Abstract 22 — Derivation and Internal Validation of a Multi-Biomarker-Based Disease Activity Prediction Score for Psoriatic Arthritis Patients

Background While C-reactive protein (CRP) is commonly used to monitor disease activity in Psoriatic Arthritis (PsA), over half of the patients with moderate-to-high disease activity had normal CRP level. Our study aims to investigate the correlation of serum protein biomarkers and disease activity i...

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Main Authors: Yingzhao Jin, Isaac T Cheng, Ho So, Terry Cheuk Fung Yip, CK Wong, Lai-shan Tam
Format: Article
Language:English
Published: World Scientific Publishing 2023-11-01
Series:Journal of Clinical Rheumatology and Immunology
Online Access:https://www.worldscientific.com/doi/10.1142/S2661341723740383
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author Yingzhao Jin
Isaac T Cheng
Ho So
Terry Cheuk Fung Yip
CK Wong
Lai-shan Tam
author_facet Yingzhao Jin
Isaac T Cheng
Ho So
Terry Cheuk Fung Yip
CK Wong
Lai-shan Tam
author_sort Yingzhao Jin
collection DOAJ
description Background While C-reactive protein (CRP) is commonly used to monitor disease activity in Psoriatic Arthritis (PsA), over half of the patients with moderate-to-high disease activity had normal CRP level. Our study aims to investigate the correlation of serum protein biomarkers and disease activity in patients with PsA. Methods 176 patients fulfilled the CASPAR (ClASsification criteria for Psoriatic ARthritis) were recruited in this cross-sectional study. Disease activity was measured by the clinical Disease Activity in Psoriatic Arthritis (cDAPSA). 45 protein biomarkers, cartilage and bone turn-over markers level were assessed (Table 1). The patients were randomly divided into a derivation-cohort and a validation-cohort at a ratio of 7:3. Least absolute shrinkage and selection operator (LASSO) was used to select biomarkers which were associated with moderate/high disease activity in the derivation cohort. Receiver operating characteristic (ROC) curve, GiViTI calibration belt were used to assess the performance of the model in both cohorts. Results The cohort [age: 55.5 (44.0-62.75) years, male: 80 (45.5%)] had moderate disease activity [DAPSA: 15.9 (8.3-26.9); PASI: 3.2 (0.5-6.8)]. 101 PsA patients (57.4%) had moderate/high disease activity. Biomarker levels associated with moderate/high disease activity included SAA (Serum amyloid A), IL8 (Interleukin 8), IP10 (Interferon gamma-induced protein 10), M-CSF (Macrophage colony-stimulating factor), SCGF-[Formula: see text] (Stem cell growth factor), SDF-1[Formula: see text] (Stromal cell-derived factor 1[Formula: see text]) (Figure 1A, B). The model’s equation including the 6 biomarker levels was applied to the validation-cohort. The area under the ROC curve (AUC) for discriminating moderate/high disease activity was 0.802 and 0.835 for the derivation-and-validation-cohorts, respectively (Figure 1C, D). The multi-biomarkers panel model had higher-AUC when compared with that of CRP (AUC=0.727, p=0.022). The P-values of calibration charts in the two sets were 0.902 and 0.123 (Figure 1E, F). Conclusions The multi-biomarkers panel had excellent performance in discriminating patients with moderate/high disease activity from those with low disease activity/remission.
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spelling doaj.art-7221feae5417455eb744f445657ee01a2023-11-30T07:52:31ZengWorld Scientific PublishingJournal of Clinical Rheumatology and Immunology2661-34172661-34252023-11-0123Supp01485010.1142/S2661341723740383Abstract 22 — Derivation and Internal Validation of a Multi-Biomarker-Based Disease Activity Prediction Score for Psoriatic Arthritis PatientsYingzhao Jin0Isaac T Cheng1Ho So2Terry Cheuk Fung Yip3CK Wong4Lai-shan Tam5The Chinese University of Hong Kong, Hong Kong, ChinaThe Chinese University of Hong Kong, Hong Kong, ChinaThe Chinese University of Hong Kong, Hong Kong, ChinaMedical Data Analytics Centre, Institute of Digestive Disease, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, ChinaDepartment of Chemical Patholgoy, Hong Kong, ChinaThe Chinese University of Hong Kong, Hong Kong, ChinaBackground While C-reactive protein (CRP) is commonly used to monitor disease activity in Psoriatic Arthritis (PsA), over half of the patients with moderate-to-high disease activity had normal CRP level. Our study aims to investigate the correlation of serum protein biomarkers and disease activity in patients with PsA. Methods 176 patients fulfilled the CASPAR (ClASsification criteria for Psoriatic ARthritis) were recruited in this cross-sectional study. Disease activity was measured by the clinical Disease Activity in Psoriatic Arthritis (cDAPSA). 45 protein biomarkers, cartilage and bone turn-over markers level were assessed (Table 1). The patients were randomly divided into a derivation-cohort and a validation-cohort at a ratio of 7:3. Least absolute shrinkage and selection operator (LASSO) was used to select biomarkers which were associated with moderate/high disease activity in the derivation cohort. Receiver operating characteristic (ROC) curve, GiViTI calibration belt were used to assess the performance of the model in both cohorts. Results The cohort [age: 55.5 (44.0-62.75) years, male: 80 (45.5%)] had moderate disease activity [DAPSA: 15.9 (8.3-26.9); PASI: 3.2 (0.5-6.8)]. 101 PsA patients (57.4%) had moderate/high disease activity. Biomarker levels associated with moderate/high disease activity included SAA (Serum amyloid A), IL8 (Interleukin 8), IP10 (Interferon gamma-induced protein 10), M-CSF (Macrophage colony-stimulating factor), SCGF-[Formula: see text] (Stem cell growth factor), SDF-1[Formula: see text] (Stromal cell-derived factor 1[Formula: see text]) (Figure 1A, B). The model’s equation including the 6 biomarker levels was applied to the validation-cohort. The area under the ROC curve (AUC) for discriminating moderate/high disease activity was 0.802 and 0.835 for the derivation-and-validation-cohorts, respectively (Figure 1C, D). The multi-biomarkers panel model had higher-AUC when compared with that of CRP (AUC=0.727, p=0.022). The P-values of calibration charts in the two sets were 0.902 and 0.123 (Figure 1E, F). Conclusions The multi-biomarkers panel had excellent performance in discriminating patients with moderate/high disease activity from those with low disease activity/remission.https://www.worldscientific.com/doi/10.1142/S2661341723740383
spellingShingle Yingzhao Jin
Isaac T Cheng
Ho So
Terry Cheuk Fung Yip
CK Wong
Lai-shan Tam
Abstract 22 — Derivation and Internal Validation of a Multi-Biomarker-Based Disease Activity Prediction Score for Psoriatic Arthritis Patients
Journal of Clinical Rheumatology and Immunology
title Abstract 22 — Derivation and Internal Validation of a Multi-Biomarker-Based Disease Activity Prediction Score for Psoriatic Arthritis Patients
title_full Abstract 22 — Derivation and Internal Validation of a Multi-Biomarker-Based Disease Activity Prediction Score for Psoriatic Arthritis Patients
title_fullStr Abstract 22 — Derivation and Internal Validation of a Multi-Biomarker-Based Disease Activity Prediction Score for Psoriatic Arthritis Patients
title_full_unstemmed Abstract 22 — Derivation and Internal Validation of a Multi-Biomarker-Based Disease Activity Prediction Score for Psoriatic Arthritis Patients
title_short Abstract 22 — Derivation and Internal Validation of a Multi-Biomarker-Based Disease Activity Prediction Score for Psoriatic Arthritis Patients
title_sort abstract 22 derivation and internal validation of a multi biomarker based disease activity prediction score for psoriatic arthritis patients
url https://www.worldscientific.com/doi/10.1142/S2661341723740383
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