Dataset Information

A Clinical Tool to Guide Selection and Utilization of Marginal Donor Livers With Graft Steatosis in Liver Transplantation.

ABSTRACT:

Background

Donor liver biopsy (DLBx) in liver transplantation provides information on allograft quality; however, predicting outcomes from these allografts remains difficult.

Methods

Between 2006 and 2015, 16 691 transplants with DLBx were identified from the Standard Transplant Analysis and Research database. Cox proportional hazard regression analyses identified donor and recipient characteristics associated with 30-d, 90-d, 1-y, and 3-y graft survival. A composite model, the Liver Transplant After Biopsy (LTAB) score, was created. The Mini-LTAB was then derived consisting of only donor age, macrosteatosis on DLBx, recipient model for end-stage liver disease score, and cold ischemic time. Risk groups were identified for each score and graft survival was evaluated. P values <0.05 were considered significant.

Results

The LTAB model used 14 variables and 5 risk groups and identified low-, mild-, moderate-, high-, and severe-risk groups. Compared with moderate-risk recipients, severe-risk recipients had increased risk of graft loss at 30 d (hazard ratio, 3.270; 95% confidence interval, 2.568-4.120) and at 1 y (2.258; 1.928-2.544). The Mini-LTAB model identified low-, moderate-, and high-risk groups. Graft survival in Mini-LTAB high-risk transplants was significantly lower than moderate- or low-risk transplants at all time points.

Conclusions

The LTAB and Mini-LTAB scores represent guiding principles and provide clinically useful tools for the successful selection and utilization of marginal allografts in liver transplantation.

SUBMITTER: Steggerda JA

PROVIDER: S-EPMC8759620 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Fecal microbiota transplantation (FMT) targeting gut microbiota has recently been applied to the treatment of ulcerative colitis (UC). However, preliminary trials showed that only a subset of patients responded to FMT, and the heterogeneity in donor gut microbiota probably played important roles in patients' responses, implying the significance of matching an appropriate donor to a specified patient. We developed a strategy to build a donor-recipient matching model to guide rational donor selection for UC in FMT. We collected and uniformly reanalyzed 656 fecal 16S rRNA gene sequencing samples (350 from UC patients and 306 from healthy subjects) from 9 studies. Significantly lower α-diversity indexes were observed in UC patients by random effects model. Thirty-four bacterial genera and 34 predicted pathways were identified with significant odds ratios and classification potentials for UC patients. Based on six bacterial indicators, including richness, overall distance, genera, and pathways (beneficial and harmful), the analytic hierarchy process-based donor-recipient matching model was set to rank and select appropriate donors for patients with UC. Finally, the model showed favorable classification powers (>70%) for FMT effectiveness in two previous clinical trials. This study revealed the dysbiosis of fecal bacterial diversity, composition, and predicted pathways of patients with UC by meta-analysis and hereby developed a donor-recipient matching strategy to guide donor selection for UC in FMT. This strategy can also be applied to other diseases associated with gut microbiota. IMPORTANCE Modulation of gut microbiota by FMT from donors has been applied to the treatment of UC and yielded variable effectiveness in clinical trials. One possibility is that this variable effectiveness was related to donor selection, as a patient's response to FMT may rely on the capability of the used donor's microbiota to restore the specific gut disturbances of the patient. However, the biggest issues on the practical level are what should be considered in the selection process and how to set up such a donor-recipient matching model. In this study, we presented a bacterial profile-based donor-recipient matching strategy to guide donor selection for UC in FMT by first meta-analysis of 656 fecal 16S rRNA gene sequencing samples from 9 studies to identify significant indicators and then setting up the model by an analytic hierarchy process. The applicability and accuracy of this model were verified in the data sets from two previous FMT clinical studies. Our data indicate that the donor-recipient matching model built in this study enables researchers to rationally select donors for UC patients in FMT clinical practice, although it needs more samples and prospective trials for validation. The strategy adopted in this study to leverage existing data sets to build donor-recipient matching models for precision FMT is feasible for other diseases associated with gut microbiota.