Comparisons of Prognosis between Surgically and Clinically Diagnosed Idiopathic Pulmonary Fibrosis Using Gap Model: A Korean National Cohort Study

Comparing effectiveness of prognostic tests in idiopathic pulmonary fibrosis

Introduction: Idiopathic pulmonary fibrosis (IPF) is a debilitating and progressive fibrotic interstitial lung disease often resulting in death over several years. Prediction of disease course or survival remains of keen interest for clinicians and patients though a commonly used test or tool remain elusive. Areas covered: We undertook a comprehensive review of the published literature highlighting prognostic indicators and predictors of survival in IPF. Baseline and longitudinal clinical, functional, histopathologic, and radiologic findings have been extensively studied as prognostic predictors, both individually and in composite models. Recent approaches include automated quantifiable radiologic scoring, circulating biomarkers, and genetic polymorphisms or abnormalities. This review highlights individual and composite predictors and their relative utility in clinical practice and research studies. Expert opinion: There is a growing body of knowledge highlighting readily available individual and composite predictors of outcome, though none have come to the forefront for common clinical use. Recent advances include quantitative imaging analysis, circulating serologic markers, and genetic testing, which may be more standardized and less prone to lead-time bias or related complications and comorbidities.

Predicting Outcome in Idiopathic Pulmonary Fibrosis: Addition of Fibrotic Score at Thin-Section CT of the Chest to Gender, Age, and Physiology Score Improves the Prediction Model

Purpose

To assess the impact of adding thin-section CT-derived semiquantitative fibrotic score to gender, age, and physiology (GAP) model for predicting survival in idiopathic pulmonary fibrosis (IPF).

Materials and Methods

In this retrospective study of 194 patients with IPF, primary outcome was transplant-free survival. Two thoracic radiologists visually estimated the percentage of reticulation and honeycombing at baseline thin-section CT, which were added to give fibrotic score. For analysis, fibrotic score cutoff (x) determined by using receiver operating characteristic analysis categorized patients into group A (<x) and group B (≥x). Another categorization based on GAP score created group 1 (score 0-3) and group 2 (score >3). Combining the above categories gave four groups (A1, A2, B1, B2). Kaplan-Meier survival analysis was performed with comparison statistics (log-rank test), and hazard ratios were calculated by using the Cox model.

Results

The study patients included 141 men (72.7%), with average age of 66.1 years ± 9.1 (standard deviation). Eighty-four patients (43.3%) has stage I disease with a median follow up of 3.3 years. The interobserver agreement for thin-section CT fibrotic score was substantial (83.3%; κ = 0.64). The optimal cutoff for fibrotic score was 25% (x), with area under the curve of 0.654 (95% confidence interval [CI]: 0.569, 0.74). Survival for group A1 was significantly better than in the other three groups (P < .001). The hazard ratios for respective groups were as follows: B1 was 4.03 (95% CI: 2.02, 8.07), A2 was 4.10 (95% CI: 1.89, 8.87), and B2 was 5.62 (95% CI: 2.86, 11.06) (P < .001 for all). Within the group with GAP score less than or equal to 3 (A1, B1), participants with higher fibrotic score (B1) had four times the increased risk of death or transplantation (P < .001).

Conclusion

Incorporating semiquantitative fibrotic score from thin-section CT to GAP score provides an improved prediction model for survival in idiopathic pulmonary fibrosis.© RSNA, 2019See also the commentary by Chung in this issue.

Underlying and immediate causes of death in patients with idiopathic pulmonary fibrosis

Background

The most common cause of death of patients with idiopathic pulmonary fibrosis (IPF) has been reported to be the lung disease itself and mortality from IPF appears to be increasing. However, the causes of death in patients with IPF taking into account differences between genders and smoking histories as well as disease progression, have not been previously explored.

Methods

Retrospective data from hospital register and death certificates from national database of IPF patients treated in Kuopio University Hospital (KUH) from 2002 to 2012 were collected. Mortality was also explored from the death registry database via ICD-10 code J84 revealing the numbers of deaths from pulmonary fibrosis in Finland from 1998 to 2015.

Results

Out of 117 deaths, 26.5% were females and 73.5% males in KUH. The most common underlying causes of death were IPF 67.5% and ischemic heart diseases 14.8%. More males died for reasons other than IPF (39.5%) compared to females (12.9%) (p = 0.007). Pneumonia as the immediate cause of death was more common in males (27.9%) than in females (3.2%) (p = 0.004) and in ex-smokers (32.7%) compared to non-smokers (9.3%) (p = 0.007). Death register based mortality from pulmonary fibrosis is increasing in Finland.

Conclusions

Even though the overall mortality was higher in males with IPF, the disease-specific mortality for IPF was higher in females i.e. in males, comorbidities were more often the underlying causes of death. Pneumonia-triggered acute exacerbations of IPF may be associated with smoking and gender since females and non-smokers were less likely to succumb to pneumonia. We conclude that disease progression at the end of life may vary depending on smoking habits and gender.

Comparison of CPI and GAP models in patients with idiopathic pulmonary fibrosis: a nationwide cohort study

The clinical course of idiopathic pulmonary fibrosis (IPF) is difficult to predict, partly owing to its heterogeneity. Composite physiologic index (CPI) and gender-age-physiology (GAP) models are easy-to-use predictors of IPF progression. This study aimed to compare the predictive values of these two models. From 2003 to 2007, the Korean Interstitial Lung Disease (ILD) Study Group surveyed ILD patients using the 2002 ATS/ERS criteria. A total of 832 patients with IPF were enrolled in this study. CPI was calculated as follows: 91.0 − (0.65 × %DL_CO) − [0.53 × %FVC + [0.34 × %FEV₁. GAP stage was calculated based on gender (0–1 points), age (0–2 points), and two physiologic lung function parameters (0–5 points). The two models had similar significant predictive values for patients with IPF (p < 0.001). The area under the curve (AUC) was higher for CPI than GAP for prediction of 1-, 2-, and 3-year mortality in this study. The AUC was higher for surgically diagnosed IPF patients than for clinically diagnosed patients. However, neither CPI nor GAP yielded good predictions of outcomes; the AUC was approximately 0.61~0.65. Although both CPI and GAP stage are significantly useful predictors for IPF, they have limited capability to accurately predict outcomes.