Clinical Trial Details
— Status: Active, not recruiting
Administrative data
| NCT number |
NCT03818698 |
| Other study ID # |
XJTU1AF-CRF-2018-026 |
| Secondary ID |
|
| Status |
Active, not recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
April 1, 2019 |
| Est. completion date |
December 31, 2022 |
Study information
| Verified date |
August 2021 |
| Source |
First Affiliated Hospital Xi'an Jiaotong University |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
The rapid changes of tissue-typing technology, including the widely used of highly specific
molecular typing methods and solid phase analysis technology for detection of alleles
specific anti-HLA antibodies, promoted the selection of organ transplant recipients to a more
accurate level and promoted the scientific development of organ transplant matching. At
present, the graft survival rate has been greatly improved through the prevention and
treatment of T-cell-mediated rejection (TCMR), but the humoral immune response, the main
cause of late graft loss, is still not effectively controlled.
HLA eplets matching is based on the principle that if a donor HLA antigen shares a specific
epitope with a recipient's HLA antigen, that eplets will not be recognized as foreign and
will therefore not provoke a humoral immune response. The selection of transplant recipients
based on this principle can avoid antibody-mediated rejection (AMR), reduce sensitization
after transplantation, and select the most appropriate organs to avoid pre-existing
antibodies in the case of persisting HLA antibody positive recipients choosing.
In this study, the HLA high-resolution typing data of kidney transplant recipients from 2014
to the end of 2017 were analyzed with HLA Matchmaker for eplets mismatching number. To
analyze the incidence of dnDSA and AMR after kidney transplant recipients with different
eplets mismatching number posttransplant, and to elucidate the important role of tissue
configuration patterns based on HLA eplets matching in long-term graft survival.
Description:
This study is a retrospective cohort study. The investigators design to analyze the HLA
high-resolution typing data of kidney transplant recipients from 2014 to the end of 2017 with
HLA Matchmaker for eplets mismatching number, and analyze the incidence of dnDSA and AMR
after kidney transplant recipients with different eplets mismatching number post transplant,
and elucidate the important role of tissue configuration patterns based on HLA eplets
matching in long-term graft survival.
The study contents including the followings:
1. Collecting the HLA high resolution typing data The high-resolution HLA typing data of
the recipients were analyzed with the HLA Matchmaker software for Eplets mismatching
numbers, and the experiment groups were conducted according to the results of Eplets
mismatching numbers. Based on the normal distribution characteristics of the Eplets
mismatching numbers and the references, the study is divided into the following four
groups: group 1, with the Eplets mismatching numbers <5; 2. Group 2, with Eplets
mismatching numbers 5-19; Group 3, with Eplets mismatching numbers 20-35; Group 4: with
Eplets mismatching numbers greater than or equal to 36.
2. Collecting Clinical follow-up data of patients after kidney transplantation. It mainly
includes renal function, DSA level, and pathological diagnosis data of diseases and
venereal diseases.
1) sCr： 1 month, 6 months, 1 year, 2 years after surgery... 2) Preoperative PRA-: 1 month, 6
months, 1 year, 2 years after surgery... 3) Preoperative PRA+:2 weeks after surgery, January,
march, June, September, 1 year, 2 years...
4) DSA was classified according to the type of antibody: DSA of HLA A site, DSA of HLA B
site, DSA of HLA C site, DSA of HLA DR site, DSA of HLA DQ site; 5) According to DSA MFI
value classification：MFI<3000, 3000≤MFI<6000, 6000≤MFI<10000,MFI≥10000; 6) AMR：Pathological
biopsy data collection (according to Banff 2013 standard diagnosis) 3. Statistical analysis
SPSS17.0 Chinese version was used for descriptive analysis of the data. The continuous
variable is represented by the mean plus or minus the standard deviation. The chi-square test
analyzed the relationship between the Eplets mismatching numbers and the generation of dnDSA,
as well as the differences in the Eplets mismatching numbers between the DSA positive group
and the DSA negative group, and the differences in Eplets mismatching numbers between the AMR
group and the non-AMR group. Kaplan-meier survival curve was used to analyze the differences
in long-term graft survival among groups with different Eplets mismatching numbers. P<0.05
was considered statistically significant.
