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Original Research: CYSTIC FIBROSIS |

Bronchiectasis and Pulmonary Exacerbations in Children and Young Adults With Cystic FibrosisBronchiectasis and Exacerbation in Cystic Fibrosis FREE TO VIEW

Martine Loeve, MD; Krista Gerbrands, MD; Wim C. Hop, PhD; Margaret Rosenfeld, MD, MPH; Ieneke C. Hartmann, MD, PhD; Harm A. Tiddens, MD, PhD
Author and Funding Information

From the Department of Pediatric Pulmonology and Allergology (Drs Loeve, Gerbrands, and Tiddens), Erasmus Medical Center-Sophia Children’s Hospital, Rotterdam, The Netherlands; Departments of Radiology (Drs Loeve, Hartmann, and Tiddens) and Biostatistics (Dr Hop), Erasmus Medical Center, Rotterdam, The Netherlands; and Division of Pulmonary Medicine (Dr Rosenfeld), Department of Pediatrics, University of Washington School of Medicine, Seattle, WA.

Correspondence to: Harm A. Tiddens, MD, PhD, Dr Molewaterplein 60, 3015 GJ Rotterdam, The Netherlands; e-mail: h.tiddens@erasmusmc.nl


Funding/Support: This study was supported by grants from the Sophia Cystic Fibrosis Research Fund, the Dutch Cystic Fibrosis Foundation, the Italian Cystic Fibrosis Fund, and the Cystic Fibrosis Foundation.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (http://www.chestpubs.org/site/misc/reprints.xhtml).


© 2011 American College of Chest Physicians


Chest. 2011;140(1):178-185. doi:10.1378/chest.10-1152
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Objective:  Respiratory tract exacerbation rate (RTE-R) is a key clinical efficacy end point in cystic fibrosis (CF) trials. Chest CT scanning holds great potential as a surrogate end point. Evidence supporting the ability of CT scan scores to predict RTE-R is an important step in validating CT scanning as a surrogate end point. The objective of this study was to investigate the association between CT scan scores and RTE-R in a cohort of pediatric patients with CF.

Methods:  A retrospective review of data from pediatric patients with CF included chest CT scans, spirometry, and 2 years follow-up. RTE-R was defined as the number of IV antibiotics courses per year. CT scans were scored with the Brody-II system, assessing bronchiectasis, airway wall thickening, mucus, and opacities.

Results:  One hundred fifteen patients contributed 170 CT scans. Median age and FEV1 at first CT scan were 12 years (range, 5-20 years) and 90% predicted (range, 23% predicted-132% predicted), respectively. Analyzing exacerbation counts using Poisson regression models, bronchiectasis score and FEV1 both were found to be strong independent predictors of RTE-R in the subsequent 2 years. For the bronchiectasis score categorized in quartiles, RTE-R increased by factors of 1.8 (95% CI, 0.6-6.1; P = .31), 5.5 (95% CI, 1.9-15.4; P = .001), and 10.6 (95% CI, 3.8-29.4; P < .001), respectively, for each quartile compared with the quartile with the best (ie, lowest) scores. Similarly, time to first respiratory tract exacerbation was significantly associated with quartiles of both bronchiectasis score and FEV1.

Conclusions:  The CT scan bronchiectasis score is strongly associated with RTE-R in pediatric patients with CF, providing an important piece of evidence in the validation of CT scans as an end point for CF clinical trials.

Figures in this Article

In cystic fibrosis (CF), many end points for clinical trials have been evaluated, including respiratory tract exacerbation rate (RTE-R), spirometry, BAL markers, and imaging.1,2 Of these end points, only RTE-R is considered a clinical outcome parameter, whereas the others are surrogate end points. Unfortunately, RTE-R lacks a standardized definition and frequently requires a relatively large sample size to detect a relevant treatment effect.3 Therefore, surrogate end points have been used, of which FEV1 is the most common.4 However, FEV1 has become relatively insensitive for monitoring the progression of CF lung disease because average lung function is now in the normal range until adolescence, and average annual FEV1 decline currently is < 1% per year.5 FEV1 also is insensitive to important localized structural damage, such as bronchiectasis.6 Thus, there is a need for more sensitive surrogate end points with the ability to detect disease onset and progression at an early stage.

CT scanning has great potential for use as a surrogate end point in CF lung disease because it is the gold standard for the detection of bronchiectasis, the defining structural abnormality in CF.7 CT scanning has been shown to be more sensitive than FEV1 in detecting early CF lung disease and in monitoring disease progression.8 In addition, CT scan parameters such as mucus plugging and centrilobular nodules have been shown to respond to treatment.9 Importantly, the use of CT scan-related parameters instead of FEV1 potentially could reduce the sample size in intervention studies,10 significantly enhancing the feasibility of clinical studies in CF.

An important step in the validation process of CT scanning as a clinical trial end point is establishing its association with clinical outcomes, such as RTE-R.3 To date, the association between CT scan scores and RTE-R has been investigated in only one small selected cohort. Among 61 patients with CF aged 6 to 11 years with well-preserved lung function participating in the Pulmozyme Early Intervention Trial, Brody et al11 found a statistically significant but relatively poor correlation between CT scan scores and RTE-R. Whether CT scan-related parameters correlate with RTE-R in an unselected CF population has never been investigated. Therefore, as one step in validating CT scan scores as a clinical trial end point, our primary aim was to investigate the predictive value of CT scan scores for RTE-R in the ensuing 2 years. Because lung function is the most widespread surrogate end point in CF clinical trials, a secondary objective was to evaluate the predictive value of CT scan scores while taking account of spirometric measurements with regard to RTE-R in the ensuing 2 years.

Study Population

This institutional review board-approved, retrospective, single-center study used clinical data from patients with CF who were followed at the Sophia Children’s Hospital Cystic Fibrosis Clinic in Rotterdam, The Netherlands. Inclusion criteria were: (1) confirmed CF diagnosis, (2) one or more routine biannual chest CT scans performed between March 2002 and March 2006 while clinically stable (CT scans performed for acute respiratory deterioration were not included in the current analysis), (3) at least one routine spirometry while clinically stable within 4 months of each CT scan, (4) age between 5 and 20 years at the first CT scan, (5) ≥ 2 years of follow-up after each CT scan, and (6) informed consent. Exclusion criteria were: (1) CT scans performed under general anesthesia (due to risk of anesthesia-induced atelectasis), (2) non-CF-related lung abnormalities, and (3) comorbidity potentially affecting RTE-R (severe tracheomalacia [n = 1], IgM deficiency [n = 1]).

Because there is no universal consensus on the definition of a respiratory tract exacerbation (RTE)12 we selected a conservative approach and defined RTEs as episodes of treatment with IV antibiotics for pulmonary indications, as used in other studies.11,13,14 For each subject, annual RTE-R was determined by detailed chart review. For one subject with severe lung disease requiring continuous IV treatment of > 1 year, the number of exacerbations was arbitrarily set at 10, a number larger than the highest observed count in the cohort. Pseudomonas aeruginosa culture positivity was defined as the presence of one or more positive respiratory cultures at any point in time before each CT scan (Pseudomonas positivity ever).

CT Scanning Protocol

Scans were performed on two scanners (Prospeed SX; GE Medical Systems; Waukesha, Wisconsin, and Somaton Emotion; Siemens Medical Solutions; Erlangen, Germany) in the supine position from apex to base. Only inspiratory scans were analyzed because protocols before September 2003 did not include expiratory acquisitions. All scans were performed during voluntary breath holds at end inspiration. CT scans performed from March 2002 to July 2004 were high-resolution scans and obtained at 80- to 120-kVp and 100- to 130-mA fixed tube current, 1.0-mm slice thickness at 5- to 10-mm intervals, 0.8- to 1.0-s rotation time, and high spatial frequency algorithm. Average radiation dose for these protocols was 0.9 mSv (based on a mean gap of 7.5 mm and calculated using the impact dosimetry calculator15 and multiplied with pediatric normalized values16). From August 2004 to March 2006, volumetric CT scans were obtained at 80- to 110-kVp and 20-mA reference tube current with 2-mm collimation, 3-mm slice thickness, 0.6-s rotation time, pitch of 1.5, and high spatial frequency algorithm. Average radiation dose for this protocol was approximately 1 mSv (inspiratory scan, 0.69 mSv, plus expiratory scan, 0.35 mSv).

CT Scan Scoring and Spirometry

Scans were scored with the Brody-II scoring system, evaluating bronchiectasis, airway wall thickening, mucus plugging, and opacities.17 Trapped air was excluded from the total score. Hence, the maximal possible total score (207 points) was reduced by 27 points for trapped air, changing the maximal score to 180 points. Scores were expressed as percentages of maximal scores on a zero-to-100 scale. All scans were deidentified, randomized, and scored by one experienced observer (K. G.).18 For within-observer variability, this observer rescored 25 random scans after 1 month. For between-observer variability, a second blinded observer (M. L.) scored 25 random scans. Both observers were blinded to lung function results and clinical status. The observers were trained using a scoring manual including reference images, and established good interobserver and intraobserver agreement prior to scoring CT scans for the current study. Spirometry was performed using the Jaeger diagnostic system (Jaeger AG; Hoechberg, Germany). FEV1, FVC, and forced expiratory flow at 75% of vital capacity were analyzed. All reference values were according to Zapletal et al.19

Statistical Analysis

Descriptive statistics were used to characterize the patients at the time of their first CT scan. For patients with two CT scans, the paired t test and Wilcoxon signed rank test were used to compare spirometry and CT scan scores, respectively, at the time of the first vs the second CT scan.

To evaluate the predictive value of CT scan score and spirometry on annual RTE-R in the subsequent 2 years, we used univariate and multivariable Poisson regression with generalized estimating equations to account for the correlation between repeated measures within an individual using SAS PROC GENMOD (SAS Institute; Cary, North Carolina). To account for the effect of the temporal change in CT scanning protocols, CT scans performed between March 2002 and July 2004 were coded CT1, and CT scans performed between August 2004 and March 2006 were coded CT2, with log e (observation time) per period as an offset. CT scan scores and spirometric measurements were grouped into quartiles based on their observed distributions in the study population, with the lowest CT scan score or highest FEV1 quartile as the reference category. This grouping into quartiles was chosen because there are no “natural” cutoff levels for the CT scan scores. The same grouping into quartiles was used for spirometry data. Kaplan-Meier curves were used to assess the time from each CT scan to the first subsequent RTE, and the log-rank test was used to evaluate differences between the quartiles.

Intraclass correlation coefficients (ICCs) were used to evaluate between- and within-observer agreement for CT scan scores. ICC values between 0.4 and 0.6, between 0.6 and 0.8, or ≥ 0.80 generally are considered to indicate moderate, good, and very good agreement, respectively. SPSS, version 15.0 (SPSS Inc; Chicago, Illinois) and SAS, version 9.2, statistical software were used for analyses. P < .05 (two-sided) was considered statistically significant.

We identified 156 patients who had at least one chest CT scan during the study period. From this cohort, 41 patients were excluded for reasons outlined in Figure 1. Thus, 115 patients were included in the current analyses, with 55 contributing two scans and 60 contributing one scan for a total of 170 scans. Total person-years of follow-up was 335. The mean ± SD follow-up period was 23.6 ± 2.2 months after each CT scan. Spirometry was performed on the same day as CT scanning for 149 of 170 observations. For the 21 remaining observations, the median time between CT scan and spirometry was 0 days (range, −42 to 125 days). Baseline subject characteristics are shown in Table 1.

Figure Jump LinkFigure 1. Flowchart of the study cohort. CF = cystic fibrosis.Grahic Jump Location
Table Graphic Jump Location
Table 1 —Baseline Characteristics of the Study Cohort

Data are presented as No. (%) or median (range), unless otherwise indicated. FEF75 = forced expiratory flow at 75% of vital capacity.

a 

Includes all P aeruginosa cultures ever before the time of the first CT scan.

Among the 55 subjects contributing two CT scans, a significant decrease in lung function (except for FVC) and increase in CT scan scores (except for airway wall thickening subscore) was observed between the first and second CT scans (Table 2). Mean ± SD time between the first and second CT scan was 1.9 ± 0.31 years.

Table Graphic Jump Location
Table 2 —Spirometry, Pseudomonas Culture Status, and CT Scan Scores at the Time of the First and Second CT Scans Among Subjects Contributing Two CT Scans (n = 55)

Data are presented as mean ± SD, median (range), or No. (%), unless otherwise indicated. See Table 1 legend for expansion of abbreviations.

a 

Includes all P aeruginosa cultures ever before the time of CT scan. The P value is not calculated because this percentage can only increase.

Among the 115 subjects, 51 (44%) experienced a total of 148 RTEs during follow-up. The mean annual RTE-R in the 2 years following each CT scan by quartile of CT scan score and spirometric measurements, derived from univariate Poisson modeling, is shown in Table 3. (Definitions of the parameters for all quartiles are presented in Table 4.) RTE-R increased significantly with both worsening lung function and CT scan score.

Table Graphic Jump Location
Table 3 —Annual Number of RTEs During the 2 Years Following Spirometry and CT Scans by Observed Quartile of the Parameter in the Study Populationa

Data are presented as mean (95% CI). P values are for the overall difference among quartiles from univariate Poisson regression models. RTE = respiratory tract exacerbation. See Table 1 legend for expansion of abbreviation.

a 

See Table 4 for definitions of quartiles for all parameters.

Table Graphic Jump Location
Table 4 —Definitions of Parameters for All Quartiles

Spirometry is presented as % predicted, and CT scan scores are presented as % of maximal scores. See Table 1 legend for expansion of abbreviation.

In separate multivariable models for spirometry and CT scan scores, the strongest spirometric predictor for annual RTE-R was FEV1, with FVC and forced expiratory flow at 75% of vital capacity not adding significantly to the model. For CT scan scores, the bronchiectasis score was the strongest predictor, with no additional significant effect of the other CT scan scores, including the total score (data not shown).

Table 5 shows the results of the multivariable Poisson regression model, including FEV1 and bronchiectasis score; age was not included because it did not add significantly to the model (P = .83). These results show that both FEV1 and bronchiectasis score have significant, independent predictive values for RTE-R in the ensuing 2 years.

Table Graphic Jump Location
Table 5 —Exacerbation RRs According to FEV1 and CT Scan Bronchiectasis Score

RR = rate ratio.

a 

From the multivariable Poisson regression model, including FEV1 and bronchiectasis score quartiles, adjusted for CT scan number. Both parameters were divided into quartiles as detailed in Table 3.

Kaplan-Meier plots of time to first RTE according to bronchiectasis score and FEV1 quartile are shown in Figure 2. Time to first RTE was significantly associated with quartiles of both bronchiectasis score and FEV1. Reproducibility was good for all CT scan scores. ICCs for within-observer agreement were all > 0.95, whereas between-observer agreement ranged from 0.61 (mucus plugging) to 0.86 (total score).

Figure Jump LinkFigure 2. Kaplan-Meier plots for time to first respiratory tract exacerbation after CT scan. A and B, Individuals are grouped by quartile of bronchiectasis score. C and D, Individuals are grouped by quartile of FEV1. Quartiles for FEV1 (% predicted) are as follows: quartile 1, ≥ 100%; quartile 2, 90%-100%; quartile 3, 79%-89%; quartile 4, ≤ 78%. Quartiles for bronchiectasis score are as follows: quartile 1, ≤ 1%; quartile 2, 2%-6%; quartile 3, 7%-15%; quartile 4, ≥ 16%. P values are derived from log-rank test for trend.Grahic Jump Location

The US Food and Drug Administration defines a surrogate end point as “a laboratory measurement or physical sign that is used in therapeutic trials as a substitute for a clinically meaningful endpoint that is a direct measure of how a patient feels, functions, or survives.”20 Surrogate end points, such as CT scan scores, generally are used as a substitute for true clinical efficacy measures, such as RTEs, when the clinical benefit may not be detectable in trials of reasonable cost, duration, or size.3 Food and Drug Administration regulations state that a surrogate end point is considered to be “reasonably likely to predict clinical benefit and, therefore, useable for drug approval if there is evidence based on epidemiologic, therapeutic, pathophysiologic, or other data supporting the association of the surrogate with the clinical benefit.”21

In the present study, we demonstrate the clear association between CT scan scores, particularly the bronchiectasis score, and RTEs in a cohort of patients with CF. This step is important in the process of validating CT scanning as a surrogate end point for CF clinical trials. The association between bronchiectasis and RTEs has been observed previously in a small cohort of young patients with CF with mild disease enrolled in a clinical trial,11 in patients with non-CF bronchiectasis,22 and in patients with COPD.23 In CF, RTE-R is an important clinical end point for intervention studies. RTE-R has been shown to increase with age and more severe lung function impairment.24 Furthermore, RTE-Rs clearly are associated with survival.25 Unfortunately, RTE-R is a relatively insensitive end point, especially in patients with well-preserved lung function, and requires a large sample size when used in clinical studies.3 In addition, there is no consensus regarding the definition of an RTE.12 Currently, FEV1 is still the most widely used surrogate end point; however, its use as a surrogate end point has substantial limitations. First, the annual change in FEV1 has become so small that intervention studies using rate of decline in FEV1 as the primary end point would require large sample sizes.10 In addition, FEV1 has poor sensitivity to detect early structural airway damage.8 It has been estimated that the use of bronchiectasis scores as a surrogate end point would require a smaller sample size10 and would increase the feasibility of clinical trials in CF. Other arguments that favor the use of the bronchiectasis score as a surrogate end point are that bronchiectasis is progressive,8 detectable early in the disease process,26 an important component of end-stage CF lung disease,27 and associated with impaired quality of life.28 An important next step in validating CT scanning as a surrogate end point will be to demonstrate that the effect of a therapy on the CT scan score predicts the drug’s effect on a clinical end point, such as RTE.3

To be able to use CT scan parameters such as the bronchiectasis score as end points in multicenter trials, CT scanning protocols and image analysis will need to be standardized to avoid bias related to differences in image resolution and density distribution and to improve the sensitivity and reproducibility of the scores. In addition, to use CT scanning in clinical studies, it is of utmost importance that the radiation dose be minimized. Scan protocols requiring low doses of radiation without losing relevant information have been developed.29 The volumetric CT scan protocol used in this study, which we still use in clinical practice, can acquire volumetric inspiratory and expiratory scans with a mean total effective dose of approximately 1 mSv (depending on tube voltage and patient size).18 This dose is comparable to one-third of the annual US background radiation dose.30 These doses likely can be further reduced in the near future.18 Keeping the risk-benefit ratio of clinical trials in mind, the bronchiectasis score should be considered as an end point in studies aiming to slow the progression of CF lung disease. Although the use of MRI in patients with CF as an alternative to CT scan seems promising,31 the spatial resolution of MRI, and therefore its use in the assessment of bronchiectasis, currently is still inferior to that of CT scan.32 For spirometry, methods such as lung clearance index may prove to be good surrogate markers for early disease in the future2,33,34; however, this needs to be investigated further.

The present study has several limitations. First, it was retrospective; therefore, we had to select a robust and conservative definition for RTE by defining it as the need for IV antibiotics treatment of pulmonary deterioration and increased symptoms. These data were easily extracted and validated using our electronic patient record. Unfortunately, there is no accepted consensus for RTEs in CF. Our definition has been used in other studies.11,13,14 Using this definition, RTEs were unlikely to be missed. However, any lack of ascertainment of RTEs would be unlikely to alter the association between CT scan scores and RTE-R. Second, this study was performed in a single center, potentially affecting the generalizability of the results. Although we included patients aged up to 20 years, our cohort consisted of relatively few adult patients with severe lung disease (n = 8 with FEV1 35% to 49% predicted, severe as defined by American Thoracic Society/European Respiratory Society criteria35). Hence, our model may not be adequate for the adult population with more advanced lung disease. Similarly, the model’s fit on an infant CF population could not be studied because children aged < 5 years were not included in this study. Whether bronchiectasis on CT scan is predictive for RTE in children aged < 6 years has to be further investigated because the nature and frequency of exacerbations may be different in these children relative to the population included in our study. Third, the importance of trapped air on CT images could not be established because 40 of the 170 scans did not contain expiratory images. In general, the importance of trapped air is less well established than that of bronchiectasis. Trapped air is present early in the disease process26 and in end-stage lung disease.27 However, its reversibility and impact on quality of life have not been established. Future studies are needed to determine the importance of trapped air as a possible surrogate end point in CF. Fourth, the CT scans in this study were performed using two different scanners and, thus, potentially could have introduced some bias related to differences in resolution and density distribution. However, we consider it unlikely that the differences in scanning techniques were substantial enough to cause significant differences in CT scan scores. In addition, we used a manual scoring system that generally is thought to be less sensitive to differences between CT scans and protocols.10,36 Despite these limitations, the results showed that the bronchiectasis score has significant additional predictive value for RTE-R beyond that provided by FEV1 in children and adolescents with mild to moderate CF lung disease, supporting further validation in a prospective study using the bronchiectasis score as a clinically relevant surrogate end point in clinical trials designed for this patient population.

Author contributions:Dr Loeve: contributed to the study design, CT scan scoring, statistical analysis, and writing of the manuscript.

Dr Gerbrands: contributed to the data collection, CT scan scoring, and critical reading of the manuscript.

Dr Hop: contributed to the study design, statistical analysis, and writing of the manuscript.

Dr Hartmann: contributed to the study design and critical reading of the manuscript.

Dr Rosenfeld: contributed to the study design and writing of the manuscript.

Dr Tiddens: contributed as principal investigator in the study design, analysis, and writing of the manuscript.

Other contributions: We thank A. Vaessen-Verberne, MD, PhD, for providing information on patients receiving care in one of the general hospitals associated with our hospital’s shared care model.

Financial/nonfinancial disclosures: The authors have reported to CHEST the following conflicts of interest: Dr Rosenfeld is a member of the North American Scientific Advisory Group, Epidemiology Study of CF, Genentech; has spoken on pulmonary exacerbations at national and international meetings; and receives research grants from the National Institutes of Health and the Cystic Fibrosis Foundation. Dr Tiddens has been involved in the process of setting up a core laboratory for chest imaging analysis since September 2010. Drs Loeve, Gerbrands, Hop, and Hartmann have reported to CHEST that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Role of sponsors: The sponsors had no role in the design of the study, the collection and analysis of the data, or in the preparation of the manuscript.

Other contributions: We thank A. Vaessen-Verberne, MD, PhD, for providing information on patients receiving care in one of the general hospitals associated with our hospital's shared care model.

CF

cystic fibrosis

ICC

intraclass correlation coefficient

RTE

respiratory tract exacerbation

RTE-R

respiratory tract exacerbation rate

Rosenfeld M. An overview of endpoints for cystic fibrosis clinical trials: one size does not fit all. Proc Am Thorac Soc. 2007;44:299-301. [CrossRef] [PubMed]
 
Davis SD, Brody AS, Emond MJ, Brumback LC, Rosenfeld M. Endpoints for clinical trials in young children with cystic fibrosis. Proc Am Thorac Soc. 2007;44:418-430. [CrossRef] [PubMed]
 
Mayer-Hamblett N, Ramsey BW, Kronmal RA. Advancing outcome measures for the new era of drug development in cystic fibrosis. Proc Am Thorac Soc. 2007;44:370-377. [CrossRef] [PubMed]
 
Ramsey BW, Boat TF. Outcome measures for clinical trials in cystic fibrosis. Summary of a Cystic Fibrosis Foundation consensus conference. J Pediatr. 1994;1242:177-192. [CrossRef] [PubMed]
 
Que C, Cullinan P, Geddes D. Improving rate of decline of FEV1 in young adults with cystic fibrosis. Thorax. 2006;612:155-157. [CrossRef] [PubMed]
 
Tiddens HA. Detecting early structural lung damage in cystic fibrosis. Pediatr Pulmonol. 2002;343:228-231. [CrossRef] [PubMed]
 
Hansell DM. Bronchiectasis. Radiol Clin North Am. 1998;361:107-128. [CrossRef] [PubMed]
 
de Jong PA, Lindblad A, Rubin L, et al. Progression of lung disease on computed tomography and pulmonary function tests in children and adults with cystic fibrosis. Thorax. 2006;611:80-85. [CrossRef] [PubMed]
 
Robinson TE, Leung AN, Northway WH, et al. Spirometer-triggered high-resolution computed tomography and pulmonary function measurements during an acute exacerbation in patients with cystic fibrosis. J Pediatr. 2001;1384:553-559. [CrossRef] [PubMed]
 
Tiddens HA, de Jong PA. Imaging and clinical trials in cystic fibrosis. Proc Am Thorac Soc. 2007;44:343-346. [CrossRef] [PubMed]
 
Brody AS, Sucharew H, Campbell JD, et al. Computed tomography correlates with pulmonary exacerbations in children with cystic fibrosis. Am J Respir Crit Care Med. 2005;1729:1128-1132. [CrossRef] [PubMed]
 
Rosenfeld M, Emerson J, Williams-Warren J, et al. Defining a pulmonary exacerbation in cystic fibrosis. J Pediatr. 2001;1393:359-365. [CrossRef] [PubMed]
 
Ortiz JR, Neuzil KM, Victor JC, Wald A, Aitken ML, Goss CH. Influenza-associated cystic fibrosis pulmonary exacerbations. Chest. 2010;1374:852-860. [CrossRef] [PubMed]
 
Sanders DB, Hoffman LR, Emerson J, et al. Return of FEV1 after pulmonary exacerbation in children with cystic fibrosis. Pediatr Pulmonol. 2010;452:127-134. [CrossRef] [PubMed]
 
Jones D, Shrimpton P. Survey of CT Practice in the UK. Part 3: Normalised Organ Doses for X-ray Computed Tomography Using Monte Carlo Techniques. NRPB-R250. 1991; London, England HMSO
 
Khursheed A, Hillier MC, Shrimpton PC, Wall BF. Influence of patient age on normalized effective doses calculated for CT examinations. Br J Radiol. 2002;75898:819-830. [PubMed]
 
Brody AS, Klein JS, Molina PL, Quan J, Bean JA, Wilmott RW. High-resolution computed tomography in young patients with cystic fibrosis: distribution of abnormalities and correlation with pulmonary function tests. J Pediatr. 2004;1451:32-38. [CrossRef] [PubMed]
 
Loeve M, Lequin MH, de Bruijne M, et al. Cystic fibrosis: are volumetric ultra-low-dose expiratory CT scans sufficient for monitoring related lung disease? Radiology. 2009;2531:223-229. [CrossRef] [PubMed]
 
Zapletal A, Paul T, Samanek M. Significance of contemporary methods of lung function testing for the detection of airway obstruction in children and adolescents [in German]. Z Erkr Atmungsorgane. 1977;149:343-371
 
New drug, antibiotic and biological drug product regulations: accelerated approval. Proposed rule. Fed Regist. 1992;57:13234-13242
 
Katz R. Biomarkers and surrogate markers: an FDA perspective. NeuroRx. 2004;12:189-195. [CrossRef] [PubMed]
 
Redding GJ. Bronchiectasis in children. Pediatr Clin North Am. 2009;561:157-171. [CrossRef] [PubMed]
 
Wedzicha JA, Hurst JR. Structural and functional co-conspirators in chronic obstructive pulmonary disease exacerbations. Proc Am Thorac Soc. 2007;48:602-605. [CrossRef] [PubMed]
 
Goss CH, Burns JL. Exacerbations in cystic fibrosis. 1: Epidemiology and pathogenesis. Thorax. 2007;624:360-367. [CrossRef] [PubMed]
 
Liou TG, Adler FR, Fitzsimmons SC, Cahill BC, Hibbs JR, Marshall BC. Predictive 5-year survivorship model of cystic fibrosis. Am J Epidemiol. 2001;1534:345-352. [CrossRef] [PubMed]
 
Long FR, Williams RS, Castile RG. Structural airway abnormalities in infants and young children with cystic fibrosis. J Pediatr. 2004;1442:154-161. [CrossRef] [PubMed]
 
Loeve M, van Hal PT, Robinson P, et al. The spectrum of structural abnormalities on CT scans from patients with CF with severe advanced lung disease. Thorax. 2009;6410:876-882. [CrossRef] [PubMed]
 
Courtney JM, Kelly MG, Watt A, et al. Quality of life and inflammation in exacerbations of bronchiectasis. Chron Respir Dis. 2008;53:161-168. [CrossRef] [PubMed]
 
Jung KJ, Lee KS, Kim SY, Kim TS, Pyeun YS, Lee JY. Low-dose, volumetric helical CT: image quality, radiation dose, and usefulness for evaluation of bronchiectasis. Invest Radiol. 2000;359:557-563. [CrossRef] [PubMed]
 
Brody AS, Frush DP, Huda W, Brent RL. American Academy of Pediatrics Section on Radiology American Academy of Pediatrics Section on Radiology Radiation risk to children from computed tomography. Pediatrics. 2007;1203:677-682. [CrossRef] [PubMed]
 
Altes TA, Eichinger M, Puderbach M. Magnetic resonance imaging of the lung in cystic fibrosis. Proc Am Thorac Soc. 2007;44:321-327. [CrossRef] [PubMed]
 
Failo R, Wielopolski PA, Tiddens HA, Hop WC, Mucelli RP, Lequin MH. Lung morphology assessment using MRI: a robust ultra-short TR/TE 2D steady state free precession sequence used in cystic fibrosis patients. Magn Reson Med. 2009;612:299-306. [CrossRef] [PubMed]
 
Kozlowska WJ, Bush A, Wade A, et al; London Cystic Fibrosis Collaboration London Cystic Fibrosis Collaboration Lung function from infancy to the preschool years after clinical diagnosis of cystic fibrosis. Am J Respir Crit Care Med. 2008;1781:42-49. [CrossRef] [PubMed]
 
Gustafsson PM, De Jong PA, Tiddens HA, Lindblad A. Multiple-breath inert gas washout and spirometry versus structural lung disease in cystic fibrosis. Thorax. 2008;632:129-134. [CrossRef] [PubMed]
 
Pellegrino R, Viegi G, Brusasco V, et al. Interpretative strategies for lung function tests. Eur Respir J. 2005;265:948-968. [CrossRef] [PubMed]
 
de Jong PA, Tiddens HA. Cystic fibrosis specific computed tomography scoring. Proc Am Thorac Soc. 2007;44:338-342. [CrossRef] [PubMed]
 

Figures

Figure Jump LinkFigure 1. Flowchart of the study cohort. CF = cystic fibrosis.Grahic Jump Location
Figure Jump LinkFigure 2. Kaplan-Meier plots for time to first respiratory tract exacerbation after CT scan. A and B, Individuals are grouped by quartile of bronchiectasis score. C and D, Individuals are grouped by quartile of FEV1. Quartiles for FEV1 (% predicted) are as follows: quartile 1, ≥ 100%; quartile 2, 90%-100%; quartile 3, 79%-89%; quartile 4, ≤ 78%. Quartiles for bronchiectasis score are as follows: quartile 1, ≤ 1%; quartile 2, 2%-6%; quartile 3, 7%-15%; quartile 4, ≥ 16%. P values are derived from log-rank test for trend.Grahic Jump Location

Tables

Table Graphic Jump Location
Table 1 —Baseline Characteristics of the Study Cohort

Data are presented as No. (%) or median (range), unless otherwise indicated. FEF75 = forced expiratory flow at 75% of vital capacity.

a 

Includes all P aeruginosa cultures ever before the time of the first CT scan.

Table Graphic Jump Location
Table 2 —Spirometry, Pseudomonas Culture Status, and CT Scan Scores at the Time of the First and Second CT Scans Among Subjects Contributing Two CT Scans (n = 55)

Data are presented as mean ± SD, median (range), or No. (%), unless otherwise indicated. See Table 1 legend for expansion of abbreviations.

a 

Includes all P aeruginosa cultures ever before the time of CT scan. The P value is not calculated because this percentage can only increase.

Table Graphic Jump Location
Table 3 —Annual Number of RTEs During the 2 Years Following Spirometry and CT Scans by Observed Quartile of the Parameter in the Study Populationa

Data are presented as mean (95% CI). P values are for the overall difference among quartiles from univariate Poisson regression models. RTE = respiratory tract exacerbation. See Table 1 legend for expansion of abbreviation.

a 

See Table 4 for definitions of quartiles for all parameters.

Table Graphic Jump Location
Table 4 —Definitions of Parameters for All Quartiles

Spirometry is presented as % predicted, and CT scan scores are presented as % of maximal scores. See Table 1 legend for expansion of abbreviation.

Table Graphic Jump Location
Table 5 —Exacerbation RRs According to FEV1 and CT Scan Bronchiectasis Score

RR = rate ratio.

a 

From the multivariable Poisson regression model, including FEV1 and bronchiectasis score quartiles, adjusted for CT scan number. Both parameters were divided into quartiles as detailed in Table 3.

References

Rosenfeld M. An overview of endpoints for cystic fibrosis clinical trials: one size does not fit all. Proc Am Thorac Soc. 2007;44:299-301. [CrossRef] [PubMed]
 
Davis SD, Brody AS, Emond MJ, Brumback LC, Rosenfeld M. Endpoints for clinical trials in young children with cystic fibrosis. Proc Am Thorac Soc. 2007;44:418-430. [CrossRef] [PubMed]
 
Mayer-Hamblett N, Ramsey BW, Kronmal RA. Advancing outcome measures for the new era of drug development in cystic fibrosis. Proc Am Thorac Soc. 2007;44:370-377. [CrossRef] [PubMed]
 
Ramsey BW, Boat TF. Outcome measures for clinical trials in cystic fibrosis. Summary of a Cystic Fibrosis Foundation consensus conference. J Pediatr. 1994;1242:177-192. [CrossRef] [PubMed]
 
Que C, Cullinan P, Geddes D. Improving rate of decline of FEV1 in young adults with cystic fibrosis. Thorax. 2006;612:155-157. [CrossRef] [PubMed]
 
Tiddens HA. Detecting early structural lung damage in cystic fibrosis. Pediatr Pulmonol. 2002;343:228-231. [CrossRef] [PubMed]
 
Hansell DM. Bronchiectasis. Radiol Clin North Am. 1998;361:107-128. [CrossRef] [PubMed]
 
de Jong PA, Lindblad A, Rubin L, et al. Progression of lung disease on computed tomography and pulmonary function tests in children and adults with cystic fibrosis. Thorax. 2006;611:80-85. [CrossRef] [PubMed]
 
Robinson TE, Leung AN, Northway WH, et al. Spirometer-triggered high-resolution computed tomography and pulmonary function measurements during an acute exacerbation in patients with cystic fibrosis. J Pediatr. 2001;1384:553-559. [CrossRef] [PubMed]
 
Tiddens HA, de Jong PA. Imaging and clinical trials in cystic fibrosis. Proc Am Thorac Soc. 2007;44:343-346. [CrossRef] [PubMed]
 
Brody AS, Sucharew H, Campbell JD, et al. Computed tomography correlates with pulmonary exacerbations in children with cystic fibrosis. Am J Respir Crit Care Med. 2005;1729:1128-1132. [CrossRef] [PubMed]
 
Rosenfeld M, Emerson J, Williams-Warren J, et al. Defining a pulmonary exacerbation in cystic fibrosis. J Pediatr. 2001;1393:359-365. [CrossRef] [PubMed]
 
Ortiz JR, Neuzil KM, Victor JC, Wald A, Aitken ML, Goss CH. Influenza-associated cystic fibrosis pulmonary exacerbations. Chest. 2010;1374:852-860. [CrossRef] [PubMed]
 
Sanders DB, Hoffman LR, Emerson J, et al. Return of FEV1 after pulmonary exacerbation in children with cystic fibrosis. Pediatr Pulmonol. 2010;452:127-134. [CrossRef] [PubMed]
 
Jones D, Shrimpton P. Survey of CT Practice in the UK. Part 3: Normalised Organ Doses for X-ray Computed Tomography Using Monte Carlo Techniques. NRPB-R250. 1991; London, England HMSO
 
Khursheed A, Hillier MC, Shrimpton PC, Wall BF. Influence of patient age on normalized effective doses calculated for CT examinations. Br J Radiol. 2002;75898:819-830. [PubMed]
 
Brody AS, Klein JS, Molina PL, Quan J, Bean JA, Wilmott RW. High-resolution computed tomography in young patients with cystic fibrosis: distribution of abnormalities and correlation with pulmonary function tests. J Pediatr. 2004;1451:32-38. [CrossRef] [PubMed]
 
Loeve M, Lequin MH, de Bruijne M, et al. Cystic fibrosis: are volumetric ultra-low-dose expiratory CT scans sufficient for monitoring related lung disease? Radiology. 2009;2531:223-229. [CrossRef] [PubMed]
 
Zapletal A, Paul T, Samanek M. Significance of contemporary methods of lung function testing for the detection of airway obstruction in children and adolescents [in German]. Z Erkr Atmungsorgane. 1977;149:343-371
 
New drug, antibiotic and biological drug product regulations: accelerated approval. Proposed rule. Fed Regist. 1992;57:13234-13242
 
Katz R. Biomarkers and surrogate markers: an FDA perspective. NeuroRx. 2004;12:189-195. [CrossRef] [PubMed]
 
Redding GJ. Bronchiectasis in children. Pediatr Clin North Am. 2009;561:157-171. [CrossRef] [PubMed]
 
Wedzicha JA, Hurst JR. Structural and functional co-conspirators in chronic obstructive pulmonary disease exacerbations. Proc Am Thorac Soc. 2007;48:602-605. [CrossRef] [PubMed]
 
Goss CH, Burns JL. Exacerbations in cystic fibrosis. 1: Epidemiology and pathogenesis. Thorax. 2007;624:360-367. [CrossRef] [PubMed]
 
Liou TG, Adler FR, Fitzsimmons SC, Cahill BC, Hibbs JR, Marshall BC. Predictive 5-year survivorship model of cystic fibrosis. Am J Epidemiol. 2001;1534:345-352. [CrossRef] [PubMed]
 
Long FR, Williams RS, Castile RG. Structural airway abnormalities in infants and young children with cystic fibrosis. J Pediatr. 2004;1442:154-161. [CrossRef] [PubMed]
 
Loeve M, van Hal PT, Robinson P, et al. The spectrum of structural abnormalities on CT scans from patients with CF with severe advanced lung disease. Thorax. 2009;6410:876-882. [CrossRef] [PubMed]
 
Courtney JM, Kelly MG, Watt A, et al. Quality of life and inflammation in exacerbations of bronchiectasis. Chron Respir Dis. 2008;53:161-168. [CrossRef] [PubMed]
 
Jung KJ, Lee KS, Kim SY, Kim TS, Pyeun YS, Lee JY. Low-dose, volumetric helical CT: image quality, radiation dose, and usefulness for evaluation of bronchiectasis. Invest Radiol. 2000;359:557-563. [CrossRef] [PubMed]
 
Brody AS, Frush DP, Huda W, Brent RL. American Academy of Pediatrics Section on Radiology American Academy of Pediatrics Section on Radiology Radiation risk to children from computed tomography. Pediatrics. 2007;1203:677-682. [CrossRef] [PubMed]
 
Altes TA, Eichinger M, Puderbach M. Magnetic resonance imaging of the lung in cystic fibrosis. Proc Am Thorac Soc. 2007;44:321-327. [CrossRef] [PubMed]
 
Failo R, Wielopolski PA, Tiddens HA, Hop WC, Mucelli RP, Lequin MH. Lung morphology assessment using MRI: a robust ultra-short TR/TE 2D steady state free precession sequence used in cystic fibrosis patients. Magn Reson Med. 2009;612:299-306. [CrossRef] [PubMed]
 
Kozlowska WJ, Bush A, Wade A, et al; London Cystic Fibrosis Collaboration London Cystic Fibrosis Collaboration Lung function from infancy to the preschool years after clinical diagnosis of cystic fibrosis. Am J Respir Crit Care Med. 2008;1781:42-49. [CrossRef] [PubMed]
 
Gustafsson PM, De Jong PA, Tiddens HA, Lindblad A. Multiple-breath inert gas washout and spirometry versus structural lung disease in cystic fibrosis. Thorax. 2008;632:129-134. [CrossRef] [PubMed]
 
Pellegrino R, Viegi G, Brusasco V, et al. Interpretative strategies for lung function tests. Eur Respir J. 2005;265:948-968. [CrossRef] [PubMed]
 
de Jong PA, Tiddens HA. Cystic fibrosis specific computed tomography scoring. Proc Am Thorac Soc. 2007;44:338-342. [CrossRef] [PubMed]
 
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