Abstract
Background
Previously we assessed risk factors for FEV1 decline in children and adolescents using the Epidemiologic Study of Cystic Fibrosis (J Pediatr 2007;151:134-139); the current study assessed risk factors in adults.
Methods
Risk factors for FEV1 decline over 3-5.5 years for ages 18-24 and ≥25 years were assessed using mixed-model regression.
Results
Mean rates of FEV1 decline (% predicted/year) were −1.92 for ages 18-24y (n=2793) and −1.45 for ages ≥25y (n=1368). For the 18-24y group, B. cepacia, pancreatic enzyme use, multidrug-resistant P. aeruginosa, cough, mucoid P. aeruginosa, and female sex predicted greater decline; low baseline FEV1 and sinusitis predicted less decline. For the ≥25y group, only pancreatic enzyme use predicted greater decline; low baseline FEV1 and sinusitis predicted less decline.
Conclusions
Risk factors for FEV1 decline in adults <25 years are similar to those previously identified in children and adolescents; older adults had few statistically significant risk factors.
Keywords: cystic fibrosis, epidemiology, FEV1, rate of decline, risk factors
INTRODUCTION
Loss of lung function as measured by forced expiratory volume in 1 second (FEV1) in cystic fibrosis (CF) patients varies between individuals and over time and is associated with increased mortality (1,2). In a previous report using data from the Epidemiologic Study of Cystic Fibrosis (ESCF), we evaluated risk factors for decline in FEV1 for patients age 6-17 years (3). We confirmed the findings of other authors that an increased risk of lung function decline is associated with high baseline lung function, female sex, pancreatic insufficiency (as indicated by enzyme use), poor nutritional status, and infection with Pseudomonas aeruginosa. We also identified crackles, daily sputum production, wheezing, sinusitis, the number of pulmonary exacerbations treated with intravenous (IV) antibiotics, and elevated liver function tests as additional risk factors for FEV1 decline in these children. The magnitude and significance of the effect of these risk factors on FEV1 decline (% predicted/year) varied depending on the patient’s age group (6-8, 9-12, or 13-17 years).
Previous studies of risk factors for lung function decline have not focused specifically on adults with CF, or did not evaluate adults separately by age groups, possibly due to small numbers of patients available for analysis. ESCF includes information on a large number of adult patients collected over more than 10 years, allowing a comprehensive analysis of risk factors for decline in adults with CF. The objectives of this analysis were to (a) characterize the decline in FEV1 % predicted over a 3-5.5-year period in adults with CF; and (b) identify and compare risk factors for decline in FEV1 % predicted in two adult age groups (18-24 and ≥25 years old) and to compare these risk factors with those from children and adolescents from our previous work (3).
METHODS
ESCF was a prospective, multicenter, encounter-based, observational study designed to characterize the natural history of CF in a large population of patients in the US and Canada. Clinical, therapeutic, microbiologic, and pulmonary function data were collected from 1994 to 2005 (4). The study was approved by the Copernicus Group institutional review board (tracking number OVA1-03-008). Where required, it was approved by local institutional review boards, and participants or their guardians provided informed consent.
Patients 18 years old and above were included in this analysis if they had at least 3 spirometries performed at times of clinical stability: one at baseline (from the lead-in period), one 13-24 months after baseline, and one 49-78 months after baseline (Figure 1). Clinical characteristics and at least one respiratory tract culture result were required during the 12-month lead-in period following the baseline spirometry. The subsequent 66 months (5.5 years) comprised the outcome period during which the rate of decline in FEV1% predicted was calculated. We included only spirometry measures obtained at times of clinical stability. For each 6 months of the outcome period, we included at most one spirometry (the one closest to the midpoint) in order to reduce potential bias due to frequency of testing. The equations of Hankinson et al. (5) were used to calculate FEV1 % predicted. Repeated-measures, mixed-model linear regression analysis was used to estimate mean rate of change in FEV1% predicted within age groups and to assess risk factors for decline in FEV1% predicted.
Figure 1. Schematic of study design.
Potential risk factors were derived from information obtained at the baseline encounter, the last encounter during the lead-in period, the last respiratory tract culture during lead-in, or from information throughout the lead-in period. Potential risk factors from the baseline encounter were sex, age at baseline spirometry, and baseline FEV1% predicted (from the lead-in period). Nutritional indices (height-for-age, weight-for-age, and body mass index) were obtained from the last visit during the lead-in period. The last respiratory tract culture result during the lead-in period was used to determine presence of P. aeruginosa (any mucoid, any non-mucoid, or any multidrug-resistant), Staphylococcus aureus (any MRSA, any MSSA), Haemophilus influenzae, Burkholderia cepacia, Stenotrophomonas maltophilia, other gram-negative organisms, atypical mycobacteria, Candida, and Aspergillus. For other potential risk factors, which were assessed at encounters throughout the 12-month lead-in period, patients were categorized as positive for each characteristic that was recorded on at least half of their encounters: signs and symptoms included daily cough, daily sputum production, clubbing, crackles, and wheezing; medical conditions included hemoptysis, asthma, allergic bronchopulmonary aspergillosis (ABPA), sinusitis, nasal polyps, elevated liver function tests, CF-related diabetes mellitus (using treatment with insulin or an oral hypoglycemic agent as an indicator), and pancreatic insufficiency (using treatment with pancreatic enzymes as an indicator). An additional risk factor assessed was the number of pulmonary exacerbations treated with IV antibiotics (IV exacerbations) initiated during the 12-month lead-in period. Other than these treatments used as indicators of underlying medical conditions, we did not include therapies as potential risk factors.
Risk factors were first assessed one at a time for their overall effect on the rate of decline separately by age group using linear regression. Risk factors with p<.10 were then entered into multivariable linear regression models with backwards selection, separately by age group, retaining those with p<.05. Risk factors retained in either age group were combined in the final multivariable model for both age groups. Final estimated rates of decline and 95% confidence intervals were generated using the ESTIMATE statement within the MIXED procedure in SAS Version 9.1 (SAS Institute, Inc., Cary, NC).
RESULTS
From the 32,585 patients enrolled in ESCF between 1994 and 2005, 14,283 had a stable baseline spirometry after the 18th birthday (9724 ages 18-24; 4559 ages 25 and older). Upon application of the additional inclusion criteria (initial outcome spirometry, a qualifying outcome spirometry, and evaluable baseline encounter and microbiology data), a total of 4161 patients (2793 ages 18-24; 1368 ages 25 and older) met the study inclusion criteria, as shown in Figure 2. The patient distribution of the time between baseline and initial outcome spirometries was as follows: 13-15 months (58%), 16-18 months (25%), 19-21 months (11%), and 22-24 months (7%). For the time between baseline and qualifying outcome spirometries, the patient distribution was as follows: 49-54 months (14%), 55-60 months (12%), 61-66 months (11%), 67-72 months (17%), and 73-78 months (47%).
Figure 2. Patient disposition.
The mean duration of observation during the outcome period (from the end of the lead-in year to the last spirometry) was 4.6 years (SD=0.8). The median number of spirometries included per patient was 8. The mean rates of FEV1 decline for the 18-24y and ≥25y groups over the observation period were −1.92 (95% CI −2.04 to −1.81) and −1.45 (95% CI −1.62 to −1.27) % predicted per year, respectively. Figure 3 shows these results for the two groups of adults in this study in the context of the previously reported results for children and adolescents (3).
Figure 3. Estimated decline in FEV1% predicted by age group.
Vectors representing the observed average changes in FEV1 % predicted over the study period for the two adult age groups in this study are plotted together with 3 vectors previously published for younger patients with CF. For each age group, the line segment is positioned to begin at the mean age at study baseline and extends to cover the central 90% of follow-up (approximately 5 years). For example, the line for the age ≥25y group is centered at about age 35 and extends about 5 years, but represents the average decline over a 5-year period across all ages 25 and older.
We considered 30 risk factors for inclusion in the multivariable model. Half of these variables were found not to have a univariate relation significant at p<.10 with change in FEV1 and were therefore eliminated from consideration for subsequent multivariable modeling (Table 1, dark shading). Of the remaining 15 variables, all of which were significant by univariate analysis, 7 failed to be statistically significant at p<.05 in the multivariable models for both age groups, and were excluded from the final multivariable regression model (Table 1, light shading).The final set of 8 risk factors are those that were significant in either age group (Table 1, not shaded). The two final multivariable models are shown in Table 2, and the independent effect and estimated rate of decline are shown in Figure 4. To determine the rate of FEV1 change predicted by this model for an individual patient with CF using Figure 4, the independent risk factors are added to the overall rate of decline (first row). For example, the estimated annual rate of FEV1 change over the next 4 years for a 20-year-old female with 60% predicted FEV1 who coughs daily, does not have sinusitis, is taking pancreatic enzymes, has mucoid P. aeruginosa that is multidrug-resistant, but does not have B. cepacia is −1.92 (overall mean) −0.13 (female) −0.25 (FEV1 40%-69% predicted) −0.08 (daily cough) −0.05 (no sinusitis) −0.08 (pancreatic enzyme use) −0.15 (positive for mucoid P. aeruginosa) −0.57 (positive for multidrug-resistant P. aeruginosa) + 0.04 (negative for B. cepacia) = −3.19 percent predicted points of expected FEV1 per year. In other words, this patient’s FEV1 percent predicted would be expected to drop by 13 percentage points (from 60% predicted to 47% predicted) during the next four years. In contrast, a patient with the same characteristics except being age ≥ 25 years would have an estimated rate of decline of −1.82, leading to a 4-year predicted drop of only 7 percentage points.
Table 1. Patient characteristics by age group.
| Characteristic | Ages 18-24y | Association with decline (p value*) |
Ages ≥25y | Association with decline (p value*) |
|---|---|---|---|---|
| Total patients, N | N = 2793 | N = 1368 | ||
| Sex, n (%) | ||||
| Male | 1469 (52.6%) | .028 | 733 (53.6%) | .368 |
| Female | 1324 (47.4%) | 635 (46.4%) | ||
| Baseline FEV1 % predicted, n (%) | ||||
| 100+ | 204 (7.001%) | <001 | 26 (1.9%) | <.001 |
| 70–<100 | 1080 (38.7%) | 327 (23.9%) | ||
| 40–<70 | 1176 (42.1%) | 662 (48.4%) | ||
| <40 | 333 (11.9%) | 353 (25.8%) | ||
| Daily cough, n (%) | 2146 (76.8%) | .011 | 1134 (83.0%) | .512 |
| Sinusitis, n (%) | 253 (9.1%) | .063 | 187 (13.7%) | .053 |
| Pancreatic enzyme use, n (%) | 2617 (93.7%) | <.001 | 1147 (84.0%) | .088 |
| Mucoid P. aeruginosa, n (%) | 1466 (52.5%) | .013 | 701 (51.2%) | .703 |
| Multidrug-resistant P. aeruginosa, n (%) | 167 (6.0%) | .004 | 98 (7.2%) | .754 |
| B. cepacia, n (%) | 125 (4.5%) | .010 | 50 (3.7%) | .185 |
| Daily sputum, n (%) | 1749 (62.6%) | .015 | 1022 (74.8%) | .548 |
| Clubbing, n (%) | 2094 (75.0%) | .007 | 1035 (75.8%) | .680 |
| Wheezing, n (%) | 175 (6.3%) | .056 | 196 (14.3%) | .249 |
| Asthma, n (%) | 474 (17.0%) | .053 | 271 (19.8%) | .216 |
| Number of IV exacerbations, n (%) | ||||
| 0 | 1436 (51.4%) | .052 | 783 (57.2%) | .725 |
| 1 | 697 (25.0%) | 339 (24.8%) | ||
| 2 | 323 (11.6%) | 160 (11.7%) | ||
| 3 | 183 (6.6%) | 51 (3.7%) | ||
| 4+ | 154 (5.5%) | 35 (2.6%) | ||
| Other gram-negative bacteria, n (%) | 305 (10.9%) | .173 | 177 (12.9%) | .146 |
| Aspergillus, n (%) | 207 (7.4%) | .192 | 153 (11.2%) | .060 |
| Weight-for-age z score, Mean ± SD | −0.9 ± 1.16 | .532 | −0.5 ± 1.15 | .579 |
| Height-for-age z score, Mean ± SD | −0.5 ± 1.04 | .134 | −0.4 ± 1.03 | .948 |
| BMI z score, mean ± SD | −0.8 ± 1.12 | .893 | −0.4 ± 1.13 | .569 |
| Crackles, n (%) | 999 (35.8%) | .685 | 667 (48.8%) | .221 |
| Hemoptysis, n (%) | 34 (1.2%) | .572 | 35 (2.6%) | .917 |
| ABPA, n (%) | 85 (3.0%) | .618 | 22 (1.6%) | .214 |
| Nasal polyps, n (%) | 216 (7.7%) | .664 | 91 (6.7%) | .911 |
| Elevated liver enzymes, n (%) | 83 (3.0%) | .403 | 33 (2.4%) | .212 |
| Nonmucoid P. aeruginosa, n (%) | 1419 (50.8%) | .435 | 649 (47.4%) | .391 |
| MSSA, n (%) | 1009 (36.1%) | .439 | 398 (29.1%) | .331 |
| MRSA, n (%) | 44 (1.6%) | .733 | 10 (0.7%) | .797 |
| H. influenzae, n (%) | 204 (7.3%) | .862 | 92 (6.7%) | .759 |
| S. maltophilia, n (%) | 69 (2.5%) | .842 | 54 (3.9%) | .541 |
| Candida, n (%) | 267 (9.6%) | .773 | 135 (9.9%) | .310 |
| Insulin or oral hypoglycemic, n (%) | 301 (10.8%) | .118 | 187 (13.7%) | .703 |
p values evaluate the univariate association between each variable and decline in FEV1% predicted.
Table 2. Statistical significance of factors in final multivariate models, by age group.
|
pvalue |
||
|---|---|---|
| Factor | Age 18-24y n = 2793 |
Ages ≥ 25y n = 1368 |
| Female | .028 | .332 |
| Baseline FEV1 % predicted | <.001 | <.001 |
| Daily cough | .008 | .411 |
| Sinusitis | .025 | .049 |
| Pancreatic enzyme use | <.001 | .037 |
| Mucoid P. aeruginosa | .007 | .489 |
| Multidrug-resistant P. aeruginosa | .010 | .929 |
| B. cepacia | .002 | .199 |
Figure 4. Results of multivariable models of FEV1 percent predicted by age group.
Risk factors remaining in the final multivariable regression (Table 2) are shown in the left column. For a patient in either the 18-24y group (left) or ≥25y group (right), an estimate of the rate of annual decline in FEV1 percent predicted is obtained by summing parameter estimates (labeled “Est.”) associated with each variable state for the patient. The graphical display shows the reference line (mean rate of decline for each age group), the estimated effect of each variable, and the associated 95% confidence interval.
The impact of multidrug-resistant P. aeruginosa on observed rates of decline was substantial in the younger adults, where the observed rate of decline was −2.49 percentage points per year for those with multidrug-resistant P. aeruginosa compared with −1.88 percentage points per year for those without. For older adults, multidrug-resistant P. aeruginosa did not affect decline estimates. B. cepacia also had a greater negative effect on the estimated decline for the younger compared with the older adults. Younger pancreatic-sufficient adults (based on pancreatic enzyme use) had a smaller rate of decline than pancreatic-insufficient patients within the same age group, a difference that was less pronounced for older adults. A comparison of baseline FEV1 categories in the multivariable models shows that patients in the lowest baseline FEV1 category (<40% predicted) declined less rapidly than those with higher FEV1 in both age groups, after adjustment for the other risk factors. This is likely due in part to a survivor effect arising because patients had to remain alive for a minimum of 3 years after the baseline to be included in this analysis. Patients with particularly low lung function who died or had a lung transplant before the minimum follow-up time are excluded from this prediction.
To better evaluate the impact of risk factors on rates of decline in older adults, as well as any influence patients with low FEV1 had on the overall model, two additional analyses were performed. First, we refit the model separately for patients age 25-31y (n=772) and ≥32y (n=606) and found no material differences between these two age groups with respect to impact of risk factors on rates of decline. Second, we repeated the modeling process, beginning with the backward stepwise regression, after excluding all patients with FEV1<40 % predicted. In this subset analysis, we found baseline FEV1 % predicted and daily cough were no longer significant risk factors for the 18-24 year old patients, whereas daily sputum (p=.031) and asthma (p=.028) became significant negative factors. In the ≥25-year age group with FEV1 ≥40 % predicted, the risk factors changed only slightly with two exceptions: the magnitude of the effect of pancreatic enzyme use was similar, but was no longer statistically significant, and Aspergillus became a significant negative risk factor (p=.043)
DISCUSSION
This study used data from ESCF, a large, prospective observational study of patients with CF (4). We characterized the rate of FEV1 decline in adults for two age groups: 18-24y and ≥25y. The overall values and average rates of decline of FEV1 % predicted that we found for the younger adults (Figure 3) were remarkably consistent with those we previously reported for children and adolescents (3). FEV1 % predicted values and rates of decline among adults ≥25y were better than might be expected based upon the results of the younger patients (Figure 3). This finding presumably reflects a survivor effect as evidenced by genotype and pancreatic function differences reported in older CF patients (6,7).
The impact of risk factors for decline in FEV1 % predicted in adults with CF was assessed using multivariable regression. Many variables that were identified as significant independent risk factors for lung function decline in younger CF adults (18-24y) were similar to those observed for children and adolescents ages 6-17y with CF in our previous study (3). Low FEV1 (<40% predicted) and presence of sinusitis were associated with a lower rate of decline. Being female, having daily cough, using pancreatic enzymes, and having a positive culture for B. cepacia or for mucoid or multidrug-resistant P. aeruginosa were all associated with greater rate of decline.
For the older adults (≥25y), baseline FEV1 was the only strong predictor of lung function decline, again with low FEV1 (<40% predicted) being associated with a lower rate of decline. In these older adults, the estimated effects of the risk factors were similar to young adults, but tended to be somewhat smaller in magnitude and have wider confidence bounds, partially due to the smaller number of older patients. The P. aeruginosa variables were an exception: neither mucoid nor multidrug-resistant P. aeruginosa appeared to have an impact on rate of lung function decline in older adults with CF. Marginal statistical significance was reached for pancreatic enzyme use (a surrogate for pancreatic insufficiency) and sinusitis. Risk factors may have fallen short of statistical significance in the older age group not only because of smaller numbers, but also because risk factors present for many years might no longer be changing the course of the patients’ lung disease.
Patients with low FEV1 (<40 % predicted) tend to have only modest decline compared to those with higher lung function. This phenomenon has been previously described and is partly due to a “floor” effect (8-10). To better understand the risk factors for decline in lung function in adults without the influence of these patients, we repeated the analyses including only patients with FEV1 ≥ 40 % predicted. For the younger adults, we found that daily cough was no longer a risk factor; however, daily sputum production and asthma became significantly associated with lung function decline. Further, in this healthier subgroup, baseline FEV1 % predicted was no longer a risk factor in either age group. This finding differs from our previously reported results in children and adolescents, where patients with higher baseline lung function had a greater risk for more rapid decline (3). In that paper, we speculated that children with the highest lung function were not treated aggressively. Among the adults with baseline FEV1 ≥ 40% predicted, only 8% of young adults and 3% of older adults had FEV1 ≥100 % predicted, and it is for this group that treatment may be least aggressive. This concentration of the values of FEV1 % predicted into a narrow range may explain why baseline level of lung function was not predictive of subsequent decline in this subset.
Interestingly, the presence of sinusitis, which often correlates with increased lower respiratory symptoms (11), was associated with a lower decline in FEV1 in both age groups and regardless of whether patients with FEV1 less than 40 % predicted were excluded. In ESCF, the medical condition of sinusitis was recorded only for currently symptomatic sinusitis, which was likely treated. We conjecture that antibiotic therapy for sinusitis may have incidentally treated lung disease and thereby slowed the decline in FEV1. It is also possible that patients with severe sinusitis were treated surgically and are no longer symptomatic, leaving only patients with mild sinusitis.
Our findings confirm earlier reports that higher FEV1, airway infection with P. aeruginosa, female sex, and poorer nutritional status are among those factors associated with higher rates of FEV1 decline in children and/or adults with CF (1,8,12-16). It is noteworthy that the well-established gender differences in childhood and adolescence are still significant in adulthood. In this study, we not only focused exclusively upon adults, but also divided the adult population into those above and below 25 years of age. Our study also includes a large selection of potential risk factors, a number of which were not found to be significant in this analysis. For some factors, this may be because they are relatively rare (e.g., hemoptysis and ABPA). For other factors, this may be because adult patients typically have had the risk factor for an extended period, and thus the disease progression associated with its onset has already occurred (e.g., crackles). We were unable to adequately assess genotype and socioeconomic status information on enough patients to warrant including those factors in the analysis.
Adult CF patients commonly have fairly frequent respiratory exacerbations which are treated with IV antibiotics. The frequency of these exacerbations has been associated with an increased risk for lung transplantation or death (17). However, in contrast to our previous finding in children and adolescents, the number of IV exacerbations during the baseline year was not a statistically significant predictor of change in FEV1 in adults after controlling for other risk factors, even when limited to patients with FEV1 ≥40 % predicted. This could be related to survivor effect, more aggressive treatment of exacerbations in adults, or differences in the pathophysiology and progression of lung disease in adults. Further, the decision to treat an exacerbation in adults may be conditioned upon a patient’s wishes or social concerns more than for younger patients. This would tend to weaken any relationship between exacerbation frequency and subsequent lung function decline.
This analysis provides insight into risk factors for FEV1 decline in adults and identifies a marked age effect for different risk factors. The effect of baseline FEV1 was quite striking when considering all adults and reinforces our previous finding in children and adolescents that low FEV1 predicts a smaller decline in FEV1 % predicted. Lung disease progression is not uniform within the adult CF population. It is possible that modeling relative change in FEV1 % predicted rather than absolute change would better reflect the natural course of CF lung function and might even eliminate the protective effect associated with FEV1 < 40% predicted. Identification of specific patient characteristics (i.e., risk factors) associated with more rapid disease progression can not only better inform patient management, but can also aid in the design and analysis of clinical trials to assess new CF therapies targeted at arresting lung disease progression (18). Similar to our previous study on children and adolescents (3), we also provide clinicians with a method for estimating the rate of FEV1 decline in an individual adult patient.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge the more than 400 site investigators and coordinators in ESCF. This study is sponsored by Genentech, Inc.
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Disclosure of Conflict of Interest
Michael Konstan, Jeffrey Wagener, Donald VanDevanter, and Wayne Morgan have received honoraria from Genentech for serving as members of the Scientific Advisory Group for the Epidemiologic Study of Cystic Fibrosis (ESCF). Michael Konstan, Jeffrey Wagener, Donald VanDevanter, and Wayne Morgan have served as consultants to Genentech. No compensation was provided to these authors in exchange for production of this manuscript. David Pasta and Lawrence Rasouliyan are employees of ICON Late Phase & Outcomes Research, which was paid by Genentech for providing analytical services for this study. Ashley Yegin is currently and Jeffrey Wagener was previously an employee of Genentech.
References
- 1.Corey M, Edwards L, Levison H, Knowles M. Longitudinal analysis of pulmonary function decline in patients with cystic fibrosis. J Pediatr. 1997;131:809–814. doi: 10.1016/s0022-3476(97)70025-8. [DOI] [PubMed] [Google Scholar]
- 2.Schluchter MD, Konstan MW, Davis PB. Jointly modeling the relationship between survival and pulmonary function in cystic fibrosis patients. Stat Med. 2002;21:1271–1287. doi: 10.1002/sim.1104. [DOI] [PubMed] [Google Scholar]
- 3.Konstan MW, Morgan WJ, Butler SM, et al. Risk factors for rate of decline in forced expiratory volume in one second in children and adolescents with cystic fibrosis. J Pediatr. 2007;151:134–139. doi: 10.1016/j.jpeds.2007.03.006. [DOI] [PubMed] [Google Scholar]
- 4.Morgan WJ, Butler SM, Johnson CA, et al. Epidemiologic study of cystic fibrosis: design and implementation of a prospective, multicenter, observational study of patients with cystic fibrosis in the U.S. and Canada. Pediatr Pulmonol. 1999;28:231–41. doi: 10.1002/(sici)1099-0496(199910)28:4<231::aid-ppul1>3.0.co;2-2. [DOI] [PubMed] [Google Scholar]
- 5.Hankinson JL, Odencrantz JR, Fedan KB. Spirometric reference values from a sample of the general U.S. population. Am J Respir Crit Care Med. 1999;159:179–187. doi: 10.1164/ajrccm.159.1.9712108. [DOI] [PubMed] [Google Scholar]
- 6.The Cystic Fibrosis Genotype-Phenotype Consortium Correlation between genotype and phenotype in patients with cystic fibrosis. New Engl J Med. 1993;329:1308–1313. doi: 10.1056/NEJM199310283291804. [DOI] [PubMed] [Google Scholar]
- 7.Kristidis P, Bozon D, Corey M, Markiewicz D, Rommens J, Tsui LC, et al. Genetic determination of exocrine pancreatic function in cystic fibrosis. Am J Hum Genet. 1992;50(6):1178–1184. [PMC free article] [PubMed] [Google Scholar]
- 8.Corey M, Levison H, Crozier D. Five- to seven-year course of pulmonary function in cystic fibrosis. Am Rev Respir Dis. 1976;114:1085–1192. doi: 10.1164/arrd.1976.114.6.1085. [DOI] [PubMed] [Google Scholar]
- 9.Davis PB, Byard PJ, Konstan MW. Identifying treatments that halt progression of pulmonary disease in cystic fibrosis. Pediatr Res. 1997;41:161–165. doi: 10.1203/00006450-199702000-00001. [DOI] [PubMed] [Google Scholar]
- 10.Konstan MW, Wagener JS, Pasta DJ, et al. Clinical use of dornase alfa is associated with a slower rate of FEV1 decline in cystic fibrosis. Pediatr Pulmonol. 2011;46:545–553. doi: 10.1002/ppul.21388. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Umetsu DT, Moss RB, King VV, Lewiston NJ. Sinus disease in patients with severe cystic fibrosis; relation to pulmonary exacerbation. Lancet. 1990;335:1077–1078. doi: 10.1016/0140-6736(90)92642-u. [DOI] [PubMed] [Google Scholar]
- 12.Kerem E, Corey M, Gold R, Levison H. Pulmonary function and clinical course in patients with cystic fibrosis after pulmonary colonization with Pseudomonas aeruginosa. J Pediatr. 1990;116:714–719. doi: 10.1016/s0022-3476(05)82653-8. [DOI] [PubMed] [Google Scholar]
- 13.Lewin LO, Byard PJ, Davis PB. Effect of Pseudomonas cepacia colonization on survival and pulmonary function of cystic fibrosis patients. J Clin Epidemiol. 1990;43:125–131. doi: 10.1016/0895-4356(90)90175-o. [DOI] [PubMed] [Google Scholar]
- 14.Demko CA, Byard PJ, Davis PB. Gender differences in cystic fibrosis: Pseudomonas aeruginosa infection. J Clin Epidemiol. 1995;48:1041–1049. doi: 10.1016/0895-4356(94)00230-n. [DOI] [PubMed] [Google Scholar]
- 15.Steinkamp G, Wiedemann B. Relationship between nutritional status and lung function in cystic fibrosis: cross sectional and longitudinal analyses from the German CF quality assurance (CFQA) project. Thorax. 2002;57:596–601. doi: 10.1136/thorax.57.7.596. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Schaedel C, de Monestrol I, Hjelte L, et al. Predictors of deterioration of lung function in cystic fibrosis. Pediatr Pulmonol. 2002;33:483–491. doi: 10.1002/ppul.10100. [DOI] [PubMed] [Google Scholar]
- 17.Liou TG, Adler FR, Cox DR, Cahill BC. Lung transplantation and survival in children with cystic fibrosis. N Engl J Med. 2007;357:2143–2152. doi: 10.1056/NEJMoa066359. Erratum in: N Engl J Med. 2008; 359:e6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Konstan MW, Wagener JS, Yegin A, Millar SJ, Pasta DJ, VanDevanter DR. Design and powering of cystic fibrosis clinical trials using rate of FEV1 decline as an efficacy endpoint. J Cyst Fibros. 2010;9:332–338. doi: 10.1016/j.jcf.2010.05.004. [DOI] [PMC free article] [PubMed] [Google Scholar]