Latent class analysis to define radiological subgroups in pulmonary nontuberculous mycobacterial disease

BMC Pulm Med. 2018 Aug 31;18(1):145. doi: 10.1186/s12890-018-0675-8.

Abstract

Background: Nontuberculous mycobacterial (NTM) pulmonary disease has conventionally been classified on the basis of radiology into fibrocavitary and nodular-bronchiectatic disease. Whilst being of great clinical utility, this may not capture the full spectrum of radiological appearances present. The aim of this study was to use latent class analysis (LCA) as an unbiased method of grouping subjects with NTM-pulmonary disease based on their CT features and to compare the clinical characteristics of these groups.

Methods: Individuals with NTM-pulmonary disease were recruited and a contemporaneous CT scan obtained. This was scored using an NTM-specific scoring system. LCA was used to identify groups with common radiological characteristics. The analysis was then repeated in an independent cohort.

Results: Three classes were identified in the initial cohort of 85 subjects. Group 1 was characterised by severe bronchiectasis, cavitation and aspergillomas, Group 2 by relatively minor radiological changes, and Group 3 by predominantly bronchiectasis only. These findings were reproduced in an independent cohort of 62 subjects. Subjects in Group 1 had a lower BMI and serum albumin, higher serum CRP, and a higher mortality.

Conclusions: These findings suggest that NTM-pulmonary may be divided into three radiological subgroups, and that important clinical and survival differences exist between these groups.

Keywords: High resolution computed tomography; Latent class analysis; Nontuberculous mycobacteria.

MeSH terms

  • Aged
  • Female
  • Humans
  • Latent Class Analysis
  • Lung / diagnostic imaging
  • Lung / pathology
  • Lung Diseases / diagnostic imaging*
  • Lung Diseases / microbiology
  • Male
  • Middle Aged
  • Mycobacterium Infections, Nontuberculous / diagnostic imaging*
  • Nontuberculous Mycobacteria
  • Survival Analysis
  • Tomography, X-Ray Computed / methods*