OBJECTIVE: Lung cancer patients with interstitial lung diseases (ILDs) who have undergone pulmonary resection often develop acute exacerbation of interstitial pneumonia (AE) in the post-operative period. To predict who is at high risk of AE, we propose a scoring system that evaluates the risk of AE in lung cancer patients with ILDs. METHODS: We derived a score for 30-day risk of AE onset after pulmonary resection in lung cancer patients with ILDs (n = 1,022; outcome: risk of AE) based on seven risk factors for AE that were identified in a previous retrospective multi-institutional cohort study. A logistic regression model was employed to develop a risk prediction model for AE. RESULTS: A risk score (RS) was derived: 5 × (history of AE) + 4 × (surgical procedures) + 4 × (UIP appearance in CT scan) + 3 × (male sex) + 3 × (preoperative steroid use) + 2 × (elevated serum sialylated carbohydrate antigen, KL-6 level) + 1 × (low vital capacity). The RS was shown to be moderately discriminatory with a c-index of 0.709 and accurate with the Hosmer-Lemeshow goodness-of-fit test (p = 0.907). The patients were classified into three groups: low risk (RS: 0-10; predicted probability <0.1; n = 439), intermediate risk (RS: 11-14; predicted probability 0.1-0.25; n = 559), and high risk (RS: 15-22; predicted probability >0.25; n = 24). CONCLUSION: Although further validation and refinement are needed, the risk score can be used in routine clinical practice to identify high risk individuals and to select proper treatment strategies.
OBJECTIVE:Lung cancerpatients with interstitial lung diseases (ILDs) who have undergone pulmonary resection often develop acute exacerbation of interstitial pneumonia (AE) in the post-operative period. To predict who is at high risk of AE, we propose a scoring system that evaluates the risk of AE in lung cancerpatients with ILDs. METHODS: We derived a score for 30-day risk of AE onset after pulmonary resection in lung cancerpatients with ILDs (n = 1,022; outcome: risk of AE) based on seven risk factors for AE that were identified in a previous retrospective multi-institutional cohort study. A logistic regression model was employed to develop a risk prediction model for AE. RESULTS: A risk score (RS) was derived: 5 × (history of AE) + 4 × (surgical procedures) + 4 × (UIP appearance in CT scan) + 3 × (male sex) + 3 × (preoperative steroid use) + 2 × (elevated serum sialylated carbohydrate antigen, KL-6 level) + 1 × (low vital capacity). The RS was shown to be moderately discriminatory with a c-index of 0.709 and accurate with the Hosmer-Lemeshow goodness-of-fit test (p = 0.907). The patients were classified into three groups: low risk (RS: 0-10; predicted probability <0.1; n = 439), intermediate risk (RS: 11-14; predicted probability 0.1-0.25; n = 559), and high risk (RS: 15-22; predicted probability >0.25; n = 24). CONCLUSION: Although further validation and refinement are needed, the risk score can be used in routine clinical practice to identify high risk individuals and to select proper treatment strategies.
Authors: Robert Timmerman; Rebecca Paulus; James Galvin; Jeffrey Michalski; William Straube; Jeffrey Bradley; Achilles Fakiris; Andrea Bezjak; Gregory Videtic; David Johnstone; Jack Fowler; Elizabeth Gore; Hak Choy Journal: JAMA Date: 2010-03-17 Impact factor: 56.272
Authors: Roland M du Bois; Derek Weycker; Carlo Albera; Williamson Z Bradford; Ulrich Costabel; Alex Kartashov; Lisa Lancaster; Paul W Noble; Ganesh Raghu; Steven A Sahn; Javier Szwarcberg; Michiel Thomeer; Dominique Valeyre; Talmadge E King Journal: Am J Respir Crit Care Med Date: 2011-08-15 Impact factor: 21.405
Authors: Talmadge E King; Jürgen Behr; Kevin K Brown; Roland M du Bois; Lisa Lancaster; Joao A de Andrade; Gerd Stähler; Isabelle Leconte; Sébastien Roux; Ganesh Raghu Journal: Am J Respir Crit Care Med Date: 2007-09-27 Impact factor: 21.405