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Abstract Number: 0637

Comparison of Four Risk Stratification Models for Prediction of Mortality in Systemic Sclerosis-associated Pulmonary Arterial Hypertension in the EUSTAR Cohort

Hilde Jenssen Bjørkekjær1, Cosimo Bruni2, Cathrine Brunborg3, Patricia Carreira4, Paolo Airò5, Carmen Pilar Simeon-Aznar6, Marie-Elise Truchetet7, Alessandro Giollo8, Alexandra Balbir-Gurman9, Mickael Martin10, Christopher Denton11, Armando Gabrielli12, Havard Fretheim13, Imon Barua13, Helle Bitter14, Oyvind Midtvedt13, Torhild Garen15, Kaspar Broch16, Arne Andreassen17, Yoshiya Tanaka18, Gabriela Riemekasten19, Ulf Müller-Ladner20, marco Matucci Cerinic21, Ivan Castellvi22, Elise Siegert23, Eric Hachulla24, Oliver Distler2 and Anna-Maria Hoffmann-Vold13, 1Department of Rheumatology, Hospital of Southern Norway, Kristiansand & University of Oslo, Institute of Clinical Medicine, Oslo, Norway, 2Department of Rheumatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland, 3Oslo Centre for Biostatistics and Epidemiology, Research Support Services, Oslo University Hospital - Rikshospitalet, Oslo, Norway, 4Hospital Universitario 12 de Octubre, Madrid, Spain, 5Spedali Civili di Brescia, Scleroderma UNIT, UOC Reumatologia ed Immunologia Clinica, Piazzale Spedali Civili 1, 25123, Brescia, Italy, 6Department of Internal Medicine, Systemic Autoimmune Diseases Unit, Hospital Universitario Vall d'Hebronh, Barcelona, Spain, 7Bordeaux University Hospital, Bordeaux, France, 8University of Verona, Rheumatology Section, Department of Medicine, Verona, Italy, Verona, Italy, 9Rheumatology Institute, Rambam Health Care Campus and Rappaport Faculty of |Medicine, Technion, Haifa, Israel, 10Department of Internal Medicine, INSERM U1313, Poitiers University, Poitiers University Hospital, Poitiers, France, 11University College London, London, United Kingdom, 12Ospedali Riuniti Marche, Ancona, Italy, 13Oslo University Hospital, Oslo, Norway, 14Sorlandet sykehus, Kristiansand, Norway, 15Dept of Rheumatology, University Hospital Oslo, Oslo, Norway, 16Oslo University Hospital, Rikshospitalet, Department of Cardiology, Oslo, Norway, KG Jebsen center, Institute for Experimental Medical Research, University of Oslo, Oslo, Norway, 17Oslo University Hospital, Rikshospitalet, Department of Cardiology, Oslo, Norway, 18University of Occupational and Environmental Health, Kitakyushu, Japan, 19University Clinic Schleswit-Holstein (UKSH), Lübeck, Germany, 20Justus Liebig University Gießen, Campus Kerckhoff, Bad Nauheim, Germany, 21Unit of Immunology, Rheumatology, Allergy and Rare diseases, IRCCS San Raffaele Hospital, Milan, Milan, Italy, 22Rheumatology, Hospital Universitari de la Santa Creu i Sant Pau, Sant Just Desvern, Spain, 23Department of Rheumatology, Charité University Hospital, Charité Platz 1, D-10117, Berlin, Germany, 24University of Lille, Lille, France

Meeting: ACR Convergence 2023

Keywords: pulmonary, risk assessment, Systemic sclerosis

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Session Information

Date: Sunday, November 12, 2023

Title: (0609–0672) Systemic Sclerosis & Related Disorders – Clinical Poster I: Research

Session Type: Poster Session A

Session Time: 9:00AM-11:00AM

Background/Purpose: The 2022 ESC/ERS Guidelines recommend comprehensive risk stratification at diagnosis of pulmonary arterial hypertension (PAH) to guide optimized management.1Several risk stratification tools have been developed with data derived mainly from patients with idiopathic PAH. However, patients with systemic sclerosis (SSc)-associated PAH have a worse prognosis. We aimed to assess the performance of current risk stratification tools to predict mortality in SSc-PAH by adding variables specific to SSc.

Methods: We included SSc patients from the EUSTAR database who were diagnosed with PAH by right heart catheterization (RHC) between 2001-2021 (Project Number: CP122). PAH was defined as a mean pulmonary arterial pressure >20 mmHg, pulmonary artery wedge pressure ≤15 mmHg and pulmonary vascular resistance >2 WU. We excluded patients with previous PAH-specific treatment and meaningful interstitial lung disease (ILD), defined as an extent of ILD >20% on HRCT or FVC < 70% in patients with missing quantification. We applied four different approaches:

(I) 2022 ESC/ERS 3-strata: Three risk groups based on the mean of up to 17 risk parameters from the guidelines graded 1-3 representing low-high risk

(II) 2022 ESC/ERS 4-strata: Equals no. (I), but divides the intermediate-risk group into two groups

(III) COMPERA 2.0: Four risk groups based on the mean of WHO-functional class (FC) and/or six-minute walk distance (6MWD) and NT-proBNP graded 1-4 representing low-high risk.2

(IV) REVEAL Lite 2:Three risk groups based on six weighted variables (WHO-FC, systolic blood pressure, heart rate, 6MWD, NT-pro-BNP, and eGFR)3

We performed Cox regression adjusted for general and SSc-specific factors associated with worse outcome based on expert opinion and published literature (age, male sex, anti-centromere antibodies, digital ulcers, DLCO and limited ILD). Harrell’s C-index and ROC analysis with area under the curve (AUC) were applied to compare the performance and discriminating ability of the models with >0.7 defined as acceptable.

Results: Of 890 patients who had RHC, 367 were eligible. Among these, 87% were females, mean age was 66 years, and 83% had limited cutaneous SSc.

In univariable analysis, only COMPERA 2.0 and REVEAL Lite 2 had acceptable predictive value with a C-index >0.7 (table). Adjusted for general and SSc-specific variables, all models were acceptable (table, fig. 1).Numerically, COMPERA 2.0 and REVEAL Lite 2 were the most accurate to predict mortality (table, fig. 1). Hazard ratios increased with higher risk scores (fig. 2). However, COMPERA 2.0 and REVEAL Lite 2 did not significantly discriminate the lower risk groups (fig. 2).

Conclusion: In SSc-PAH, we suggest that risk stratification at time of PAH diagnosis should take general and SSc-specific variables into account. The COMPERA 2.0 and REVEAL Lite 2 risk stratification models perform best when used as stand-alone tools. Neither requires invasive measurements, making them easily applicable in clinical practice. Importantly, these models identify patients in the high-risk group where aggressive upfront treatment is recommended.

References:
1Humbert, Eur Heart J, 2022
2Hoeper, Eur Respir J, 2022
3Benza, Chest, 2021

Supporting image 1

Table: Harrell’s C-index and AUC in the four approaches

Supporting image 2

Figure 1: ROC curve with AUC in the four multivariable Cox regression models

Supporting image 3

Figure 2: Forest plots of the multivariable cox regression models


Disclosures: H. Jenssen Bjørkekjær: Janssen, 5; C. Bruni: AbbVie/Abbott, 5, Boehringer-Ingelheim, 2, 12, Travel Support, Eli Lilly, 6; C. Brunborg: None; P. Carreira: None; P. Airò: Boehringer-Ingelheim, 2, 5, 6, Bristol-Myers Squibb(BMS), 2, 5, 6, CSL Behring, 2, 5, 6, Janssen-Cilag, 2, 5, 6, Novartis, 2, 5, 6, Roche, 2, 5, 6; C. Simeon-Aznar: None; M. Truchetet: AbbVie/Abbott, 2, 6, Boehringer-Ingelheim, 2, 6, Gilead, 5, 6, Merck/MSD, 6, UCB, 6, 12, support for conferences; A. Giollo: Eli Lilly, 6, Galapagos, 2, 6, Novartis, 2, Sandoz, 2; A. Balbir-Gurman: None; M. Martin: Boehringer-Ingelheim, 6, GlaxoSmithKlein(GSK), 6; C. Denton: AbbVie, 2, Acceleron, 2, Arxx Therapeutics, 5, Bayer, 2, Boehringer-Ingelheim, 2, 6, Corbus, 2, 6, CSL Behring, 2, 5, GlaxoSmithKline, 2, 5, Horizon Therapeutics, 2, Inventiva, 2, 5, Janssen, 6, Roche, 2, Sanofi, 2, Servier, 5; A. Gabrielli: Boehringer-Ingelheim, 12, Educational Grants, Janssen, 12, Educational Grants, Roche, 12, Educational Grants; H. Fretheim: actelion, 5, bayer, 2, Boehringer-Ingelheim, 6, GlaxoSmithKlein(GSK), 5; I. Barua: None; H. Bitter: Boehringer-Ingelheim, 6; O. Midtvedt: None; T. Garen: None; K. Broch: Amgen, 2, 6, AstraZeneca, 2, 6, Boehringer-Ingelheim, 2, 6, Novartis, 2, 6, Orion Pharma, 2, 6, Pfizer, 2, 6, Pharmacosmos, 2, 6; A. Andreassen: Amgen, 2, 6, Janssen, 2, 6, Novartis, 2, 6, Orion Pharma, 2, 6, Pfizer, 2, 6; Y. Tanaka: AbbVie, 6, AstraZeneca, 6, BMS, 6, Boehringer-Ingelheim, 6, Chugai, 5, 6, Eisai, 5, 6, Eli Lilly, 6, Gilead, 6, GSK, 6, Mitsubishi-Tanabe, 5, Pfizer, 6, Taiho, 6, Taisho, 5, 6; G. Riemekasten: None; U. Müller-Ladner: None; m. Matucci Cerinic: accelerong, 2, 6, actelion, 2, 6, bayer, 2, 6, biogen, 2, 6, Boehringer-Ingelheim, 2, 6, Chemomab, 2, 6, corbus, 2, 6, CSL Behring, 2, 6, Eli Lilly, 2, 6, galapagos, 2, 6, Inventiva, 2, 6, Janssen, 2, 6, Merck/MSD, 2, 6, Mitsubishi, 2, 6, Pfizer, 2, 6, regeneron, 2, 6, Roche, 2, 6, samsung, 2, 6; I. Castellvi: None; E. Siegert: None; E. Hachulla: Bayer, 2, CSL Behring, 5, GlaxoSmithKlein(GSK), 2, 5, 6, johnson&Johnson, 2, 5, 6, Novartis, 2, 5, Otsuka, 6, Roche-Chugai, 2, 5, 6, sanofi-genzyme, 2, 5, Sobi, 5; O. Distler: 4P-Pharma, 2, 5, 6, AbbVie, 2, 5, 6, Acceleron, 2, 5, 6, Alcimed, 2, 5, 6, Altavant Sciences, 2, 5, 6, Amgen, 2, 5, 6, AnaMar, 2, 5, 6, Arxx, 2, 5, 6, AstraZeneca, 2, 5, 6, Bayer, 2, 5, 6, Blade Therapeutics, 2, 5, 6, Boehringer Ingelheim, 2, 5, 6, Citus AG, 12, Co-Founder, Corbus Pharmaceuticals, 2, 5, 6, CSL Behring, 2, 5, 6, Galapagos, 2, 5, 6, Galderma, 2, 5, 6, Glenmark, 2, 5, 6, Gossamer, 2, 5, 6, Horizon Therapeutics, 2, 5, 6, Janssen, 2, 5, 6, Kymera, 2, 5, 6, Lupin, 2, 5, 6, Medscape, 2, 5, 6, Miltenyi Biotec, 2, 5, 6, Mitsubishi Tanabe, 2, 5, 6, MSD, 2, 5, 6, Novartis, 2, 5, 6, Patent issued “mir-29 for the treatment of systemic sclerosis” (US8247389, EP2331143), 10, Prometheus Biosciences, 2, 5, 6, Redx Pharma, 2, 5, 6, Roivant, 2, 5, 6, Topadur, 2, 5, 6; A. Hoffmann-Vold: Arxx Therapeutics, 2, Boehringer-Ingelheim, 2, 5, 6, 12, Support for travel, Genentech, 2, Janssen, 2, 5, 6, Medscape, 2, 6, 12, Support for travel, Roche, 2, 6, 12, Support for travel.

To cite this abstract in AMA style:

Jenssen Bjørkekjær H, Bruni C, Brunborg C, Carreira P, Airò P, Simeon-Aznar C, Truchetet M, Giollo A, Balbir-Gurman A, Martin M, Denton C, Gabrielli A, Fretheim H, Barua I, Bitter H, Midtvedt O, Garen T, Broch K, Andreassen A, Tanaka Y, Riemekasten G, Müller-Ladner U, Matucci Cerinic m, Castellvi I, Siegert E, Hachulla E, Distler O, Hoffmann-Vold A. Comparison of Four Risk Stratification Models for Prediction of Mortality in Systemic Sclerosis-associated Pulmonary Arterial Hypertension in the EUSTAR Cohort [abstract]. Arthritis Rheumatol. 2023; 75 (suppl 9). https://acrabstracts.org/abstract/comparison-of-four-risk-stratification-models-for-prediction-of-mortality-in-systemic-sclerosis-associated-pulmonary-arterial-hypertension-in-the-eustar-cohort/. Accessed .
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