<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03818698</url>
  </required_header>
  <id_info>
    <org_study_id>XJTU1AF-CRF-2018-026</org_study_id>
    <nct_id>NCT03818698</nct_id>
  </id_info>
  <brief_title>Study of Eplets Matching in Kidney Transplantation</brief_title>
  <official_title>Application Study of Eplets Matching in Kidney Transplantation</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>First Affiliated Hospital Xi'an Jiaotong University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>First Affiliated Hospital Xi'an Jiaotong University</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      The rapid changes of tissue-typing technology, including the widely used of highly specific&#xD;
      molecular typing methods and solid phase analysis technology for detection of alleles&#xD;
      specific anti-HLA antibodies, promoted the selection of organ transplant recipients to a more&#xD;
      accurate level and promoted the scientific development of organ transplant matching. At&#xD;
      present, the graft survival rate has been greatly improved through the prevention and&#xD;
      treatment of T-cell-mediated rejection (TCMR), but the humoral immune response, the main&#xD;
      cause of late graft loss, is still not effectively controlled.&#xD;
&#xD;
      HLA eplets matching is based on the principle that if a donor HLA antigen shares a specific&#xD;
      epitope with a recipient's HLA antigen, that eplets will not be recognized as foreign and&#xD;
      will therefore not provoke a humoral immune response. The selection of transplant recipients&#xD;
      based on this principle can avoid antibody-mediated rejection (AMR), reduce sensitization&#xD;
      after transplantation, and select the most appropriate organs to avoid pre-existing&#xD;
      antibodies in the case of persisting HLA antibody positive recipients choosing.&#xD;
&#xD;
      In this study, the HLA high-resolution typing data of kidney transplant recipients from 2014&#xD;
      to the end of 2017 were analyzed with HLA Matchmaker for eplets mismatching number. To&#xD;
      analyze the incidence of dnDSA and AMR after kidney transplant recipients with different&#xD;
      eplets mismatching number posttransplant, and to elucidate the important role of tissue&#xD;
      configuration patterns based on HLA eplets matching in long-term graft survival.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      This study is a retrospective cohort study. The investigators design to analyze the HLA&#xD;
      high-resolution typing data of kidney transplant recipients from 2014 to the end of 2017 with&#xD;
      HLA Matchmaker for eplets mismatching number, and analyze the incidence of dnDSA and AMR&#xD;
      after kidney transplant recipients with different eplets mismatching number post transplant,&#xD;
      and elucidate the important role of tissue configuration patterns based on HLA eplets&#xD;
      matching in long-term graft survival.&#xD;
&#xD;
      The study contents including the followings:&#xD;
&#xD;
        1. Collecting the HLA high resolution typing data The high-resolution HLA typing data of&#xD;
           the recipients were analyzed with the HLA Matchmaker software for Eplets mismatching&#xD;
           numbers, and the experiment groups were conducted according to the results of Eplets&#xD;
           mismatching numbers. Based on the normal distribution characteristics of the Eplets&#xD;
           mismatching numbers and the references, the study is divided into the following four&#xD;
           groups: group 1, with the Eplets mismatching numbers &lt;5; 2. Group 2, with Eplets&#xD;
           mismatching numbers 5-19; Group 3, with Eplets mismatching numbers 20-35; Group 4: with&#xD;
           Eplets mismatching numbers greater than or equal to 36.&#xD;
&#xD;
        2. Collecting Clinical follow-up data of patients after kidney transplantation. It mainly&#xD;
           includes renal function, DSA level, and pathological diagnosis data of diseases and&#xD;
           venereal diseases.&#xD;
&#xD;
      1) sCr： 1 month, 6 months, 1 year, 2 years after surgery... 2) Preoperative PRA-: 1 month, 6&#xD;
      months, 1 year, 2 years after surgery... 3) Preoperative PRA+:2 weeks after surgery, January,&#xD;
      march, June, September, 1 year, 2 years...&#xD;
&#xD;
      4) DSA was classified according to the type of antibody: DSA of HLA A site, DSA of HLA B&#xD;
      site, DSA of HLA C site, DSA of HLA DR site, DSA of HLA DQ site; 5) According to DSA MFI&#xD;
      value classification：MFI&lt;3000, 3000≤MFI&lt;6000, 6000≤MFI&lt;10000,MFI≥10000; 6) AMR：Pathological&#xD;
      biopsy data collection (according to Banff 2013 standard diagnosis) 3. Statistical analysis&#xD;
      SPSS17.0 Chinese version was used for descriptive analysis of the data. The continuous&#xD;
      variable is represented by the mean plus or minus the standard deviation. The chi-square test&#xD;
      analyzed the relationship between the Eplets mismatching numbers and the generation of dnDSA,&#xD;
      as well as the differences in the Eplets mismatching numbers between the DSA positive group&#xD;
      and the DSA negative group, and the differences in Eplets mismatching numbers between the AMR&#xD;
      group and the non-AMR group. Kaplan-meier survival curve was used to analyze the differences&#xD;
      in long-term graft survival among groups with different Eplets mismatching numbers. P&lt;0.05&#xD;
      was considered statistically significant.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Active, not recruiting</last_known_status>
  <start_date type="Actual">April 1, 2019</start_date>
  <completion_date type="Anticipated">December 31, 2022</completion_date>
  <primary_completion_date type="Actual">April 1, 2020</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Cohort</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>The occurrence of dnDSA and AMR</measure>
    <time_frame>3 years</time_frame>
    <description>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&lt;0.05 was considered statistically significant.</description>
  </primary_outcome>
  <enrollment type="Anticipated">1000</enrollment>
  <condition>Kidney Transplantation</condition>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Eplets mismatching numbers</intervention_name>
    <description>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>
  </intervention>
  <biospec_retention>Samples Without DNA</biospec_retention>
  <biospec_descr>
    <textblock>
      The biospecimen in the study is sera of recipients after kidney transplantation.&#xD;
    </textblock>
  </biospec_descr>
  <eligibility>
    <study_pop>
      <textblock>
        Patients after kidney transplantation.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Patients with normal or nearly normal renal function after transplantation&#xD;
&#xD;
          -  Patients with abnormal renal function indicators after transplantation but in a stable&#xD;
             state without loss of function (serum creatinine 176-265 mmol/l)&#xD;
&#xD;
          -  Patients who are able to take immunosuppressive agents orally in strict accordance&#xD;
             with the doctor's instructions and can be regularly reviewed&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  All patients with renal transplantation function damage caused by surgical factors,&#xD;
             medicinal factors, acute tubular necrosis (ATN) and other factors&#xD;
&#xD;
          -  Postoperative patients complicated with malignant tumors or infectious diseases such&#xD;
             as tuberculosis and hepatitis&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>10 Years</minimum_age>
    <maximum_age>60 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <location>
    <facility>
      <name>The First Affiliated Hospital of Xi'an Jiaotong University</name>
      <address>
        <city>Xi'an</city>
        <state>Shaanxi</state>
        <zip>710061</zip>
        <country>China</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>China</country>
  </location_countries>
  <verification_date>August 2021</verification_date>
  <study_first_submitted>January 24, 2019</study_first_submitted>
  <study_first_submitted_qc>January 24, 2019</study_first_submitted_qc>
  <study_first_posted type="Actual">January 28, 2019</study_first_posted>
  <last_update_submitted>May 25, 2022</last_update_submitted>
  <last_update_submitted_qc>May 25, 2022</last_update_submitted_qc>
  <last_update_posted type="Actual">May 27, 2022</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03818698
org study id: XJTU1AF-CRF-2018-026
nct id: NCT03818698
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
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.
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.
observational model: Cohort
time perspective: Prospective
measure: The occurrence of dnDSA and AMR
time frame: 3 years
description: 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.
intervention type: Other
intervention name: Eplets mismatching numbers
description: 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.
The biospecimen in the study is sera of recipients after kidney transplantation.
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 10 Years
maximum age: 60 Years
healthy volunteers: No
facility: 
country: China
responsible party type: Sponsor