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Dynamic Risk Profiling Using Serial Tumor Biomarkers for Personalized Outcome Prediction.
Kurtz, David M; Esfahani, Mohammad S; Scherer, Florian; Soo, Joanne; Jin, Michael C; Liu, Chih Long; Newman, Aaron M; Dührsen, Ulrich; Hüttmann, Andreas; Casasnovas, Olivier; Westin, Jason R; Ritgen, Matthais; Böttcher, Sebastian; Langerak, Anton W; Roschewski, Mark; Wilson, Wyndham H; Gaidano, Gianluca; Rossi, Davide; Bahlo, Jasmin; Hallek, Michael; Tibshirani, Robert; Diehn, Maximilian; Alizadeh, Ash A.
Afiliación
  • Kurtz DM; Division of Oncology, Department of Medicine, Stanford University, Stanford, CA, USA; Division of Hematology, Department of Medicine, Stanford University, Stanford, CA, USA; Department of Bioengineering, Stanford University, Stanford, CA, USA.
  • Esfahani MS; Division of Oncology, Department of Medicine, Stanford University, Stanford, CA, USA.
  • Scherer F; Division of Oncology, Department of Medicine, Stanford University, Stanford, CA, USA.
  • Soo J; Division of Oncology, Department of Medicine, Stanford University, Stanford, CA, USA.
  • Jin MC; Division of Oncology, Department of Medicine, Stanford University, Stanford, CA, USA.
  • Liu CL; Division of Oncology, Department of Medicine, Stanford University, Stanford, CA, USA.
  • Newman AM; Division of Oncology, Department of Medicine, Stanford University, Stanford, CA, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA.
  • Dührsen U; Department of Hematology, University Hospital Essen, Essen, Germany.
  • Hüttmann A; Department of Hematology, University Hospital Essen, Essen, Germany.
  • Casasnovas O; Department of Hematology, Hopital F. Mitterrand, CHU Dijon and INSERM 1231, Dijon, France.
  • Westin JR; Department of Lymphoma/Myeloma, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Ritgen M; Department II of Internal Medicine, Campus Kiel, University of Schleswig-Holstein, Kiel, Germany.
  • Böttcher S; Department III of Internal Medicine, University Hospital Rostock, Rostock, Germany.
  • Langerak AW; Department of Immunology, Laboratory Medical Immunology, Erasmus MC, Rotterdam, the Netherlands.
  • Roschewski M; Lymphoid Malignancies Branch, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, USA.
  • Wilson WH; Lymphoid Malignancies Branch, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, USA.
  • Gaidano G; Division of Hematology, Department of Translational Medicine, University of Eastern Piedmont, Novara, Italy.
  • Rossi D; Hematology, Oncology Institute of Southern Switzerland and Institute of Oncology Research, Bellinzona, Switzerland.
  • Bahlo J; German CLL Study Group, Department I of Internal Medicine and Center of Integrated Oncology Cologne Bonn, University Hospital of Cologne, Cologne, Germany.
  • Hallek M; German CLL Study Group, Department I of Internal Medicine and Center of Integrated Oncology Cologne Bonn, University Hospital of Cologne, Cologne, Germany; Cologne Cluster of Excellence on Cellular Stress Responses in Aging-Related Diseases (CECAD), University of Cologne, Cologne, Germany.
  • Tibshirani R; Department Statistics, Stanford University, Stanford, CA, USA; Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
  • Diehn M; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA; Stanford Cancer Institute, Stanford University, Stanford, CA, USA; Department of Radiation Oncology, Stanford University, Stanford, CA, USA. Electronic address: diehn@stanford.edu.
  • Alizadeh AA; Division of Oncology, Department of Medicine, Stanford University, Stanford, CA, USA; Division of Hematology, Department of Medicine, Stanford University, Stanford, CA, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA; Stanford Cancer Institute,
Cell ; 178(3): 699-713.e19, 2019 07 25.
Article en En | MEDLINE | ID: mdl-31280963
Accurate prediction of long-term outcomes remains a challenge in the care of cancer patients. Due to the difficulty of serial tumor sampling, previous prediction tools have focused on pretreatment factors. However, emerging non-invasive diagnostics have increased opportunities for serial tumor assessments. We describe the Continuous Individualized Risk Index (CIRI), a method to dynamically determine outcome probabilities for individual patients utilizing risk predictors acquired over time. Similar to "win probability" models in other fields, CIRI provides a real-time probability by integrating risk assessments throughout a patient's course. Applying CIRI to patients with diffuse large B cell lymphoma, we demonstrate improved outcome prediction compared to conventional risk models. We demonstrate CIRI's broader utility in analogous models of chronic lymphocytic leukemia and breast adenocarcinoma and perform a proof-of-concept analysis demonstrating how CIRI could be used to develop predictive biomarkers for therapy selection. We envision that dynamic risk assessment will facilitate personalized medicine and enable innovative therapeutic paradigms.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Biomarcadores de Tumor / Linfoma de Células B Grandes Difuso / Medicina de Precisión Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: Cell Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Biomarcadores de Tumor / Linfoma de Células B Grandes Difuso / Medicina de Precisión Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: Cell Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos