%0 Journal Article
%A Borys, Katarzyna
%A Haubold, Johannes
%A Keyl, Julius
%A Bali, Maria A
%A De Angelis, Riccardo
%A Boni, Kévin Brou
%A Coquelet, Nicolas
%A Kohnke, Judith
%A Baldini, Giulia
%A Kroll, Lennard
%A Schramm, Sara
%A Stang, Andreas
%A Malamutmann, Eugen
%A Kleesiek, Jens
%A Kim, Moon
%A Kasper, Stefan
%A Siveke, Jens
%A Wiesweg, Marcel
%A Merkel-Jens, Anja
%A Schaarschmidt, Benedikt M
%A Gruenwald, Viktor
%A Bauer, Sebastian
%A Oezcelik, Arzu
%A Bölükbas, Servet
%A Herrmann, Ken
%A Kimmig, Rainer
%A Lang, Stephan
%A Treckmann, Jürgen
%A Stuschke, Martin
%A Hadaschik, Boris
%A Umutlu, Lale
%A Forsting, Michael
%A Schadendorf, Dirk
%A Friedrich, Christoph M
%A Schuler, Martin
%A Hosch, René
%A Nensa, Felix
%T Leveraging Sarcopenia index by automated CT body composition analysis for pan cancer prognostic stratification.
%J npj digital medicine
%V 8
%N 1
%@ 2398-6352
%C [Basingstoke]
%I Macmillan Publishers Limited
%M DKFZ-2025-02115
%P 611
%D 2025
%X This study evaluates the CT-based volumetric sarcopenia index (SI) as a baseline prognostic factor for overall survival (OS) in 10,340 solid tumor patients (40
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:41087591
%R 10.1038/s41746-025-02016-z
%U https://inrepo02.dkfz.de/record/305374