Risk factors for progression of pulmonary fibrosis: a single-centered, retrospective study

Abstract

Objective: This study aimed to identify clinical characteristics associated with the prevalence of progressive pulmonary fibrosis (PPF) in interstitial lung disease (ILD) and to develop a prognostic nomogram model for clinical use.

Methods: In this single-centered, retrospective study, we enrolled ILD patients with relatively comprehensive clinical data and assessed the incidence of PPF within a year using collected demographics, laboratory data, high-resolution computed tomography (HRCT), and pulmonary function test (PFT) results. We used a training cohort of ILD patients to identify early predictors of PPF and then validated them in an internal validation cohort and subsets of ILD patients using a multivariable logistic regression analysis. A prognostic nomogram was formulated based on these predictors, and the accuracy and efficiency were evaluated using the area under the receiver operating characteristic curve (AUC), calibration plot, and decision curve analysis (DCA).

Results: Among the enrolled patients, 120 (39.09%) cases had connective tissue disease-associated interstitial lung disease (CTD-ILD), 115 (37.46%) had non-idiopathic pulmonary fibrosis idiopathic interstitial pneumonia (non-IPF IIP), and 35 (11.4%) had hypersensitivity pneumonitis (HP). Overall, 118 (38.4%) cases experienced pulmonary fibrosis progression. We found that baseline DLco% pred (OR 0.92; 95% CI, 8.93-0.95) was a protective factor for ILD progression, whereas combined pneumonia (OR 4.57; 95% CI, 1.24-18.43), modified Medical Research Council dyspnea score (mMRC) (OR 4.9; 95% CI, 2.8-9.5), and high-resolution computed tomography (HRCT) score (OR 1.22; 95% CI, 1.07-1.42) were independent risk factors for PPF. The AUC of the proposed nomogram in the development cohort was 0.96 (95% CI, 0.94, 0.98), and the calibration plot showed good agreement between the predicted and observed incidence of PPF (Hosmer-Lemeshow test: P = 0.86).

Conclusion: ILD patients with combined pneumonia, low baseline DLco% pred, high mMRC marks, and high HRCT scores were at higher risk of progression. This nomogram demonstrated good discrimination and calibration, indicating its potential utility for clinical practice.

Keywords: ILD; interstitial lung diseases; prognosis; progressive pulmonary fibrosis; risk factors.

Figure 1

Reporting of observational studies in the epidemiology diagram.

Figure 2

Histogram of the percentage of each abnormality on HRCT in six regions among PPF/non-PPF: (A) upper right lung, (B) middle right lung, (C) lower right lung, (D) upper left lung, (E) middle left lung, (F) lower left lung, and the total percentage of lung parenchyma occupied by the disease in six regions among PPF/non-PPF (G).

Figure 3

Axial HRCT images of a 75-year-old male, on 29 October 2021 (A) and 4 October 2022 (B) showed peripheral and basilar predominant progressive pulmonary fibrosis with the increased extent of reticulation, traction bronchiectasis, and honeycombing.

Figure 4

Nomogram derived from multivariable analysis for predicting progressive fibrosis. The points from each of the four components of the nomogram: Combined pneumonia (0 = 0 point, 1 = 9.3 points), mMRC (0 = 0 point, 1 = 12.45 points, 2 = 24.9 points, 3 = 37.35 points, 4 = 49.8 points), DLco% pred (points = 100-0.625* DLco% pred), and HRCT score (points = 1.02* HRCT score), are the predicted progressive fibrosis obtained from each scale by referring to the corresponding value.

Figure 5

Calibration plots of nomogram showing predicted progressive fibrosis against actual progressive pulmonary fibrosis in the training set (A), and validation set (B). The AUC of the combined model, mMRC, combined pneumonia, HRCT score, and DLco% pred in the training set (C), and validation set (D); decision curve analysis for the combined model, mMRC, combined pneumonia, HRCT score, and DLco% pred in the training set (E), and validation set (F).