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Clinical Investigations: CYSTIC FIBROSIS |

Lung Function Decline in Cystic Fibrosis Patients and Timing for Lung Transplantation Referral* FREE TO VIEW

Daniel B. Rosenbluth, MD, FCCP; Kevin Wilson; Thomas Ferkol, MD; Daniel P. Schuster, MD
Author and Funding Information

*From the Departments of Internal Medicine and Pediatrics, Washington University School of Medicine, St. Louis, MO.

Correspondence to: Daniel Rosenbluth, MD, FCCP, University Box 8052, 660 S Euclid Ave, St. Louis, MO 63110; e-mail: rosenbluthd@wustl.edu



Chest. 2004;126(2):412-419. doi:10.1378/chest.126.2.412
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Published online

Study objectives: To determine risk factors associated with an accelerated decline in lung function in cystic fibrosis (CF), and whether longitudinal changes in FEV1 would be a better predictor of the need for referral for lung transplantation than any single value for FEV1.

Design: The rate of decline in pulmonary function was determined by standard linear regression from each patient’s calendar year’s best percentage of predicted FEV1 (%FEV1) over at least 4 years, and patients were classified into three cohorts based on their rate of decline. Differences between groups in age, weight-for-age z score, gender, genotype, pancreatic status, diabetes, and the presence of various lung microbial isolates were analyzed. A subset of 30 patients referred for lung transplantation were further analyzed, and a prediction model for lung transplantation referral was created using the patient’s rate of decline in lung function, the mean waiting time for donor organs, and the average level of lung function of patients prior to lung transplantation.

Patients: One hundred fifty-three patients with CF followed up at the Washington University Adult Cystic Fibrosis Center.

Results: Younger age, malnutrition, and concurrent infection with both Pseudomonas aeruginosa and Staphylococcus aureus were significant (p < 0.05) risk factors for rapidly declining lung function. Among patients with rapidly declining lung function, referral for lung transplantation would have occurred 8.4 months earlier than actual referral age (p < 0.05) if the prediction model had been used, possibly resulting in additional patient salvage in several cases.

Conclusions: Rate of decline in lung function should be routinely evaluated in patients with CF, and a prediction model utilizing the rate of decline in %FEV1, and the median regional waiting period for donor lungs for patients with CF may assist in the timing of referral for lung transplantation and more rapidly declining lung function.

Figures in this Article

Cystic fibrosis (CF) is an autosomal recessive disorder affecting approximately 25,000 persons in the United States. While CF can affect many organ systems, respiratory failure eventually accounts for the vast majority of mortality seen in the disease. Accordingly, despite treatment, many patients will eventually become candidates for lung transplantation. Given the long wait times for transplantable organs, accurate predictors of prognosis are urgently needed to optimize CF patient management.

Over the past 3 decades, the median survival for patients with CF has increased significantly to approximately 33 years.1Currently, the best available predictor of survival is the FEV1. Patients with CF and an FEV1 < 30% of its predicted value have an expected 50% 2-year mortality.2 Given that wait times for lung transplantation are approximately 2 years (based on Organ Procurement and Transplantation Network data, as of July 12, 2002), an FEV1 of 30% of predicted is an oft-quoted benchmark for lung transplantation referral.3

CF, however, is a disease characterized by both long-term and short-term fluctuations in lung function, which in turn are related to the severity of disease due to CF itself (which varies from patient to patient), chronic bacterial infection, and periodic pulmonary exacerbations. The FEV1 at any given time does not distinguish between the effects of chronic inflammation and acute infection on pulmonary function. These sources of imprecision lead to uncertainty about how to use the FEV1 as a basis for transplantation referral in particular, or how best to predict the future course of the disease in general.

Because pulmonary involvement in CF is progressive, we hypothesized that longitudinal changes in FEV1 should be a better predictor of future lung function than any single value for FEV1. The present study was designed to test this hypothesis, to assess factors (if any) which might produce differences in the rate of decline, and to evaluate how information about the rate of decline might affect decisions for lung transplantation referral.

We evaluated the medical records of all 174 patients with CF followed up at the Washington University Adult Cystic Fibrosis Center between 1995 and 2002 for whom pulmonary function data spanning at least 4 years were available (n = 153). Longitudinal trends in FEV1 were evaluated using the percentage of predicted FEV1 (%FEV1). Percentage of predicted values were calculated from the equations of Knudson et al.4The best %FEV1 of each calendar year, as suggested by others,5 was used in a regression analysis of %FEV1 vs age. The slope of the regression line established a rate of decline in %FEV1 for each patient.

For further analysis, the patients were classified into three cohorts based on the rate of decline in %FEV1: rapid (group R; rate of decline greater than the group mean + 2 SE), slow (group S; less than group mean − 2 SE), and intermediate (group I; within 2 SE of mean rate of decline). Charts were then reviewed, and the following data were collected: age, weight-for-age z score, gender, genotype, pancreatic status, diabetes, and the presence of various lung microbial isolates. These factors have all previously been identified as potentially important risk factors for an accelerated decline in pulmonary function.2,610 For this analysis, all microorganisms isolated from the lower respiratory tract of the patient during the final year of the study interval were considered to be infectious.

A subset that included the 30 patients who had been followed up longitudinally at the Washington University Cystic Fibrosis Center and were referred for lung transplantation during this same time period (1995 to 2002) was analyzed separately. Again, the best %FEV1 of the calendar year was plotted against patient age. This time, however, linear regression was applied to data spanning 4 years prior to the actual date of listing for transplantation. These regression equations allowed us to calculate a predicted age for referral based on the rate of decline in %FEV1, the median waiting time for patients with CF on the transplant list (2.11 years) [Organ Procurement and Transplantation Network data, as of July 12, 2002], and the average last recorded %FEV1 among patients with CF who died without transplantation at this medical center (20.9 ± 7.0%, n = 17, from years 1996 to 2002). Thus, specifically, the rate of decline was used to predict the age at which %FEV1 would reach 20%. Then, this age minus 2.11 years equaled the predicted age for referral. This predicted age was compared to the actual age when FEV1 was approximately 30% predicted (as already noted, a commonly used benchmark for referral), and to actual age at the time of listing. Subcohorts of patients with a rapid decline in lung function (greater than group mean rate of decline + 2 SE), stable lung function (less than group mean − 2 SE), and of those who died while waiting on the list were also compared.

Variation within each group was expressed as the mean ± SD. Statistically significant differences among groups were analyzed by standard analysis of variance methods. Trends over time were analyzed by standard linear regression techniques.

The mean rate of decline in %FEV1 for all patients was – 3.89 ± 4.11%/yr. This number is similar to results of similar analyses by others.1115 The distribution is shown in Figure 1 .

Since 2 SEs about the mean defines the 95% confidence limits for the true mean, patients with rates of decline greater or less than these limits are not likely to have an “average” rate of decline in pulmonary function. The rate of decline was greater than the above overall group mean + 2 SE in 54 patients (group R). In these patients, the mean rate of decline in %FEV1 was −8.1 ± 4.0%/yr (Table 1 ). In 82 patients, the rate of decline was < 2 SE below the overall group mean. In these patients (group S), the mean rate of decline in %FEV1 was − 1.1 ± 1.2%/yr. The final 17 patients had intermediate rates of decline, ie, within 2 SE of the overall group mean. In these patients (group I), the mean rate of decline in %FEV1 was − 3.8 ± 0.4%.

The value of analyzing the “year’s best” %FEV1 is demonstrated by the strength of the correlations with age. In the group R patients, the coefficient of determination (R2) for this correlation was 0.90 ± 0.1. The coefficient of determination estimates the fraction of variation in the dependent variable that can be explained by the variation in the independent variable. Thus, on average, 90% of the decline in lung function in group R patients could be “explained” by changes in age alone. This observation suggests that the decline in lung function was characteristic of the CF lung for these patients, and was uninfluenced by clinical episodes of infection, other exacerbations, or their treatment. Coefficients of determination were 0.82 ± 0.2 and 0.44 ± 0.3 for group I and group S patients, respectively.

An example from group R is shown in Figure 2 , demonstrating the value of using only the year’s best %FEV1 in the analysis. When all values are used (Fig 2, top, A), the rate of decline in %FEV1 is underestimated at 6.7%/yr. When only the year’s best data are included (Fig 2, bottom, B), it becomes apparent that lung function in this patient is characterized by a period of stability followed by an abrupt and highly linear acceleration in the rate of decline. At this point, the rate of decline was 9.8%/yr, or nearly 50% greater than estimated when using all available pulmonary function test data.

Table 1 provides information about the prevalence of various prognostic risk factors for the decline in lung function within the various groups. Of the variables analyzed, younger age, lower weight-for-age z score, and the incidence of Staphylococcus aureus isolates in addition to Pseudomonas aeruginosa were found to be significantly different (p < 0.05) between groups R and group S.

A total of 30 patients were listed for lung transplantation (Table 2 ). In addition to these 30 patients, 8 patients died without being listed for lung transplantation. Three patients were not suitable candidates for transplantation (nonadherence to a medical regimen, poorly controlled diabetes mellitus with chronic renal insufficiency, and cirrhosis with portal hypertension), three patients declined the opportunity to be evaluated for transplantation, and two patients experienced catastrophic illnesses prior to being referred for transplant (severe exacerbation with acute respiratory failure, and pneumonia and sepsis).

At our center, patients with CF are generally referred for evaluation for transplantation when the %FEV1 is approximately 30% of predicted at a time when the patient is not experiencing an exacerbation. Some patients are referred earlier or later based on their caring physician’s impression of their clinical course, or the patient’s acceptance of the transplantation option. Once a patient is evaluated and listed, they are placed on the waiting list until an offer for a donor organ is received. Under the current United Network for Organ Sharing system, lungs are allocated on the basis of their suitability to the recipient and the recipient’s time on the waiting list. Recipients are not prioritized by disease severity. If donor organs become available to a patient who is maintaining good functional status without a transplant, transplantation may be deferred and the patient will become inactive on the transplant list. The patient does not continue to accrue waiting time, but retains the waiting time he/she has accrued to that point for use if their condition should deteriorate and they require reactivation.

For the group listed for transplantation, there was no difference between the mean age at which the patients reached %FEV1 of 30%, the mean age at which the patients were actually listed for transplantation, and the mean age at which a model using the rate of decline in lung function would have predicted the patients should be listed. However, differences were detected for the subcohorts defined on the basis of the rate of decline in lung function. For the 14 patients listed for transplantation who were part of group R, the mean age at which a model using the rate of decline in lung function would have predicted these patients should be listed for transplantation was significantly younger than the mean age at which the patients reached an FEV1 of 30% of predicted (27.1 years vs 27.8 years; ie, 8.4 months). For the 11 patients listed for transplantation who were in group S, a model using the rate of decline in lung function would have predicted that the mean age at which these patients should have been listed would have been significantly older than the actual mean age at which the patients reached an FEV1 of 30% of predicted (33.3 years vs 29.2 years).

Of the 30 patients, 5 patients died on the waiting list, while 16 patients received successful transplantations (Table 3 ). Four of the five patients who died while waiting for donor organs would have been listed sooner based on the prediction model. Assuming that patients would have undergone transplantation after 2.11 years of waiting time, at least three of the five patients who died while waiting for donor organs might have actually received transplantation had the model been employed (Table 3). Three of the five patients were also from group R; had the predictive model been employed, they would have been listed for transplantation an average of 9.5 months prior to their FEV1% reaching 30%. Although patients are often referred for transplantation when their FEV1 reaches 30% of predicted, in reality there is generally a delay of weeks to months until patients have undergone an evaluation and are listed. This delay in listing for transplantation further supports use of a predictive model in rapidly declining patients.

In contrast to the results among the 5 patients who died while on the waiting list, 7 of the 16 patients who underwent successful transplantations might not have survived to transplantation had a model been employed that calculated the age at which they should have been listed for transplantation (Table 4 ). This assumption is based on the fact that adhering to the regression model would have added more than an additional year of waiting time to each patient. Since our center will not proceed with transplantation unless patients have a significant risk of mortality within the next few months (chronic respiratory failure with hypoxemia), it is reasonable to assume that these patients likely would not have survived an additional year. All of the patients who might not have survived to transplantation (had the regression model been used) would have been listed at an FEV1 of < 30% of predicted based on their rate of decline, and six of the seven patients were from group S.

Of the remaining nine patients who received successful transplantations, five patients were in group R. Of these five patients, four patients would have been listed sooner, using the predictive regression model, than they were actually listed (average of 4.3 months). This difference could have been significant, as two of these patients received lung transplantation in less than the average 2.11 years of waiting time.

The patient shown in Figure 2 illustrates these principles. This patient (CF16 in Table 4) had a rate of decline of nearly 10%/yr. Based on this rate of decline, the patient should have been listed for transplantation at the age of 30.2 years. However, the patient was actually listed at the age of 31.1 years (nearly 11 months later). The actual age of listing was very close to the age at which the patient’s lung function reached 30% predicted. Thus, the regression model would have allowed the patient nearly an additional 11 months on the waiting list. Although she underwent successful transplantation, respiratory failure developed and the patient required mechanical ventilation prior to transplantation (which occurred after only 1 year of waiting time). The additional 11 months would have brought the patient much closer to the average waiting time of 2.11 years, and may have obviated the need for mechanical ventilation.

While a decline in lung function is typical of almost all patients with CF, the rate of decline is highly variable. In addition, Menendez et al16 noted different patterns of decline, which they characterized as early linear decline, no change, no change followed by linear decline, or no distinguishable pattern. In the current study, the overall rate of decline in lung function in our adult patients was similar to that published in other series.1115 Moreover, we also observed patterns of deterioration similar to that identified by Menendez et al.16 In some cases, these patterns emerged only after removing the “noise” of fluctuations in lung function due to clinical exacerbations (for example, the patient shown in Fig 2).

Attempts to analyze an individual patient’s rate of decline in lung function remain confounded by reversible changes that occur regularly in patients with CF. It is recommended that patients with CF have quarterly evaluations of lung function. We therefore chose the year’s best %FEV1 for our analysis since 1-year intervals would provide us with enough serial measurements to represent a patient’s status unaffected by transient episodes of acute pulmonary infection or inflammation. The year’s best FEV1 also provides an adequate period of observation that takes into account acute variations due to changes in, or adherence to the prescribed medical regimen. The value of this strategy is supported by the highly linear declines in lung function that were observed.

The linear decline in lung function that was identified in the group R patients, especially when analyzing only the year’s best %FEV1 data, was particularly striking, with an average R2 value of 0.9 ± 0.1. In these patients, this progressive decline in lung function occurred despite intensification of therapy and frequent hospitalizations for treatment of presumed respiratory exacerbations of their disease. The etiology of this apparent inexorable decline in lung function (despite temporary fluctuations due to acute infection) is uncertain of course; it may be related to inadequately treated infection, unchecked noninfectious inflammation in the CF lung, or other unknown causes. Coefficients of determination were lower in group I and group S, since little variation in lung function was observed over the 4-year analysis period.

Traditionally, disease severity in patients with CF is stratified on the basis of the FEV1. While the FEV1 is an excellent marker of respiratory impairment at any one moment in time, the %FEV1 at any one time is a poor prognostic marker of disease severity. For example, the severity of disease in a 15-year-old patient with an %FEV1 of 45% and an 8% rate of decline in lung function per year is obviously very different from a 35-year-old patient with the same %FEV1 declining at an annual rate of 1% of predicted per year. In clinical trials, this difference is partially corrected by age-matching patients in various study arms. However, in our analysis, we came across numerous patients of similar age and %FEV1 who had different rates of decline in their lung function. By routinely analyzing the rate of decline in lung function, we might be able to better identify those patients in whom more aggressive therapeutic interventions are warranted. Such analyses might also better identify patients for clinical trials, as patients with greater rates of decline in lung function would be more likely to show a benefit from an intervention at an earlier time.

As reported in other studies,2,6patients in the present study with poorer nutritional status had a worse prognosis (Table 1). While there was a trend toward poorer outcomes in patients with diabetes mellitus (26% of patients in group R vs 12% of patients in group S), the number of patients with diabetes were too few for these differences to reach statistical significance. Similarly there were very few patients in our study group with Burkholderia cepacia infection, which is also associated with more rapid decline in lung function in patients with CF.7,10

The lungs of neonates with CF are typically sterile, and bacterial cultures of respiratory secretions from infants often fail to yield a specific pathogen. S aureus, typable and nontypable Haemophilus influenzae, or Escherichia coli may be intermittently isolated from many patients early in life, but these organisms eventually are replaced by P aeruginosa. Isolation of mucoid strains of P aeruginosa from the lung of a patient has been considered virtually pathognomonic for CF, and its early acquisition is associated with a poorer prognosis. Other investigators89 have found that the acquisition of P aeruginosa infection in patients with CF and a previous S aureus infection is associated with an accelerated decline in lung function. Interestingly, we found that in our population, patients who had concurrent infections with S aureus and P aeruginosa had an accelerated decline in lung function when compared to patients with P aeruginosa infection alone. This apparent synergy is supported by a previous study by Hudson et al,,17 who demonstrated diminished survival in young children whose initial oropharyngeal culture grew P aeruginosa and S aureus. The mechanism of this synergy is not clear, but it does suggest that both infections should be treated aggressively.

Timing of referral for lung transplantation is a difficult task. Currently, patients are often referred when their %FEV1 approaches 30% of its predicted value at a time of clinical stability.3 Others have suggested that overreliance on this benchmark could adversely affect overall survival of patients with CF,18 and that the rate of decline in %FEV1 should be considered in the decision-making process.,15 In a study by Mayer-Hamblett et al,19 the investigators created and validated a multiple logistic regression for predicting 2-year mortality in CF. However, this model proved to be no better than the FEV1 criterion in timing referral for lung transplantation, and would not be easily available to caregivers throughout the world for application to their patient populations.

In our study, we examined whether predicting when a patient will reach a %FEV1 of approximately 20% predicted (the approximate average %FEV1 at which patients with CF at our center undergo transplantation) based on their current rate of decline in lung function, combined with known waiting periods for donor lungs, might be a better method for timing referral for lung transplantation. The target of 20% for the %FEV1 is similar to the mean %FEV1 of 21% found in patients with CF by Liou et al,20 who had a survival advantage from lung transplantation. Indeed, we found that for patients who had a more rapid rate of decline in lung function and an FEV1 > 30% of predicted, this method was superior to simply waiting for the FEV1 to first fall to 30% before referral. As a result, more patients might have undergone successful transplantations.

We also found, however, that for patients who had an FEV1 < 30% predicted with slower rates of decline in lung function, use of the rate of decline in lung function in order to time referral for transplantation could be dangerous and result in excess deaths. This is likely due to the fact that patients with an FEV1 of ≤ 30% predicted have so little pulmonary reserve that any new complication or alteration in the underlying disease process may not be well tolerated.

Therefore, if the patient is an appropriate candidate, we argue that all patients be referred for transplantation when their baseline %FEV1 reaches 30% of predicted, or sooner as dictated by the rate of decline in lung function and regional waiting periods for donor organs. While some might argue that this may lead to premature referral for transplantation, and that premature referral for transplantation could shorten life expectancy, we view the decision to refer for transplantation, and the decision to proceed with transplantation as separate decisions, and would only recommend proceeding with transplantation to those whose expected survival was clearly limited to a few months. Others argue that premature referral should be avoided due to the psychological impact of referral for lung transplantation on the patient.15 We agree with these reservations, but feel that various forms of psychosocial support are more appropriate as the alternative, ie, delayed referral, could be disastrous and result in death on the waiting list.

The rate of decline in lung function (using the year’s best %FEV1) should be routinely evaluated in patients with CF. This analysis can be easily performed by any caregiver for any patient with the use of commonly available spreadsheet applications. Patients with CF should be referred for transplantation at a time when based on their rate of decline in lung function, the expected time for their %FEV1 to reach 20% equals the average local waiting time for donor lungs, or when the baseline %FEV1 reaches 30%, whichever comes first.

Abbreviations: CF = cystic fibrosis; %FEV1 = percentage of predicted FEV1

Supported in part by a grant from the Cystic Fibrosis Foundation.

Figure Jump LinkFigure 1. Histogram of the rate of decline in lung function among 153 patients with CF based on analysis of the year’s best %FEV1.Grahic Jump Location
Table Graphic Jump Location
Table 1. Comparison of Prognostic Factors for Lung Function Decline*
* 

Data are presented as mean ± SD or %.

 

p < 0.05, group R vs group S.

Figure Jump LinkFigure 2. Top, A: Correlation of all available %FEV1 data vs patient age for one patient in group R (patient CF16 in Table 4). Also shown is the line of regression. Bottom, B: Correlation of only year’s best %FEV1 data vs patient age for the same patient shown in top, A. Only the filled circles were used to define the rate of decline in lung function by regression analysis. The filled arrow shows the age at which the patient would have been referred for lung transplantation based on this rate of decline. The empty arrow shows the age at which the patient was actually listed for transplantation.Grahic Jump Location
Table Graphic Jump Location
Table 2. Impact of Regression Model on Age for Referral for Lung Transplantation*
* 

Data are presented as mean ± SD.

T = actual age when FEV1 reached 30% predicted; L = actual age at the time of listing; P = predicted age when listing should occur.

 

p < 0.05 compared to age T.

Table Graphic Jump Location
Table 3. Impact of Regression Model on Age for Referral for Lung Transplantation Among Patients Who Died While on the Waiting List
Table Graphic Jump Location
Table 4. Impact of Regression Model on Age for Referral for Lung Transplantation Among Patients With Successful Transplantations
. Cystic Fibrosis Foundation (2002)Patient registry 2001 annual data report. Cystic Fibrosis Foundation. Bethesda, MD:
 
Kerem, E, Reisman, J, Corey, M, et al Prediction of mortality in patients with cystic fibrosis.N Engl J Med1992;326,1187-1191. [CrossRef] [PubMed]
 
Kotloff, RM, Zuckerman, JB Lung transplantation for cystic fibrosis: special considerations.Chest1996;109,787-798. [CrossRef] [PubMed]
 
Knudson, RJ, Lebowitz, MD, Holberg, CJ, et al Changes in the normal maximal expiratory flow-volume curve with growth and aging.Am Rev Respir Dis1983;127,725-734. [PubMed]
 
Schluchter, M, Davis, P, Drumm, M, et al Modeling the relationship between FEV1decline and survival in cystic fibrosis patients.Pediatr Pulmonol2000;30(Suppl),135-137
 
Schaedel, C, de Monestrol, I, Hjelte, L, et al Predictors of deterioration of lung function in cystic fibrosis.Pediatr Pulmonol2002;33,483-491. [CrossRef] [PubMed]
 
Lewin, LO, Byard, PJ, Davis, PB Effect ofPseudomonas cepaciacolonization on survival and pulmonary function of cystic fibrosis patients.J Clin Epidemiol1990;43,125-131. [CrossRef] [PubMed]
 
Demko, CA, Byard, PJ, Davis, PB Gender differences in cystic fibrosis:Pseudomonas aeruginosainfection.J Clin Epidemiol1995;48,1041-1049. [CrossRef] [PubMed]
 
Nixon, GM, Armstrong, DS, Carzino, R, et al Clinical outcome after earlyPseudomonas aeruginosainfection in cystic fibrosis.J Pediatr2001;138,699-704. [CrossRef] [PubMed]
 
Tablan, OC, Martone, WJ, Doershuk, CF, et al Colonization of the respiratory tract withPseudomonas cepaciain cystic fibrosis: risk factors and outcomes.Chest1987;91,527-532. [CrossRef] [PubMed]
 
Corey, M, Levison, H, Crozier, D Five- to seven-year course of pulmonary function in cystic fibrosis.Am Rev Respir Dis1976;114,1085-1092. [PubMed]
 
Corey, M, Edwards, L, Levison, H, et al Longitudinal analysis of pulmonary function decline in patients with cystic fibrosis.J Pediatr1997;131,809-814. [CrossRef] [PubMed]
 
Davis, PB, Byard, PJ, Konstan, MW Identifying treatments that halt progression of pulmonary disease in cystic fibrosis.Pediatr Res1997;41,161-165. [PubMed]
 
Konstan, MW, Byard, PJ, Hoppel, CL, et al Effect of high-dose ibuprofen in patients with cystic fibrosis.N Engl J Med1995;332,848-854. [CrossRef] [PubMed]
 
Augarten, A, Akons, H, Aviram, M, et al Prediction of mortality and timing of referral for lung transplantation in cystic fibrosis patients.Pediatr Transplant2001;5,339-342. [CrossRef] [PubMed]
 
Menendez, R, Mather, F, Waring, WW Long-term patterns of obstructive lung disease in cystic fibrosis.Chest1980;77,321-323. [PubMed]
 
Hudson, VL, Wielinski, CL, Regelmann, WE Prognostic implications of initial oropharyngeal bacterial flora in patients with cystic fibrosis diagnosed before the age of two years.J Pediatr1993;122,854-860. [CrossRef] [PubMed]
 
Doershuk, CF, Stern, RC Timing of referral for lung transplantation for cystic fibrosis: overemphasis on FEV1may adversely affect overall survival.Chest1999;115,782-787. [CrossRef] [PubMed]
 
Mayer-Hamblett, N, Rosenfeld, M, Emerson, J, et al Developing cystic fibrosis lung transplant referral criteria using predictors of 2-year mortality.Am J Respir Crit Care Med2002;166,1550-1555. [CrossRef] [PubMed]
 
Liou, TG, Adler, FR, Cahill, BC, et al Survival effect of lung transplantation among patients with cystic fibrosis.JAMA2001;286,2683-2689. [CrossRef] [PubMed]
 

Figures

Figure Jump LinkFigure 1. Histogram of the rate of decline in lung function among 153 patients with CF based on analysis of the year’s best %FEV1.Grahic Jump Location
Figure Jump LinkFigure 2. Top, A: Correlation of all available %FEV1 data vs patient age for one patient in group R (patient CF16 in Table 4). Also shown is the line of regression. Bottom, B: Correlation of only year’s best %FEV1 data vs patient age for the same patient shown in top, A. Only the filled circles were used to define the rate of decline in lung function by regression analysis. The filled arrow shows the age at which the patient would have been referred for lung transplantation based on this rate of decline. The empty arrow shows the age at which the patient was actually listed for transplantation.Grahic Jump Location

Tables

Table Graphic Jump Location
Table 1. Comparison of Prognostic Factors for Lung Function Decline*
* 

Data are presented as mean ± SD or %.

 

p < 0.05, group R vs group S.

Table Graphic Jump Location
Table 2. Impact of Regression Model on Age for Referral for Lung Transplantation*
* 

Data are presented as mean ± SD.

T = actual age when FEV1 reached 30% predicted; L = actual age at the time of listing; P = predicted age when listing should occur.

 

p < 0.05 compared to age T.

Table Graphic Jump Location
Table 3. Impact of Regression Model on Age for Referral for Lung Transplantation Among Patients Who Died While on the Waiting List
Table Graphic Jump Location
Table 4. Impact of Regression Model on Age for Referral for Lung Transplantation Among Patients With Successful Transplantations

References

. Cystic Fibrosis Foundation (2002)Patient registry 2001 annual data report. Cystic Fibrosis Foundation. Bethesda, MD:
 
Kerem, E, Reisman, J, Corey, M, et al Prediction of mortality in patients with cystic fibrosis.N Engl J Med1992;326,1187-1191. [CrossRef] [PubMed]
 
Kotloff, RM, Zuckerman, JB Lung transplantation for cystic fibrosis: special considerations.Chest1996;109,787-798. [CrossRef] [PubMed]
 
Knudson, RJ, Lebowitz, MD, Holberg, CJ, et al Changes in the normal maximal expiratory flow-volume curve with growth and aging.Am Rev Respir Dis1983;127,725-734. [PubMed]
 
Schluchter, M, Davis, P, Drumm, M, et al Modeling the relationship between FEV1decline and survival in cystic fibrosis patients.Pediatr Pulmonol2000;30(Suppl),135-137
 
Schaedel, C, de Monestrol, I, Hjelte, L, et al Predictors of deterioration of lung function in cystic fibrosis.Pediatr Pulmonol2002;33,483-491. [CrossRef] [PubMed]
 
Lewin, LO, Byard, PJ, Davis, PB Effect ofPseudomonas cepaciacolonization on survival and pulmonary function of cystic fibrosis patients.J Clin Epidemiol1990;43,125-131. [CrossRef] [PubMed]
 
Demko, CA, Byard, PJ, Davis, PB Gender differences in cystic fibrosis:Pseudomonas aeruginosainfection.J Clin Epidemiol1995;48,1041-1049. [CrossRef] [PubMed]
 
Nixon, GM, Armstrong, DS, Carzino, R, et al Clinical outcome after earlyPseudomonas aeruginosainfection in cystic fibrosis.J Pediatr2001;138,699-704. [CrossRef] [PubMed]
 
Tablan, OC, Martone, WJ, Doershuk, CF, et al Colonization of the respiratory tract withPseudomonas cepaciain cystic fibrosis: risk factors and outcomes.Chest1987;91,527-532. [CrossRef] [PubMed]
 
Corey, M, Levison, H, Crozier, D Five- to seven-year course of pulmonary function in cystic fibrosis.Am Rev Respir Dis1976;114,1085-1092. [PubMed]
 
Corey, M, Edwards, L, Levison, H, et al Longitudinal analysis of pulmonary function decline in patients with cystic fibrosis.J Pediatr1997;131,809-814. [CrossRef] [PubMed]
 
Davis, PB, Byard, PJ, Konstan, MW Identifying treatments that halt progression of pulmonary disease in cystic fibrosis.Pediatr Res1997;41,161-165. [PubMed]
 
Konstan, MW, Byard, PJ, Hoppel, CL, et al Effect of high-dose ibuprofen in patients with cystic fibrosis.N Engl J Med1995;332,848-854. [CrossRef] [PubMed]
 
Augarten, A, Akons, H, Aviram, M, et al Prediction of mortality and timing of referral for lung transplantation in cystic fibrosis patients.Pediatr Transplant2001;5,339-342. [CrossRef] [PubMed]
 
Menendez, R, Mather, F, Waring, WW Long-term patterns of obstructive lung disease in cystic fibrosis.Chest1980;77,321-323. [PubMed]
 
Hudson, VL, Wielinski, CL, Regelmann, WE Prognostic implications of initial oropharyngeal bacterial flora in patients with cystic fibrosis diagnosed before the age of two years.J Pediatr1993;122,854-860. [CrossRef] [PubMed]
 
Doershuk, CF, Stern, RC Timing of referral for lung transplantation for cystic fibrosis: overemphasis on FEV1may adversely affect overall survival.Chest1999;115,782-787. [CrossRef] [PubMed]
 
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    Print ISSN: 0012-3692
    Online ISSN: 1931-3543