Chile has a very low cadaveric organ donation rate; at the same time, living donor transplantation activity is low. The purpose of this paper is to analyze the impact on the number and quality of transplants of the potential application of different mechanisms for kidney exchange from living donors to patients on Chile’s waiting list.Organ Donation Rate, living kidney donation, kidney exchange mechanisms

Diego Contreras

Javier Dominguez

English

Research Papers in Economics

DOCUMENTO 
DE TRABAJO
Instituto de Economía
D
O
C
U
M
E
N
T
O
 
d
e
 
T
R
A
B
A
J
O
INSTITUTO DE ECONOMÍA
www.economia.puc.cl ￿ ISSN (edición impresa) 0716-7334 ￿ ISSN (edición electrónica) 0717-7593
Eﬀectiveness of Diﬀerent Kidney Exchange Mechanisms on Improving living
Donor Transplantation in Chile
Javier Domínguez; Rodrigo Harrison; Diego Contreras.
384
2010Versión impresa ISSN: 0716-7334 
Versión electrónica ISSN: 0717-7593 
 
 
PONTIFICIA UNIVERSIDAD CATOLICA DE CHILE 
INSTITUTO DE ECONOMIA 
 
 
Oficina de Publicaciones 
Casilla 76, Correo 17, Santiago 
www.economia.puc.cl 
 
 
 
 
 
 
EFFECTIVENESS OF DIFFERENT KIDNEY EXCHANGE MECHANISMS ON 
IMPROVING LIVING DONOR TRANSPLANTATION IN CHILE 
 
   Javier Domínguez 
      Rodrigo Harrison* 
      Diego Contreras 
 
Documento de Trabajo Nº 384 
 
 
 
 
 
 
Santiago, 2010 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
*harrison@uc.cl 
  
Effectiveness of different kidney exchange mechanisms on improving living donor 
transplantation in Chile. 
 
Javier Domínguez; Facultad de Medicina, Departamento de Urología. Pontificia Universidad Católica 
de Chile. Email: javierdomi@hotmail.com 
Rodrigo Harrison; Facultad de Economia Instituto de Economía Pontificia Universidad Católica de 
Chile. Email: harrison@uc.cl 
Diego  Contreras;  Facultad  de  Economia  Instituto  de  Economía  Pontificia  Universidad  Católica  de 
Chile. Email: diego.contreras.galvez@gmail.com 
 
 
Name of the departments to which the work should be attributed 
Facultad de Medicina, Departamento de Urología. Pontificia Universidad Católica de Chile. 
Facultad de Economia Instituto de Economía Pontificia Universidad Católica de Chile. 
 
Contact information for the corresponding author: 
Javier Dominguez 
Pontificia Universidad Catolica de Chile Departamento de Urologia. Marcoleta 350. Santiago. Chile. 
Phone: 56 2 3543468. Fax: 56 2  6384413      E-mail: javierdomi@hotmail.com (may be published) 
Reprint requests: 
Javier Dominguez 
Pontificia Universidad Catolica de Chile Departamento de Urologia. Marcoleta 350. Santiago. Chile. 
Phone: 56 2 3543468. Fax: 56 2  6384413      E-mail: javierdomi@hotmail.com (may be published) 
 
Number of figures and tables: 1 Table 3 figures 
  
Abstract 
Chile has a very low cadaveric organ donation rate; at the same time, living donor transplantation 
activity  is  low.  The  purpose  of  this  paper  is  to  analyze  the  impact  on  the  number  and  quality  of 
transplants of the potential application of different mechanisms for kidney exchange from living donors 
to patients on Chile’s waiting list. 
Methods 
A computerized model was developed, to simulate five different options for living kidney donation: i) 
direct donation, ii) direct donation plus pair wise and three-way exchange iii) pair wise exchange, iv) 
three-way exchange, and v) allocation of donors based on the Top Trading Cycles (TTC) mechanism. 
The projected number of transplants, adjusting for the risk of a positive crossmatch, was calculated as 
well as the average quality in terms of HLA match.  
Results 
If all patients in the waiting list have a direct donor willing to donate, 47,7% of patients will get a 
transplant. Allowing incompatible pairs and those with a positive cross match to exchange kidneys can 
increase the number of transplants to 51,8%. This figure rises to 60 and 61% for pair wise or three 
way exchanges respectively. Although TTC assures that 55% of the patients could be transplanted the 
quality is better with an average HLA match of 3,5 vs 1,25 for the others. 
Conclusions 
These  results  show  that  kidney  exchange  mechanisms  can  increase  the  number o f  l i v i n g  d o n o r  
transplants between 4 and 13%.  
 
 
 
 Introduction 
 
Chile has a very low cadaveric donation rate. Indeed, in 2010 the donation rate was only 5,4 donors 
per million people (pmp), with a significant decrease in the last 4 years (1).   
One possible alternative to relieve the difficult situation of the transplantation system in Chile is to 
promote living donation. However, the level of development of this activity is very low compared to 
other countries. In fact, in the last years, only 10% of all kidney transplants come from a living donor 
compared to around 50% for USA. (2). In order to increase the probability of finding a compatible living 
donor several mechanisms apart from direct donation have been proposed (3,4,5). In countries like 
the U.S., Germany, Romania, England and the Netherlands these complex exchanges have been 
explored and developed (6,7, 8, 9, 10). 
The purpose of this paper is to explore the impact on the number and quality of transplants of the 
implementation of different algorithms of living kidney donation in Chile. We examine not only the 
possibility  of  direct  living  donation w h e r e  a  patient  on  the  waiting  list  is  associated  with  a  donor 
(typically a family member or direct relative), but also, if they are not compatible, the option to resort to 
more complex exchange mechanisms that will enable to find compatible pairs among different directly 
incompatible donor-recipient pairs. (3,4,5). 
Methods 
We  developed  a  computerized  model  in  order  to  evaluate  a  direct  donation  mechanism a n d  f o u r  
different  exchange  mechanisms.  The  number  (percentage)  of  expected  transplant  was  calculated 
assuming different proportions of all the patients of the actual Chilean waiting list having a living donor.    
On the other hand we calculated the average HLA match for each of these mechanisms as a measure 
of the quality of these mechanisms. Finally a sensitivity analysis was performed, estimating the impact 
of different criteria of donor-recipient compatibility on the number and quality of transplants of each 
mechanism. T h u s ,  a  d o n o r -recipient  pair  was c o n s i d e r e d  c o m p a t i b l e  i f :  i )   it  has  ABO  blood 
compatibility (criterion 1), ii) it has ABO blood compatibility and at least one HLA compatibility (criterion 
2), iii) there is ABO blood compatibility and at least one common HLA-DR (criterion 3). Mechanisms: i) Direct donation is the baseline situation. It consists in allowing kidney transplant only 
between a directly (genetically or emotionally related) compatible donor-recipient pair. ii) The “Multi 
Stage” kidney exchange mechanism (MSKEM), in addition to allowing direct donation, it incorporates, 
in  a  second  stage,  the  possibility  of  cross-exchange  between  incompatible  donor-recipient  pairs. 
Subsequently, it allows cross-exchange between 3 pairs and so on until all possibilities for exchange 
are exhausted. iii) Pairwise (PW) and three way (3W) kidney exchange only. All donor recipient pairs 
are included and cross-exchange between two (PW) or three (3W) donor-recipient pairs, respectively 
are performed. iv) Top Trading Cycles Mechanism (TTC). Again all donor recipient pairs are included, 
a recipient is randomly selected and chooses the best donor among the whole pool, based on ABO 
blood-type compatibility and HLA mismatch. Next, that donor’s recipient chooses his preferred organ 
form  those  remaining i n   the  pool,  and  so  on,  creating  a  chain  of  donor  and  recipients,  until  all 
possibilities are exhausted.  This chain is eliminated from the pool and for all those remaining without 
a transplant, the procedure is repeated as many tmes as necessary. (5,11,12).  
Data 
Recipients’ characteristics were obtained from the waiting list as of August 2009. At that moment 1412 
patients were waiting for a kidney transplant: mean age 43 ± 9 years, 52% male, 70 % blood type 0, 
22% type A 6% type B and 2% type AB. Sixty nine percent had a Panel Reactive Antibody (PRA) 
under 10%, 23 % between 10 and 80% and only 8% above 80%. The actual HLA A, B and DR of each 
recipient were used in all simulations. To simulate the characteristics of potential donors, we used the 
blood type and HLA frequencies of the cadaveric donor population from January 2000 to August 2009.  
To establish the probability of transplantation success, we assumed the relationship between PRA and 
positive Crossmatch in the literature (13). With this, we obtain a weight that is used to calculate the 
number of expected transplants. 
Results 
The results of the simulations, using as matching criterion the ABO blood-type compatibility only, show 
that all of the mechanisms are superior to direct donation which in the best case scenario (all those in 
the  waiting  list  have  a  living  donor)  could  yield  a  total  of  47%  of  transplants  while  the  other mechanisms yield between 4 and 14% more transplants (Fig N 1). The highest number of transplants 
is obtained when pairwise or 3-way exchanges are performed. However if we analyze the quality of 
the HLA match the TTC mechanism outperforms all others with a mean match of 3 vs, 1,5 for all 
others moreover the number of matches increases as the percent of patients having a donor increases 
(Table. N 1). 
As expected, for all the mechanisms the expected number of transplants increases as the number of 
patients on the waiting list who have a direct donor grow. Also, the number of expected transplants 
increases  as  more  complex  kidney  exchange  mechanisms  are  considered.  The  PW  and  3W 
mechanisms show similar results and the highest number of expected transplants of near 61% of the 
population in the waiting list. Direct Donation results in the lowest number of expected transplants 
(47%).  The  Multi-Stage m e c h a n ism  adds  a  few  more  transplants a n d  T T C   is  in  between  direct 
donation and PW and 3W (55%). Irrespective of the matching criteria used  Direct Donation always 
yields the least  number of transplants followed closely by  Multi-Stage. TTC, comes in between and , 
PW and 3W exchanges are the best (Fig 2). 
For the TTC mechanism there is a consistent result in terms of the number of transplant obtainable 
and the quality in terms of HLA match that is not modified when more stringent matching criteria are  
simulated (ie at least 1 HLA DR match for all transplants) and as already shown the number of HLA 
matches consistently increases with the number  of patients having a donor (Fig 3 Table1).  
Discussion: 
In  this  paper  we  simulated  a  mechanism  for  direct  living  donation  and  four  different  exchange 
mechanisms using data from Chile’s waiting list as of August 2009. Our results could be interpreted as 
the probability of having a compatible (and cross-match negative) emotionally related living donor. 
Significant  improvements  can  be  achieved  in  quantity  and  quality  of  transplants,  when  different 
exchange mechanisms are developed. In fact the chance of having a compatible donor is around 47% 
Our findings add evidence in favor of exploring different living donation mechanisms to alleviate the 
situation of the waiting list for a kidney transplant. Although the more complex mechanisms for kidney 
exchange  can  increase  the  number  of  expected  transplants  significantly,  all  of  them  but  the  TTC present, at best, an equal average quality than Direct Donation. Interestingly, however, the differences 
in quantity between Direct Donation and the other mechanisms are reduced if only the ABO blood-
type compatibility matching criterion is used. Indeed, in this case, all the mechanisms yield a number 
of expected transplants between 50% y 60% of patients who are on the waiting list (for 100% of live-
donor recipients). A possible interpretation of this result is that expanding the compatibility criteria is 
something to consider when evaluating the implementation of policies aimed at encouraging living 
donation. The natural trade-off is that the donation quality is significantly reduced with this expansion. 
Estimating these alternatives’ monetary cost and quantifying their effect on the quality of life should be 
the subject of other studies (14). Most probably, a significant economic benefit and quality of life gain 
could be expected, taking into account the clear superiority of living donation over cadaveric donation 
(15). 
There  are  other  even  more  complex  mechanisms,  such  as  the  Top  Trading  Cycles  and  Chains 
mechanism TTCC (3,4) which were not addressed in this study since their implementation is still very 
unrealistic (6). 
Although the living donation activity yet to be developed in Chile, it is important to stress the potential 
benefits it could bring to the population that remains on the waiting list. It is clear that letting all the 
donors (even if the recipient is compatible) incorporate into to a large pool and then to assign it to the 
most suitable recipient (given that that donor’s original recipient is transplanted with an equal or better 
donor)  using  one  of  the  above  exchange  mechanisms,  would  be  of  great  benefit  to  the  whole 
community of patients on the waiting list. However we as doctors are not generally prone to these 
exchanges, even though studies that have evaluated the willingness to participate in kidney exchange 
programs, have found that direct donors are generally willing to participate in these programs involving 
two pairs, compared to other policies such as donation in exchange for better ranking on the waiting 
list, because they see the benefit of their patients directly (16). 
These results are broadly consistent with the findings in the related the literature (3,4,5). Roth, using 
data from the USA waiting list showed that under direct donation near 54% of the patients on the 
waiting  list  could  get  a  living  unrelated  transplant  with  a  mean  HLA  match  of  1,2  and  that  more complex exchange mechanisms could reach up to 92 % of transplant with  a mean HLA match of 3,4.  
These significant differences with the current paper are probably related to the size and heterogeneity 
of the study populations. 
Choosing which mechanism is more suitable depends on many factors, however given that PW and 
3W exchanges consistently yield the most transplants and that the logistics of scheduling  2 or 3 
parallel transplantations is easier than implementing a transplant chain, they seem the better way to 
go. 
Implementing a kidney exchange mechanism however is no easy task; most importantly the system 
has to be transparent, with universal access and following rules that are a consensus involving all the 
actors in the Transplant field i.e. Healthcare authorities, transplant physicians, patients, etc.. Most 
probably creating a government sponsored agency in which all of these actors have a saying could be 
a good solution.  
References. 
1.  www.trasplante.cl. Corporación del Trasplante (CT) website. Accessed 17 January 2011. ISP 
2.  www.unos.org. The United Network for Organ Sharing (UNOS) website. Accessed 20 January 
2010. 
3.  Roth A, Sönmez T, Utku Ünver M. Kidney Exchange. The Quarterly Journal of Economics 
2004; 119: 457 - 488. 
4.  Roth A, Sönmez T, Utku Ünver M. Pairwise Kidney Exchange. Journal of Economic Theory 
2005a; 25: 151 - 188. 
5.  Roth A, Sönmez T, Utku Ünver M. A Kidney Exchange Clearinghouse in New England. The 
American Economic Review 2005b; 95: 376 - 380. 
6.  Lucan,  M.  2007.  “Five  years  of  single-center  experience  with  paired  kidney  exchange 
transplantation”. In Transplantation Proceedings, vol 39, pp. 1371-1375 
7.  Keizer, K.M, et al. 2005. “The Dutch Algorithm for Allocation in Living Donor Kidney Exchange” 
In Transplatantion Proceedings, vol.37, pp. 589-591 
8.  De  Klerk,  M.  et  al.  2006.  “Living  donor  kidney  exchange  for  both    ABO-Incompatible  and Crossmatch positive donor-recipient combination” In Transplantation Proceedings, vol. 38, pp. 2793-
2795. 
9.  Rees, M. et al. 2009. “A Non-Simultaneous Extended Altruistic Donor Chain,” In New England 
Journal of Medicine vol. 360: pp 1096-1101. 
10.  Roodnat,  J.L.  Et  al.  2010.  “Altruistic  Donor  Triggered  Domino-Paired  Kidney  Donation  for 
Unsuccessful Couples from Kidney-Exchange Program.” In American Journal of Transplantation, vol. 
10, pp 821-827. 
11.  Shapley,  L.  &  Scarf,  H.  1974.  "On  cores  and  indivisibility."  In  Journal  of  Mathematical 
Economics vol. 1: pp 23-28. 
12.  Abdulkadiroglu, A. & Sönmez T. 1999. "House allocation with existing tenants." In Journal of 
Economic Theory vol.88: pp 233-260. 
13.  Saidman, S., Roth, A., Sönmez, T., Utku M., & Delmonico F., “Increasing the opportunity of 
Live Kidney Donation by Matching for Two- and Three-Way Exchange”. In Transplantation vol.81, n°5: 
pp:773-782. 
14.  Whiting JF, Kiberd B, Kalo Z, et al. Cost effectiveness of organ donation: evaluating investment 
into Donor Action and other donor initiatives. American Journal of Transplantation 2004; 4: 569-57. 
15.  A.K.  Mandal,  J.J.  Snyder,  D.T.  Gilbertson,  A.J.  Collins  ,and  J.R.  Silkensen  2003.  “Does 
cadaveric  donor  renal  transplantation  ever  provide  better  outcomes  than  live-donor  renal 
transplantation? In Transplantation vol. 75, pp. 494-500 
16.  Waterman  et  al.  2006.  “Incompatible  kidney  donor  candidate's  willingness  to  participate  in 
donor-exchange and non-directed donation”. In American Journal of Transplantation, vol. 6, pp: 1631-
1638.  Figure 1 Number of expected transplants using different exchange mechanisms. 
 Figure N 2 Effect of different matching criteria on the number of Kidney transplants for the PW and 
3W exchange mechanisms. 
 Figure N 3 Effect of different matching criteria on number of transplants for the TTC exchange 
mechanism 

Effectiveness of Different Kidney Exchange Mechanisms on Improving Living Donor Transplantation in Chile

http://www.economia.puc.cl/docs/dt_384.pdf

Effectiveness of Different Kidney Exchange Mechanisms on Improving Living Donor Transplantation in Chile

Abstract

Similar works

Full text

Available Versions

Research Papers in Economics