Rationale: Most children with cystic fibrosis (CF) experience a slow decline in spirometry, although some children continue to be at risk for more significant lung disease progression. Chest computed tomography (CT) scans have been shown to be more sensitive to changes in lung disease than spirometry and may provide a means for predicting future lung disease progression.
Objectives: We hypothesized that Brody chest CT scan scores obtained in 2000 in a prospectively monitored cohort of children with CF would be associated with the most recent measures of lung disease severity.
Methods: Brody chest CT scan scores were calculated for 81 children enrolled in the Wisconsin CF Neonatal Screening Project. Multivariable linear regression was used to determine associations between Brody scores and the most recent (age 21 yr or June 30, 2010, whichever was later) measures of CF lung disease.
Measurements and Main Results: The mean observation time after the chest CT scan was 7.5 years. Brody chest CT scan scores were significantly associated with the most recent measures of spirometry (P < 0.001) and Wisconsin and Brasfield chest radiograph scores (P < 0.001). The strength of this association was much stronger than spirometry obtained near the time of the chest CT scan (P < 0.01) but not chest radiograph scores.
Conclusions: Chest CT scan scores are associated with future lung disease severity, and quantitative chest imaging (chest CT scan and chest radiograph scores) is more strongly associated with future lung disease severity than measures of spirometry. These findings may help clinicians identify patients at risk of future lung disease progression.
Chest computed tomography (CT) scan scores are more sensitive than traditional spirometry in detecting changes in lung disease severity in children with cystic fibrosis (CF). Whether chest CT scan scores are associated with future lung disease progression is unknown.
Quantitative chest imaging (chest CT scan and chest radiography scores) are statistically significantly associated with future measures of lung disease severity. These scores may be used to identify children with CF at high risk of future lung disease progression.
With a greater proportion of children with cystic fibrosis (CF) having normal pulmonary function test (PFTs) (1) and very gradual decreases in FEV1 (2), it has become difficult or impossible to use FEV1 to identify those children at risk for more rapid lung disease progression. This is especially true in light of the study by Konstan and colleagues, which determined that the greatest risk factor for FEV1 decline in children with CF was having an FEV1 % predicted greater than 100% (3). Cross-sectional studies of children with CF have demonstrated that high-resolution chest computed tomography (CT) scans are more sensitive than traditional PFTs in detecting early signs of lung disease (4–6). Additionally, chest CT scan has been shown to be more sensitive to intercurrent changes in lung disease than PFTs (7–9). Given the sensitivity of chest CT scan in detecting early lung disease, chest CT scans may provide a tool for predicting future lung disease progression. In a recent study, Loeve and colleagues demonstrated that chest CT scans scored using the Brody scoring system (4) could predict the frequency of pulmonary exacerbation over the ensuing 2 years, independent of FEV1 severity (10). Having more frequent pulmonary exacerbations is associated with subsequent FEV1 decline (3, 11).
The Wisconsin CF Neonatal Screening Project (WI RCT) is a randomized control trial that was designed to assess the benefits to CF made possible through early diagnosis via newborn screening (12). In 2000, a chest CT scan was added to the protocol for 81 children who were still being followed systematically as a part of the WI RCT protocol (5). In the current study, we hypothesized that the Brody chest CT scan scores obtained in 2000, in a prospectively monitored cohort of children with CF, would be associated with the most recent assessment of lung disease severity for subjects followed in the WI RCT, and that the association would be stronger than for other measures of lung disease severity available in the WI RCT. Some of the results of these studies have been previously reported in the form of an abstract (13).
The design of the WI RCT is described in detail elsewhere (12). In summary, blood specimens of newborns born in Wisconsin between 1985 and 1994 were assigned either to an early CF diagnosis group or to a standard diagnosis group (12). Control patients were unblinded at 4 years of age (14). A sweat chloride level of greater than or equal to 60 mEq/L at one of Wisconsin's two CF centers was required to establish the diagnosis. This investigation was approved by the institutional review boards at the University of Wisconsin and the Childrens’ Hospital of Wisconsin.
Patients were seen every 3 months and assessed by an Evaluation and Treatment Protocol (12) developed in 1984 and reviewed regularly. Patients were prospectively followed in the study through age 21 years. Cultures of respiratory secretions were obtained quarterly (15). PFTs were generally begun when children reached 4 years of age, and were obtained at least every 6 months with strict quality-control measures (16). Chest radiographs obtained at the time of diagnosis and annually were scored using the Brasfield (BCXR) and Wisconsin (WCXR) scoring systems (17, 18). Parents reported cough frequency and sputum production at each visit.
A chest CT scan was added in 2000 for patients who continued to receive care in the protocol at the two CF centers and who gave additional informed consent, as described previously (5). Study participants obtained a chest CT scan at a study visit after the recent history, physical examination, and spirometry were reviewed to determine they were at their baseline health status. The chest CT scan (Lightspeed; GE Medical Systems, Milwaukee, WI) used a thin-section technique (1.25-mm section thickness) with inspiratory images at 10-mm intervals and expiratory images at 20-mm intervals. Hard-copy images were scored independently by three radiologists (A.S.B and two others) using the Brody scoring system (19).
Linear regression was used to determine associations between Brody scores and the most recent (age 21 years or June 30, 2010, whichever was later) measures of CF lung disease. Data within 2 years of the chest CT scan were excluded. We performed multivariable regression, adjusting for baseline factors at the time of the chest CT scan (age at the time of the chest CT scan, sex, screen or control group, genotype [homozygous F508del versus all other combinations], pancreatic insufficiency, and meconium ileus) and potential confounding factors: FEV1 and Pseudomonas aeruginosa infection at the time of the chest CT scan, and time between the CT scan and the most recent assessment, after a review of the literature to find factors associated with (1) lower pulmonary function, and/or (2) Brody scores (3, 20, 21). We repeated the analysis to determine the association between the Brody bronchiectasis subscores and the most recent lung disease measurements.
To determine associations between the other lung disease measures available within 1 year before the chest CT scan in 2000 and the most recent FEV1 and WCXR, we added each lung disease measure in 2000 individually to the multivariable regression model that included only the baseline factors. For lung disease measures in 2000 that were significantly associated with the most recent FEV1 or WCXR, we used an F test to compare the strength of association between chest CT scan and the most recent FEV1 and WCXR, adjusting for baseline factors.
At the time of the chest CT scan, 98 of the original 132 patients were still being followed. Of these 98, 9 did not give consent for the chest CT scan, and 8 either did not come to their chest CT scan appointment or had chest CT images that were not acceptable due to motion artifact. The 81 patients who obtained a chest CT scan were similar to the original WI RCT cohort (see Table E1 in the online supplement). After obtaining the chest CT scan, 10 patients did not obtain additional chest X-rays as a part of the original study protocol. The mean values for the lung disease surrogates generally revealed mild abnormalities at the time of the chest CT scan (Table 1), with the exception of WCXR (mean 15.4) and BCXR (mean 18.8). These mean values indicate the presence of irreversible abnormalities, based on criteria of a WCXR score greater than 5 and BCXR score less than 21 (22). The median Brody chest CT scan score was 2.0 (range 0–12.8) out of a possible score of 36. The mean Brody scores were not different between the control group (3.6) and the screened group (2.7, P = 0.2).
|Characteristic||Yr before Chest CT Scan||Most Recent Data||Mean (SD) Elapsed Time (yr)|
|Female sex, %||42||—||—|
|Pancreatic insufficiency, %||84||—||—|
|Meconium ileus, %||23||—||—|
|Brody chest CT scan score, median (range)||2.0 (0–12.8)||—||—|
|Age, yr, mean (SD)||11.5 (3)||19.0 (2.0)||7.5 (1.8)|
|FEV1 ,% predicted, mean (SD), N = 76||91.1 (16.7)||86.8 (19.4)||5.9 (1.9)|
|FEF25–75, % predicted, mean (SD), N = 73||85.4 (29.3)||70.5 (29.5)||5.9 (1.9)|
|RV/TLC, mean (SD), N = 70||30.2 (7.9)||30.0 (10.9)||5.6 (2.1)|
|WCXR, mean (SD), N = 71||15.4 (13.0)||24.9 (15.7)||5.3 (1.8)|
|BCXR, mean (SD), N = 71||18.8 (2.9)||17.8 (3.9)||5.3 (1.8)|
|Daily cough, %||46||64||7.5 (1.8)|
|Culture positive for Pseudomonas aeruginosa, %||48||52||7.5 (1.8)|
|Hospitalized in the last yr, %||9||24||7.5 (1.8)|
The mean observation time between the chest CT scan and the most recent observation was 7.5 years. During that time period, there was progression of all lung disease surrogates, with the exception of residual volume/total lung capacity (RV/TLC). There was a significant association between chest CT scan score in 2000 and the most recent measure of all lung disease surrogates in an unadjusted model (Table 2 and Figures 1–4), indicating that chest CT scan score severity is associated with future lung disease progression over the subsequent 2 to 10 years. The association was strongest for FEV1 % predicted; forced expiratory flow, midexpiratory phase (FEF25–75) % predicted; and WCXR score. The associations between the chest CT scan score and the most recent lung disease surrogates remained statistically significant when the multivariable model was used (Table 2). For example, using the fully adjusted model, for every one point increase in Brody chest CT scan score, the most recent FEV1 % predicted was a mean of 3.1 % predicted lower (P < 0.001).
|Lung Disease Measure||Unadjusted Model (SE)||P Value||Fully Adjusted Model (SE)||P Value|
|FEV1, % predicted||−4.3 (0.7)||<0.001||−3.1 (0.7)||<0.001|
|FEF25–75, % predicted||−5.9 (1.1)||<0.001||−4.3 (1.2)||0.001|
|RV/TLC||2.5 (0.4)||<0.001||2.6 (0.4)||<0.001|
|WCXR||3.5 (0.5)||<0.001||3.7 (0.6)||<0.001|
|BCXR||−0.9 (0.1)||<0.001||−1.1 (0.1)||<0.001|
|Pseudomonas aeruginosa||0.06 (0.02)||0.002||0.04 (0.02)||0.1|
|Hospitalization in the yr of the most recent data||0.03 (0.02)||0.09||0.06 (0.02)||0.02|
The mean Brody bronchiectasis subscore was 1.0, with a range of 0 to 5.0. The association between the Brody bronchiectasis subscore and the most recent lung disease surrogates was even stronger than the Brody score (Table 3). Using the same multivariable regression models as above, the Brody bronchiectasis subscores remained highly significantly associated with the most recent lung disease surrogate measurements, indicating that the extent and distribution of bronchiectasis (as measured by the Brody bronchiectasis subscore) is associated with future lung disease progression.
|Lung Disease Measure||Unadjusted Model (SE)||P Value||Fully Adjusted Model (SE)||P Value|
|FEV1, % predicted||−10.5 (1.7)||<0.001||−7.9 (1.7)||<0.001|
|FEF25–75, % predicted||−14.3 (2.7)||<0.001||−10.4 (3.0)||0.001|
|RV/TLC||6.0 (0.9)||<0.001||5.9 (1.0)||<0.001|
|WCXR||9.2 (1.1)||<0.001||9.2 (1.2)||<0.001|
|BCXR||−2.4 (0.2)||<0.001||−2.5 (0.3)||<0.001|
|Pseudomonas aeruginosa||0.1 (0.04)||0.003||0.1 (0.1)||0.1|
|Hospitalization in the yr of the most recent data||0.07 (0.04)||0.06||0.2 (0.1)||0.009|
Tables 4 and 5 detail the associations between the lung disease measures in 2000 and the most recent FEV1 and WCXR. In addition to the chest CT scan score, WCXR, BCXR, FEV1 % predicted, FEF25–75 % predicted, and RV/TLC in 2000 were significantly associated with the most recent FEV1 % predicted (Table 4) and WCXR (Table 5). The chest CT scan score in 2000 was more strongly associated with the most recent FEV1 % predicted than either the 2000 FEV1 % predicted (P = 0.002) or FEF25–75 % predicted (P < 0.001) (Table 4). Similarly, the chest CT scan score in 2000 was more strongly associated with the most recent WCXR than either FEV1 % predicted (P < 0.001), FEF25–75 % predicted (P < 0.001), or RV/TLC (P < 0.001) in 2000 (Table 5). On the other hand, WCXR and BCXR in 2000 were statistically significantly associated with the most recent FEV1 % predicted (P < 0.001 for each) and WCXR (P < 0.001 for each). The strengths of the associations were not statistically significantly different between the most recent FEV1 and the 2000 chest CT scan, WCXR, and BCXR scores (P > 0.1 comparing 2000 chest CT scan to 2000 WCXR or BCXR). Similarly, the strengths of the associations were not statistically significantly different between the most recent WCXR and the 2000 chest CT scan, WCXR, and BCXR scores (P > 0.4 comparing 2000 chest CT scan to 2000 WCXR or BCXR).
|Measure at the Time of the Chest CT Scan||Parameter Estimate for Group Mean (SE) Difference in FEV1||P Value||P Value (F test) Comparing CT Scan with Lung Disease Measure|
|CT scan||−4.5 (0.8)||<0.001||—|
|FEV1, % predicted||0.8 (0.1)||<0.001||0.002|
|FEF25–75, % predicted||0.4 (0.1)||<0.001||<0.001|
|Pseudomonas aeruginosa||−4.1 (5.0)||0.4||—|
|Hospitalization in 2000||−0.9 (8.5)||0.9||—|
|Measure at the Time of the Chest CT Scan||Parameter Estimate for Group Mean (SE) Difference in WCXR||P Value||P Value (F test) Comparing CT Scan with Lung Disease Measure|
|CT scan||3.9 (0.5)||<0.001||—|
|FEV1, % predicted||−0.4 (0.1)||<0.001||<0.001|
|FEF25–75, % predicted||−0.1 (0.1)||0.03||<0.001|
|Pseudomonas aeruginosa||3.9 (3.6)||0.3||—|
|Hospitalization in 2000||−6.9 (6.5)||0.3||—|
We found that Brody chest CT scan scores were significantly associated with measures of lung disease severity obtained, on average, 5 to 7 years later for subjects followed prospectively in the WI RCT. The strength of this association was generally much stronger than other measures of lung disease severity obtained near the time of the chest CT scan. Previous studies have shown chest CT scans are able to detect early structural abnormalities in children with CF and lung disease progression even in children who have normal PFTs (4, 5, 7–9). However, only a few studies have evaluated the association between chest CT scan scores and future lung disease severity. Cademartiri and colleagues (23) reviewed Bhalla scores of chest CT scans performed at their center between 1991 and 2001 to evaluate the association between chest CT scan scores and future lung disease. There were 57 patients with two to three chest CT scans, performed at a mean age of 15 years (range 9 mo to 38 yr). Bhalla scores did not predict progression of PFTs. However, the strength of their evidence was weakened because the authors did not report actual Bhalla scores or PFT values, and correlations between chest CT scan scores and PFTs were only compared for PFTs expressed in liters, which does not take into account lung growth with age for children.
In a recent study, Loeve and colleagues demonstrated that Brody bronchiectasis subscores predict pulmonary exacerbation frequency over the ensuing 2 years, independent of FEV1 (10). Subjects with a Brody chest CT scan score worse than the median had more than five times as many pulmonary exacerbations as subjects with a Brody score less than 1. When we examined bronchiectasis subscores, we found that the strength of association with the most recent lung disease measures was even stronger than for the overall Brody chest CT scan score. The long-term significance of bronchiectasis in CF seems clear from Loeve and colleagues’ data and our data reported herein. Although there has been limited research on specific respiratory pathogens and their association with bronchiectasis, observations we published recently (5) revealed that P. aeruginosa infections correlated closely with development of this irreversible, structural lesion. The apparent role of mucoid P. aeruginosa as a determinant of bronchiectasis is consistent with its pathobiology, that is, its protective biofilm resistant to antibiotics (24) and many toxins and virulence factors (25).
Clinically, the implication of our findings, as well as those of Loeve and colleagues, is that chest CT scan scores may be used to identify children with CF who are at significant risk of lung disease progression. These findings are especially helpful because the slow rates of change of traditional spirometry (4, 7, 26) make using spirometry to monitor progression of lung disease severity in children difficult. Moreover, the patients at most risk of a greater subsequent decline in FEV1 are those with the highest FEV1 (27). It is unknown what the chest CT scan appearance is in these children with supranormal FEV1. Patients with high FEV1 and chest CT scan abnormalities may in fact be at greater risk of lung disease progression. Additional studies that use spirometry and chest CT scan scores may be useful to determine if targeting these patients for aggressive treatment decreases the rate of disease progression.
Although chest CT scan scores were more strongly associated with future lung disease severity than spirometry, we found that quantitative chest radiography (Wisconsin and Brasfield chest radiograph scores) were as strongly associated with future lung disease severity as the chest CT scan score. We (28) and others (29, 30) have previously demonstrated the sensitivity of quantitative chest imaging in monitoring lung disease progression in children with CF. Although further study is needed, it may be that quantitative chest imaging has a role in detecting bronchiectasis and may provide similar insight into future lung disease progression as chest CT scan, but without exposing patients to larger doses of ionizing radiation with chest CT scan (31).
Our study is limited in several ways. First, there was a wide range of follow up times after the chest CT scan: 2 to 10 years. Patients in the study began ageing out of the Wisconsin Neonatal Screening Project in 2005, when the oldest patients turned 21. This raises the possibility that the association we are identifying is between the chest CT scan and the lung disease measures obtained only a short time afterward. However, the strength of association remained when we adjusted for the time between the chest CT scan and the most recent measure of lung disease severity. Also, when we stratified the data by the median follow-up time, the parameter estimates were similar (data not shown). We are unable to make meaningful comparisons between the strengths of association with future lung disease progression between chest CT scan, infection with P. aeruginosa, and pulmonary exacerbation frequency because of the large standard errors for P. aeruginosa and pulmonary exacerbation frequency (Table 4). We did take into account the effects of infection with P. aeruginosa by adjusting for the presence of P. aeruginosa in our final model. We had relatively few patients hospitalized for a pulmonary exacerbation (9% of the cohort in 2000 and 24% in the year of the most recent data). Finally, these data were obtained from two CF centers with protocol-managed patients who generally had mild disease and who, before the chest CT scan in 2000, did not receive many of the standard treatments available to patients with CF today. However, given that patients with CF continue to have improvements in PFTs, these data should continue to be applicable.
We have shown that chest CT scan scores are associated with future lung disease severity, and that quantitative chest imaging (chest CT scan and chest radiograph scores) is more strongly associated with future lung disease severity than measures of spirometry. These findings may help clinicians identify patients at risk of future lung disease progression. More studies are needed that include chest imaging and spirometry, and over a longer time frame, to better understand the risk of lung disease progression in children with CF.
The authors thank the patients and the families who participated in this project and the entire Wisconsin Neonatal CF Screening Project team in Madison and Milwaukee. They also thank Anita Laxova for assistance with the database.
|1.||CF Foundation. Cystic Fibrosis Foundation Patient Registry 2008 Annual Data Report. Bethesda, MD: CF Foundation; 2009.|
|2.||Amin R, Lam M, Dupuis A, Ratjen F. The effect of early Pseudomonas aeruginosa treatment on lung function in pediatric cystic fibrosis. Pediatr Pulmonol 2011;46:554–558.|
|3.||Konstan M, Morgan W, Butler S, Pasta D, Craib M, Silva S, Stokes D, Wohl M, Wagener J, Regelmann W, 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.e1.|
|4.||Brody A, Klein J, Molina P, Quan J, Bean J, Wilmott R. High-resolution computed tomography in young patients with cystic fibrosis: distribution of abnormalities and correlation with pulmonary function tests. J Pediatr 2004;145:32–38.|
|5.||Farrell P, Collins J, Broderick L, Rock M, Li Z, Kosorok M, Laxova A, Gershan W, Brody A. Association between mucoid Pseudomonas infection and bronchiectasis in children with cystic fibrosis. Radiology 2009;252:534–543.|
|6.||Stick S, Brennan S, Murray C, Douglas T, von Ungern-Sternberg B, Garratt L, Gangell C, De Klerk N, Linnane B, Ranganathan S, et al..; Australian Respiratory Early Surveillance Team for Cystic Fibrosis (AREST CF). Bronchiectasis in infants and preschool children diagnosed with cystic fibrosis after newborn screening. J Pediatr 2009;155:623–628.e1.|
|7.||de Jong P, Nakano Y, Lequin M, Mayo J, Woods R, Paré P, Tiddens H. Progressive damage on high resolution computed tomography despite stable lung function in cystic fibrosis. Eur Respir J 2004;23:93–97.|
|8.||Brody A, Sucharew H, Campbell J, Millard S, Molina P, Klein J, Quan J. Computed tomography correlates with pulmonary exacerbations in children with cystic fibrosis. Am J Respir Crit Care Med 2005;172:1128–1132.|
|9.||de Jong P, Lindblad A, Rubin L, Hop W, de Jongste J, Brink M, Tiddens H. Progression of lung disease on computed tomography and pulmonary function tests in children and adults with cystic fibrosis. Thorax 2006;61:80–85.|
|10.||Loeve M, Gerbrands K, Hop WC, Rosenfeld M, Hartmann IC, Tiddens HA. Bronchiectasis and pulmonary exacerbations in children and young adults with CF. Chest 2011;140:178–185.|
|11.||Sanders D, Bittner R, Rosenfeld M, Redding G, Goss C. Pulmonary exacerbations are associated with subsequent FEV(1) decline in both adults and children with cystic fibrosis. Pediatr Pulmonol 2011;46:393–400.|
|12.||Farrell PM. Improving the health of patients with cystic fibrosis through newborn screening. Wisconsin Cystic Fibrosis Neonatal Screening Study Group. Adv Pediatr 2000;47:79–115.|
|13.||Sanders DB, Li Z, Brody A, Collins J, Broderick L, Farrell PM. Chest CT scores of severity predict future lung disease progression in children with CF [abstract]. Am J Respir Crit Care Med 2011;183:A2508.|
|14.||Farrell P, Kosorok M, Rock M, Laxova A, Zeng L, Lai H, Hoffman G, Laessig R, Splaingard M. Early diagnosis of cystic fibrosis through neonatal screening prevents severe malnutrition and improves long-term growth. Wisconsin Cystic Fibrosis Neonatal Screening Study Group. Pediatrics 2001;107:1–13.|
|15.||Kosorok M, Jalaluddin M, Farrell P, Shen G, Colby C, Laxova A, Rock M, Splaingard M. Comprehensive analysis of risk factors for acquisition of Pseudomonas aeruginosa in young children with cystic fibrosis. Pediatr Pulmonol 1998;26:81–88.|
|16.||Farrell P, Li Z, Kosorok M, Laxova A, Green C, Collins J, Lai H, Makholm L, Rock M, Splaingard M. Longitudinal evaluation of bronchopulmonary disease in children with cystic fibrosis. Pediatr Pulmonol 2003;36:230–240.|
|17.||Koscik R, Kosorok M, Farrell P, Collins J, Peters M, Laxova A, Green C, Zeng L, Rusakow L, Hardie R, et al.. Wisconsin cystic fibrosis chest radiograph scoring system: validation and standardization for application to longitudinal studies. Pediatr Pulmonol 2000;29:457–467.|
|18.||Brasfield D, Hicks G, Soong S, Tiller R. The chest roentgenogram in cystic fibrosis: a new scoring system. Pediatrics 1979;63:24–29.|
|19.||Brody AS, Kosorok MR, Li Z, Broderick LS, Foster JL, Laxova A, Bandla H, Farrell PM. Reproducibility of a scoring system for computed tomography scanning in cystic fibrosis. J Thorac Imaging 2006;21:14–21.|
|20.||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.|
|21.||Courtney J, Bradley J, Mccaughan J, O'Connor T, Shortt C, Bredin C, Bradbury I, Elborn J. Predictors of mortality in adults with cystic fibrosis. Pediatr Pulmonol 2007;42:525–532.|
|22.||Li Z, Lai H, Kosorok M, Laxova A, Rock M, Splaingard M, Farrell P. Longitudinal pulmonary status of cystic fibrosis children with meconium ileus. Pediatr Pulmonol 2004;38:277–284.|
|23.||Cademartiri F, Luccichenti G, Palumbo AA, Maffei E, Pisi G, Zompatori M, Krestin GP. Predictive value of chest ct in patients with cystic fibrosis: A single-center 10-year experience. AJR Am J Roentgenol 2008;190:1475–1480.|
|24.||Gibson R, Burns J, Ramsey B. Pathophysiology and management of pulmonary infections in cystic fibrosis. Am J Respir Crit Care Med 2003;168:918–951.|
|25.||Corech R, Rao A, Laxova A, Moss J, Rock MJ, Li Z, Kosorok MR, Splaingard ML, Farrell PM, Barbieri JT. Early immune response to the components of the type III system of pseudomonas aeruginosa in children with cystic fibrosis. J Clin Microbiol 2005;43:3956–3962.|
|26.||Gustafsson P, De Jong P, Tiddens H, Lindblad A. Multiple-breath inert gas washout and spirometry versus structural lung disease in cystic fibrosis. Thorax 2008;63:129–134.|
|27.||VanDevanter DR, Wagener JS, Pasta DJ, Elkin E, Jacobs JR, Morgan WJ, Konstan MW. Pulmonary outcome prediction (POP) tools for cystic fibrosis patients. Pediatr Pulmonol 2010;45:1156–1166.|
|28.||Farrell P, Li Z, Kosorok M, Laxova A, Green C, Collins J, Lai H, Rock M, Splaingard M. Bronchopulmonary disease in children with cystic fibrosis after early or delayed diagnosis. Am J Respir Crit Care Med 2003;168:1100–1108.|
|29.||Terheggen-Lagro SW, Arets HG, van der Laag J, van der Ent CK. Radiological and functional changes over 3 years in young children with cystic fibrosis. Eur Respir J 2007;30:279–285.|
|30.||Slattery DM, Zurakowski D, Colin AA, Cleveland RH. Cf: An x-ray database to assess effect of aerosolized tobramycin. Pediatr Pulmonol 2004;38:23–30.|
|31.||Donadieu J, Roudier C, Saguintaah M, Maccia C, Chiron R. Estimation of the radiation dose from thoracic CT scans in a cystic fibrosis population. Chest 2007;132:1233–1238.|
Supported by National Institutes of Health grants R01 DK34108 and DK34108–23S1 Revised (P.M.F.).
Author contributions: Conception, Design, Analysis, and Interpretation: D.B.S., Z.L., A.S.B., P.M.F.
This article has an online supplement, which is accessible from this issue's table of contents at www.atsjournals.org
Originally Published in Press as DOI: 10.1164/rccm.201105-0816OC on July 7, 2011