Johannes Thaler1, Cihan Ay1, Alexandra Kaider1, Eva-Maria Reitter1, Johanna Haselböck1, Christine Mannhalter1, Christoph Zielinski1, Christine Marosi1, Ingrid Pabinger1. 1. Clinical Division of Haematology and Haemostaseology, Department of Medicine I, Medical University of Vienna, Austria (J.T., C.A., E-M.R., J.H., I.P.); Comprehensive Cancer Center Vienna, Medical University of Vienna, Vienna General Hospital, Vienna, Austria (J.T., C.A., E-M.R., C.Z., C.MAR., J.H., I.P.); Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria (C.MAN.); Clinical Division of Oncology, Department of Medicine I, Medical University of Vienna, Vienna, Austria (C.Z., C.MAR.); Center for Medical Statistics, Informatics and Intelligent Systems, Section for Clinical Biometrics, Medical University of Vienna, Vienna, Austria (A.K.).
Abstract
BACKGROUND: High-grade gliomas (HGGs) are among the most prothrombotic of malignancies. METHODS: We performed a prospective study to investigate 11 potential biomarkers for prediction of venous thromboembolism (VTE) in newly diagnosed HGG patients who had undergone a neurosurgical intervention. In addition, we tested 2 VTE risk assessment models (RAMs). The strongest predictors of VTE, which were identified by statistical forward selection, were used for the first RAM. The parameters used for the second RAM were both predictive of VTE and available in routine clinical practice. RESULTS: One hundred forty-one HGG patients were included in this study, and 24 (17%) of them developed VTE during follow-up. An association with the risk of future VTE was found for the following parameters: leukocyte count, platelet count, sP-selectin, prothrombin-fragment 1 + 2, FVIII activity, and D-dimer. The first RAM included low platelet count (<25th percentile of the study population) and elevated sP-selectin (≥75th percentile). The cumulative VTE probability after 12 months was 9.7% for score 0 (n = 76), 18.9% for score 1 (n = 59), and 83.3% for score 2 (n = 6). The second RAM included low platelet count (<25th percentile), elevated leukocyte count, and elevated D-dimer (≥75th percentile). The probability of VTE was 3.3% for score 0 (n = 63), 23.0% for score 1 (n = 53), and 37.7% for score 2 (n = 22) or score 3 (n = 3). CONCLUSIONS: We identified biomarkers suitable for assessing the VTE risk in newly diagnosed HGG patients. The application of 2 RAMs allowed identification of patients at high risk of developing VTE. We could also define patients at low risk of VTE, who would most probably not benefit from extended primary thromboprophylaxis.
BACKGROUND: High-grade gliomas (HGGs) are among the most prothrombotic of malignancies. METHODS: We performed a prospective study to investigate 11 potential biomarkers for prediction of venous thromboembolism (VTE) in newly diagnosed HGG patients who had undergone a neurosurgical intervention. In addition, we tested 2 VTE risk assessment models (RAMs). The strongest predictors of VTE, which were identified by statistical forward selection, were used for the first RAM. The parameters used for the second RAM were both predictive of VTE and available in routine clinical practice. RESULTS: One hundred forty-one HGG patients were included in this study, and 24 (17%) of them developed VTE during follow-up. An association with the risk of future VTE was found for the following parameters: leukocyte count, platelet count, sP-selectin, prothrombin-fragment 1 + 2, FVIII activity, and D-dimer. The first RAM included low platelet count (<25th percentile of the study population) and elevated sP-selectin (≥75th percentile). The cumulative VTE probability after 12 months was 9.7% for score 0 (n = 76), 18.9% for score 1 (n = 59), and 83.3% for score 2 (n = 6). The second RAM included low platelet count (<25th percentile), elevated leukocyte count, and elevated D-dimer (≥75th percentile). The probability of VTE was 3.3% for score 0 (n = 63), 23.0% for score 1 (n = 53), and 37.7% for score 2 (n = 22) or score 3 (n = 3). CONCLUSIONS: We identified biomarkers suitable for assessing the VTE risk in newly diagnosed HGG patients. The application of 2 RAMs allowed identification of patients at high risk of developing VTE. We could also define patients at low risk of VTE, who would most probably not benefit from extended primary thromboprophylaxis.
Authors: A A Brandes; E Scelzi; G Salmistraro; M Ermani; C Carollo; F Berti; P Zampieri; C Baiocchi; M V Fiorentino Journal: Eur J Cancer Date: 1997-09 Impact factor: 9.162
Authors: J P Zou; L A Morford; C Chougnet; A R Dix; A G Brooks; N Torres; J D Shuman; J E Coligan; W H Brooks; T L Roszman; G M Shearer Journal: J Immunol Date: 1999-04-15 Impact factor: 5.422
Authors: Ralph Simanek; Rainer Vormittag; Marco Hassler; Karl Roessler; Martin Schwarz; Christoph Zielinski; Ingrid Pabinger; Christine Marosi Journal: Neuro Oncol Date: 2007-02-27 Impact factor: 12.300
Authors: R A Rodas; R A Fenstermaker; P E McKeever; M Blaivas; L D Dickinson; S M Papadopoulos; J T Hoff; L N Hopkins; M Duffy-Fronckowiak; H S Greenberg Journal: J Neurosurg Date: 1998-08 Impact factor: 5.115
Authors: Cihan Ay; Lea V Jungbauer; Thomas Sailer; Theres Tengler; Silvia Koder; Alexandra Kaider; Simon Panzer; Peter Quehenberger; Ingrid Pabinger; Christine Mannhalter Journal: Clin Chem Date: 2007-05-17 Impact factor: 8.327
Authors: Ingrid Pabinger; Nick van Es; Georg Heinze; Florian Posch; Julia Riedl; Eva-Maria Reitter; Marcello Di Nisio; Gabriela Cesarman-Maus; Noémie Kraaijpoel; Christoph Carl Zielinski; Harry Roger Büller; Cihan Ay Journal: Lancet Haematol Date: 2018-06-07 Impact factor: 18.959
Authors: Michael B Streiff; Xiaobu Ye; Thomas S Kickler; Serena Desideri; Jayesh Jani; Joy Fisher; Stuart A Grossman Journal: J Neurooncol Date: 2015-06-23 Impact factor: 4.130
Authors: David Schiff; Eudocia Q Lee; Lakshmi Nayak; Andrew D Norden; David A Reardon; Patrick Y Wen Journal: Neuro Oncol Date: 2014-10-30 Impact factor: 12.300
Authors: Shlomit Yust-Katz; Jacob J Mandel; Jimin Wu; Ying Yuan; Courtney Webre; Tushar A Pawar; Harshad S Lhadha; Mark R Gilbert; Terri S Armstrong Journal: J Neurooncol Date: 2015-05-19 Impact factor: 4.130
Authors: Dusten Unruh; Steven R Schwarze; Laith Khoury; Cheddhi Thomas; Meijing Wu; Li Chen; Rui Chen; Yinxing Liu; Margaret A Schwartz; Christina Amidei; Priya Kumthekar; Carolina G Benjamin; Kristine Song; Caleb Dawson; Joanne M Rispoli; Girish Fatterpekar; John G Golfinos; Douglas Kondziolka; Matthias Karajannis; Donato Pacione; David Zagzag; Thomas McIntyre; Matija Snuderl; Craig Horbinski Journal: Acta Neuropathol Date: 2016-09-23 Impact factor: 17.088
Authors: Adrian Lee; Malmaruha Arasaratnam; David Lok Hang Chan; Mustafa Khasraw; Viive M Howell; Helen Wheeler Journal: Cochrane Database Syst Rev Date: 2020-05-12
Authors: Julia Riedl; Matthias Preusser; Pegah Mir Seyed Nazari; Florian Posch; Simon Panzer; Christine Marosi; Peter Birner; Johannes Thaler; Christine Brostjan; Daniela Lötsch; Walter Berger; Johannes A Hainfellner; Ingrid Pabinger; Cihan Ay Journal: Blood Date: 2017-01-10 Impact factor: 22.113