American Journal of Respiratory and Critical Care Medicine

Rationale: Lung transplantation (LT) is an established treatment for end-stage lung diseases, including chronic obstructive pulmonary disease (COPD) associated with α1-antitrypsin deficiency (AATD).

Objectives: We sought to compare the post-transplantation course of patients with AATD and AAT-replete COPD.

Methods: Between June 1991 and January 2008, a total of 231 patients with AAT-replete COPD and 45 with AATD underwent LT at Cleveland Clinic. Data reviewed included baseline recipient, donor, and surgical data; all spirometry evaluations; acute cellular rejection (ACR) events; and survival data. Endpoints included temporal change in FEV1, severity of ACR, and survival. A longitudinal temporal decomposition model was used for analysis.

Measurements and Main Results: Comparison of overall rates of FEV1 decline in AATD and AAT-replete patients with COPD showed no significant differences (P > 0.09). However, although the single LT patients had similar trends in FEV1 in both groups, patients with AATD with double LT declined faster (P < 0.002) than the AAT-replete patients. No differences in the frequency or severity of ACR episodes were observed (P = 0.32). Furthermore, there was no difference in early or late mortality between patients with AATD and patients with AAT-replete COPD (P > 0.09).

Conclusions: Although overall the post-LT FEV1 slope, severity of ACR, and survival among patients with AATD is similar to that of AAT-replete patients with COPD, patients with AATD with double LT have a faster rate of FEV1 decline. These findings support the eligibility of patients with AATD for LT, and suggest the need for additional studies to better understand the difference between single and double LT in AATD.

Scientific Knowledge on the Subject

Patients with α1-antitrypsin deficiency (AATD) are at increased risk of proteolytic lung damage after lung transplantation but the post–lung transplantation course of patients with AATD has received little attention. Available observations suggest that the unadjusted survival rates following lung transplantation are higher for patients with AATD than with “usual” chronic obstructive pulmonary disease and that elastase-antielastase balance is disrupted during episodes of rejection and infection in AATD lung transplant patients.

What This Study Adds to the Field

The current study describes the natural history of spirometric lung function following lung transplantation among patients with AATD and compares their course with that of patients with chronic obstructive pulmonary disease with normal α1-antitrypsin levels. This study also compares the incidence and severity of acute cellular rejection episodes among these two groups and reports independent predictors of changes in post–transplant lung function among patients with AATD. Finally, the crude survival among the two groups along with the risk factors for early and late deaths after lung transplantation are described.

α1-Antitrypsin deficiency (AATD) is an autosomal-codominant condition characterized by reduced serum levels of α1-antitrypsin (AAT), an inhibitor of neutrophil elastase that is a member of the serine proteinase inhibitor (serpin) family. Homozygous Z allele AATD (so-called PI*ZZ type) is the most common variant associated with emphysema risk (1) for which contributing factors include exposures to tobacco smoke and occupational dusts (2). Spirometry has classically been used to measure and follow the progression of obstructive lung disease, with emerging evidence suggesting the enhanced sensitivity of chest computed tomography (CT) for emphysema (3). To date, FEV1 has been shown to be an important predictor of survival among patients with AATD and chronic obstructive pulmonary disease (COPD) in general, with CT densitometry contributing as well (4, 5),

Lung transplantation (LT) is an established treatment for various end-stage lung diseases, including AATD. In 2010, more than 3,500 lung transplant procedures were performed in the United States (6), approximately 8% of which were performed for AATD-associated emphysema (7). Data from the International Society of Heart and Lung Transplantation (ISHLT) report more favorable long-term outcomes among patients with AATD in comparison with those with COPD in the absence of AATD (hereafter called AAT-replete COPD) (6). In fact, allograft half-life among patients with AATD is reportedly 6.2 years, the second longest of all conditions, and exceeded only by patients undergoing LT for cystic fibrosis (6). At the same time, these survival data are unadjusted for key demographic variables, such as the younger age of AATD patients, which may contribute to their enhanced post-LT survival rates. Other than overall survival, little attention has been given to the post-LT course of patients with AATD with, to our knowledge, only two studies addressing the issue of pulmonary protease-antiprotease balance in patients with AATD post-LT (8, 9).

To address this gap, the current study characterizes the natural history of spirometric lung function following LT in patients with AATD and compares their course with that of AAT-replete patients with COPD. Because episodes of acute cellular rejection (ACR) can also impact lung function, we also compare the prevalence and severity of ACR episodes between the two groups. Finally, we compare survival rates post-LT.

Part of this work was presented as a paper at the annual meeting of the American Thoracic Society and published in an abstract form (10).

The study was approved with a waiver of patient consent by the Cleveland Clinic Institutional Review Board. Data were extracted from an established registry of Cleveland Clinic LT patients (called the Unified Transplant Database) assembled from the electronic medical record (EPIC, Madison, WI). Vital status follow-up information was extracted from prospective Electronic Data Interface for Transplant registry.

Patient Management

Routine post-LT care at the Cleveland Clinic center consists of allograft monitoring using home or office spirometry and periodic post-LT flexible bronchoscopy. All spirometry testing for this study was performed in the Cleveland Clinic Pulmonary Function Laboratory using protocols compliant with American Thoracic Society standards (11).

Surveillance flexible bronchoscopy was routinely performed at 3 and 6 weeks, and at 3, 6, 9, and 12 months post-LT, and otherwise when deemed clinically indicated. Surveillance flexible bronchoscopy included an airway examination, bronchoalveolar lavage (BAL), and transbronchial lung biopsies (TBLB). A total of 8–10 biopsy samples were taken and were reviewed and graded by dedicated lung pathologists based on the ISHLT guidelines (12). Depending on the clinical condition and severity, any ACR seen on TBLB was managed aggressively with corticosteroid bursts (1 mg/kg orally daily with weekly taper) or pulse therapy (7.5 mg/kg methylprednisolone intravenously daily for 3 d followed by oral taper).

Subject Selection

To allow 3-year follow-up, patients undergoing LT with an indication of COPD (AATD or AAT-replete) between the inception of the database through January 2008 were eligible. Between June 1991 and January 2008, a total of 231 patients with AAT-replete COPD and 45 with AATD-associated COPD underwent LT at Cleveland Clinic. The recipient, donor, and surgical data were extracted from the Unified Transplant Database. Use of augmentation therapy and the timing of its use among patients with AATD were reviewed. All spirometry evaluations done after transplantation were recorded. The results of TBLB were reviewed to determine incident events of ACR episodes (type A or vascular) and the Lung Rejection Study Group (LRSG) severity of rejection episodes in both groups (12).


The two primary endpoints for the study were FEV1% predicted (using reference equations from National Health and Nutrition Examination Survey [13]) and episodes of cellular rejection, based on bronchoscopic TBLB results (with occurrence of any rejection coded as an ordinal variable) (12). Survival after transplantation was the secondary endpoint.

Statistical Analysis

Temporal change in the longitudinal measurements of post-LT FEV1% predicted was analyzed using a temporal decomposition model (14). A nonlinear mixed-effects regression (15) (PROC NLMIXED SAS) was used to implement the temporal decomposition model (16). To identify risk factors associated with the higher FEV1% predicted, preoperative and intraoperative variables were used in the multivariable analyses. Because of limited capability of PROC NLMIXED in variable selection, variables were initially screened using ordinary multivariable linear regression (PROC REG SAS) with entry criteria (0.12) and stay criteria (0.1). These candidates and their transformations, if any, were entered into our nonlinear multiphase model, and then eliminated one by one until all variables remaining had a value of P less than or equal to 0.05.

A nonlinear cumulative logistic mixed model (PROC NLMIXED) was used to analyze the prevalence of rejection grades over time. Prevalence of biopsy grades over time was estimated by averaging the patient-specific profiles. Because age may be a confounder, we have assessed the age-adjusted difference in the prevalence between the two groups. Because of smaller frequencies in grades 3 and 4, these categories were collapsed together with grade 2 in the data analysis.

Survival was assessed nonparametrically by the Kaplan-Meier method and parametrically by a multiphase hazard model. The parametric model was used to resolve a number of phases of instantaneous risk of death (hazard function) and to estimate shaping parameters (17). To identify risk factors for death, multivariable analysis was performed in the multiphase hazard function domain. Preoperative (recipient and donor) and procedure variables were considered in the multivariable analyses.

Variable selection, with a P value criterion for retention of variables in the model of 0.05, used bootstrap bagging (bootstrap aggregation) (18, 19). This was a four-step process. First, a patient was randomly selected from the original data set to begin a new data set. The original data set continued to be sampled until the new data set was 100% of the size of the original. Second, risk factors were identified using automated forward stepwise selection. Third, results of the variable selection were stored. These three steps were repeated 500 times. Finally, the frequency of occurrence of variables related to group membership was ascertained and indicated the reliability of each variable (aggregation step). All variables with bootstrap reliability of 50% or greater were retained in the guided analysis.

In this retrospective cohort study, because many patient variables had missing values, a fivefold multiple imputation using the Markov Chain Monte Carlo technique was used (20, 21) to impute missing values.

Simple descriptive statistics were used to summarize the data. Continuous variables are presented as mean ± standard deviation and as the 15th, 50th (median), and 85th percentiles. Comparisons were made using the Wilcoxon rank-sum nonparametric test. Categorical data are described using frequencies and percentages. Comparisons were made using chi-square test and Fisher exact test when the frequency was smaller than five. All analyses were performed using SAS statistical software (SAS v9.1; SAS, Inc., Cary, NC).

Overall, 4,725 postoperative spirometry records were available for 236 of the eligible patients (85.5% of the total population). The median length of post-LT follow-up time was 1.2 years (range, 3 d–5 yr; 25th–75th percentile, 0.35–3.2 yr) and 5% of the records were obtained after 5.5 years.

Overall Trends

The temporal decomposition model yielded two time phases for FEV1% predicted post-LT: an early peaking phase, followed by a late plateau phase (see Figure E1 in the online supplement). A rise of FEV1 from 42% predicted after transplant to approximately 55% by 6 months post-LT was observed. Thereafter, there was an overall gradual decrease in FEV1 to about 41% predicted by 8 years (see Figure E2).

AAT-Deficient versus AAT-Replete Patients with COPD

Few differences were observed between recipient, donor, and procedure baseline variables other than that patients with AATD were younger on average (Table 1). In general, double LT recipients seemed to have higher values of post-LT FEV1% predicted than single LT recipients (P < 0.0001). Comparison of temporal trends of FEV1% predicted in AAT-deficient with those of AAT-replete COPD groups showed no significant differences (P > 0.09) (Figure 1). However, although patients undergoing only single LT showed no difference in FEV1 slopes between the AAT-deficient and AAT-replete patients with COPD (P > 0.6), the AAT-replete patients with COPD undergoing double LT seemed to have a higher late post-LT FEV1 than the patients with AATD with double LT. As shown in Figure 2, the slopes of the curves describing post-LT FEV1% predicted for AATD and AAT-replete patients with double LT were similar for 2 years and started diverging thereafter (P < 0.002) (Figure 2).

Table 1. Patient Characteristics in the Compared Groups

VariableAAT-Replete COPD (n = 231)AAT Deficiency (n = 45)P Value
NMean ± SD or n (%)15/50/85th PercentileNMean ± SD or n (%)15/50/85th Percentile
Demographic features       
 Age at the time of transplant (years)23157 ± 6.151/58/634549 ± 7.542/50/56<0.0001
 Body mass index23124 ± 4.719/25/294524 ± 4.818/23/280.2
 Female231117 (51) 4518 (40) 0.2
 Race: white231224 (97) 4545 (100) 0.6
Comorbid conditions       
 Creatinine, mg/dl1780.67 ± 0.20.5/0.6/0.9250.74 ± 0.180.5/0.75/0.90.06
 Diastolic blood pressure, mm Hg16972 ± 1260/71/822870 ± 1060/70/800.3
 Systolic blood pressure, mm Hg169120 ± 18110/120/14028120 ± 14100/120/1300.04
 Mean blood pressure, mm Hg16989 ± 1278/89/1002885 ± 9.476/87/930.1
Serology, immunology       
 PRA: B screen cytotoxicity, %2283.3 ± 120/0/5442.5 ± 7.10/0/50.9
 PRA: T screen cytotoxicity, %2301.1 ± 5.30/0/0450.73 ± 2.30/0/00.4
Pulmonary function       
 FEV1, % of predicted19320 ± 7.114/18/253020 ± 5.414/20/270.2
 FVC, % of predicted18054 ± 1438/54/682859 ± 1832/60/770.1
 Ratio: FEV1/FVC1800.36 ± 0.130.27/0.34/0.44280.37 ± 0.110.27/0.35/0.430.5
 Demographic features       
  Age of recipient at transplant, yr22937 ± 1420/37/534539 ± 1422/41/550.4
  Body mass index23025 ± 5.920/24/304525 ± 4.320/24/300.8
  Female229107 (47) 4517 (38) 0.3
  Race: white230197 (86) 4540 (89) 0.6
 Comorbid conditions       
  Creatinine, mg/dl2111.1 ± 1.50.6/0.8/1.4371.2 ± 0.780.6/1.1/1.40.07
  Maximum ischemic time, min202220 ± 70150/220/30041200 ± 68120/200/2800.1
  Double lung transplant23160 (26) 4513 (29) 0.6
  Single left side23186 (37) 4519 (42) 0.5
  Single right side23185 (37) 4513 (29) 0.3
Predicted percentages of postoperative FEV1% (predicted mean response from the mixed-effect model) (P > 0.09)
 1 yr5458 
 3 yr4848 
 5 yr4645 
Survival (Kaplan-Meier nonparametric estimate) (P[early risk of death] = 0.09; P[late risk of death] = 0.7)
 1 yr, %8673 
 5 yr, %5038 
 10 yr, %2417 
 15 yr, %1614 

Definition of abbreviations: AAT = α1-antitrypsin; COPD = chronic obstructive pulmonary disease; PRA = panel reactive antibody.

Augmentation therapy was administered to a total of six (13.3%) patients with AATD (three each undergoing single and double LT) but was begun within 3 years post-LT only in the three double LT recipients.

Predictors of Post-transplantation Lung Function

Factors associated with higher post-LT FEV1% predicted included higher pre-LT FEV1, older age, lower pre-LT class-I panel reactive antibody, and having the right lung (vs. the left) transplanted. In the first 3 years after transplantation, the factors associated with higher FEV1 were donor cause of death other than head trauma and having a negative donor status for cytomegalovirus IgG antibodies (Table 2).

Table 2. Factors Associated with Higher Postoperative FEV1

FactorEstimate ± SEP Value
 Older age*−0.33 ± 0.140.02
 Higher preoperative FEV1−0.12 ± 0.0480.02
 Lower class I PRA (B cell)0.079 ± 0.0470.1
 Double lung transplant0.72 ± 0.057<0.0001
 Diagnosis: AAT deficiency0.093 ± 0.0670.2
 Right lung (single)0.092 ± 0.0390.02
 Interaction: double lung transplant by AAT deficiency−0.33 ± 0.110.003
Early phase  
 Donor had no CMV IgG antibodies2.3 ± 0.810.004
 Donor cause of death: no head trauma0.29 ± 0.110.008
 Diagnosis: COPD0.48 ± 0.180.009
Late phase  
 Diagnosis: AAT-replete COPD−0.037 ± 0.120.8
 Interaction: AAT-replete COPD by double lung transplant−1.2 ± 0.27<0.0001

Definition of abbreviations: AAT = α1-antitrypsin; CMV = cytomegalovirus; COPD = chronic obstructive pulmonary disease; PRA = panel reactive antibody.

*52/age, inverse transformation.

20/FEV1 (% of predicted), inverse transformation.

50/(PRA + 1), inverse transformation.

Episodes of ACR

Overall, a total of 1,498 post-LT biopsy records were available for 247 of the eligible patients (90% of the total population). The median length of post-LT follow-up time was 6 months (range, 1 d–9 yr; 25th–75th percentile, 1.5–11.5 mo), and 5% of the records were obtained after 2.8 years. The overall temporal trend showed an early peaking and a later constant phase.

Although the prevalence of LRSG grade 0 increased from 47% to 82%, the prevalence of grade 1 and grades 2/3/4 decreased from approximately 24% to 11%, and from approximately 28% to 7% within the first 6 months, respectively (see Figure E3). Subsequently, there seemed to be a slight increase in the prevalence of LRSG grade 1 and 2/3/4 ACR to approximately 17% and 12% by Year 3, respectively. Age-adjusted comparison of the prevalence of ACR (grade 1 and grades 2/3/4) in AATD versus AAT-replete COPD groups showed no significant difference between the groups regarding both early and late rejection episodes (P > 0.5) (Figures 3A and 3B).

Post-transplantation Survival

As of May 26, 2014, a total of 213 deaths were observed in this cohort with a total of 1,475 patient-years available for analysis. Multiphase hazard function analysis showed an early peaking hazard followed by a constant hazard phase of death following LT. Kaplan-Meier nonparametric estimates of survival for the two groups are shown in Table 1 and Figure 4. Risk factors for death after LT for all patients are presented in Table 3. Having AATD does not seem to be a risk factor for early or late death (P = 0.09), but having a history of diabetes and receiving a single LT do pose risk for late death (Table 3).

Table 3. Incremental Risk Factors for Death after Lung Transplantation

FactorCoefficient ± SEP ValueR* (%)
Early hazard phase   
 α1-Antitrypsin deficiency (compared with COPD)1.1 ± 0.660.0923
Late hazard phase   
 History of diabetes0.59 ± 0.300.0544
 Single lung transplant0.63 ± 0.190.00188
 α1-Antitrypsin deficiency (compared with COPD)−0.088 ± 0.210.727

Definition of abbreviation: COPD = chronic obstructive pulmonary disease.

*Percentage of times factor appeared in the 500 bootstrap models.

This study extends available knowledge of the natural history of lung function among patients with AATD because, to our understanding, this is the first report to compare longitudinal post-LT pulmonary outcomes of AATD LT recipients with AAT-replete LT recipients. The few prior reports examining the post-LT course in AATD recipients have focused on survival post-LT (7) and on the elastase-antielastase balance during episodes of rejection and infection (8, 9). Specifically, King and coworkers (8) showed an abnormal proteinase-antiproteinase balance in BAL after lung transplantation. Patients with clinical infections were shown to newly develop free elastase activity in the BAL fluid that was not present before intercurrent illness. In a second report, Meyer and coworkers (9) demonstrated that the effect of acute reperfusion injury and acute or chronic rejection was to stimulate increases in AAT serum levels (6), although the elevations were blunted in patients with PI*ZZ AATD. Furthermore, intravenous augmentation therapy (i.e., with purified, pooled human plasma AAT) was reported to help reverse what seemed to be impending chronic rejection in one patient.

Key findings in this study of the post-LT outcomes of AATD and AAT-replete patients with COPD were that no differences were observed regarding overall post-LT rates of change of FEV1% predicted, or the incidence or severity of rejection episodes in the post-LT period. However, the subset of double LT recipients with AATD did experience more rapid post-LT FEV1 decline than did AAT-replete patients, which was evident more than 2 years following LT. Although FEV1 values among patients with AATD were consistently lower than those with AAT-replete patients with COPD, the gap seemed to widen beyond 2 years post-LT. Furthermore, the unadjusted early survival rate following LT was lower among patients with AATD.

Although these findings do suggest a difference between AATD and AAT-replete double LT recipients, the study leaves unanswered several questions. For example, why did the post-LT FEV1 decline more in double LT AATD recipients than in AAT-replete patients? Also, why is this difference in the rates of post-LT FEV1 decline evident only in double lung but not in single lung AATD transplantation recipients?

To address the latter question, we wondered whether more frequent use of augmentation therapy by single lung AATD recipients versus double lung recipients could explain the difference. To the extent that augmentation therapy has been suggested to slow the rate of FEV1 decline in AAT-deficient individuals (2225), a higher prevalence of augmentation therapy use by AATD subjects undergoing single LT could cause the decline of lung function to be slower as compared with AAT-replete patients. However, the data showed that none of the single LT patients received augmentation therapy during the first 3 years after transplantation, thereby discounting this possibility. Furthermore, the three patients who did receive augmentation therapy during the first 3 post-LT years had all undergone double LT, possibly reflecting the faster decline some of these patients were experiencing (i.e., as might be explained by “confounding by indication” [26]).

Although AATD did not emerge as an independent predictor of mortality, a trend toward worse early post-LT survival was evident among patients with AATD versus those with AAT-replete COPD. This trend accords with findings from the ISHLT registry database, where patients with COPD had the lowest 3-month mortality among all diagnostic groups and where AATD was an independent predictor of 1-year mortality (27). These findings may be explained by events during the perioperative period, including reperfusion injury that may lead to an abnormal proteinase-antiproteinase balance with consequent adverse effects. Also, if patients with AATD had more pulmonary hypertension, early outcomes post-LT might be expected to be poorer. Regrettably, the unavailability of pulmonary hemodynamic data in the current study precluded adjustment in the model.

This study applies a novel statistical technique (temporal decomposition) to model and analyze the changes in FEV1 post-LT (14), stratifying the post-LT course of FEV1 into two phases. An initial rise followed by a subsequent decline was used to model the post-LT course of FEV1 decline. This outcome variable is a continuous longitudinal repeated measure with expected nonlinear trends at varying time intervals. The nonlinear mixed-effects modeling allowed us to incorporate two key aspects of this analysis: the variable number of FEV1 measurements that were done at different time points, and the possible clustering effect caused by repeated measurements.

Notwithstanding the distinctive analysis in this study, several shortcomings of the study warrant mention. First, because the experience was based on a single center, the number of evaluable patients and events was limited, leaving the generalizability of the conclusions to remain uncertain. Second, although the duration of post-LT follow-up was longer, because routine post-LT surveillance bronchoscopy was performed only through 1 year following LT, later episodes of ACR could have escaped recognition. Third, post-LT airway complications (e.g., stenosis, dehiscence, malacia) could affect post-LT lung function but were neither recorded in the Unified Transplant Database nor included in the analysis. Fourth, although the statistical analytic methods used were selected specifically for the biphasic course of post-LT FEV1% predicted, a remaining limitation is the difficulty of interpreting results from analyses that were unadjusted for potential unobserved (or unavailable) confounders, such as associated comorbidities, background severity of AATD, and lung allocation score (among patients transplanted after 2005). Although an alternative method, such as propensity matching, might address this shortcoming, the relatively small sample size precluded such an approach. Finally, although measuring FEV1 represents the usual strategy for monitoring the post-LT pulmonary course, increasing evidence suggests that CT imaging can detect emphysematous changes that are not evident by spirometry (3). Routine post-LT chest CT imaging was not performed in these patients. To the extent that such imaging could detect emphysema that can go unrecognized by spirometry, it is conceivable that true differences in emphysema progression between AATD and AAT-replete patients went unrecognized. Further imaging studies in these populations is needed to explicate this possibility.

In summary, in this first-of-a kind observational cohort study, the overall post-LT FEV1% predicted did not differ over 3 years between patients undergoing LT for COPD associated with AATD and others, although AATD double LT recipients did experience an accelerated late decline of FEV1. The findings support the eligibility of patients with AATD for LT while suggesting the need for additional post-LT study with chest CT imaging to clarify emphysema progression and in other centers to ensure generalizability.

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Correspondence and requests for reprints should be addressed to Amit Banga, M.D., Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390-8550. E-mail:

Supported by a grant from the Alpha-1 Foundation.

Author Contributions: A.B., acquisition of the data, data management and analysis, data analysis, preparation of the manuscript. T.G., study design, acquisition of the data, data management and analysis, preparation of the manuscript. J.R., data management and analysis, preparation of the manuscript. H.R., preparation of the manuscript. E.H.B., data management and analysis, preparation of the manuscript. J.K.S., study design, data acquisition, preparation of the manuscript.

This article has an online supplement, which is accessible from this issue's table of contents at

Originally Published in Press as DOI: 10.1164/rccm.201401-0031OC on July 8, 2014

Author disclosures are available with the text of this article at


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American Journal of Respiratory and Critical Care Medicine

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