Rationale:The cystic fibrosis (CF) modulator drug elexacaftor/tezacaftor/ivacaftor (ETI) proved highly effective in controlled clinical trials for individuals with ≥1 F508del allele, which occurs in at least 85% of people with CF (PwCF). Objective: PROMISE is a post-approval study to understand the broad effects of ETI through 30 months clinical use in a more diverse US patient population with planned analyses after 6 months. Methods: Prospective, observational study in 487 PwCF age ≥12 years with ≥1 F508del allele starting ETI for the first time. Assessments occurred before and 1, 3, and 6 months into ETI therapy. Outcomes included change in ppFEV 1 , sweat chloride concentration, body mass index, and selfreported respiratory symptoms. Results: average age was 25.1 years. 44.1% entered the study using tezacaftor/ivacaftor or lumacaftor/ivacaftor while 6.7% were using ivacaftor, consistent with F508del homozygosity and G551D allele, respectively. At 6 months into ETI therapy, ppFEV 1 improved 9.76 percentage points (95% CI 8.76, 10.76) from baseline, CFQ-R Respiratory Domain score improved 20.4 points (95% CI 18.3, 22.5), and sweat chloride decreased -41.7 mmol/L (95% ). BMI also significantly increased.Changes were larger in those naïve to modulators but substantial in all groups, including those treated with ivacaftor at baseline. Conclusions: ETI by clinical prescription provided large improvements in lung function, respiratory symptoms, and BMI in a diverse population naïve to modulator drug therapy, using existing two-drug combinations, or using ivacaftor alone. Each group also experienced significant reductions in sweat chloride concentration, which correlated with improved ppFEV 1 in the overall study population.

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Background The COVID-19 pandemic has accelerated the transition to telehealth, including the use of home spirometry in cystic fibrosis. Evaluating the accuracy and precision of longitudinal home spirometry is a requisite for telehealth-based research. This secondary analysis of a CF study (eICE) evaluates whether there are cross-sectional or longitudinal differences between home and clinic spirometry. Methods Participants age ≥14 years with ppFEV 1 >25 were recruited from 2011-2015, issued a home spirometer, and asked to complete spirometry efforts twice per week for one year. Clinic spirometry was collected at baseline and every three months. Cross-sectional differences between clinic spirometry and the closest home spirometry measurement were analyzed. Longitudinally, we apply 5 methods to analyze the precision of home spirometry, and differences between clinic vs. home data. Results Home spirometry is estimated to be 2.0 (95% CI: 0.3, 3.5) percentage points lower than clinic spirometry cross-sectionally. Longitudinally, the estimates of 12-month change in home spirometry varied by analysis method from -2.6 to -1.0 ppFEV 1 / year, with precision markedly different. However, home spirometry change estimates were qualitatively similar to the clinic results: -3.0 ppFEV 1 /year (95% CI: -4.1, -1.9). Conclusions To leverage the potential cost, feasibility and convenience of home spirometry, the differences with clinic spirometry must be acknowledged. Significantly lower ppFEV 1 in home devices shows that direct comparison to clinic spirometers may induce a spurious change from baseline, and additional variability in home devices impacts statistical power. The effect of coaching, setting, and equipment must be understood to use and improve home spirometry in CF.

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Our goal is to estimate the true number of classes in a population, called the species richness. We consider the case where multiple frequency count tables have been collected from a homogeneous population and investigate a penalized maximum likelihood estimator under a negative binomial model. Because high probabilities of unobserved classes increase the variance of species richness estimates, our method penalizes the probability of a class being unobserved. Tuning the penalization parameter is challenging because the true species richness is never known, and so we propose and validate four novel methods for tuning the penalization parameter. We illustrate and contrast the performance of the proposed methods by estimating the strain-level microbial diversity of Lake Champlain over three consecutive years, and global human host-associated species-level microbial richness.