Removing administrative boundaries using a gravity model for a national liver allocation system.

Geographic disparities emerged as an increasing issue in organ allocation policies. Because of the sequential and discrete geographical models used for allocation scores, artificial regional boundaries may impede the access of candidates with the greatest medical urgency to vital organs. This article describes a continuous geographical allocation model that provides accurate organ access by introducing a multiplicative interaction between the patient's condition and the distance to the graft by using a gravity model. Patients with the most urgent need will thus have access to organs from farther away, while those in less urgent need may only have access to organs geographically closer. Compared to the previous French liver allocation scheme, the gravity model precluded transplantations for candidates with a Model for End-Stage Liver Disease (MELD) ≤ 14 for decompensated cirrhosis from 10.3% to 0.6%. Death and delisting while on the waiting list at 1 year also decreased from 30.1% to 22.4% for MELD ≥ 35. Waiting list (cumulative hazard ratio (CHR)  0.84 after adjustment) and posttransplant survival improved significantly (hazard ratio = 0.83 after adjustment). This new liver allocation system provides more equitable access to liver transplants and an efficient and safe alternative to administrative boundaries for geographical models in organ allocation.

New French heart allocation system: Comparison with Eurotransplant and US allocation systems.

Graft allocation rules for heart transplantation are necessary because of the shortage of heart donors, resulting in high waitlist mortality. The Agence de la biomédecine is the agency in charge of the organ allocation system in France. Assessment of the 2004 urgency-based allocation system identified challenging limitations. A new system based on a score ranking all candidates was implemented in January 2018. In the revised system, medical urgency is defined according to candidate characteristics rather than the treatment modalities, and an interplay between urgency, donor-recipient matching, and geographic sharing was introduced. In this article, we describe in detail the new allocation system and compare these allocation rules to Eurotransplant and US allocation policies.

Continuous Monitoring of Transplant Center Performance: Different Options for Different Goals.

BACKGROUND: In France, the need for continuous monitoring of transplant center performance has recently become apparent. Cumulative sum (CUSUM) monitoring of transplantation is already been used to monitor transplant outcomes in the United Kingdom and in the United States. Because CUSUM monitoring can be applied by different methods, the objective was to assess and compare the performance of different CUSUM methods for detecting higher than expected (ie, excessive) graft failure rates. METHODS: Data come from the French transplant registry. Lung and kidney transplants in 2011-2013 constituted the control cohort, and those in 2014-2016 the observed cohort. The performance of CUSUM monitoring, according to center type and predefined control limits, was measured by simulation. The outcome monitored was 3-month graft failure. RESULTS: In a low-volume center with a low failure rate, 3 different types of control limits produced successful detection rates of excessive graft failures of 15%, 62%, and 73% and false alarm rates of 5%, 40%, and 52%, with 3, 1, and 1 excess failures necessary before a signal occurred. In a high-volume center with a high failure rate, successful detection rates were 83%, 93%, and 100% and false alarm rates were 5%, 16%, and 69%, with 6, 13, and 17 excess failures necessary before a signal occurred. CONCLUSIONS: CUSUM performances vary greatly depending on the type of control limit used. A new control limit set to maximize specificity and sensitivity of detection is an appropriate alternative to those commonly used. Continued attention is necessary for centers with characteristics making it difficult to obtain adequate sensitivity or sufficiently prompt response.

Between-center disparities in access to heart transplantation in France: contribution of candidate and center factors - A comprehensive cohort study.

Transplantation represents the last option for patients with advanced heart failure. We assessed between-center disparities in access to heart transplantation in France 1 year after registration and evaluated the contribution of factors to these disparities. Adults (n = 2347) registered on the French national waiting list between January 1, 2010, and December 31, 2014, in the 23 transplant centers were included. Associations between candidate and transplant center characteristics and access to transplantation were assessed by proportional hazards frailty models. Candidate blood groups O and A, sensitization, and body mass index ≥30 kg/m2 were independently associated with lower access to transplantation, while female gender, severity of heart failure, and high serum bilirubin levels were independently associated with greater access to transplantation. Center factors significantly associated with access to transplantation were heart donation rate in the donation service area, proportion of high-urgency candidates among listed patients, and donor heart offer decline rate. Between-center variability in access to transplantation increased by 5% after adjustment for candidate factors and decreased by 57% after adjustment for center factors. After adjustment for candidate and center factors, five centers were still outside of normal variability. These findings will be taken into account in the future French heart allocation system.

R. S. WebTool, a web server for random sampling-based significance evaluation of pairwise distances.

Pairwise comparison of data vectors represents a large part of computational biology, especially with the continuous increase in genome-wide approaches yielding more information from more biological samples simultaneously. Gene clustering for function prediction as well as analyses of signalling pathways and the time-dependent dynamics of a system are common biological approaches that often rely on large dataset comparison. Different metrics can be used to evaluate the similarity between entities to be compared, such as correlation coefficients and distances. While the latter offers a more flexible way of measuring potential biological relationships between datasets, the significance of any given distance is highly dependent on the dataset and cannot be easily determined. Monte Carlo methods are robust approaches for evaluating the significance of distance values by multiple random permutations of the dataset followed by distance calculation. We have developed R. S. WebTool (http://rswebtool.kwaklab.org), a user-friendly online server for random sampling-based evaluation of distance significances that features an array of visualization and analysis tools to help non-bioinformaticist users extract significant relationships from random noise in distance-based dataset analyses.

Evolution of biological sequences implies an extreme value distribution of type I for both global and local pairwise alignment scores.

BACKGROUND: Confidence in pairwise alignments of biological sequences, obtained by various methods such as Blast or Smith-Waterman, is critical for automatic analyses of genomic data. Two statistical models have been proposed. In the asymptotic limit of long sequences, the Karlin-Altschul model is based on the computation of a P-value, assuming that the number of high scoring matching regions above a threshold is Poisson distributed. Alternatively, the Lipman-Pearson model is based on the computation of a Z-value from a random score distribution obtained by a Monte-Carlo simulation. Z-values allow the deduction of an upper bound of the P-value (1/Z-value2) following the TULIP theorem. Simulations of Z-value distribution is known to fit with a Gumbel law. This remarkable property was not demonstrated and had no obvious biological support. RESULTS: We built a model of evolution of sequences based on aging, as meant in Reliability Theory, using the fact that the amount of information shared between an initial sequence and the sequences in its lineage (i.e., mutual information in Information Theory) is a decreasing function of time. This quantity is simply measured by a sequence alignment score. In systems aging, the failure rate is related to the systems longevity. The system can be a machine with structured components, or a living entity or population. "Reliability" refers to the ability to operate properly according to a standard. Here, the "reliability" of a sequence refers to the ability to conserve a sufficient functional level at the folded and maturated protein level (positive selection pressure). Homologous sequences were considered as systems 1) having a high redundancy of information reflected by the magnitude of their alignment scores, 2) which components are the amino acids that can independently be damaged by random DNA mutations. From these assumptions, we deduced that information shared at each amino acid position evolved with a constant rate, corresponding to the information hazard rate, and that pairwise sequence alignment scores should follow a Gumbel distribution, which parameters could find some theoretical rationale. In particular, one parameter corresponds to the information hazard rate. CONCLUSION: Extreme value distribution of alignment scores, assessed from high scoring segments pairs following the Karlin-Altschul model, can also be deduced from the Reliability Theory applied to molecular sequences. It reflects the redundancy of information between homologous sequences, under functional conservative pressure. This model also provides a link between concepts of biological sequence analysis and of systems biology.

A configuration space of homologous proteins conserving mutual information and allowing a phylogeny inference based on pair-wise Z-score probabilities.

BACKGROUND: Popular methods to reconstruct molecular phylogenies are based on multiple sequence alignments, in which addition or removal of data may change the resulting tree topology. We have sought a representation of homologous proteins that would conserve the information of pair-wise sequence alignments, respect probabilistic properties of Z-scores (Monte Carlo methods applied to pair-wise comparisons) and be the basis for a novel method of consistent and stable phylogenetic reconstruction. RESULTS: We have built up a spatial representation of protein sequences using concepts from particle physics (configuration space) and respecting a frame of constraints deduced from pair-wise alignment score properties in information theory. The obtained configuration space of homologous proteins (CSHP) allows the representation of real and shuffled sequences, and thereupon an expression of the TULIP theorem for Z-score probabilities. Based on the CSHP, we propose a phylogeny reconstruction using Z-scores. Deduced trees, called TULIP trees, are consistent with multiple-alignment based trees. Furthermore, the TULIP tree reconstruction method provides a solution for some previously reported incongruent results, such as the apicomplexan enolase phylogeny. CONCLUSION: The CSHP is a unified model that conserves mutual information between proteins in the way physical models conserve energy. Applications include the reconstruction of evolutionary consistent and robust trees, the topology of which is based on a spatial representation that is not reordered after addition or removal of sequences. The CSHP and its assigned phylogenetic topology, provide a powerful and easily updated representation for massive pair-wise genome comparisons based on Z-score computations.