026ndash;2.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.045 (0.025\u0026ndash;0.065)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e3.78 (2.18\u0026ndash;6.56)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAntifungal prescription\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.0% (147/1,336)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.9% (79/1,336)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.86 (1.43\u0026ndash;2.42)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.97 (1.48\u0026ndash;2.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.051 (0.030\u0026ndash;0.072)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e2.17 (1.65\u0026ndash;2.85)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAny new infection (sensitivity)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.2% (43/600)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.4% (28/637)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.63 (1.03\u0026ndash;2.59)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.68 (1.03\u0026ndash;2.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.028 (0.002\u0026ndash;0.054)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1.90 (1.18\u0026ndash;3.06)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eIL-23i IL-23 inhibitor class. HR hazard ratio. OR odds ratio. RD risk difference. RR risk ratio. Fungal infection analyses exclude patients with outcomes prior to the observation window.\u003c/em\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this large, propensity score-matched real-world cohort study, bimekizumab was associated with a consistently higher risk of candidiasis, mucocutaneous infections, and antifungal medication use compared to IL-23 inhibitors across all pre-specified endpoints. The magnitude of the risk increase, a 2- to 3-fold for fungal-specific outcomes, is clinically substantial and consistent with the postulated biological mechanism underlying bimekizumab's unique safety profile.\u003c/p\u003e \u003cp\u003eThe mechanistic basis for this finding is well-grounded. IL-17A and IL-17F signal through overlapping but non-identical receptor complexes (IL-17RA/RC) and elicit overlapping but distinct transcriptional programs at mucosal surfaces [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Both cytokines independently stimulate epithelial production of anti-\u003cem\u003eCandida\u003c/em\u003e defensins, cathelicidins, S100 proteins, and neutrophil chemoattractants essential for Candida killing [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. By simultaneously neutralizing both cytokines, bimekizumab may produce a more complete abrogation of mucosal IL-17 signaling than agents that suppress only IL-17A or that block IL-17 production indirectly via IL-23. IL-23 inhibitors, acting on the upstream Th17-polarizing cytokine, are thought to attenuate rather than abolish IL-17 activity at tissue surfaces, preserving a residual level of antifungal mucosal immunity [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe non-proportional hazard test result for antifungal prescriptions (p\u0026thinsp;=\u0026thinsp;0.001) is particularly noteworthy, suggesting that the highest incremental candidiasis risk with bimekizumab is concentrated in the early treatment period, consistent with phase III trial data reporting the highest incidence in the first 16 weeks [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This temporal pattern has implications for monitoring strategy: clinicians may consider more intensive surveillance for oral and mucocutaneous candidiasis during the first four months of bimekizumab therapy.\u003c/p\u003e \u003cp\u003eOur findings augment the safety literature in several important ways. Randomized controlled trials systematically exclude patients with recurrent candidiasis histories, immunosuppressant combinations, and multiple comorbidities, all of which characterize real-world psoriasis populations [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The present study captures these patients and demonstrates that the candidiasis signal observed in trials translates robustly into routine clinical practice. Notably, after propensity score matching, both cohorts were balanced for corticosteroid use, diabetes, CKD, and BMI, factors that independently predispose to candidiasis, providing strong evidence that the observed risk difference is attributable to the biologic agent itself rather than residual confounding.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eClinical Implications\u003c/h2\u003e \u003cp\u003eThese findings help refine the benefit-risk calculus for individual patients. Patients with a history of recurrent candidiasis, those with diabetes mellitus, those requiring concomitant corticosteroids, and immunocompromised individuals may be at disproportionately elevated risk and should be counseled accordingly before initiating bimekizumab [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Proactive strategies including baseline candidiasis risk assessment, patient education regarding early symptoms, and a low threshold for empiric antifungal therapy may mitigate patient harm. Prescribers might also consider prophylactic oral antifungal strategies in highest-risk patients, though this approach requires formal evaluation in prospective trials [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eAs a retrospective real-world study, unmeasured confounding cannot be excluded despite rigorous propensity score matching. Variables such as psoriasis severity scores, prior biologic exposure history, mucosal hygiene behaviors, and socioeconomic factors were not available in the TriNetX dataset. ICD-10-CM coding for candidiasis also may be subject to under-ascertainment bias if mild infections were managed empirically without formal diagnosis codes; however, the antifungal prescription endpoint provides a complementary, potentially more sensitive capture. Additionally, the TriNetX platform does not provide information on psoriasis phenotype, severity, or prior biologic failure, which may have differentially influenced prescribing patterns between cohorts.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this large, propensity score-matched real-world cohort study, bimekizumab was associated with a 2- to 3-fold higher risk of clinically treated candidiasis and mucocutaneous infections compared to IL-23 inhibitors in adults with psoriasis, with the antifungal prescription rate being 86% higher in bimekizumab-treated patients. These findings align with the pharmacological mechanism of dual IL-17A/F inhibition and complement the existing trial-based safety literature with real-world evidence across a diverse, comorbid U.S. population. Clinicians should incorporate candidiasis risk assessment into shared decision-making when selecting bimekizumab, implement patient education regarding early signs of candidiasis, and maintain a low clinical threshold for antifungal evaluation and treatment during the first 6 months of therapy.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding.\u0026nbsp;\u003c/strong\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests.\u0026nbsp;\u003c/strong\u003eThe authors have no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval.\u0026nbsp;\u003c/strong\u003eThis study used de-identified data from the TriNetX platform, which complies with the HIPAA Privacy Rule \u0026sect;164.514(a). Institutional review board exemption was obtained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate / for publication.\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability.\u0026nbsp;\u003c/strong\u003eData were accessed via the TriNetX platform and are available to institutions with TriNetX membership. TriNetX data are de-identified and cannot be shared externally per the platform\u0026rsquo;s data use agreement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions.\u0026nbsp;\u003c/strong\u003eCZS contributed to study conception, analysis, and drafting. ATZ contributed to analysis and drafting. All authors approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements.\u0026nbsp;\u003c/strong\u003eNone.\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eArmstrong AW, Read C (2020) Pathophysiology, clinical presentation, and treatment of psoriasis: a review. 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N Engl J Med 385:130\u0026ndash;141. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1056/NEJMoa2101400\u003c/span\u003e\u003cspan address=\"10.1056/NEJMoa2101400\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"archives-of-dermatological-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Archives of Dermatological Research](https://www.springer.com/journal/403)","snPcode":"403","submissionUrl":"https://submission.nature.com/new-submission/403/3","title":"Archives of Dermatological Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"bimekizumab, IL-23 inhibitor, psoriasis, candidiasis, infection risk, fungal infection","lastPublishedDoi":"10.21203/rs.3.rs-9169541/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9169541/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBimekizumab, a dual IL-17A/F inhibitor, achieves superior skin clearance in moderate-to-severe plaque psoriasis but may impair mucosal antifungal immunity more profoundly than agents targeting upstream IL-23. Real-world comparative safety data versus IL-23 inhibitors are currently lacking. Using the TriNetX health research network, we conducted a propensity score-matched cohort study in adults with psoriasis comparing bimekizumab initiators (n\u0026thinsp;=\u0026thinsp;1,336) to initiators of IL-23 inhibitors, tildrakizumab, guselkumab, or risankizumab, (n\u0026thinsp;=\u0026thinsp;19,352 before matching). Matching variables included age, sex, race/ethnicity, BMI, type 2 diabetes, chronic kidney disease, hypertension, and concurrent corticosteroid use. Outcomes were assessed from 1 to 180 days after the biologic index date. Four endpoints were examined: clinically treated fungal infections, mucocutaneous infections, antifungal prescriptions, and any new infection. After matching, bimekizumab was associated with significantly higher risk across all endpoints versus IL-23 inhibitors. Clinically treated fungal infections: 6.7% vs. 2.4% (hazard ratio [HR] 3.36, 95% CI 2.04\u0026ndash;5.52; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Mucocutaneous infections: 10.0% vs. 5.5% (HR 3.78, 95% CI 2.18\u0026ndash;6.56; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Antifungal prescriptions: 11.0% vs. 5.9% (HR 2.17, 95% CI 1.65\u0026ndash;2.85; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Any new infection: 7.2% vs. 4.4% (RR 1.63, 95% CI 1.03\u0026ndash;2.59; log-rank p\u0026thinsp;=\u0026thinsp;0.007). These findings confirm that bimekizumab's candidiasis signal observed in phase III trials translates into routine clinical practice, with a 2- to 4-fold higher risk versus IL-23 inhibitors. Clinicians should incorporate candidiasis risk counseling into shared decision-making and maintain a low threshold for antifungal evaluation during the first six months of therapy.\u003c/p\u003e","manuscriptTitle":"Real-World Infection Burden with Bimekizumab Versus IL-23 Inhibitors in Psoriasis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-14 17:55:19","doi":"10.21203/rs.3.rs-9169541/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"103099758180565168631803210528788210157","date":"2026-05-11T14:07:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-06T04:18:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-21T12:16:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-21T12:16:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"Archives of Dermatological Research","date":"2026-03-19T12:22:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"archives-of-dermatological-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Archives of Dermatological Research](https://www.springer.com/journal/403)","snPcode":"403","submissionUrl":"https://submission.nature.com/new-submission/403/3","title":"Archives of Dermatological Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e6bbb2ae-4619-4102-aafc-11ea544a9595","owner":[],"postedDate":"May 14th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"103099758180565168631803210528788210157","date":"2026-05-11T14:07:47+00:00","index":26,"fulltext":""},{"type":"reviewersInvited","content":"20","date":"2026-05-06T04:18:25+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T17:55:20+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-14 17:55:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9169541","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9169541","identity":"rs-9169541","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}