Low morphometric complexity of emphysematous lesions predicts survival in chronic obstructive pulmonary disease patients.

Abstract

To investigate whether morphometric complexity in the lung can predict survival and act as a new prognostic marker in patients with chronic obstructive pulmonary disease (COPD). COPD (n = 302) patients were retrospectively reviewed. All patients underwent volumetric computed tomography and pulmonary function tests at enrollment (2005-2015). For complexity analysis, we applied power law exponent of the emphysema size distribution (D_size) as well as box-counting fractal dimension (D_box3D) analysis. Patients' survival at February 2017 was ascertained. Univariate and multivariate Cox proportional hazards analyses were performed, and prediction performances of various combinatorial models were compared. Patients were 66 ± 6 years old, had 41 ± 28 pack-years' smoking history and variable GOLD stages (n = 20, 153, 108 and 21 in stages I-IV). The median follow-up time was 6.1 years (range: 0.2-11.6 years). Sixty-three patients (20.9%) died, of whom 35 died of lung-related causes. In univariate Cox analysis, lower D_size and D_box3D were significantly associated with both all-cause and lung-related mortality (both p < 0.001). In multivariate analysis, the backward elimination method demonstrated that D_box3D, along with age and the BODE index, was an independent predictor of survival (p = 0.014; HR, 2.08; 95% CI, 1.16-3.71). The contributions of D_size and D_box3D to the combinatorial survival model were comparable with those of the emphysema index and lung-diffusing capacity. Low morphometric complexity in the lung is a predictor of survival in patients with COPD. • A newly suggested method for quantifying lung morphometric complexity is feasible. • Morphometric complexity measured on chest CT images predicts COPD patients' survival. • Complexity, diffusing capacity and emphysema index contribute similarly to the survival model.