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257 lines
9.7 KiB
TeX
257 lines
9.7 KiB
TeX
% Unofficial University of Cambridge Poster Template
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% https://github.com/andiac/gemini-cam
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% a fork of https://github.com/anishathalye/gemini
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% ====================
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% Title
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% ====================
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\title{Development and Validation of a french kidney donor marginality score}
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\author{Corentin Choisy \inst{1} \and Magali Giral \inst{2,3} \and Etienne Dantan \inst{1}}
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\institute[shortinst]{\inst{1} SPHERE UMR 1246, Nantes Université, Univ Tours, CHU Nantes, Inserm, Nantes, France \and \inst{2} CR2TI UMR 1064, Nantes Université, ITUN, CHU Nantes, RTRS Centaure, Nantes, France \and \inst{3} Centre d'Investigation Clinique en Biothérapie, Nantes, France}
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\footercontent{
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\href{https://www.divat.fr/}{https://www.sphere-inserm.fr/} \hfill
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Congrès Nan'thèse 2023, Nantes --- France \hfill
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\href{mailto:corentin.choisy@univ-nantes.fr}{corentin.choisy@univ-nantes.fr}}
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% ====================
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% Body
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% ====================
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\begin{document}
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% Refer to https://github.com/k4rtik/uchicago-poster
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% logo: https://www.cam.ac.uk/brand-resources/about-the-logo/logo-downloads
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% \addtobeamertemplate{headline}{}
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% \begin{tikzpicture}[remember picture,overlay]
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% \node [anchor=north west, inner sep=3cm] at ([xshift=-2.5cm,yshift=1.75cm]current page.north west)
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% {\includegraphics[height=7cm]{logos/unott-logo.eps}};
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\begin{column}{\colwidth}
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\begin{block}{Background}
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\begin{itemize}
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\item \textbf{Kidney transplantation (KT)}: recognised as the best treatment for \textbf{end-stage chronic renal disease}
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\begin{itemize}
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\setlength{\itemindent}{1em}
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\item \textbf{Graft shortage} in countries with aging population
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\textbf{\textcolor{nottblue}{$\Rightarrow$ Necessity for expansion of graft pool}}
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\end{itemize}
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\item Wide use of \textbf{marginal grafts} with suboptimal properties for patient-graft survival
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\item Decision making tools to assist clinicians in evaluating graft proposals
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\begin{itemize}
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\setlength{\itemindent}{1em}
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\item \textbf{ECD \cite{metzger2003expanded}} Older than 60 years old or between 50 and 59 with at least 2 comorbidities among: high serum creatinine, history of hypertension and death by CVA
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\textbf{\textcolor{nottblue}{$\Rightarrow$ Binary criterion, no gradient between less and more marginal donors}}
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\item \textbf{KDRI/KDPI \cite{rao2009comprehensive}} Continuous/percentile scale defined by 10 donor features
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\textbf{\textcolor{nottblue}{$\Rightarrow$ Not adapted to the french population \cite{dantan2021covariates} and prone to increased graft refusal rate \cite{aubert2019disparities}}}
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\end{itemize}
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\end{itemize}
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\vskip-0.5em
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{\centering\includegraphics[scale=1.6]{Images/Chronic renal disease prevalence.pdf}\par}
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\vskip-1em
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\end{block}
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\begin{block}{Objectives}
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Develop and validate a \textbf{\textcolor{nottblue}{kidney donor marginality score}}, \textbf{adapted to the french population} and \textbf{suited for the current practices} in KT in France
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\begin{itemize}
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\item \textbf{Donor/recipient interactions} will be studied in order to express donor marginality in relation to recipient characteristics
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\item \textcolor{darkgray}{\textbf{Recipient loss-of-chance} related to receiving a marginal graft as defined by the proposed score will be studied}
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\end{itemize}
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\end{block}
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\begin{alertblock}{Materials and Methods}
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\begin{itemize}
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\item \textbf{7622 patients} from the DIVAT national kidney transplant cohort
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\item First-time deceased donor graft recipients without donor-recipient ABO incompatibility
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\item \textbf{Multivariate Cox regression} model built via blockwise variable selection approach (Donor/Graft/Recipient features integrated/removed from the model in 11 steps)
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\item Assessment of \textbf{period/center effect} via adjusted and frailty models
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\item New variable selection steps after integration of period/center effects
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\end{itemize}
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{\centering\includegraphics[scale=0.36]{Images/analyse.png}\par}
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{\centering\small \textbf{Variable selection process} (square nodes indicate all previously included predictors were forced in the model during backward selection, circle nodes indicate no variable was forced)\par}
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\end{alertblock}
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\begin{block}{Funding}
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\centering
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This work was supported by the French Biomedicine Agency (reference: AOR Greffe 2022)
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\end{block}
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\vskip-0.15em
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\begin{block}{}
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{\centering\includegraphics[scale=0.8]{logos/logband.png}\par}
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\end{block}
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\end{column}
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\separatorcolumn
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\begin{block}{Results}
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\vskip-1em
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\begin{figure}
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\centering
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\includegraphics[scale=1.5]{Images/km_global.pdf}
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\vskip-1.25em
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\caption{Patient/allograft survival analysis}
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\label{fig:km}
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\end{figure}
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\begin{table}[]
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\centering
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\begin{tabular}{@{}lcccc@{}}
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\toprule
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& \beta & 95\% CI \\ \midrule
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Donor age & -0.020 & {[-0.037}-- {-0.003]} \\
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Donor after cardiac death & 0.691 & {[0.416}--{0.967]} \\
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Donor death by CVA & -0.616 & {[-1.224}-- {-0.008]} \\
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Donor serum creatinine & 0.001 & {[0.0001}--{0.002]} \\
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Donor height & -0.011 & {[-0.018}-- {-0.004]} \\
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Donor weight & 0.005 & {[0.001}--{0.010]} \\
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Positive donor CMV serology & 0.124 & {[0.010}--{0.239]} \\
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\addlinespace\addlinespace
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\textcolor{darkgray}{\textbf{HLA incompatibilities \geq 4}} & 0.151 & {[0.009}--{0.293]} \\
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Time on dialysis & 0.0001 & {[0.0001}--{0.0001]} \\
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Transplanted before 2012 & 0.190 & {[0.040}--{0.340]} \\
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\addlinespace\addlinespace
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Recipient age & -0.021 & {[-0.036}-- {-0.005]} \\
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Recipient BMI & 0.011 & {[-0.003}--{0.025]} \\
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Recipient history of diabetes & 0.376 & {[0.234}--{0.517]} \\
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Recipient history of cardiovascular disease & 0.408 & {[0.239}--{0.527]} \\
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Hemodialysis & 0.250 & {[0.048}--{0.452]} \\
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\textcolor{darkgray}{\textbf{Donor age*Recipient age}} & 0.001 & {[0.0001}--{0.001]} \\
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\textcolor{darkgray}{\textbf{Donor death by CVA*Recipient age}} & 0.014 & {[0.003}--{0.024]} \\ \bottomrule
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\end{tabular}
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\caption{\label{mod-table}Proportional hazards Cox model analysis of retained factors and interactions after multivariate selection}
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\end{table}
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\vskip-1em
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\begin{itemize}
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\item Donor age, beating heart status ($HR=2.00$), cause of death, creatininemia, height, weight and CMV serology ($HR=1.13$) will be integrated into the score. For a given donor, the score will differ depending on recipient age and donor/recipient HLA ABDR incompatibilities.
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\end{itemize}
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\end{block}
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\vskip-0.5em
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\begin{exampleblock}{What's next}
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\vskip0.3em
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\begin{itemize}
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\item \textbf{Internal validation} of the model, $\frac{1}{3}$ of the database allocated to a random validation sample
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\item \textbf{Validity assessed through:}
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\begin{itemize}
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\setlength{\itemindent}{1em}
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\item \textbf{Calibration:} calibration plot, predicted survival by score quantile, Brier score
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\item \textbf{Discrimination:} time-dependent ROC curve (AUC, PPV/NPV) and time-dependent ROC curve per recipient strata
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\end{itemize}
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\item \textbf{Propensity score}-based analysis to estimate population-averaged effects and propose a recipient loss-of-chance-based approach
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\item Development of an \textbf{online score computation tool} for clinicians
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\end{itemize}
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\end{exampleblock}
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\vskip-1em
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\begin{block}{References}
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\vskip-0.15em
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\nocite{*}
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\footnotesize{\bibliographystyle{plain}\bibliography{poster}}
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\end{document}
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