PMID- 31548419
OWN - NLM
STAT- MEDLINE
DCOM- 20200406
LR  - 20200408
IS  - 1091-6490 (Electronic)
IS  - 0027-8424 (Print)
IS  - 0027-8424 (Linking)
VI  - 116
IP  - 41
DP  - 2019 Oct 8
TI  - Predicting kidney transplant outcomes with partial knowledge of HLA mismatch.
PG  - 20339-20345
LID - 10.1073/pnas.1911281116 [doi]
AB  - We consider prediction of graft survival when a kidney from a deceased donor is 
      transplanted into a recipient, with a focus on the variation of survival with 
      degree of human leukocyte antigen (HLA) mismatch. Previous studies have used data 
      from the Scientific Registry of Transplant Recipients (SRTR) to predict survival 
      conditional on partial characterization of HLA mismatch. Whereas earlier studies 
      assumed proportional hazards models, we used nonparametric regression methods. 
      These do not make the unrealistic assumption that relative risks are invariant as 
      a function of time since transplant, and hence should be more accurate. To refine 
      the predictions possible with partial knowledge of HLA mismatch, it has been 
      suggested that HaploStats statistics on the frequencies of haplotypes within 
      specified ethnic/national populations be used to impute complete HLA types. We 
      counsel against this, showing that it cannot improve predictions on average and 
      sometimes yields suboptimal transplant decisions. We show that the HaploStats 
      frequency statistics are nevertheless useful when combined appropriately with the 
      SRTR data. Analysis of the ecological inference problem shows that informative 
      bounds on graft survival probabilities conditional on refined HLA typing are 
      achievable by combining SRTR and HaploStats data with immunological knowledge of 
      the relative effects of mismatch at different HLA loci.
FAU - Manski, Charles F
AU  - Manski CF
AUID- ORCID: 0000-0001-7260-7686
AD  - Department of Economics, Northwestern University, Evanston, IL 60208; 
      cfmanski@northwestern.edu.
AD  - Institute for Policy Research, Northwestern University, Evanston, IL 60208.
FAU - Tambur, Anat R
AU  - Tambur AR
AUID- ORCID: 0000-0002-0320-9825
AD  - Feinberg School of Medicine, Northwestern University, Chicago, IL 60611.
FAU - Gmeiner, Michael
AU  - Gmeiner M
AD  - Department of Economics, Northwestern University, Evanston, IL 60208.
LA  - eng
PT  - Journal Article
DEP - 20190923
PL  - United States
TA  - Proc Natl Acad Sci U S A
JT  - Proceedings of the National Academy of Sciences of the United States of America
JID - 7505876
RN  - 0 (HLA Antigens)
SB  - IM
MH  - HLA Antigens/*genetics
MH  - Haplotypes
MH  - Host vs Graft Reaction/*genetics
MH  - Humans
MH  - Kidney Transplantation/*adverse effects
MH  - *Models, Biological
MH  - Predictive Value of Tests
MH  - Proportional Hazards Models
MH  - Tissue Donors
MH  - Transplant Recipients
PMC - PMC6789916
OTO - NOTNLM
OT  - HLA matching
OT  - ecological inference
OT  - nonparametric prediction
OT  - transplant risk assessment
COIS- The authors declare no conflict of interest.
EDAT- 2019/09/25 06:00
MHDA- 2020/04/09 06:00
PMCR- 2020/03/23
CRDT- 2019/09/25 06:00
PHST- 2019/09/25 06:00 [pubmed]
PHST- 2020/04/09 06:00 [medline]
PHST- 2019/09/25 06:00 [entrez]
PHST- 2020/03/23 00:00 [pmc-release]
AID - 1911281116 [pii]
AID - 201911281 [pii]
AID - 10.1073/pnas.1911281116 [doi]
PST - ppublish
SO  - Proc Natl Acad Sci U S A. 2019 Oct 8;116(41):20339-20345. doi: 
      10.1073/pnas.1911281116. Epub 2019 Sep 23.