Changes in Care during the COVID-19 Pandemic for People with Cystic Fibrosis

Predicting lung function decline in cystic fibrosis: the impact of initiating ivacaftor therapy

BACKGROUND

Modulator therapies that seek to correct the underlying defect in cystic fibrosis (CF) have revolutionized the clinical landscape. Given the heterogeneous nature of lung disease progression in the post-modulator era, there is a need to develop prediction models that are robust to modulator uptake.

METHODS

We conducted a retrospective longitudinal cohort study of the CF Foundation Patient Registry (N = 867 patients carrying the G551D mutation who were treated with ivacaftor from 2003 to 2018). The primary outcome was lung function (percent predicted forced expiratory volume in 1 s or FEV1pp). To characterize the association between ivacaftor initiation and lung function, we developed a dynamic prediction model through covariate selection of demographic and clinical characteristics. The ability of the selected model to predict a decline in lung function, clinically known as an FEV1-indicated exacerbation signal (FIES), was evaluated both at the population level and individual level.

RESULTS

Based on the final model, the estimated improvement in FEV1pp after ivacaftor initiation was 4.89% predicted (95% confidence interval [CI]: 3.90 to 5.89). The rate of decline was reduced with ivacaftor initiation by 0.14% predicted/year (95% CI: 0.01 to 0.27). More frequent outpatient visits prior to study entry and being male corresponded to a higher overall FEV1pp. Pancreatic insufficiency, older age at study entry, a history of more frequent pulmonary exacerbations, lung infections, CF-related diabetes, and use of Medicaid insurance corresponded to lower FEV1pp. The model had excellent predictive accuracy for FIES events with an area under the receiver operating characteristic curve of 0.83 (95% CI: 0.83 to 0.84) for the independent testing cohort and 0.90 (95% CI: 0.89 to 0.90) for 6-month forecasting with the masked cohort. The root-mean-square errors of the FEV1pp predictions for these cohorts were 7.31% and 6.78% predicted, respectively, with standard deviations of 0.29 and 0.20. The predictive accuracy was robust across different covariate specifications.

CONCLUSIONS

The methods and applications of dynamic prediction models developed using data prior to modulator uptake have the potential to inform post-modulator projections of lung function and enhance clinical surveillance in the new era of CF care.

Improved recognition of lung function decline as signal of cystic fibrosis pulmonary exacerbation: a Cystic Fibrosis Learning Network Innovation Laboratory quality improvement initiative

INTRODUCTION

Cystic fibrosis (CF) is a systemic autosomal recessive condition characterised by progressive lung disease. CF pulmonary exacerbations (PEx) are episodes of worsening respiratory status, and frequent PEx are a risk factor for accelerated lung function decline, yet many people with CF (PwCF) go untreated at the time of decline. The goal of this quality improvement (QI) initiative was to improve recognition, treatment and follow-up of PEx in PwCF.

METHODS

Using the Model for Improvement, the Cystic Fibrosis Learning Network (CFLN) initiated a QI innovation laboratory (iLab) with a global aim to decrease the rate of lung function decline in PwCF. The iLab standardised definitions for signals of PEx using a threshold for decline in forced expiratory volume in one second (FEV1) and/or changes in symptoms. The FEV1 decline signal was termed FIES (FEV1-indicated exacerbation signal). Processes for screening and recognition of FIES and/or symptom changes, a treatment algorithm and follow-up in the presence of a signal were tested concurrently in multiple settings.

SPECIFIC AIMS

The specific aim is to increase the per cent of PwCF assessed for a PEx signal at ambulatory encounters and to increase the per cent of recommendations to follow-up within 6 weeks for PwCF experiencing a PEx signal.

RESULTS

FIES recognition increased from 18.6% to 73.4% across all teams during the iLab, and every team showed an improvement. Of PwCF assessed, 15.8% experienced an FIES event (>10% decline in FEV1 per cent predicted (FEV1pp)). Follow-up within 6 weeks was recommended for an average of 70.5% of those assessed for FIES and had an FEV1pp decline greater than 5%.

CONCLUSION

The CFLN iLab successfully defined and implemented a process to recognise and follow-up PEx signals. This process has the potential to be spread to the larger CF community. Further studies are needed to assess the impact of these processes on PwCF outcomes.

Clinical features associated with pulmonary exacerbation diagnosis in infants and young children with cystic fibrosis

RATIONALE

Diagnosing cystic fibrosis (CF) pulmonary exacerbations (PEx) in very young people with CF <3 years (VY-PwCF) is challenging because of the frequency of respiratory viral infections in this age group, and there are limited data on the clinical features associated with the diagnosis of PEx in this age group. The goal of this study was to identify clinical features associated with the diagnosis of PEx in VY-PwCF.

METHODS

We reviewed the medical records of VY-PwCF followed at the Children's Hospital of Philadelphia born between 2013 and 2019. We collected data from all encounters with respiratory symptoms. PEx was defined by treatment with oral or intravenous antibiotics. Clinical features of PEx and non-PEx encounters were compared using descriptive statistics, and odds ratios of PEx diagnosis were calculated.

RESULTS

A total of 78 patients were included in the analysis. The mean (SD) number of PEx per patient was 6.17 (5.88). The presence of a wet or nighttime cough and symptoms >3 days in duration were significantly associated with PEx diagnosis (p < .001). In contrast, symptoms such as sore throat or rhinorrhea were not associated with a higher likelihood of PEx.

CONCLUSIONS

The presence of a wet or night-time cough and longer symptom duration are common features of PEx in VY-PwCF, whereas symptoms suggestive of upper respiratory viral infection are not. Our results will be helpful in counseling families of VY-PwCF in the signs and symptoms of PEx and in planning future research in PEx in this age group.

Cystic fibrosis year in review 2022

Remarkable medical advancements have been made for people with cystic fibrosis (CF) in recent years, with an abundance of research continuing to be conducted worldwide. With concern for limitations in access to highly effective CFTR modulators, as well as the recent Coronavirus Disease-19 pandemic, there has been a consistent effort to understand and improve CF screening, disease burden, diagnosis, and management. Our aim in this review is to present articles from 2022 with an emphasis on clinically relevant studies. We hope this will serve as a broad overview of the research published in the past year.

Respiratory Viruses and Cystic Fibrosis

The threat of respiratory virus infection to human health and well-being has been clearly highlighted by the coronavirus disease 2019 (COVID-19) pandemic. For people with cystic fibrosis (CF), the clinical significance of viral infections long predated the emergence of severe acute respiratory syndrome coronavirus 2. This article reviews the epidemiology, diagnosis, and treatment of respiratory virus infection in the context of CF as well as the current understanding of interactions between viruses and other microorganisms in the CF lung. The incidence of respiratory virus infection in CF varies by age with young children typically experiencing more frequent episodes than adolescents and adults. At all ages, respiratory viruses are very common in CF and are associated with pulmonary exacerbations. Respiratory viruses are identified at up to 69% of exacerbations, while viruses are also frequently detected during clinical stability. The full impact of COVID-19 in CF is yet to be established. Early studies found that rates of COVID-19 were lower in CF cohorts than in the general population. The reasons for this are unclear but may be related to the effects of shielding, infection control practices, maintenance CF therapies, or the inflammatory milieu in the CF lung. Observational studies have consistently identified that prior solid organ transplantation is a key risk factor for poor outcomes from COVID-19 in CF. Several key priorities for future research are highlighted. First, the impact of highly effective CFTR modulator therapy on the epidemiology and pathophysiology of viral infections in CF requires investigation. Second, the impact of respiratory viruses on the development and dynamics of the CF lung microbiota is poorly understood and viral infection may have important interactions with bacteria and fungi in the airway. Finally, bacteriophages represent a key focus of future investigation both for their role in transmission of antimicrobial resistance and as a promising treatment modality for multiresistant pathogens.

Short and Long-Term Impact of COVID-19 Infection on Previous Respiratory Diseases

On March 11, 2020, the World Health Organization declared Coronavirus Disease 2019 (COVID-19) a pandemic. Till now, it affected 452.4 million (Spain, 11.18 million) persons all over the world with a total of 6.04 million of deaths (Spain, 100,992). It is observed that 75% of hospitalized COVID-19 patients have at least one COVID-19 associated comorbidity. It was shown that people with underlying chronic illnesses are more likely to get it and grow seriously ill. Individuals with COVID-19 who have a past medical history of cardiovascular disorder, cancer, obesity, chronic lung disease, diabetes, or neurological disease had the worst prognosis and are more likely to develop acute respiratory distress syndrome or pneumonia. COVID-19 can affect the respiratory system in a variety of ways and across a spectrum of levels of disease severity, depending on a person's immune system, age and comorbidities. Symptoms can range from mild, such as cough, shortness of breath and fever, to critical disease, including respiratory failure, shock and multi-organ system failure. So, COVID-19 infection can cause overall worsening of these previous respiratory diseases, such as asthma, chronic obstructive pulmonary disease (COPD), interstitial lung disease, etc. This review aims to provide information on the impact of the COVID-19 disease on pre-existing lung comorbidities.