HHS Public Access Author manuscript Author Manuscript
Am J Transplant. Author manuscript; available in PMC 2017 April 01. Published in final edited form as: Am J Transplant. 2016 April ; 16(4): 1207–1215. doi:10.1111/ajt.13599.
Lung Quality and Utilization in Controlled Donation after Circulatory Determination of Death Donors within the United States
Author Manuscript
Joshua J Mooney, MD1, Haley Hedlin, PhD1, Paul K Mohabir, MD1, Rodrigo Vazquez, MD2, John Nguyen, RN3, Richard Ha, MD4, Peter Chiu, MD4, Kapilkumar Patel, MD1, Martin R. Zamora, MD5, David Weill, MD1, Mark R Nicolls, MD1, and Gundeep S Dhillon, MD1 1Department
of Medicine, Stanford University School of Medicine, Stanford, CA
2Department
of Medicine, University of New Mexico, Albuquerque, NM
3Donor
Network West, San Ramon, CA
4Department
of Cardiothoracic Surgery, Stanford University School of Medicine, Stanford, CA
5Department
of Medicine, University of Colorado Health Sciences Center, Aurora, CO
Abstract
Author Manuscript Author Manuscript
While controlled donation after circulatory determination of death (cDCDD) donors could increase the supply of donor lungs within the United States, the yield of lungs from cDCDD donors remain low compared to donation after neurologic determination of death (DNDD) donors. To explore the reason for low lung yield from cDCDD donors, Scientific Registry of Transplant Recipient data were used to assess the impact of donor lung quality on cDCDD lung utilization by fitting a logistic regression model. The relationship between center volume and cDCDD use was assessed and distance between center and donor hospital was calculated by cDCDD status. Recipient survival was compared using a multivariable Cox regression model. Lung utilization was 2.1% for cDCDD donors and 21.4% for DNDD donors. Being a cDCDD donor decreased lung donation (adjusted OR 0.101, CI 0.085–0.120). A minority of centers have performed cDCDD transplant with higher volume centers generally performing more cDCDD transplants. There was no difference in center to donor distance or recipient survival (adjusted HR 1.03, CI 0.78–1.37) between cDCDD and DNDD transplants. cDCDD lungs are underutilized compared to DNDD lungs after adjusting for lung quality. Increasing transplant center expertise and commitment to cDCDD lung procurement is needed to improve utilization.
Corresponding Author: Joshua J Mooney, MD; Stanford University School of Medicine; Department of Medicine; 300 Pasteur Drive, H3145, Stanford, CA 94305; [email protected]. Disclaimer The SRTR data reported here have been supplied by the Minneapolis Medical Research Foundation (MMRF) as the contractor for the Scientific Registry of Transplant Recipients (SRTR). The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as an official policy of or interpretation by the SRTR or the U.S. Government. Disclosure The authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of Transplantation.
Mooney et al.
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Author Manuscript
INTRODUCTION Lung transplantation, a life-sustaining procedure for individuals with end-stage lung disease, is limited by the low rate of lung utilization in deceased donors. While donor lung utilization rates have improved with an increase in the rate of lungs transplanted per donor from 0.25 in 2000 to 0.37 in 2012, there is a disparity between the number of lung transplant candidates and the deficit of donor lungs.(1) This disparity, in conjunction with increasingly ill lung transplant candidates, has contributed to a rising waiting list mortality from 13.5 per 100 waitlist years in 2004 to 15.4 per 100 waitlist years from 2010–2012.(1, 2)
Author Manuscript
Expanding the number of donor lung organs through the use of controlled donation after circulatory determination of death (cDCDD) donors has the potential to improve this disparity while preserving long-term recipient outcomes.(3–6) Multiple U.S. (7–12) and international (13–20) studies have demonstrated comparable to favorable survival in cDCDD lung recipients compared to donation after neurological determination of death (DNDD) lung recipients. Additionally, the use of cDCDD for organ transplantation is deemed ethical and is endorsed by multiple professional organizations.(6, 21–23) In 2006, the Institute of Medicine recommended that initiatives to increase cDCDD rates be implemented.(6) Despite similar recipient outcomes and these recommended initiatives, the yield of lungs from cDCDD donors in the United States remains low.(3)
Author Manuscript
A population-based cohort study estimated that universal identification and referral of all cDCDD donors could increase the lung organ supply by up to 22.7% for optimal donor lungs and by 50% for suboptimal donor lungs.(24) Successful utilization of this theoretical donor pool requires collaboration amongst intensive care unit (ICU) and end-of-life caregivers, organ procurement organizations (OPOs), and transplant physicians. Previous studies have assessed perceived barriers to cDCDD amongst ICU and end-of-life caregivers. (25–27) While important, addressing these barriers is of limited benefit without also identifying and addressing the barriers to OPOs and/or lung transplant programs’ utilization of available cDCDD lung organs.
Author Manuscript
Studies evaluating the quality and utilization of available cDCDD donors for lung transplant within the U.S. are lacking. The overall quality of cDCDD lungs and whether lung quality impacts utilization is particularly relevant as differences in end-of-life care and management within the U.S., as compared to other countries, may affect the quality of cDCDD lungs. The aims of this study are the following: (1) to describe the donor factors, including cDCDD status, that are associated with lung utilization and to compare cDCDD and DNDD lung utilization when adjusted for lung quality, (2) to assess lung transplant center and OPO factors associated with cDCDD lung use, (3) to calculate whether distance from transplant center to donor hospital differs between utilized cDCDD and DNDD lungs, and (4) to provide an updated analysis of outcomes between cDCDD and DNDD recipients within the post lung allocation score era. Understanding of the above is essential to identifying and addressing the barriers that contribute to the low rate of cDCDD lungs utilization within the U.S., as compared to other regions of the world.
Am J Transplant. Author manuscript; available in PMC 2017 April 01.
Mooney et al.
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Author Manuscript
METHODS Subjects
Author Manuscript
Using Scientific Registry of Transplant Recipients (SRTR) standard analysis files, we identified all eligible organ donors and all lung transplant recipients between January 1, 2006 and March 3, 2014. Donors were identified as either cDCDD or DNDD and those without a specified donor type were excluded. Descriptive variables were generated from the existing SRTR data fields and compared between cDCDD and DNDD donors and recipients. Categorical variables were displayed as number (%) and continuous variables were displayed as median (25th, 75th percentiles). This study used data from the Scientific Registry of Transplant Recipients (SRTR). The SRTR data system includes data on all donor, wait-listed candidates, and transplant recipients in the U.S., submitted by the members of the Organ Procurement and Transplantation Network (OPTN). The Health Resources and Services Administration (HRSA), U.S. Department of Health and Human Services provides oversight to the activities of the OPTN and SRTR contractors. This study received an exemption from the Stanford University Institutional Review Board as it uses deidentified data. Outcomes
Author Manuscript
To compare cDCDD and DNDD lung utilization, the primary donor outcome assessed was whether a lung from an eligible donor was transplanted. Secondary outcomes included cDCDD utilization over time, the relationship between OPO and lung transplant center volume and cDCDD transplantation, and the median distance from transplant center to donor hospital for utilized cDCDD and DNDD lungs. To compare outcomes between cDCDD and DNDD recipients, the primary outcome was time to death. Recipients who were not observed to have the outcome of interest were right-censored at the time we received the SRTR database (March 3, 2014). Secondary recipient outcomes analyzed were hospital length of stay (LOS) and duration of ventilator support. Statistical Analysis
Author Manuscript
A multivariable logistic regression was fit to assess the donor factors associated with the primary outcome of lung utilization. Donor type (cDCDD versus DNDD), along with age in years, cigarette use history greater than 20 pack-years, and PaO2 on 100% FiO2 were a priori included in the model. Sex, race, body mass index (BMI), diabetes mellitus, heavy alcohol use, history of cocaine use, history of other drug abuse, high risk donor status, cause of death, chest x-ray (normal, abnormal, or none), blood infection, and lung infection were all considered for inclusion. We identified variables that were most important for inclusion in the model by constructing random forests.(28, 29) A forest was grown using 500 trees with 4 variables sampled at each split in a tree. The variable importance measure was used to rank the variables in relation to their importance in predicting lung donation for transplantation and variables selected were chosen by visually inspecting a plot of variable importance. An identical secondary analysis was performed using a subgroup of patients from 2010–2014. The R package ‘randomForest’, version 4.6–7, was used to construct the random forest.(30)
Am J Transplant. Author manuscript; available in PMC 2017 April 01.
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Author Manuscript
We evaluated the relationship of cDCDD status on travel distance between the transplant center and the donor hospital. Geodesic distance was calculated according to the law of cosines in the ‘geosphere’ R package by using SRTR provided transplant center and donor hospital latitude and longitude global positioning system (GPS) degree coordinates.(31) We used a Mann-Whitney test to assess whether the distance between donor hospital and transplant center differed by cDCDD status. The frequency of donors and transplant centers residing in the same OPO or UNOS region were calculated and compared by cDCDD status.
Author Manuscript
Kaplan-Meier curves were plotted to display recipient survival by cDCDD status. Recipient survival was analyzed using a multivariable Cox proportional hazards regression model. Models included an indicator of cDCDD status to evaluate the association between donor type (cDCDD versus DNDD) and recipient survival. Models were a priori adjusted for donor characteristics including age, sex, race, BMI, PaO2 on 100% FiO2, diabetes mellitus, smoking history, public health service (PHS) increased risk donor status, chest radiograph, and presence of lung or blood infection. Models were also a priori adjusted for transplant center volume and recipient characteristics including age, sex, primary diagnosis, cytomegalovirus match status, procedure type (single, bilateral, re-transplant), pre-transplant medical status (hospitalized in ICU, hospitalized not in ICU, not hospitalized), and lung allocation score (LAS) at time of transplant. The proportional hazards assumption was assessed by visual examination of martingale residual plots and Kaplan-Meier plots. An identical analysis was performed for a sub group of recipients from 2010–2014. Hospital length of stay and post-transplant ventilator support were compared by cDCDD status using a two-tailed Mann-Whitney test and a Fisher’s exact test, respectively.
Author Manuscript
We used multiple imputations by chained equations with predictive mean matching to avoid omitting patients with missing data and to protect against biases due to excluding missing observations in all regression models. Multiple imputation was performed separately for the donor lung utilization model and recipient outcome model. From each dataset, five separate data sets were created with imputed values and the models were fit on each of the five data sets. The estimates from each data set were pooled to obtain a final estimate with a standard error estimate that accounts for the additional uncertainty due to the unobserved entries being imputed. All statistical analyses were performed with R 3.1.0.(32) Multiple imputations were implemented using the R package ‘mice’, version 2.21.(33) All model estimates are shown with 95% confidence intervals and all tests were conducted at the 0.05 significance level.
RESULTS Author Manuscript
Lung Utilization and Quality by cDCDD Status We evaluated 65,973 eligible donors (7,690 cDCDD and 58,283 DNDD) of which 12,657 donated lungs (162 cDCDD, 12,495 DNDD) to 13,563 recipients (169 cDCDD, 13,394 DNDD) as shown in Figure 1. Ten donors missing cDCDD status were excluded. The overall donor lung utilization rate was 2.1% for cDCDD donors and 21.4% for DNDD donors. Similar to DNDD utilization, the rate of cDCDD lung utilization slightly increased over time as shown in Figure 2. Eligible cDCDD and DNDD donor characteristics are displayed in Table 1. cDCDD donors were more likely to be white (85% versus 64%) and Am J Transplant. Author manuscript; available in PMC 2017 April 01.
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Author Manuscript
less likely to be black (7% versus 18%) or Hispanic (6% versus 14%). cDCDD donors were less likely to have a PaO2 ≥ 300 and had an overall lower median PaO2 on 100% oxygen. The median time from withdrawal of life-sustaining treatment (WLST) to death for all eligible cDCDD donors was 18 minutes (IQR 12–25 minutes). The median time from WLST to cannulation for all eligible cDCDD donors was 25 minutes (IQR 23–33 minutes).
Author Manuscript
cDCDD status significantly decreased lung utilization (adjusted [adj.] OR 0.101, CI 0.085– 0.120), along with older age (adj. OR 0.981 per year, CI 0.980–0.983), greater than 20 packyears smoking history (adj. OR 0.353, CI 0.328–0.379), and abnormal chest radiograph (adj. OR 0.384, CI 0.364–0.404) or absence of chest radiograph (adj. OR 0.518, CI 0.391–0.685). Increasing PaO2 on 100% FiO2 (adj. OR 1.083 per 10 additional mmHg, CI 1.081–1.085) was associated with higher lung utilization (Table 2). Within a 2010–2014 subgroup analysis, cDCDD donor type remained the most significant negative predictor of lung utilization (adj. OR 0.086, CI 0.069–0.108). Organ Procurement Organization and Lung Transplant Center cDCDD Experience Fifty-seven of 58 U.S. organ procurement organizations (OPOs) have assisted in the procurement of any type of cDCDD organ. When limited to cDCDD lungs, 35 OPOs have assisted in procurement of at least one cDCDD lung. Of 84 identified U.S. lung transplant centers, 26 (31%) have performed at least one cDCDD lung transplant. Higher total lung transplant volume is correlated with higher cDCDD lung transplant volume for both OPOs (R2 0.337, p value 20 pack years (%)
Author Manuscript
Increased Risk Donor (%) Cause of Death
0%
Chest X-Ray
13%
No Chest X-ray (%)
Author Manuscript
Bronchoscopy Left Lung
92%
No Bronchoscopy (%)
492 (75%)
2338 (14%)
Normal (%)
125 (19%)
10,556 (65%)
19 (3%)
1976 (12%)
Purulent Secretions (%) Right Lung
92%
No Bronchoscopy (%)
488 (75%)
2395 (15%)
Normal (%)
116 (18%)
9951 (62%)
Purulent Secretions (%) PaO2 ≥ 300 mmHg on 100% FiO2 (%) PaO2 on 100% FiO2
26 (4%)
2215 (14%)
835 (11%)
17,159 (30%)
5%
60 (40, 100)
100 (50, 100)
5%
162 (2%)
12,495 (21%)
0%
Lung transplanted
Author Manuscript
*
WLST refers to withdrawal of life-sustaining treatment
N (%) given for categorical variables Median (25th, 75th percentiles) given for continuous variables
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Table 2
Author Manuscript
Multivariable Analysis of Factors Associated with Lung Utilization Odds Ratio
95% Confidence Interval
Donation after Circulatory Determination of Death
0.101
(0.085, 0.120)
Age (years)*
0.981
(0.980, 0.983)
Body Mass Index (kg/m2)*
1.003
(0.999, 1.007)
Cigarette Use > 20 pack-years
0.353
(0.328, 0.379)
Abnormal Chest Radiograph**
0.384
(0.364, 0.404)
No Chest Radiograph**
0.518
(0.391, 0.685)
PaO2 on 100% FiO2 (mmHg)***
1.083
(1.081, 1.085)
*
Odds Ratio per 1 Unit Change
Author Manuscript
**
Compared to Normal Chest Radiograph
***
Odds Ratio per 10 Unit Change
Author Manuscript Author Manuscript Am J Transplant. Author manuscript; available in PMC 2017 April 01.
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Table 3
Author Manuscript
Lung Donor and Recipient Characteristics Donation after Circulatory Determination of Death (DCDD)
Donation after Neurologic Determination of Death (DNDD)
Donor Characteristics
n = 162 (1.3%)
n = 12495 (98.7%)
Age
37.5 (25.25, 47)
31 (21, 46)
0%
97 (60%)
7386 (59%)
0%
Male (%) Race
Percent missing
0%
White (%)
139 (86%)
7631 (61%)
Black (%)
9 (6%)
2504 (20%)
Asian/Pacific Islander (%)
3 (2%)
359 (3%)
Hispanic (%)
10 (6%)
1931 (15%)
Other (%)
Author Manuscript
1 (1%)
70 (1%)
25.14 (22.67, 28.93)
24.82 (22.03, 28.26)
0%
Cigarette Use > 20 pack years (%)
13 (8%)
1283 (10%)
1%
Increased Risk Donor (%)
8 (5%)
1033 (8%)
0%
21 (16, 29)
NA
14%
26.5 (22.8, 33.0)
NA
75%
4 (2%)
80 (1%)
Normal (%)
90 (56%)
6284 (50%)
Abnormal (%)
66 (42%)
6032 (48%)
Body Mass Index
WLST to Death Time (min)* WLST to Cannulation Time (min)* Chest Radiograph
0%
No Chest X-ray (%)
Bronchoscopy Left Lung
5%
Author Manuscript
No Bronchoscopy (%)
48 (31%)
594 (5%)
Normal (%)
89 (57%)
9147 (77%)
Purulent Secretions (%)
10 (6%)
1211 (10%)
Right Lung
7%
No Bronchoscopy (%)
47 (32%)
580 (5%)
Normal (%)
85 (57%)
8587 (74%)
Purulent Secretions (%) PaO2 ≥ 300 mmHg on 100% FiO2 (%) PaO2 on 100% FiO2 Recipient Characteristics
7 (5%)
1402 (12%)
109 (69%)
8924 (72%)
1%
398 (196.5, 480.5)
420 (247, 492)
1%
n = 169
n = 13,394
Age
58 (44, 63)
58 (47, 64)
0%
Male (%)
106 (63%)
7866 (59%)
0%
46 (27%)
3933 (29%)
LAS Primary Diagnosis Group (%)
Author Manuscript
A (Obstructive Lung Disease) B (Pulmonary Vascular Disease)
0%
8 (5%)
466 (3%)
C (Cystic Fibrosis)
30 (18%)
1760 (13%)
D (Restrictive Lung Disease)
84 (50%)
7202 (54%)
1 (1%)
33 (0%)
Other
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Donation after Circulatory Determination of Death (DCDD)
Donation after Neurologic Determination of Death (DNDD)
Percent missing
317 (257.5, 410.5)
301 (244, 350.5)
98%
Author Manuscript
Cold Ischemia Time Pre-Transplant Medical Condition
1%
Hospitalized in ICU (%)
23 (14%)
1293 (10%)
Hospitalized not in ICU (%)
19 (12%)
1175 (9%)
Not Hospitalized (%)
122 (74%)
10728 (81%)
Extracorporeal Membrane Oxygenation (%)
11 (7%)
269 (2%)
0%
Mechanical Ventilation (%)
17 (10%)
1035 (8%)
0%
LAS
0%
At Listing
36.27 (33.55, 42.94)
37.01 (33.48, 44.12)
At Transplant
39.57 (34.47, 52.12)
39.89 (34.71, 50.69)
*
WLST refers to withdrawal of life-sustaining treatment
Author Manuscript Author Manuscript Author Manuscript Am J Transplant. Author manuscript; available in PMC 2017 April 01.
Am J Transplant. Author manuscript; available in PMC 2017 April 01. Published in final edited form as: Am J Transplant. 2016 April ; 16(4): 1207–1215. doi:10.1111/ajt.13599.
Lung Quality and Utilization in Controlled Donation after Circulatory Determination of Death Donors within the United States
Author Manuscript
Joshua J Mooney, MD1, Haley Hedlin, PhD1, Paul K Mohabir, MD1, Rodrigo Vazquez, MD2, John Nguyen, RN3, Richard Ha, MD4, Peter Chiu, MD4, Kapilkumar Patel, MD1, Martin R. Zamora, MD5, David Weill, MD1, Mark R Nicolls, MD1, and Gundeep S Dhillon, MD1 1Department
of Medicine, Stanford University School of Medicine, Stanford, CA
2Department
of Medicine, University of New Mexico, Albuquerque, NM
3Donor
Network West, San Ramon, CA
4Department
of Cardiothoracic Surgery, Stanford University School of Medicine, Stanford, CA
5Department
of Medicine, University of Colorado Health Sciences Center, Aurora, CO
Abstract
Author Manuscript Author Manuscript
While controlled donation after circulatory determination of death (cDCDD) donors could increase the supply of donor lungs within the United States, the yield of lungs from cDCDD donors remain low compared to donation after neurologic determination of death (DNDD) donors. To explore the reason for low lung yield from cDCDD donors, Scientific Registry of Transplant Recipient data were used to assess the impact of donor lung quality on cDCDD lung utilization by fitting a logistic regression model. The relationship between center volume and cDCDD use was assessed and distance between center and donor hospital was calculated by cDCDD status. Recipient survival was compared using a multivariable Cox regression model. Lung utilization was 2.1% for cDCDD donors and 21.4% for DNDD donors. Being a cDCDD donor decreased lung donation (adjusted OR 0.101, CI 0.085–0.120). A minority of centers have performed cDCDD transplant with higher volume centers generally performing more cDCDD transplants. There was no difference in center to donor distance or recipient survival (adjusted HR 1.03, CI 0.78–1.37) between cDCDD and DNDD transplants. cDCDD lungs are underutilized compared to DNDD lungs after adjusting for lung quality. Increasing transplant center expertise and commitment to cDCDD lung procurement is needed to improve utilization.
Corresponding Author: Joshua J Mooney, MD; Stanford University School of Medicine; Department of Medicine; 300 Pasteur Drive, H3145, Stanford, CA 94305; [email protected]. Disclaimer The SRTR data reported here have been supplied by the Minneapolis Medical Research Foundation (MMRF) as the contractor for the Scientific Registry of Transplant Recipients (SRTR). The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as an official policy of or interpretation by the SRTR or the U.S. Government. Disclosure The authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of Transplantation.
Mooney et al.
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Author Manuscript
INTRODUCTION Lung transplantation, a life-sustaining procedure for individuals with end-stage lung disease, is limited by the low rate of lung utilization in deceased donors. While donor lung utilization rates have improved with an increase in the rate of lungs transplanted per donor from 0.25 in 2000 to 0.37 in 2012, there is a disparity between the number of lung transplant candidates and the deficit of donor lungs.(1) This disparity, in conjunction with increasingly ill lung transplant candidates, has contributed to a rising waiting list mortality from 13.5 per 100 waitlist years in 2004 to 15.4 per 100 waitlist years from 2010–2012.(1, 2)
Author Manuscript
Expanding the number of donor lung organs through the use of controlled donation after circulatory determination of death (cDCDD) donors has the potential to improve this disparity while preserving long-term recipient outcomes.(3–6) Multiple U.S. (7–12) and international (13–20) studies have demonstrated comparable to favorable survival in cDCDD lung recipients compared to donation after neurological determination of death (DNDD) lung recipients. Additionally, the use of cDCDD for organ transplantation is deemed ethical and is endorsed by multiple professional organizations.(6, 21–23) In 2006, the Institute of Medicine recommended that initiatives to increase cDCDD rates be implemented.(6) Despite similar recipient outcomes and these recommended initiatives, the yield of lungs from cDCDD donors in the United States remains low.(3)
Author Manuscript
A population-based cohort study estimated that universal identification and referral of all cDCDD donors could increase the lung organ supply by up to 22.7% for optimal donor lungs and by 50% for suboptimal donor lungs.(24) Successful utilization of this theoretical donor pool requires collaboration amongst intensive care unit (ICU) and end-of-life caregivers, organ procurement organizations (OPOs), and transplant physicians. Previous studies have assessed perceived barriers to cDCDD amongst ICU and end-of-life caregivers. (25–27) While important, addressing these barriers is of limited benefit without also identifying and addressing the barriers to OPOs and/or lung transplant programs’ utilization of available cDCDD lung organs.
Author Manuscript
Studies evaluating the quality and utilization of available cDCDD donors for lung transplant within the U.S. are lacking. The overall quality of cDCDD lungs and whether lung quality impacts utilization is particularly relevant as differences in end-of-life care and management within the U.S., as compared to other countries, may affect the quality of cDCDD lungs. The aims of this study are the following: (1) to describe the donor factors, including cDCDD status, that are associated with lung utilization and to compare cDCDD and DNDD lung utilization when adjusted for lung quality, (2) to assess lung transplant center and OPO factors associated with cDCDD lung use, (3) to calculate whether distance from transplant center to donor hospital differs between utilized cDCDD and DNDD lungs, and (4) to provide an updated analysis of outcomes between cDCDD and DNDD recipients within the post lung allocation score era. Understanding of the above is essential to identifying and addressing the barriers that contribute to the low rate of cDCDD lungs utilization within the U.S., as compared to other regions of the world.
Am J Transplant. Author manuscript; available in PMC 2017 April 01.
Mooney et al.
Page 3
Author Manuscript
METHODS Subjects
Author Manuscript
Using Scientific Registry of Transplant Recipients (SRTR) standard analysis files, we identified all eligible organ donors and all lung transplant recipients between January 1, 2006 and March 3, 2014. Donors were identified as either cDCDD or DNDD and those without a specified donor type were excluded. Descriptive variables were generated from the existing SRTR data fields and compared between cDCDD and DNDD donors and recipients. Categorical variables were displayed as number (%) and continuous variables were displayed as median (25th, 75th percentiles). This study used data from the Scientific Registry of Transplant Recipients (SRTR). The SRTR data system includes data on all donor, wait-listed candidates, and transplant recipients in the U.S., submitted by the members of the Organ Procurement and Transplantation Network (OPTN). The Health Resources and Services Administration (HRSA), U.S. Department of Health and Human Services provides oversight to the activities of the OPTN and SRTR contractors. This study received an exemption from the Stanford University Institutional Review Board as it uses deidentified data. Outcomes
Author Manuscript
To compare cDCDD and DNDD lung utilization, the primary donor outcome assessed was whether a lung from an eligible donor was transplanted. Secondary outcomes included cDCDD utilization over time, the relationship between OPO and lung transplant center volume and cDCDD transplantation, and the median distance from transplant center to donor hospital for utilized cDCDD and DNDD lungs. To compare outcomes between cDCDD and DNDD recipients, the primary outcome was time to death. Recipients who were not observed to have the outcome of interest were right-censored at the time we received the SRTR database (March 3, 2014). Secondary recipient outcomes analyzed were hospital length of stay (LOS) and duration of ventilator support. Statistical Analysis
Author Manuscript
A multivariable logistic regression was fit to assess the donor factors associated with the primary outcome of lung utilization. Donor type (cDCDD versus DNDD), along with age in years, cigarette use history greater than 20 pack-years, and PaO2 on 100% FiO2 were a priori included in the model. Sex, race, body mass index (BMI), diabetes mellitus, heavy alcohol use, history of cocaine use, history of other drug abuse, high risk donor status, cause of death, chest x-ray (normal, abnormal, or none), blood infection, and lung infection were all considered for inclusion. We identified variables that were most important for inclusion in the model by constructing random forests.(28, 29) A forest was grown using 500 trees with 4 variables sampled at each split in a tree. The variable importance measure was used to rank the variables in relation to their importance in predicting lung donation for transplantation and variables selected were chosen by visually inspecting a plot of variable importance. An identical secondary analysis was performed using a subgroup of patients from 2010–2014. The R package ‘randomForest’, version 4.6–7, was used to construct the random forest.(30)
Am J Transplant. Author manuscript; available in PMC 2017 April 01.
Mooney et al.
Page 4
Author Manuscript
We evaluated the relationship of cDCDD status on travel distance between the transplant center and the donor hospital. Geodesic distance was calculated according to the law of cosines in the ‘geosphere’ R package by using SRTR provided transplant center and donor hospital latitude and longitude global positioning system (GPS) degree coordinates.(31) We used a Mann-Whitney test to assess whether the distance between donor hospital and transplant center differed by cDCDD status. The frequency of donors and transplant centers residing in the same OPO or UNOS region were calculated and compared by cDCDD status.
Author Manuscript
Kaplan-Meier curves were plotted to display recipient survival by cDCDD status. Recipient survival was analyzed using a multivariable Cox proportional hazards regression model. Models included an indicator of cDCDD status to evaluate the association between donor type (cDCDD versus DNDD) and recipient survival. Models were a priori adjusted for donor characteristics including age, sex, race, BMI, PaO2 on 100% FiO2, diabetes mellitus, smoking history, public health service (PHS) increased risk donor status, chest radiograph, and presence of lung or blood infection. Models were also a priori adjusted for transplant center volume and recipient characteristics including age, sex, primary diagnosis, cytomegalovirus match status, procedure type (single, bilateral, re-transplant), pre-transplant medical status (hospitalized in ICU, hospitalized not in ICU, not hospitalized), and lung allocation score (LAS) at time of transplant. The proportional hazards assumption was assessed by visual examination of martingale residual plots and Kaplan-Meier plots. An identical analysis was performed for a sub group of recipients from 2010–2014. Hospital length of stay and post-transplant ventilator support were compared by cDCDD status using a two-tailed Mann-Whitney test and a Fisher’s exact test, respectively.
Author Manuscript
We used multiple imputations by chained equations with predictive mean matching to avoid omitting patients with missing data and to protect against biases due to excluding missing observations in all regression models. Multiple imputation was performed separately for the donor lung utilization model and recipient outcome model. From each dataset, five separate data sets were created with imputed values and the models were fit on each of the five data sets. The estimates from each data set were pooled to obtain a final estimate with a standard error estimate that accounts for the additional uncertainty due to the unobserved entries being imputed. All statistical analyses were performed with R 3.1.0.(32) Multiple imputations were implemented using the R package ‘mice’, version 2.21.(33) All model estimates are shown with 95% confidence intervals and all tests were conducted at the 0.05 significance level.
RESULTS Author Manuscript
Lung Utilization and Quality by cDCDD Status We evaluated 65,973 eligible donors (7,690 cDCDD and 58,283 DNDD) of which 12,657 donated lungs (162 cDCDD, 12,495 DNDD) to 13,563 recipients (169 cDCDD, 13,394 DNDD) as shown in Figure 1. Ten donors missing cDCDD status were excluded. The overall donor lung utilization rate was 2.1% for cDCDD donors and 21.4% for DNDD donors. Similar to DNDD utilization, the rate of cDCDD lung utilization slightly increased over time as shown in Figure 2. Eligible cDCDD and DNDD donor characteristics are displayed in Table 1. cDCDD donors were more likely to be white (85% versus 64%) and Am J Transplant. Author manuscript; available in PMC 2017 April 01.
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less likely to be black (7% versus 18%) or Hispanic (6% versus 14%). cDCDD donors were less likely to have a PaO2 ≥ 300 and had an overall lower median PaO2 on 100% oxygen. The median time from withdrawal of life-sustaining treatment (WLST) to death for all eligible cDCDD donors was 18 minutes (IQR 12–25 minutes). The median time from WLST to cannulation for all eligible cDCDD donors was 25 minutes (IQR 23–33 minutes).
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cDCDD status significantly decreased lung utilization (adjusted [adj.] OR 0.101, CI 0.085– 0.120), along with older age (adj. OR 0.981 per year, CI 0.980–0.983), greater than 20 packyears smoking history (adj. OR 0.353, CI 0.328–0.379), and abnormal chest radiograph (adj. OR 0.384, CI 0.364–0.404) or absence of chest radiograph (adj. OR 0.518, CI 0.391–0.685). Increasing PaO2 on 100% FiO2 (adj. OR 1.083 per 10 additional mmHg, CI 1.081–1.085) was associated with higher lung utilization (Table 2). Within a 2010–2014 subgroup analysis, cDCDD donor type remained the most significant negative predictor of lung utilization (adj. OR 0.086, CI 0.069–0.108). Organ Procurement Organization and Lung Transplant Center cDCDD Experience Fifty-seven of 58 U.S. organ procurement organizations (OPOs) have assisted in the procurement of any type of cDCDD organ. When limited to cDCDD lungs, 35 OPOs have assisted in procurement of at least one cDCDD lung. Of 84 identified U.S. lung transplant centers, 26 (31%) have performed at least one cDCDD lung transplant. Higher total lung transplant volume is correlated with higher cDCDD lung transplant volume for both OPOs (R2 0.337, p value 20 pack years (%)
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Increased Risk Donor (%) Cause of Death
0%
Chest X-Ray
13%
No Chest X-ray (%)
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Bronchoscopy Left Lung
92%
No Bronchoscopy (%)
492 (75%)
2338 (14%)
Normal (%)
125 (19%)
10,556 (65%)
19 (3%)
1976 (12%)
Purulent Secretions (%) Right Lung
92%
No Bronchoscopy (%)
488 (75%)
2395 (15%)
Normal (%)
116 (18%)
9951 (62%)
Purulent Secretions (%) PaO2 ≥ 300 mmHg on 100% FiO2 (%) PaO2 on 100% FiO2
26 (4%)
2215 (14%)
835 (11%)
17,159 (30%)
5%
60 (40, 100)
100 (50, 100)
5%
162 (2%)
12,495 (21%)
0%
Lung transplanted
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*
WLST refers to withdrawal of life-sustaining treatment
N (%) given for categorical variables Median (25th, 75th percentiles) given for continuous variables
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Table 2
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Multivariable Analysis of Factors Associated with Lung Utilization Odds Ratio
95% Confidence Interval
Donation after Circulatory Determination of Death
0.101
(0.085, 0.120)
Age (years)*
0.981
(0.980, 0.983)
Body Mass Index (kg/m2)*
1.003
(0.999, 1.007)
Cigarette Use > 20 pack-years
0.353
(0.328, 0.379)
Abnormal Chest Radiograph**
0.384
(0.364, 0.404)
No Chest Radiograph**
0.518
(0.391, 0.685)
PaO2 on 100% FiO2 (mmHg)***
1.083
(1.081, 1.085)
*
Odds Ratio per 1 Unit Change
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**
Compared to Normal Chest Radiograph
***
Odds Ratio per 10 Unit Change
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Table 3
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Lung Donor and Recipient Characteristics Donation after Circulatory Determination of Death (DCDD)
Donation after Neurologic Determination of Death (DNDD)
Donor Characteristics
n = 162 (1.3%)
n = 12495 (98.7%)
Age
37.5 (25.25, 47)
31 (21, 46)
0%
97 (60%)
7386 (59%)
0%
Male (%) Race
Percent missing
0%
White (%)
139 (86%)
7631 (61%)
Black (%)
9 (6%)
2504 (20%)
Asian/Pacific Islander (%)
3 (2%)
359 (3%)
Hispanic (%)
10 (6%)
1931 (15%)
Other (%)
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1 (1%)
70 (1%)
25.14 (22.67, 28.93)
24.82 (22.03, 28.26)
0%
Cigarette Use > 20 pack years (%)
13 (8%)
1283 (10%)
1%
Increased Risk Donor (%)
8 (5%)
1033 (8%)
0%
21 (16, 29)
NA
14%
26.5 (22.8, 33.0)
NA
75%
4 (2%)
80 (1%)
Normal (%)
90 (56%)
6284 (50%)
Abnormal (%)
66 (42%)
6032 (48%)
Body Mass Index
WLST to Death Time (min)* WLST to Cannulation Time (min)* Chest Radiograph
0%
No Chest X-ray (%)
Bronchoscopy Left Lung
5%
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No Bronchoscopy (%)
48 (31%)
594 (5%)
Normal (%)
89 (57%)
9147 (77%)
Purulent Secretions (%)
10 (6%)
1211 (10%)
Right Lung
7%
No Bronchoscopy (%)
47 (32%)
580 (5%)
Normal (%)
85 (57%)
8587 (74%)
Purulent Secretions (%) PaO2 ≥ 300 mmHg on 100% FiO2 (%) PaO2 on 100% FiO2 Recipient Characteristics
7 (5%)
1402 (12%)
109 (69%)
8924 (72%)
1%
398 (196.5, 480.5)
420 (247, 492)
1%
n = 169
n = 13,394
Age
58 (44, 63)
58 (47, 64)
0%
Male (%)
106 (63%)
7866 (59%)
0%
46 (27%)
3933 (29%)
LAS Primary Diagnosis Group (%)
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A (Obstructive Lung Disease) B (Pulmonary Vascular Disease)
0%
8 (5%)
466 (3%)
C (Cystic Fibrosis)
30 (18%)
1760 (13%)
D (Restrictive Lung Disease)
84 (50%)
7202 (54%)
1 (1%)
33 (0%)
Other
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Donation after Circulatory Determination of Death (DCDD)
Donation after Neurologic Determination of Death (DNDD)
Percent missing
317 (257.5, 410.5)
301 (244, 350.5)
98%
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Cold Ischemia Time Pre-Transplant Medical Condition
1%
Hospitalized in ICU (%)
23 (14%)
1293 (10%)
Hospitalized not in ICU (%)
19 (12%)
1175 (9%)
Not Hospitalized (%)
122 (74%)
10728 (81%)
Extracorporeal Membrane Oxygenation (%)
11 (7%)
269 (2%)
0%
Mechanical Ventilation (%)
17 (10%)
1035 (8%)
0%
LAS
0%
At Listing
36.27 (33.55, 42.94)
37.01 (33.48, 44.12)
At Transplant
39.57 (34.47, 52.12)
39.89 (34.71, 50.69)
*
WLST refers to withdrawal of life-sustaining treatment
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