Search

IMPORTANCE Identifying the optimal long-term biologic therapy for patients with psoriasis is often done through trial and error. OBJECTIVE To identify the optimal biologic therapy for individual patients with psoriasis using predictive statistical and machine learning models. DESIGN, SETTING, AND PARTICIPANTS This population-based cohort study used data from Danish nationwide registries, primarily DERMBIO, and included adult patients treated for moderate-to-severe psoriasis with biologics. Data were processed and analyzed between spring 2021 and spring 2022. MAIN OUTCOMES AND MEASURES Patient clusters of clinical relevance were identified and their success rates estimated for each drug. Furthermore, predictive prognostic models to identify optimal biologic treatment at the individual level based on data from nationwide registries were evaluated. RESULTS Assuming a success criterion of 3 years of sustained treatment, this study included 2034 patients with a total of 3452 treatment series. Most treatment series involved male patients (2147 [62.2%]) originating from Denmark (3190 [92.4%]), and 2414 (69.9%) had finished an education longer than primary school. The average ages were 24.9 years at psoriasis diagnosis and 45.5 years at initiation of biologic therapy. Gradient-boosted decision trees and logistic regression were able to predict a specific cytokine target (eg, interleukin-17 inhibition) associated with a successful treatment with accuracies of 63.6% and 59.2%, and top 2 accuracies of 95.9% and 93.9%. When predicting specific drugs resulting in success, gradient boost and logistic regression had accuracies of 48.5% and 44.4%, top 2 accuracies of 77.6% and 75.9%, and top 3 accuracies of 89.9% and 89.0%. CONCLUSIONS AND RELEVANCE Of the treatment prediction models used in this cohort study of patients with psoriasis, gradient-boosted decision trees performed significantly, IMPORTANCE Identifying the optimal long-term biologic therapy for patients with psoriasis is often done through trial and error. OBJECTIVE To identify the optimal biologic therapy for individual patients with psoriasis using predictive statistical and machine learning models. DESIGN, SETTING, AND PARTICIPANTS This population-based cohort study used data from Danish nationwide registries, primarily DERMBIO, and included adult patients treated for moderate-to-severe psoriasis with biologics. Data were processed and analyzed between spring 2021 and spring 2022. MAIN OUTCOMES AND MEASURES Patient clusters of clinical relevance were identified and their success rates estimated for each drug. Furthermore, predictive prognostic models to identify optimal biologic treatment at the individual level based on data from nationwide registries were evaluated. RESULTS Assuming a success criterion of 3 years of sustained treatment, this study included 2034 patients with a total of 3452 treatment series. Most treatment series involved male patients (2147 [62.2%]) originating from Denmark (3190 [92.4%]), and 2414 (69.9%) had finished an education longer than primary school. The average ages were 24.9 years at psoriasis diagnosis and 45.5 years at initiation of biologic therapy. Gradient-boosted decision trees and logistic regression were able to predict a specific cytokine target (eg, interleukin-17 inhibition) associated with a successful treatment with accuracies of 63.6% and 59.2%, and top 2 accuracies of 95.9% and 93.9%. When predicting specific drugs resulting in success, gradient boost and logistic regression had accuracies of 48.5% and 44.4%, top 2 accuracies of 77.6% and 75.9%, and top 3 accuracies of 89.9% and 89.0%. CONCLUSIONS AND RELEVANCE Of the treatment prediction models used in this cohort study of patients with psoriasis, gradient-boosted decision trees performed significantly

Importance: The efficacy of adalimumab biosimilars is similar to that of brand-name adalimumab (Humira, hereinafter originator) in clinical trials. However, limited knowledge about real-world data exists for adalimumab biosimilars. Objective: To assess the outcomes following a mandatory nonmedical switch from adalimumab originator to adalimumab biosimilars in patients with psoriasis. Design, Setting, and Participants: This cohort study assesses the outcomes following a switch from adalimumab originator to an adalimumab biosimilar. Patients in the Biological Treatment in Danish Dermatology (DERMBIO) registry, a Danish nationwide registry of all patients treated with biologics (including biosimilars) for psoriasis since 2007, were assessed for eligibility. All patients who switched from adalimumab originator to an adalimumab biosimilar between November 1, 2018, and May 1, 2019, were included in the adalimumab biosimilar cohort. All patients with a visit between May 1, 2017, and November 1, 2017, treated with adalimumab originator were included in the adalimumab originator cohort. Data were analyzed from June 1, 2020, to October 10, 2021. Exposure: Switch from adalimumab originator to an adalimumab biosimilar. Main Outcomes and Measures: The primary outcome was 1-year drug retention in patients switching to adalimumab biosimilars compared with patients treated with adalimumab originator. Crude and adjusted retention rates for the adalimumab biosimilar cohort were compared with the adalimumab originator cohort with Cox proportional hazards regression using robust variance. Results: A total of 348 patients were included in the adalimumab biosimilar cohort (mean [SD] age, 52.2 [13.6] years; 251 [72.1%] male) and 378 patients in the adalimumab originator cohort (mean [SD] age, 51.1 [14.1] years; 272 [72.0%] male). The 1-year drug retention rates were 92.0% (95% CI, 89.0%-94.9%) for the adalimumab biosimilar cohort and 92.1% (95% CI, 89.4%-94.8%) for the adalimumab origi

Early response to treatment with biologics might be important for the stability of psoriasis and long-term outcome. The aim of this study was therefore to assess whether risk of flares and drug survival are associated with disease activity in the first 6 months of treatment of psoriasis with biologics. Biologic-naïve patients from the Danish nationwide registry, DERMBIO, were grouped based on absolute Psoriasis Area and Severity Index (PASI) during the first 6 months of treatment, as: PASI = 0, PASI > 0–≤2, PASI > 2–≤ 4, and PASI > 4. Among 1,684 patients, 746 achieved PASI= 0, 485 PASI > 0–≤2, 246 PASI > 2–≤4, and 207 PASI > 4. Longer flare-free period and drug survival were observed for patients with lower PASI in the first 6 months of treatment (adjusted hazard ratios for flares (95% confidence interval) with PASI= 0 as reference: PASI > 0–≤2 (1.35 (1.11–1.72]), PASI > 2–≤ 4 (2.32 [1.80–2.99]), and PASI > 4 (2.38 [1.80–3.15])). In conclusion, a low PASI in the first 6 months of treatment with biologics in biologic-naïve patients with psoriasis was associated with a more stable disease course, lower risk of flares, and longer drug survival.

Objective. To asses a cohort of 105 consecutive patients with angiotensin converting enzyme-inhibitor induced angioedema withregard to demographics, risk factors, family history of angioedema, hospitalization, airway management, outcome, and use ofdiagnostic codes used for the condition. Study Design. Cohort study. Methods.This was a retrospective cohort study of 105 patientswith angiotensin converting enzyme-inhibitor induced angioedema in the period 1995–2014. Results. The cohort consisted of 67females and 38 males (F :Mratio 1.8), with a mean age of 63 [range 26–86] years. Female gender was associated with a significantlyhigher risk of angiotensin converting enzyme-inhibitor induced angioedema. 6.7% had a positive family history of angioedema.Diabetes seemed to be a protective factor with regard to angioedema. 95% experienced angioedema of the head and neck. 4.7%needed intubation or tracheostomy. 74 admissions took place during the study period with a total of 143 days spent in the hospital.The diagnosis codes most often used for this condition were “DT783 Quincke’s oedema” and “DT78.4 Allergy unspecified”.Complement C1 inhibitor was normal in all tested patients. Conclusion. Female gender predisposes to angiotensin convertingenzyme-inhibitor induced angioedema, whereas diabetes seems to be a protective factor.