International prognostic score for asymptomatic early-stage chronic lymphocytic leukemia von Condoluci, Adalgisa, Terzi di Bergamo, Lodovico, Langerbeins, Petra, Hoechstetter, Manuela A., Herling, Carmen D., De Paoli, Lorenzo, Delgado, Julio, Rabe, Kari G., Gentile, Massimo, Doubek, Michael, Mauro, Francesca R., Chiodin, Giorgia, Mattsson, Mattias, Bahlo, Jasmin, Cutrona, Giovanna, Kotaskova, Jana, Deambrogi, Clara, Smedby, Karin E., Spina, Valeria, Bruscaggin, Alessio, Wu, Wei, Moia, Riccardo, Bianchi, Elena, Gerber, Bernhard, Zucca, Emanuele, Gillessen, Silke, Ghielmini, Michele, Cavalli, Franco, Stussi, Georg, Hess, Mark A., Baumann, Tycho S., Neri, Antonino, Ferrarini, Manlio, Rosenquist, Richard, Forconi, Francesco, Foà, Robin, Pospisilova, Sarka, Morabito, Fortunato, Stilgenbauer, Stephan, Döhner, Hartmut, Parikh, Sameer A., Wierda, William G., Montserrat, Emili, Gaidano, Gianluca, Hallek, Michael, Rossi, Davide

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Identifying patients with chronic lymphocytic leukemia without need of treatment: End of endless watch and wait? von Brieghel, Christian, Galle, Veerle, Agius, Rudi, da Cunha‐Bang, Caspar, Andersen, Michael A., Vlummens, Philip, Mattsson, Mattias, Rosenquist, Richard, Smedby, Karin E., Herling, Carmen D., Bahlo, Jasmin, Hallek, Michael, Lundgren, Jens D., Offner, Fritz, Niemann, Carsten U.

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Machine learning can identify newly diagnosed patients with CLL at high risk of infection von Agius, R, Brieghel, C, Andersen, MA, Pearson, AT, Ledergerber, B, Cozzi-Lepri, A, Louzoun, Y, Andersen, CL, Bergstedt, J, von Stemann, JH, Jørgensen, M, Tang, M-HE, Fontes, M, Bahlo, J, Herling, CD, Hallek, M, Lundgren, J, MacPherson, CR, Larsen, J, Niemann, CU

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