Dataset Information

Bounded integer model-based analysis of psoriasis area and severity index in patients with moderate-to-severe plaque psoriasis receiving BI 730357.

ABSTRACT: BI 730357 is investigated as an oral treatment of plaque psoriasis. We analyzed the impact of three dosage regimens on the Psoriasis Area and Severity Index (PASI) response with modeling based on phase I and II data from 109 healthy subjects and 274 patients with moderate-to-severe plaque psoriasis. The pharmacokinetics (PK) was characterized by a two-compartment model with dual absorption paths and a first-order elimination. Higher baseline C-reactive protein was associated with lower clearance and patients generally had lower clearance compared with healthy subjects. A bounded integer PK/pharmacodynamic model characterized the effect on the observed PASI. The maximum drug effect was largest for patients with no prior biologic use, smaller for patients with prior use of non-interleukin-17 inhibitors, and smallest for patients with prior interleukin-17 inhibitor use. The models allowed robust simulation of large patient populations, predicting a plateau in PASI outcomes for BI 730357 exposure above 2000 nmol/L.

SUBMITTER: Ooi QX

PROVIDER: S-EPMC10272300 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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Bounded integer model-based analysis of psoriasis area and severity index in patients with moderate-to-severe plaque psoriasis receiving BI 730357.

Ooi Qing Xi QX Kristoffersson Anders A Korell Julia J Flack Mary M L Plan Elodie E Weber Benjamin B

CPT: pharmacometrics & systems pharmacology 20230501 6

BI 730357 is investigated as an oral treatment of plaque psoriasis. We analyzed the impact of three dosage regimens on the Psoriasis Area and Severity Index (PASI) response with modeling based on phase I and II data from 109 healthy subjects and 274 patients with moderate-to-severe plaque psoriasis. The pharmacokinetics (PK) was characterized by a two-compartment model with dual absorption paths and a first-order elimination. Higher baseline C-reactive protein was associated with lower clearance ...[more]

PMID: 36919398

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Project description:BackgroundRisankizumab has demonstrated durable, high rates of efficacy in patients with moderate-to-severe plaque psoriasis as assessed by the achievement of relative Psoriasis Area and Severity Index (PASI) improvement and Dermatology Life Quality Index (DLQI) 0/1.ObjectivesThe aim of this post hoc analysis is to assess the achievement of absolute PASI thresholds and related improvements in health-related quality of life (HRQoL) in patients with moderate-to-severe plaque psoriasis treated with (i) risankizumab compared with ustekinumab, and (ii) long-term (>52 weeks to 172 weeks) risankizumab.MethodsData from patients randomised to 150 mg risankizumab or 45 or 90 mg ustekinumab in replicate randomised controlled trials UltIMMa-1 and UltIMMa-2 were analysed for the achievement of absolute PASI thresholds PASI ≤ 3, PASI ≤ 1, and PASI = 0, time to achieve these thresholds, and combined PASI and DLQI endpoints. Data from pat ients initially randomised to risankizumab who continued on risankizumab in the open-label extension study LIMMitless were analysed for the achievement of absolute PASI levels, mean DLQI scores, and DLQI 0/1.ResultsSignificantly greater proportions of patients treated with risankizumab compared with ustekinumab achieved PASI ≤ 3, PASI ≤ 1, and PASI = 0, as well as combined endpoints for absolute PASI and DLQI [(PASI ≤ 3 and DLQI ≤ 5) or (PASI ≤ 1 and DLQI 0/1)]. The median time to first achieve PASI ≤ 3, PASI ≤ 1, and PASI = 0 was significantly lower for risankizumab-treated patients compared with ustekinumab-treated patients. Among patients treated with long-term risankizumab, more than 90% achieved PASI ≤ 3 though week 172 and more than 80% achieved DLQI 0/1. Low absolute PASI scores corresponded with low mean absolute DLQI scores through week 172 of continuous risankizumab treatment.ConclusionsRisankizumab treatment demonstrated high rates of rapid and durable efficacy as measured by absolute PASI thresholds and improvements in patient HRQoL.

Project description:BackgroundThe Psoriasis Area and Severity Index (PASI) score is commonly used in clinical practice and research to monitor disease severity and determine treatment efficacy. Automating the PASI score with deep learning algorithms, like Convolutional Neural Networks (CNNs), could enable objective and efficient PASI scoring.ObjectivesTo assess the performance of image-based automated PASI scoring in anatomical regions by CNNs and compare the performance of CNNs to image-based scoring by physicians.MethodsImaging series were matched to PASI subscores determined in real life by the treating physician. CNNs were trained using standardized imaging series of 576 trunk, 614 arm and 541 leg regions. CNNs were separately trained for each PASI subscore (erythema, desquamation, induration and area) in each anatomical region (trunk, arms and legs). The head region was excluded for anonymity. Additionally, PASI-trained physicians retrospectively determined image-based subscores on the test set images of the trunk. Agreement with the real-life scores was determined with the intraclass correlation coefficient (ICC) and compared between the CNNs and physicians.ResultsIntraclass correlation coefficients between the CNN and real-life scores of the trunk region were 0.616, 0.580, 0.580 and 0.793 for erythema, desquamation, induration and area, respectively, with similar results for the arms and legs region. PASI-trained physicians (N = 5) were in moderate-good agreement (ICCs 0.706-0.793) with each other for image-based PASI scoring of the trunk region. ICCs between the CNN and real-life scores were slightly higher for erythema (0.616 vs. 0.558), induration (0.580 vs. 0.573) and area scoring (0.793 vs. 0.694) than image-based scoring by physicians. Physicians slightly outperformed the CNN on desquamation scoring (0.580 vs. 0.589).ConclusionsConvolutional Neural Networks have the potential to automatically and objectively perform image-based PASI scoring at an anatomical region level. For erythema, desquamation and induration scoring, CNNs performed similar to physicians, while for area scoring CNNs outperformed physicians on image-based PASI scoring.

Dataset Information

Bounded integer model-based analysis of psoriasis area and severity index in patients with moderate-to-severe plaque psoriasis receiving BI 730357.

Publications

Bounded integer model-based analysis of psoriasis area and severity index in patients with moderate-to-severe plaque psoriasis receiving BI 730357.

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