Research ExplorerPublicationsUse of platelet inhibitors for digital ulcers related to sys...

Use of platelet inhibitors for digital ulcers related to systemic sclerosis: EUSTAR study on derivation and validation of the DU-VASC model

Standard

Use of platelet inhibitors for digital ulcers related to systemic sclerosis: EUSTAR study on derivation and validation of the DU-VASC model. / Garaiman, Alexandru; Steigmiller, Klaus; Gebhard, Catherine; Mihai, Carina; Dobrota, Rucsandra; Bruni, Cosimo; Matucci-Cerinic, Marco; Henes, Joerg; de Vries-Bouwstra, Jeska; Smith, Vanessa; Doria, Andrea; Allanore, Yannick; Dagna, Lorenzo; Anić, Branimir; Montecucco, Carlomaurizio; Kowal-Bielecka, Otylia; Martin, Mickael; Tanaka, Yoshiya; Hoffmann-Vold, Anna-Maria; Held, Ulrike; Distler, Oliver; Becker, Mike Oliver; EUSTAR Collaborators.

In: RHEUMATOLOGY, Vol. 62, No. SI, 06.02.2023, p. SI91-SI100.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Garaiman, A, Steigmiller, K, Gebhard, C, Mihai, C, Dobrota, R, Bruni, C, Matucci-Cerinic, M, Henes, J, de Vries-Bouwstra, J, Smith, V, Doria, A, Allanore, Y, Dagna, L, Anić, B, Montecucco, C, Kowal-Bielecka, O, Martin, M, Tanaka, Y, Hoffmann-Vold, A-M, Held, U, Distler, O, Becker, MO & EUSTAR Collaborators 2023, 'Use of platelet inhibitors for digital ulcers related to systemic sclerosis: EUSTAR study on derivation and validation of the DU-VASC model', RHEUMATOLOGY, vol. 62, no. SI, pp. SI91-SI100. https://doi.org/10.1093/rheumatology/keac405

APA

Garaiman, A., Steigmiller, K., Gebhard, C., Mihai, C., Dobrota, R., Bruni, C., Matucci-Cerinic, M., Henes, J., de Vries-Bouwstra, J., Smith, V., Doria, A., Allanore, Y., Dagna, L., Anić, B., Montecucco, C., Kowal-Bielecka, O., Martin, M., Tanaka, Y., Hoffmann-Vold, A-M., ... EUSTAR Collaborators (2023). Use of platelet inhibitors for digital ulcers related to systemic sclerosis: EUSTAR study on derivation and validation of the DU-VASC model. RHEUMATOLOGY, 62(SI), SI91-SI100. https://doi.org/10.1093/rheumatology/keac405

Vancouver

Garaiman A, Steigmiller K, Gebhard C, Mihai C, Dobrota R, Bruni C et al. Use of platelet inhibitors for digital ulcers related to systemic sclerosis: EUSTAR study on derivation and validation of the DU-VASC model. RHEUMATOLOGY. 2023 Feb 6;62(SI):SI91-SI100. https://doi.org/10.1093/rheumatology/keac405

Bibtex

@article{2251464d4c4b4debbced6d4868eee756,
title = "Use of platelet inhibitors for digital ulcers related to systemic sclerosis: EUSTAR study on derivation and validation of the DU-VASC model",
abstract = "OBJECTIVE: To develop and validate the prognostic prediction model DU-VASC to assist the clinicians in decision-making regarding the use of platelet inhibitors (PIs) for the management of digital ulcers in patients with systemic sclerosis. Secondly, to assess the incremental value of PIs as predictor.METHODS: We analysed patient data from the European Scleroderma Trials and Research group registry (one time point assessed). Three sets of derivation/validation cohorts were obtained from the original cohort. Using logistic regression, we developed a model for prediction of digital ulcers (DUs). C-Statistics and calibration plots were calculated to evaluate the prediction performance. Variable importance plots and the decrease in C-statistics were used to address the importance of the predictors.RESULTS: Of 3710 patients in the original cohort, 487 had DUs and 90 were exposed to PIs. For the DU-VASC model, which includes 27 predictors, we observed good calibration and discrimination in all cohorts (C-statistic = 81.1% [95% CI: 78.9%, 83.4%] for the derivation and 82.3% [95% CI: 779.3%, 85.3%] for the independent temporal validation cohort). Exposure to PIs was associated with absence of DUs and was the most important therapeutic predictor. Further important factors associated with absence of DUs were lower modified Rodnan skin score, anti-Scl-70 negativity and normal CRP. Conversely, the exposure to phosphodiesterase-5 inhibitor, prostacyclin analogues or endothelin receptor antagonists seemed to be associated with the occurrence of DUs. Nonetheless, previous DUs remains the most impactful predictor of DUs.CONCLUSION: The DU-VASC model, with good calibration and discrimination ability, revealed that PI treatment was the most important therapy-related predictor associated with reduced DU occurrence.",
author = "Alexandru Garaiman and Klaus Steigmiller and Catherine Gebhard and Carina Mihai and Rucsandra Dobrota and Cosimo Bruni and Marco Matucci-Cerinic and Joerg Henes and {de Vries-Bouwstra}, Jeska and Vanessa Smith and Andrea Doria and Yannick Allanore and Lorenzo Dagna and Branimir Ani{\'c} and Carlomaurizio Montecucco and Otylia Kowal-Bielecka and Mickael Martin and Yoshiya Tanaka and Anna-Maria Hoffmann-Vold and Ulrike Held and Oliver Distler and Becker, {Mike Oliver} and {EUSTAR Collaborators} and Ina K{\"o}tter",
note = "{\textcopyright} The Author(s) 2022. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.",
year = "2023",
month = feb,
day = "6",
doi = "10.1093/rheumatology/keac405",
language = "English",
volume = "62",
pages = "SI91--SI100",
journal = "RHEUMATOLOGY",
issn = "1462-0324",
publisher = "Oxford University Press",
number = "SI",

}

RIS

TY - JOUR

T1 - Use of platelet inhibitors for digital ulcers related to systemic sclerosis: EUSTAR study on derivation and validation of the DU-VASC model

AU - Garaiman, Alexandru

AU - Steigmiller, Klaus

AU - Gebhard, Catherine

AU - Mihai, Carina

AU - Dobrota, Rucsandra

AU - Bruni, Cosimo

AU - Matucci-Cerinic, Marco

AU - Henes, Joerg

AU - de Vries-Bouwstra, Jeska

AU - Smith, Vanessa

AU - Doria, Andrea

AU - Allanore, Yannick

AU - Dagna, Lorenzo

AU - Anić, Branimir

AU - Montecucco, Carlomaurizio

AU - Kowal-Bielecka, Otylia

AU - Martin, Mickael

AU - Tanaka, Yoshiya

AU - Hoffmann-Vold, Anna-Maria

AU - Held, Ulrike

AU - Distler, Oliver

AU - Becker, Mike Oliver

AU - EUSTAR Collaborators

AU - Kötter, Ina

N1 - © The Author(s) 2022. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

PY - 2023/2/6

Y1 - 2023/2/6

N2 - OBJECTIVE: To develop and validate the prognostic prediction model DU-VASC to assist the clinicians in decision-making regarding the use of platelet inhibitors (PIs) for the management of digital ulcers in patients with systemic sclerosis. Secondly, to assess the incremental value of PIs as predictor.METHODS: We analysed patient data from the European Scleroderma Trials and Research group registry (one time point assessed). Three sets of derivation/validation cohorts were obtained from the original cohort. Using logistic regression, we developed a model for prediction of digital ulcers (DUs). C-Statistics and calibration plots were calculated to evaluate the prediction performance. Variable importance plots and the decrease in C-statistics were used to address the importance of the predictors.RESULTS: Of 3710 patients in the original cohort, 487 had DUs and 90 were exposed to PIs. For the DU-VASC model, which includes 27 predictors, we observed good calibration and discrimination in all cohorts (C-statistic = 81.1% [95% CI: 78.9%, 83.4%] for the derivation and 82.3% [95% CI: 779.3%, 85.3%] for the independent temporal validation cohort). Exposure to PIs was associated with absence of DUs and was the most important therapeutic predictor. Further important factors associated with absence of DUs were lower modified Rodnan skin score, anti-Scl-70 negativity and normal CRP. Conversely, the exposure to phosphodiesterase-5 inhibitor, prostacyclin analogues or endothelin receptor antagonists seemed to be associated with the occurrence of DUs. Nonetheless, previous DUs remains the most impactful predictor of DUs.CONCLUSION: The DU-VASC model, with good calibration and discrimination ability, revealed that PI treatment was the most important therapy-related predictor associated with reduced DU occurrence.

AB - OBJECTIVE: To develop and validate the prognostic prediction model DU-VASC to assist the clinicians in decision-making regarding the use of platelet inhibitors (PIs) for the management of digital ulcers in patients with systemic sclerosis. Secondly, to assess the incremental value of PIs as predictor.METHODS: We analysed patient data from the European Scleroderma Trials and Research group registry (one time point assessed). Three sets of derivation/validation cohorts were obtained from the original cohort. Using logistic regression, we developed a model for prediction of digital ulcers (DUs). C-Statistics and calibration plots were calculated to evaluate the prediction performance. Variable importance plots and the decrease in C-statistics were used to address the importance of the predictors.RESULTS: Of 3710 patients in the original cohort, 487 had DUs and 90 were exposed to PIs. For the DU-VASC model, which includes 27 predictors, we observed good calibration and discrimination in all cohorts (C-statistic = 81.1% [95% CI: 78.9%, 83.4%] for the derivation and 82.3% [95% CI: 779.3%, 85.3%] for the independent temporal validation cohort). Exposure to PIs was associated with absence of DUs and was the most important therapeutic predictor. Further important factors associated with absence of DUs were lower modified Rodnan skin score, anti-Scl-70 negativity and normal CRP. Conversely, the exposure to phosphodiesterase-5 inhibitor, prostacyclin analogues or endothelin receptor antagonists seemed to be associated with the occurrence of DUs. Nonetheless, previous DUs remains the most impactful predictor of DUs.CONCLUSION: The DU-VASC model, with good calibration and discrimination ability, revealed that PI treatment was the most important therapy-related predictor associated with reduced DU occurrence.

U2 - 10.1093/rheumatology/keac405

DO - 10.1093/rheumatology/keac405

M3 - SCORING: Journal article

C2 - 35904554

VL - 62

SP - SI91-SI100

JO - RHEUMATOLOGY

JF - RHEUMATOLOGY

SN - 1462-0324

IS - SI

ER -