BMC Infectious Diseases (Jun 2017)

Development and validation of a prognostic scoring model for Mycobacterium avium complex lung disease: an observational cohort study

  • Shogo Kumagai,
  • Akihiro Ito,
  • Toru Hashimoto,
  • Satoshi Marumo,
  • Hironobu Tokumasu,
  • Aya Kotani,
  • Haruka Yamaki,
  • Masahiro Shirata,
  • Koji Furuuchi,
  • Motonari Fukui,
  • Tadashi Ishida

DOI
https://doi.org/10.1186/s12879-017-2544-0
Journal volume & issue
Vol. 17, no. 1
pp. 1 – 9

Abstract

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Abstract Background Patients with Mycobacterium avium complex (MAC) lung disease (LD) have a heterogeneous prognosis. This study aimed to develop and validate a prognostic scoring model for these patients using independent risk factors for survival. Methods We retrospectively analyzed the data of patients with MAC-LD from two hospitals (cohort 1, n = 368; cohort 2, n = 118). Cohort 1 was evaluated using a multivariate Cox proportional hazards model to identify independent risk factors for overall survival (OS). A prognostic scoring model composed of these factors was developed, and cohort 1 was stratified into three groups according to risk using the log-rank test. Finally, the prognostic scoring model was validated using the data of cohort 2. Results Seven independent risk factors for OS were selected from cohort 1, including the male sex, age ≥ 70 years, the presence of a malignancy, body mass index <18.5 kg/m2, lymphocyte count <1000 cells/μL, serum albumin levels <3.5 g/dL, and fibrocavitary disease. The areas under the receiver operating characteristic curves for the prognostic scoring model were 0.84 [95% confidence interval (CI), 0.80 − 0.89] for cohort 1 and 0.84 (95% CI, 0.75 − 0.92) for cohort 2. The 5-year OS rates of patients stratified into low-risk, intermediate-risk, and high-risk groups were 97.6, 76.6, and 30.8%, respectively (P < 0.001), in cohort 1, and 97.2, 82.3, and 45.4%, respectively (P < 0.001), in cohort 2. Conclusions This study is the first to develop and validate a prognostic scoring model for patients with MAC-LD. This model may prove useful in clinical settings and practical in estimating the prognosis.

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