Mortality Risk Prediction in Scleroderma-Related Interstitial Lung Disease

The SADL Model

Julie Morisset, Eric Vittinghoff, Brett M. Elicker, Xiaowen Hu, Stephanie Le, Jay H Ryu, Kirk D. Jones, Anna Haemel, Jeffrey A. Golden, Francesco Boin, Brett Ley, Paul J. Wolters, Talmadge E. King, Harold R. Collard, Joyce S. Lee

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

Background Interstitial lung disease (ILD) is an important cause of morbidity and mortality in patients with scleroderma (Scl). Risk prediction and prognostication in patients with Scl-ILD are challenging because of heterogeneity in the disease course. Methods We aimed to develop a clinical mortality risk prediction model for Scl-ILD. Patients with Scl-ILD were identified from two ongoing longitudinal cohorts: 135 patients at the University of California, San Francisco (derivation cohort) and 90 patients at the Mayo Clinic (validation cohort). Using these two separate cohorts, a mortality risk prediction model was developed and validated by testing every potential candidate Cox model, each including three or four variables of a possible 19 clinical predictors, for time to death. Model discrimination was assessed using the C-index. Results Three variables were included in the final risk prediction model (SADL): ever smoking history, age, and diffusing capacity of the lung for carbon monoxide (% predicted). This continuous model had similar performance in the derivation (C-index, 0.88) and validation (C-index, 0.84) cohorts. We created a point scoring system using the combined cohort (C-index, 0.82) and used it to identify a classification with low, moderate, and high mortality risk at 3 years. Conclusions The SADL model uses simple, readily accessible clinical variables to predict all-cause mortality in Scl-ILD.

Original languageEnglish (US)
Pages (from-to)999-1007
Number of pages9
JournalChest
Volume152
Issue number5
DOIs
StatePublished - Nov 1 2017

Fingerprint

Interstitial Lung Diseases
Mortality
Lung Volume Measurements
San Francisco
Carbon Monoxide
Proportional Hazards Models
Smoking
History
Morbidity

Keywords

  • interstitial lung disease
  • prognosis
  • risk prediction
  • systemic sclerosis

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine
  • Critical Care and Intensive Care Medicine
  • Cardiology and Cardiovascular Medicine

Cite this

Morisset, J., Vittinghoff, E., Elicker, B. M., Hu, X., Le, S., Ryu, J. H., ... Lee, J. S. (2017). Mortality Risk Prediction in Scleroderma-Related Interstitial Lung Disease: The SADL Model. Chest, 152(5), 999-1007. https://doi.org/10.1016/j.chest.2017.06.009

Mortality Risk Prediction in Scleroderma-Related Interstitial Lung Disease : The SADL Model. / Morisset, Julie; Vittinghoff, Eric; Elicker, Brett M.; Hu, Xiaowen; Le, Stephanie; Ryu, Jay H; Jones, Kirk D.; Haemel, Anna; Golden, Jeffrey A.; Boin, Francesco; Ley, Brett; Wolters, Paul J.; King, Talmadge E.; Collard, Harold R.; Lee, Joyce S.

In: Chest, Vol. 152, No. 5, 01.11.2017, p. 999-1007.

Research output: Contribution to journalArticle

Morisset, J, Vittinghoff, E, Elicker, BM, Hu, X, Le, S, Ryu, JH, Jones, KD, Haemel, A, Golden, JA, Boin, F, Ley, B, Wolters, PJ, King, TE, Collard, HR & Lee, JS 2017, 'Mortality Risk Prediction in Scleroderma-Related Interstitial Lung Disease: The SADL Model', Chest, vol. 152, no. 5, pp. 999-1007. https://doi.org/10.1016/j.chest.2017.06.009
Morisset, Julie ; Vittinghoff, Eric ; Elicker, Brett M. ; Hu, Xiaowen ; Le, Stephanie ; Ryu, Jay H ; Jones, Kirk D. ; Haemel, Anna ; Golden, Jeffrey A. ; Boin, Francesco ; Ley, Brett ; Wolters, Paul J. ; King, Talmadge E. ; Collard, Harold R. ; Lee, Joyce S. / Mortality Risk Prediction in Scleroderma-Related Interstitial Lung Disease : The SADL Model. In: Chest. 2017 ; Vol. 152, No. 5. pp. 999-1007.
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abstract = "Background Interstitial lung disease (ILD) is an important cause of morbidity and mortality in patients with scleroderma (Scl). Risk prediction and prognostication in patients with Scl-ILD are challenging because of heterogeneity in the disease course. Methods We aimed to develop a clinical mortality risk prediction model for Scl-ILD. Patients with Scl-ILD were identified from two ongoing longitudinal cohorts: 135 patients at the University of California, San Francisco (derivation cohort) and 90 patients at the Mayo Clinic (validation cohort). Using these two separate cohorts, a mortality risk prediction model was developed and validated by testing every potential candidate Cox model, each including three or four variables of a possible 19 clinical predictors, for time to death. Model discrimination was assessed using the C-index. Results Three variables were included in the final risk prediction model (SADL): ever smoking history, age, and diffusing capacity of the lung for carbon monoxide ({\%} predicted). This continuous model had similar performance in the derivation (C-index, 0.88) and validation (C-index, 0.84) cohorts. We created a point scoring system using the combined cohort (C-index, 0.82) and used it to identify a classification with low, moderate, and high mortality risk at 3 years. Conclusions The SADL model uses simple, readily accessible clinical variables to predict all-cause mortality in Scl-ILD.",
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T2 - The SADL Model

AU - Morisset, Julie

AU - Vittinghoff, Eric

AU - Elicker, Brett M.

AU - Hu, Xiaowen

AU - Le, Stephanie

AU - Ryu, Jay H

AU - Jones, Kirk D.

AU - Haemel, Anna

AU - Golden, Jeffrey A.

AU - Boin, Francesco

AU - Ley, Brett

AU - Wolters, Paul J.

AU - King, Talmadge E.

AU - Collard, Harold R.

AU - Lee, Joyce S.

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N2 - Background Interstitial lung disease (ILD) is an important cause of morbidity and mortality in patients with scleroderma (Scl). Risk prediction and prognostication in patients with Scl-ILD are challenging because of heterogeneity in the disease course. Methods We aimed to develop a clinical mortality risk prediction model for Scl-ILD. Patients with Scl-ILD were identified from two ongoing longitudinal cohorts: 135 patients at the University of California, San Francisco (derivation cohort) and 90 patients at the Mayo Clinic (validation cohort). Using these two separate cohorts, a mortality risk prediction model was developed and validated by testing every potential candidate Cox model, each including three or four variables of a possible 19 clinical predictors, for time to death. Model discrimination was assessed using the C-index. Results Three variables were included in the final risk prediction model (SADL): ever smoking history, age, and diffusing capacity of the lung for carbon monoxide (% predicted). This continuous model had similar performance in the derivation (C-index, 0.88) and validation (C-index, 0.84) cohorts. We created a point scoring system using the combined cohort (C-index, 0.82) and used it to identify a classification with low, moderate, and high mortality risk at 3 years. Conclusions The SADL model uses simple, readily accessible clinical variables to predict all-cause mortality in Scl-ILD.

AB - Background Interstitial lung disease (ILD) is an important cause of morbidity and mortality in patients with scleroderma (Scl). Risk prediction and prognostication in patients with Scl-ILD are challenging because of heterogeneity in the disease course. Methods We aimed to develop a clinical mortality risk prediction model for Scl-ILD. Patients with Scl-ILD were identified from two ongoing longitudinal cohorts: 135 patients at the University of California, San Francisco (derivation cohort) and 90 patients at the Mayo Clinic (validation cohort). Using these two separate cohorts, a mortality risk prediction model was developed and validated by testing every potential candidate Cox model, each including three or four variables of a possible 19 clinical predictors, for time to death. Model discrimination was assessed using the C-index. Results Three variables were included in the final risk prediction model (SADL): ever smoking history, age, and diffusing capacity of the lung for carbon monoxide (% predicted). This continuous model had similar performance in the derivation (C-index, 0.88) and validation (C-index, 0.84) cohorts. We created a point scoring system using the combined cohort (C-index, 0.82) and used it to identify a classification with low, moderate, and high mortality risk at 3 years. Conclusions The SADL model uses simple, readily accessible clinical variables to predict all-cause mortality in Scl-ILD.

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