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      A laboratory-based scoring system predicts early treatment in Rai 0 chronic lymphocytic leukemia

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          Abstract

          We present a laboratory-based prognostic calculator (designated CRO score) to risk stratify treatment-free survival in early stage (Rai 0) chronic lymphocytic leukemia (CLL) developed using a training-validation model in a series of 1,879 cases from Italy, the United Kingdom and the United States. By means of regression analysis, we identified five prognostic variables with weighting as follows: deletion of the short arm of chromosome 17 and unmutated immunoglobulin heavy chain gene status, 2 points; deletion of the long arm of chromosome 11, trisomy of chromosome 12, and white blood cell count >32.0x10 3/microliter, 1 point. Low-, intermediate- and high-risk categories were established by recursive partitioning in a training cohort of 478 cases, and then validated in four independent cohorts of 144 / 395 / 540 / 322 cases, as well as in the composite validation cohort. Concordance indices were 0.75 in the training cohort and ranged from 0.63 to 0.74 in the four validation cohorts (0.69 in the composite validation cohort). These findings advocate potential application of our novel prognostic calculator to better stratify early-stage CLL, and aid case selection in risk-adapted treatment for early disease. Furthermore, they support immunocytogenetic analysis in Rai 0 CLL being performed at the time of diagnosis to aid prognosis and treatment, particularly in today’s chemofree era.

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          Most cited references27

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          Precision oncology for acute myeloid leukemia using a knowledge bank approach

          Peter Campbell, Hartmut Döhner and colleagues present an analysis of genetic mutations and clinical information from 1,540 patients with acute myeloid leukemia, demonstrating the utility of clinical knowledge banks for personalized medicine. They show that use of their approach could reduce the number of hematopoietic cell transplants in patients with AML by up to 25% while maintaining survival rates.
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            Prognostic nomogram and index for overall survival in previously untreated patients with chronic lymphocytic leukemia.

            The clinical course for patients with chronic lymphocytic leukemia is extremely heterogeneous. The Rai and Binet staging systems have been used to risk-stratify patients; most patients present with early-stage disease. We evaluated a group of previously untreated patients with chronic lymphocytic leukemia (CLL) at initial presentation to University of Texas M. D. Anderson Cancer Center to identify independent characteristics that predict for overall survival. Clinical and routine laboratory characteristics for 1674 previously untreated patients who presented for evaluation of CLL from 1981 to 2004 were included. Univariate and multivariate analyses identified several patient characteristics at presentation that predicted for overall survival in previously untreated patients with CLL. A multivariate Cox proportional hazards model was developed, including the following independent characteristics: age, beta-2 microglobulin, absolute lymphocyte count, sex, Rai stage, and number of involved lymph node groups. Inclusion of patients from a single institution and the proportion of patients younger than 65 years may limit this model. A weighted prognostic model, or nomogram, predictive for overall survival was constructed using these 6 characteristics for 5- and 10-year survival probability and estimated median survival time. This prognostic model may help patients and clinicians in clinical decision making as well as in clinical research and clinical trial design.
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              Development of a comprehensive prognostic index for patients with chronic lymphocytic leukemia.

              In addition to clinical staging, a number of biomarkers predicting overall survival (OS) have been identified in chronic lymphocytic leukemia (CLL). The multiplicity of markers, limited information on their independent prognostic value, and a lack of understanding of how to interpret discordant markers are major barriers to use in routine clinical practice. We therefore performed an analysis of 23 prognostic markers based on prospectively collected data from 1948 CLL patients participating in phase 3 trials of the German CLL Study Group to develop a comprehensive prognostic index. A multivariable Cox regression model identified 8 independent predictors of OS: sex, age, ECOG status, del(17p), del(11q), IGHV mutation status, serum β2-microglobulin, and serum thymidine kinase. Using a weighted grading system, a prognostic index was derived that separated 4 risk categories with 5-year OS ranging from 18.7% to 95.2% and having a C-statistic of 0.75. The index stratified OS within all analyzed subgroups, including all Rai/Binet stages. The validity of the index was externally confirmed in a series of 676 newly diagnosed CLL patients from Mayo Clinic. Using this multistep process including external validation, we developed a comprehensive prognostic index with high discriminatory power and prognostic significance on the individual patient level. The studies were registered as follows: CLL1 trial (NCT00262782, http://clinicaltrials.gov), CLL4 trial (ISRCTN 75653261, http://www.controlled-trials.com), and CLL8 trial (NCT00281918, http://clinicaltrials.gov).
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                Author and article information

                Journal
                Haematologica
                Haematologica
                haematol
                Haematologica
                Haematologica
                Ferrata Storti Foundation
                0390-6078
                1592-8721
                June 2020
                03 October 2019
                : 105
                : 6
                : 1613-1620
                Affiliations
                [1 ]Clinical and Experimental Onco-Haematology Unit, Centro di Riferimento Oncologico, I.R.C.C.S., Aviano (PN), Italy
                [2 ]Institute of Oncology Research, Bellinzona, Switzerland
                [3 ]Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
                [4 ]Immunopathology and Cancer Biomarkers, Centro di RiferimentoOncologico, I.R.C.C.S., Aviano (PN), Italy
                [5 ]Unit of Cancer Epidemiology, Centro di Riferimento Oncologico, I.R.C.C.S., Aviano (PN), Italy
                [6 ]Division of Haematology, S. Eugenio Hospital and University of Tor Vergata, Rome, Italy
                [7 ]Hematology Institute, Catholic University of the Sacred Heart, Fondazione Policlinico A. Gemelli, Rome, Italy
                [8 ]UO Molecular Pathology, Ospedale Policlinico San Martino IRCCS, Genova, Italy
                [9 ]Onco-Haematology Department, Centro di Riferimento Oncologico della Basilicata, I.R.C.C.S., Rionero in Vulture, Italy
                [10 ]Department of Internal Medicine and Haematology, Maggiore General Hospital, University of Trieste, Trieste, Italy
                [11 ]Division of Haematology, Ferrarotto Hospital, Catania, Italy
                [12 ]Hematology, Oncology Institute of Southern Switzerland, Bellinzona, Switzerland
                [13 ]Universita’ della Svizzera Italiana, Lugano, Switzerland
                [14 ]Hematology Unit, AO, Cosenza, Italy
                [15 ]Biotechnology Research Unit, Aprigliano, Cosenza, Italy
                [16 ]Hematogy Department and Bone Marrow Transplant Unit, Cancer Care Center, Augusta Victoria Hospital, East Jerusalem, Israel
                [17 ]Hematology Unit, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico and University of Milan, Milan, Italy
                [18 ]Department of Experimental Medicine, University of Genova, Genova, Italy
                [19 ]Division of Cancer and Genetics, Cardiff University, School of Medicine, Heath Park, Cardiff, UK
                [20 ]University of Sussex, Brighton and Sussex Medical School, Brighton, UK
                [21 ]Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, USA
                Author notes
                Correspondence: JARED A. COHEN, jcoen781@ 123456gmail.com
                Correspondence: VALTER GATTEI, vgattei@ 123456cro.it
                Article
                1051613
                10.3324/haematol.2019.228171
                7271568
                31582547
                f684abbe-7a2d-4c2c-b80a-e10e8b0dfc51
                Copyright© 2020 Ferrata Storti Foundation

                Material published in Haematologica is covered by copyright. All rights are reserved to the Ferrata Storti Foundation. Use of published material is allowed under the following terms and conditions:

                https://creativecommons.org/licenses/by-nc/4.0/legalcode. Copies of published material are allowed for personal or internal use. Sharing published material for non-commercial purposes is subject to the following conditions:

                https://creativecommons.org/licenses/by-nc/4.0/legalcode, sect. 3. Reproducing and sharing published material for commercial purposes is not allowed without permission in writing from the publisher.

                History
                : 03 June 2019
                : 02 October 2019
                Categories
                Articles
                Chronic Lymphocytic Leukemia

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