A new data-driven model for post-transplant antibody dynamics in high risk kidney transplantation

Seeking Standardized Definitions for HLA-incompatible Kidney Transplants: A Systematic Review

BACKGROUND

There is no standard definition for "HLA incompatible" transplants. For the first time, we systematically assessed how HLA incompatibility was defined in contemporary peer-reviewed publications and its prognostic implication to transplant outcomes.

METHODS

We combined 2 independent searches of MEDLINE, EMBASE, and the Cochrane Library from 2015 to 2019. Content-expert reviewers screened for original research on outcomes of HLA-incompatible transplants (defined as allele or molecular mismatch and solid-phase or cell-based assays). We ascertained the completeness of reporting on a predefined set of variables assessing HLA incompatibility, therapies, and outcomes. Given significant heterogeneity, we conducted narrative synthesis and assessed risk of bias in studies examining the association between death-censored graft failure and HLA incompatibility.

RESULTS

Of 6656 screened articles, 163 evaluated transplant outcomes by HLA incompatibility. Most articles reported on cytotoxic/flow T-cell crossmatches (n = 98). Molecular genotypes were reported for selected loci at the allele-group level. Sixteen articles reported on epitope compatibility. Pretransplant donor-specific HLA antibodies were often considered (n = 143); yet there was heterogeneity in sample handling, assay procedure, and incomplete reporting on donor-specific HLA antibodies assignment. Induction (n = 129) and maintenance immunosuppression (n = 140) were frequently mentioned but less so rejection treatment (n = 72) and desensitization (n = 70). Studies assessing death-censored graft failure risk by HLA incompatibility were vulnerable to bias in the participant, predictor, and analysis domains.

CONCLUSIONS

Optimization of transplant outcomes and personalized care depends on accurate HLA compatibility assessment. Reporting on a standard set of variables will help assess generalizability of research, allow knowledge synthesis, and facilitate international collaboration in clinical trials.

A Systematic Review of Kidney Transplantation Decision Modelling Studies

BACKGROUND

Genome-based precision medicine strategies promise to minimize premature graft loss after renal transplantation, through precision approaches to immune compatibility matching between kidney donors and recipients. The potential adoption of this technology calls for important changes to clinical management processes and allocation policy. Such potential policy change decisions may be supported by decision models from health economics, comparative effectiveness research and operations management.

OBJECTIVE

We used a systematic approach to identify and extract information about models published in the kidney transplantation literature and provide an overview of the status of our collective model-based knowledge about the kidney transplant process.

METHODS

Database searches were conducted in MEDLINE, Embase, Web of Science and other sources, for reviews and primary studies. We reviewed all English-language papers that presented a model that could be a tool to support decision making in kidney transplantation. Data were extracted on the clinical context and modelling methods used.

RESULTS

A total of 144 studies were included, most of which focused on a single component of the transplantation process, such as immunosuppressive therapy or donor-recipient matching and organ allocation policies. Pre- and post-transplant processes have rarely been modelled together.

CONCLUSION

A whole-disease modelling approach is preferred to inform precision medicine policy, given its potential upstream implementation in the treatment pathway. This requires consideration of pre- and post-transplant natural history, risk factors for allograft dysfunction and failure, and other post-transplant outcomes. Our call is for greater collaboration across disciplines and whole-disease modelling approaches to more accurately simulate complex policy decisions about the integration of precision medicine tools in kidney transplantation.

A Glucose-Only Model to Extract Physiological Information from Postprandial Glucose Profiles in Subjects with Normal Glucose Tolerance

BACKGROUND

Current mathematical models of postprandial glucose metabolism in people with normal and impaired glucose tolerance rely on insulin measurements and are therefore not applicable in clinical practice. This research aims to develop a model that only requires glucose data for parameter estimation while also providing useful information on insulin sensitivity, insulin dynamics and the meal-related glucose appearance (GA).

METHODS

The proposed glucose-only model (GOM) is based on the oral minimal model (OMM) of glucose dynamics and substitutes the insulin dynamics with a novel function dependant on glucose levels and GA. A Bayesian method and glucose data from 22 subjects with normal glucose tolerance are utilised for parameter estimation. To validate the results of the GOM, a comparison to the results of the OMM, obtained by using glucose and insulin data from the same subjects is carried out.

RESULTS

The proposed GOM describes the glucose dynamics with comparable precision to the OMM with an RMSE of 5.1 ± 2.3 mg/dL and 5.3 ± 2.4 mg/dL, respectively and contains a parameter that is significantly correlated to the insulin sensitivity estimated by the OMM (r = 0.7) Furthermore, the dynamic properties of the time profiles of GA and insulin dynamics inferred by the GOM show high similarity to the corresponding results of the OMM.

CONCLUSIONS

The proposed GOM can be used to extract useful physiological information on glucose metabolism in subjects with normal glucose tolerance. The model can be further developed for clinical applications to patients with impaired glucose tolerance under the use of continuous glucose monitoring data.

Dynamic Behaviour of Donor Specific Antibodies in the Early Period Following HLA Incompatible Kidney Transplantation

In HLA-incompatible kidney transplantation, monitoring donor-specific antibodies (DSA) plays a crucial role in providing appropriate treatment and increases kidney survival times. This work aimed to determine if early post-transplant DSA dynamics inform graft outcome over and above other predictive factors. Eighty-eight cases were classified by unsupervised machine learning into five distinct DSA response groups: no response, fast modulation, slow modulation, rise to sustained and sustained. Fast modulation dynamics gave an 80% rate for early acute rejection, whereas the sustained group was associated with the lowest rejection rates (19%). In complete contrast, the five-year graft failure was lowest in the modulation groups (4–7%) and highest in the sustained groups (25–31%). Multivariable analysis showed that a higher pre-treatment DSA level, male gender and absence of early acute rejection were strongly associated with a sustained DSA response. The modulation group had excellent five-year outcomes despite higher rates of early rejection episodes. This work further develops an understanding of post-transplant DSA dynamics and their influence on graft survival following HLA-incompatible kidney transplantation.

Bayesian parameter estimation in the oral minimal model of glucose dynamics from non-fasting conditions using a new function of glucose appearance

BACKGROUND AND OBJECTIVE

The oral minimal model (OMM) of glucose dynamics is a prominent method for assessing postprandial glucose metabolism. The model yields estimates of insulin sensitivity and the meal-related appearance of glucose from insulin and glucose data after an oral glucose challenge. Despite its success, the OMM approach has several weaknesses that this paper addresses.

METHODS

A novel procedure introducing three methodological adaptations to the OMM approach is proposed. These are: (1) the use of a fully Bayesian and efficient method for parameter estimation, (2) the model identification from non-fasting conditions using a generalised model formulation and (3) the introduction of a novel function to represent the meal-related glucose appearance based on two superimposed components utilising a modified structure of the log-normal distribution. The proposed modelling procedure is applied to glucose and insulin data from subjects with normal glucose tolerance consuming three consecutive meals in intervals of four hours.

RESULTS

It is shown that the glucose effectiveness parameter of the OMM is, contrary to previous results, structurally globally identifiable. In comparison to results from existing studies that use the conventional identification procedure, the proposed approach yields an equivalent level of model fit and a similar precision of insulin sensitivity estimates. Furthermore, the new procedure shows no deterioration of model fit when data from non-fasting conditions are used. In comparison to the conventional, piecewise linear function of glucose appearance, the novel log-normally based function provides an improved model fit in the first 30 min of the response and thus a more realistic estimation of glucose appearance during this period. The identification procedure is implemented in freely accesible MATLAB and Python software packages.

CONCLUSIONS

We propose an improved and freely available method for the identification of the OMM which could become the future standardard for the oral minimal modelling method of glucose dynamics.

C3d-positive donor-specific antibodies have a role in pretransplant risk stratification of cross-match-positive HLA-incompatible renal transplantation: United Kingdom multicentre study

Anti-HLA-antibody characteristics aid to risk-stratify patients and improve long-term renal graft outcomes. Complement activation by donor-specific antibody (DSA) is an important characteristic that may determine renal allograft outcome. There is heterogeneity in graft outcomes within the moderate to high immunological risk cases (cross-match-positive). We explored the role of C3d-positive DSAs in sub-stratification of cross-match-positive cases and relate to the graft outcomes. We investigated 139 cross-match-positive living-donor renal transplant recipients from four transplant centres in the United Kingdom. C3d assay was performed on serum samples obtained at pretreatment (predesensitization) and Day 14 post-transplant. C3d-positive DSAs were found in 52 (37%) patients at pretreatment and in 37 (27%) patients at Day 14 post-transplant. Median follow-up of patients was 48 months (IQR 20.47-77.57). In the multivariable analysis, pretreatment C3d-positive DSA was independently associated with reduced overall graft survival, the hazard ratio of 3.29 (95% CI 1.37-7.86). The relative risk of death-censored five-year graft failure was 2.83 (95% CI 1.56-5.13). Patients with both pretreatment and Day 14 C3d-positive DSAs had the worst five-year graft survival at 45.5% compared with 87.2% in both pretreatment and Day 14 C3d-negative DSA patients with the relative risk of death-censored five-year graft failure was 4.26 (95% CI 1.79, 10.09). In this multicentre study, we have demonstrated for the first time the utility of C3d analysis as a distinctive biomarker to sub-stratify the risk of poor graft outcome in cross-match-positive living-donor renal transplantation.