Predictive factors of mortality in patients with idiopathic pulmonary fibrosis treated with antifibrotics: a novel prognostic scoring system
Main Article Content
Keywords
Idiopathic pulmonary fibrosis, Mortality, Prognosis
Abstract
Background and aim: Any test that provides sufficient prognostic information to guide treatment decisions in idiopathic pulmonary fibrosis (IPF) is not available. The aim of our study was to determine the predictive factors of mortality in patients with IPF treated with antifibrotics. Methods: Patients with diagnosis of IPF who were treated with antifibrotics between 2016 – 2021 were included in the study. Demographic, clinical and laboratory characteristics of the patients was derived from hospital records retrospectively. Kaplan Meier and multivariate cox regression analysis were achieved for detection of mortality predictors. Results: Study population was composed of 119 IPF patients with a male predominance of 80.7% (n=96). Mean age of the patients was 67.9 ± 7.07 years. On univariate analysis, sex was not a significant predictor of mortality (HR 1.79; 95% CI: 0.87 – 3.69, p =0.11). BMI ≤ 26,6 m2/kg, DLCO ≤ 3.11 ml/mmHg/min, age over 62 years, 6DWT ≤ 382 meters, NLR ≤ 2.67 and PDW ≤ 16.7% were found to be significant for predicting mortality. On multivariate cox regression analysis four parameters remained significant for prediction of mortality: RDW > 14%, NLR ≤ 2.67, BMI ≤ 26,6 m2/kg and DLCO ≤ 3.11 ml/mmHg/min (respectively, HR: 2.0. 95% CI: 1.02 – 3.91, p=0.44; HR: 2.68. 95% CI: 1.48 – 4.85, p=0.001, HR: 2.07. 95% CI: 1.14 – 3.76, p=0.02, HR: 3.46. 95% CI: 1.85 – 6.47, p<0.001). A scoring system with these parameters discriminated patients with worse prognosis with a sensitivity of 89.1 % and a specificity of 65.8 % when total point was over 2 (AUC0.83, p<0.001). Conclusions In this study, DLCO, BMI, RDW and NLR levels significantly predicted mortality in IPF patients. Along with GAP index, scoring system with these simple parameters may give information about the prognosis of an IPF patient treated with antifibrotics.
References
2. Ley B, Bradford WZ, Vittinghoff E, Weycker D, du Bois RM, Collard HR. Predictors of Mortality Poorly Predict Common Measures of Disease Progression in Idiopathic Pulmonary Fibrosis. Am J Respir Crit Care Med 2016; 194(6):711-8.
3. Ley B, Bradford WZ, Weycker D, Vittinghoff E, du Bois RM, Collard HR. Unified baseline and longitudinal mortality prediction in idiopathic pulmonary fibrosis. Eur Respir J 2015; 45(5):1374-81.
4. du Bois RM, Weycker D, Albera C, et al. Ascertainment of individual risk of mortality for patients with idiopathic pulmonary fibrosis. Am J Respir Crit Care Med 2011; 184(4):459-66.
5. Wells AU, Desai SR, Rubens MB, et al. Idiopathic pulmonary fibrosis: a composite physiologic index derived from disease extent observed by computed tomography. Am J Respir Crit Care Med 2003; 167(7):962-9.
6. Mura M, Porretta MA, Bargagli E, et al. Predicting survival in newly diagnosed idiopathic pulmonary fibrosis: a 3-year prospective study. Eur Respir J 2012; 40(1):101-9.
7. du Bois RM, Weycker D, Albera C, et al. Six-minute-walk test in idiopathic pulmonary fibrosis: test validation and minimal clinically important difference. Am J Respir Crit Care Med 2011; 183(9):1231-7.
8. Oldham JM, Ma SF, Martinez FJ, et al. TOLLIP, MUC5B, and the Response to N-Acetylcysteine among Individuals with Idiopathic Pulmonary Fibrosis. Am J Respir Crit Care Med 2015; 192(12):1475-82.
9. Peljto AL, Zhang Y, Fingerlin TE, et al. Association between the MUC5B promoter polymorphism and survival in patients with idiopathic pulmonary fibrosis. Jama 2013; 309(21):2232-9.
10. Ley B, Brown KK, Collard HR. Molecular biomarkers in idiopathic pulmonary fibrosis. Am J Physiol Lung Cell Mol Physiol 2014; 307(9):L681-91.
11. Funke-Chambour M, Azzola A, Adler D, et al. Idiopathic Pulmonary Fibrosis in Switzerland: Diagnosis and Treatment. Respiration 2017; 93(5):363-78.
12. Ley B, Ryerson CJ, Vittinghoff E, et al. A multidimensional index and staging system for idiopathic pulmonary fibrosis. Ann Intern Med 2012; 156(10):684-91.
13. Ryerson CJ, Vittinghoff E, Ley B, et al. Predicting survival across chronic interstitial lung disease: the ILD-GAP model. Chest 2014; 145(4):723-28.
14. Graham BL, Steenbruggen I, Miller MR, et al. Standardization of Spirometry 2019 Update. An Official American Thoracic Society and European Respiratory Society Technical Statement. Am J Respir Crit Care Med 2019; 200(8):e70-e88.
15. Redente EF, Jacobsen KM, Solomon JJ, et al. Age and sex dimorphisms contribute to the severity of bleomycin-induced lung injury and fibrosis. Am J Physiol Lung Cell Mol Physiol 2011; 301(4):L510-8.
16. Lee JW, Shehu E, Gjonbrataj J, et al. Clinical findings and outcomes in patients with possible usual interstitial pneumonia. Respir Med 2015; 109(4):510-6.
17. Zaman T, Moua T, Vittinghoff E, Ryu JH, Collard HR, Lee J. S. Differences in Clinical Characteristics and Outcomes Between Men and Women With Idiopathic Pulmonary Fibrosis: A Multicenter Retrospective Cohort Study. Chest 2020; 158(1):245-51.
18. Moua T, Zamora Martinez AC, Baqir M, Vassallo R, Limper AH, Ryu JH. Predictors of diagnosis and survival in idiopathic pulmonary fibrosis and connective tissue disease-related usual interstitial pneumonia. Respir Res 2014; 15(1):154.
19. Barlo NP, van Moorsel CH, van den Bosch JM, Grutters JC. Predicting prognosis in idiopathic pulmonary fibrosis. Sarcoidosis Vasc Diffuse Lung Dis 2010; 27(2):85-95.
20. Dempsey TM, Payne S, Sangaralingham L, Yao X, Shah N D, Limper AH. Adoption of the Antifibrotic Medications Pirfenidone and Nintedanib for Patients with Idiopathic Pulmonary Fibrosis. Ann Am Thorac Soc 2021; 18(7):1121-28.
21. Moon SW, Kim SY, Chung MP, et al. Longitudinal Changes in Clinical Features, Management, and Outcomes of Idiopathic Pulmonary Fibrosis. A Nationwide Cohort Study. Ann Am Thorac Soc 2021; 18(5):780-87.
22. Harari S, Caminati A, Confalonieri M, et al. The prognostic role of Gender-Age-Physiology system in idiopathic pulmonary fibrosis patients treated with pirfenidone. Clin Respir J 2019; 13(3):166-73.
23. Abe M, Tsushima K, Yoshioka K, et al. The Gender-Age-Physiology system as a prognostic model in patients with idiopathic pulmonary fibrosis treated with nintedanib: a longitudinal cohort study. Adv Respir Med 2020; 88(5):369-76.
24. Suzuki Y, Mori K, Aono Y, et al. Combined assessment of the GAP index and body mass index at antifibrotic therapy initiation for prognosis of idiopathic pulmonary fibrosis. Sci Rep 2021; 11(1):18579.
25. Moua T, Lee AS, Ryu JH. Comparing effectiveness of prognostic tests in idiopathic pulmonary fibrosis. Expert Rev Respir Med 2019; 13(10):993-1004.
26. Alakhras M, Decker PA, Nadrous HF, Collazo-Clavell M, Ryu JH. Body mass index and mortality in patients with idiopathic pulmonary fibrosis. Chest 2007; 131(5):1448-53.
27. Awano N, Jo T, Yasunaga H, et al. Body mass index and in-hospital mortality in patients with acute exacerbation of idiopathic pulmonary fibrosis. ERJ Open Res 2021; 7(2).
28. Nakatsuka Y, Handa T, Kokosi M, et al. The Clinical Significance of Body Weight Loss in Idiopathic Pulmonary Fibrosis Patients. Respiration 2018; 96(4):338-47.
29. Kulkarni T, Yuan K, Tran-Nguyen TK, et al. Decrements of body mass index are associated with poor outcomes of idiopathic pulmonary fibrosis patients. PLoS One 2019; 14(10):e0221905.
30. Suzuki Y, Yoshimura K, Enomoto Y, et al. Distinct profile and prognostic impact of body composition changes in idiopathic pulmonary fibrosis and idiopathic pleuroparenchymal fibroelastosis. Sci Rep 2018; 8(1):14074.
31. Tokgoz Akyıl F, Sevim T, Akman C, et al. The predictors of mortality in IPF - Does emphysema change the prognosis? Sarcoidosis Vasc Diffuse Lung Dis 2016; 33(3):267-74.
32. Le Rouzic O, Bendaoud S, Chenivesse C, Rémy J. and Wallaert B. Prognostic value of the initial chest high-resolution CT pattern in idiopathic pulmonary fibrosis. Sarcoidosis Vasc Diffuse Lung Dis 2016; 32(4):353-9.
33. Chen Y, Cai J, Zhang M, Yan X. Prognostic Role of NLR, PLR and MHR in Patients With Idiopathic Pulmonary Fibrosis. Front Immunol 2022; 13:882217.
34. Nathan SD, Mehta J, Stauffer J, et al. Changes in Neutrophil-Lymphocyte or Platelet-Lymphocyte Ratios and Their Associations with Clinical Outcomes in Idiopathic Pulmonary Fibrosis. J Clin Med 2021; 10(7).
35. D'Alessandro M, Bergantini L, Carleo A, et al. Neutrophil-to-lymphocyte ratio in bronchoalveolar lavage from IPF patients: a novel prognostic biomarker? Minerva Med 2022; 113(3):526-31.
36. Nathan SD, Reffett T, Brown AW, et al. The red cell distribution width as a prognostic indicator in idiopathic pulmonary fibrosis. Chest 2013; 143(6):1692-98.
37. Karampitsakos T, Torrisi S, Antoniou K, et al. Increased monocyte count and red cell distribution width as prognostic biomarkers in patients with Idiopathic Pulmonary Fibrosis. Respir Res 2021; 22(1):140.
38. Clynick B, Corte TJ, Jo HE, et al. Biomarker signatures for progressive idiopathic pulmonary fibrosis. Eur Respir J 2022; 59(3).
39. Torrisi SE, Vancheri A, Pavone M, Sambataro G, Palmucci S, Vancheri C. Comorbidities of IPF: How do they impact on prognosis. Pulm Pharmacol Ther 2018; 53:6-11.