Postdoc: Analysing pulmonary transplant activity in France: Towards a prediction of chronic rejection

5 Juillet 2024

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Catégorie : Post-doctorant

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1. Context
Lung transplantation is the ultimate treatment for end-stage respiratory failure. It is a heavy, costly treatment with pre-, peri-, and post-operative risks. In particular, 30\% of lung transplant recipients develop chronic lung allograft dysfunction (CLAD) within 3 years, which, once diagnosed, results in a life expectancy of about 2 to 3 years. A recent report on the state of lung transplantation in France was conducted by the Académie de Médecine [1]. One of the points highlighted by this report is the mismatch in France between the needs and the capacities for lung transplantation, partly due to the low number of available grafts. One way to improve this situation could be to better target recipients based on the probability of graft rejection. The medical question is therefore: 'Is it possible to estimate the probability of lung graft rejection in a given patient, the potential organ recipient, in order to optimize graft allocation?’

2. Objectives
The aim of this project is to develop a tool to estimate the probability of the occurrence of CLAD. This requires mesoscopic and temporal modeling. Preliminary analyses (univariate, multivariate statistics, and Bayesian approaches) have been conducted to identify causal links between variables. The goal is to build on these results to construct a prediction model for the onset of CLAD.
The first step will be to model the 'center effect,' that is, the biases related to the population pool managed by each transplant center (the typology of patients, including the pathologies that led to the transplant) and the specific care characteristics of the transplant centers (center expertise, care modalities).
In a second step, a model for estimating the probability of individual rejection based on this center effect and, among other factors, on the time series associated with the clinical follow-up of each patient will be proposed. In particular, it will be necessary to account for and correct the impact of practice evolution during the cohort formation.

3. COhort of Lung Tansplantation (COLT)
This cohort contains 1850 lung transplant patients across the national territory during the period 2010-2023, with follow-up for up to 10 years for most of them. It has resulted in a database aggregating pre-, peri-, and post-lung transplant information. The nature of the information is relatively varied and covers, for example, the patient's medical context, the practices of transplant centers, donor/recipient immunological matching, the evolution of respiratory function, etc. This represents approximately 450 variables of different types. In particular, the temporal evolution of respiratory function is studied. It is the largest European database on lung transplantation. We have access to and are authorized to use this database.

4. State of the art
The state of the art from the Académie de Médecine is exclusively descriptive. It does not propose any causal or predictive modeling of the observed phenomena. Furthermore, it only addresses the issue at the macroscopic level. The state of the art is relatively poor in this field and has mainly focused on the immunological approach, assuming that graft rejection is primarily determined by the donor/recipient immunological confrontation [2].

5. Ethical aspects
Ethical questions naturally arise on the legitimacy of having and using a tool that can contraindicate a potentially life-saving medical-surgical procedure (the transplant) for a patient otherwise doomed to short-term death (a few weeks) in favor of another patient whose medium- and long-term survival would be ensured. An ethical reflection will be conducted throughout the work, focusing on the medical explainability, which is necessary but may not be sufficient to convince doctors and patients, and on the patients' perception of such a model as a potential tool for medical decision support. For this, interviews with naïve patients, patients concerned with lung transplantation (waiting for a transplant, already transplanted), doctors, and project members will be conducted.

6. Administrative aspects and supervision team contacts
Refer to the complete offer for details on the administrative aspects.
Application deadline: 15/09/2024

Apply by email to the supervising team members, with [post-doc CLAD] as subject. Attach a CV, motivation letter (2 pages max), and two references (letters of recommendation are appreciated).

Stéphane Delliaux, stephane.delliaux@univ-amu.fr
Raquel Urena, raquel.urena@univ-amu.fr
Paul Chauchat, paul.chauchat@lis-lab.fr
Christophe Gonzales, christophe.gonzales@lis-lab.fr

References
[1] Rapport de l'Académie Nationale de Médecine. Transplantation pulmonaire de l'adulte en France, état des lieux, 2023.
[2] S. Janciauskiene, P-J. Royer, J. Gufe, S. Wrenger, J. Chorostowska-Wynimko, C. Falk, T. Welte, M. Reynaud-Gaubert, A. Roux, A. Tissot, et al. Plasma acute phase proteins as predictors of chronis lung allograft dysfunction in lung transplant recipients. Journal of Inflammation Research, pp. 1021-1028, 2020