Cutoff values and data handling for solid-phase testing for antibodies to HLA: Effects on listing unacceptable antigens for thoracic organ transplantation

详细信息	查看全文 | 推荐本文 |

• 作者：Chang Liu^a ; Lauren Wetter^b ; Sue Pang^b ; Donna L. Phelan^b ; Thalachallour Mohanakumar^a ; ^c ; Gerald P. Morris^a ; ^{gmorris@path.wustl.edu}
• 关键词：AHG ; anti-human globulin ; AMR ; antibody-mediated rejection ; CXM ; cytotoxicity crossmatch ; DSA ; donor-specific antibody ; FCXM ; flow cytometry crossmatch ; MFI ; mean fluorescence intensity ; MR ; MFI ratio ; ROC ; receiver operating characteristic ; RR ; relative
• 出版年：2012
• 期刊代码：75_01988859
• 类别：bio
• 出版时间：June, 2012
• 卷：73
• 期：6
• 页码：597-604
• 文件大小：1248 K

摘要

Application of single-antigen solid-phase immunoassay (SPI) in virtual crossmatch-based organ allocation has been hindered by continued debate over the biologic relevance of detected antibodies and the relationship between cutoff mean fluorescence intensity (MFI) values with crossmatch testing results. To define SPI parameters accurately predicting crossmatch testing, we analyzed a series of anti-HLA antibodies from highly-sensitized patients awaiting lung or heart transplantation. Serial dilution of serum for SPI and cytotoxic crossmatch (CXM) enabled comparison over a wide spectrum of antibody 鈥渟trengths鈥? Receiver operating characteristic (ROC) analysis identified predictive cutoff values for HLA Class I and DR-specific antibodies. However, antibodies to HLA-DQ antigens demonstrated a significantly different characteristic, highlighting difficulties in interpretation of clinical significance. We also quantitatively characterized two data handling methods, MFI ratio (MR) and relative ratio (RR), to examine their potential impact on identifying unacceptable antigens. In combination with user defined cutoff values, MFI, MR and RR lead to discordant identification of antibodies. Establishment of cutoff values for MR and RR that are comparable to MFI demonstrated increased consistency in antibody identification. This single laboratory experience is an example of establishing statistically robust cutoff values and validation across different data handling methods for use of SPI in virtual crossmatch.