Impact of Cystic Fibrosis Transmembrane Conductance Regulator Therapy on Chronic Rhinosinusitis and Health Status: Deep Learning CT Analysis and Patient-reported Outcomes

Ann Am Thorac Soc. 2022 Jan;19(1):12-19. doi: 10.1513/AnnalsATS.202101-057OC.

Abstract

Rationale: Elexacaftor, tezacaftor, and ivacaftor (ETI) in triple combination improves pulmonary health for people with cystic fibrosis (PwCF). However, its impact on objective measures of sinus disease and health utility is unestablished. Objectives: To evaluate the impact of ETI on chronic rhinosinusitis (CRS) and general health status incorporating computed tomography (CT), quality-of-life (QOL) and productivity loss. Methods: Adult PwCF+CRS with CF transmembrane conductance regulator genotype F508del/F508del or F508del/minimal function who clinically initiated ETI participated in a prospective, observational study. The primary endpoint was change in percent sinus CT opacification (%SO) after 6 months of ETI assessed via deep learning-based methods. Secondary endpoints included changes in sinonasal QOL, health utility value and productivity loss, which were evaluated monthly via validated metrics. Results: 30 PwCF provided baseline data; 25 completed the study. At baseline, the cohort had substantial CRS, with mean 22-question SinoNasal Outcome Test (SNOT-22) score 33.1 and mean sinus CT %SO 63.7%. At 6-month follow-up, %SO improved by mean 22.9% (P < 0.001). %SO improvement trended toward greater magnitude for those naïve to prior modulator therapy (P = 0.09). Mean SNOT-22 scores and health utility improved by 15.3 and 0.068 [6.8%] (all P ⩽ 0.007). Presenteeism, activity impairment and overall productivity loss improved (all P ⩽ 0.049). Improvements in SNOT-22 scores and health utility occurred by one month and remained improved over the study. Conclusions: ETI is associated with substantial improvements in sinus CT opacification and productivity loss, and clinically meaningful improvements in sinonasal QOL and health utility. Most improvements were rapid, robust, and durable over the study.

Keywords: CFTR modulator; chronic rhinosinusitis; computed tomography; cystic fibrosis; machine learning.

Publication types

  • Observational Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aminophenols
  • Cystic Fibrosis Transmembrane Conductance Regulator* / genetics
  • Deep Learning*
  • Humans
  • Mutation
  • Patient Reported Outcome Measures
  • Prospective Studies
  • Quality of Life
  • Tomography, X-Ray Computed

Substances

  • Aminophenols
  • Cystic Fibrosis Transmembrane Conductance Regulator