BACKGROUND: The management of patients with chronic lymphocytic leukaemia is currently undergoing improvements due to novel therapies and a plethora of biological and genetic variables that add prognostic information to the classic clinical staging systems. We established an international consortium with the aim to create an international prognostic index for chronic lymphocytic leukaemia (CLL-IPI) that integrates the major prognostic parameters. METHODS: We used results from a systematic search of the Cochrane Haematological Malignancies Group of MEDLINE, Embase, and Central databases for prospective, clinical phase 2 and 3 trials of chronic lymphocytic leukaemia, published between Jan 1, 1950, and Dec 31, 2010, which identified 13 trials. We contacted the principal investigators of these 13 trials, of which eight agreed to include individual patient data. We used the individual patient data from these phase 3 trials from France, Germany, Poland, the UK, and the USA to create the full analysis dataset. The full analysis dataset was randomly divided, using a random sample procedure, into training and internal-validation datasets. We did a univariate analysis and multivariate analyses using 27 baseline factors and overall survival as an endpoint. We assigned weighted risk scores to each factor included in the final multivariable model. We assessed the discriminatory value using C-statistics and also the validity and reproducibility of the CLL-IPI by subgroup analysis. We used two additional datasets from the Mayo Clinic (Rochester, MN, USA; MAYO cohort) and the SCALE Scandinavian population-based case-control study (SCAN cohort) as the external-validation datasets. FINDINGS: 3472 treatment-naive patients were included in the full analysis dataset; 2308 were randomly segregated into the training dataset and 1164 into the internal-validation dataset. 838 patients were included in the MAYO cohort and 416 in the SCAN cohort. Median age of patients in the full analysis dataset was 61 years (range 27-86). Five independent prognostic factors were identified in the training dataset: TP53 status (no abnormalities vs del[17p] or TP53 mutation or both), IGHV mutational status (mutated vs unmutated), serum β2-microglobulin concentration (≤3·5 mg/L vs >3·5 mg/L), clinical stage (Binet A or Rai 0 vs Binet B-C or Rai I-IV), and age (≤65 years vs >65 years). Using a weighted grading of the independent factors, a prognostic index was derived that identified four risk groups within the training dataset with significantly different overall survival at 5 years: low (93·2% [95% CI 90·5-96·0]), intermediate (79·3% [75·5-83·2]), high (63·3% [57·9-68·8]), and very high risk (23·3% [12·5-34·1]; log-rank test comparing survival across the four risk groups p<0·0001; C-statistic, c=0·723 [95% CI 0·684-0·752]). These risk groups were confirmed in the internal-validation and external-validation datasets. INTERPRETATION: The CLL-IPI combines genetic, biochemical, and clinical parameters into a prognostic model, discriminating four prognostic subgroups. The CLL-IPI will allow a more targeted management of patients with chronic lymphocytic leukaemia in clinical practice and in trials testing novel drugs. FUNDING: José Carreras Leukaemia Foundation.
BACKGROUND: The management of patients with chronic lymphocytic leukaemia is currently undergoing improvements due to novel therapies and a plethora of biological and genetic variables that add prognostic information to the classic clinical staging systems. We established an international consortium with the aim to create an international prognostic index for chronic lymphocytic leukaemia (CLL-IPI) that integrates the major prognostic parameters. METHODS: We used results from a systematic search of the Cochrane Haematological Malignancies Group of MEDLINE, Embase, and Central databases for prospective, clinical phase 2 and 3 trials of chronic lymphocytic leukaemia, published between Jan 1, 1950, and Dec 31, 2010, which identified 13 trials. We contacted the principal investigators of these 13 trials, of which eight agreed to include individual patient data. We used the individual patient data from these phase 3 trials from France, Germany, Poland, the UK, and the USA to create the full analysis dataset. The full analysis dataset was randomly divided, using a random sample procedure, into training and internal-validation datasets. We did a univariate analysis and multivariate analyses using 27 baseline factors and overall survival as an endpoint. We assigned weighted risk scores to each factor included in the final multivariable model. We assessed the discriminatory value using C-statistics and also the validity and reproducibility of the CLL-IPI by subgroup analysis. We used two additional datasets from the Mayo Clinic (Rochester, MN, USA; MAYO cohort) and the SCALE Scandinavian population-based case-control study (SCAN cohort) as the external-validation datasets. FINDINGS: 3472 treatment-naive patients were included in the full analysis dataset; 2308 were randomly segregated into the training dataset and 1164 into the internal-validation dataset. 838 patients were included in the MAYO cohort and 416 in the SCAN cohort. Median age of patients in the full analysis dataset was 61 years (range 27-86). Five independent prognostic factors were identified in the training dataset: TP53 status (no abnormalities vs del[17p] or TP53 mutation or both), IGHV mutational status (mutated vs unmutated), serum β2-microglobulin concentration (≤3·5 mg/L vs >3·5 mg/L), clinical stage (Binet A or Rai 0 vs Binet B-C or Rai I-IV), and age (≤65 years vs >65 years). Using a weighted grading of the independent factors, a prognostic index was derived that identified four risk groups within the training dataset with significantly different overall survival at 5 years: low (93·2% [95% CI 90·5-96·0]), intermediate (79·3% [75·5-83·2]), high (63·3% [57·9-68·8]), and very high risk (23·3% [12·5-34·1]; log-rank test comparing survival across the four risk groups p<0·0001; C-statistic, c=0·723 [95% CI 0·684-0·752]). These risk groups were confirmed in the internal-validation and external-validation datasets. INTERPRETATION: The CLL-IPI combines genetic, biochemical, and clinical parameters into a prognostic model, discriminating four prognostic subgroups. The CLL-IPI will allow a more targeted management of patients with chronic lymphocytic leukaemia in clinical practice and in trials testing novel drugs. FUNDING: José Carreras Leukaemia Foundation.
Authors: Hong Fang; Kaaren K Reichard; Kari G Rabe; Curtis A Hanson; Timothy G Call; Wei Ding; Saad S Kenderian; Eli Muchtar; Susan M Schwager; Jose F Leis; Asher A Chanan-Khan; Susan L Slager; Esteban Braggio; Stephanie A Smoley; Neil E Kay; Tait D Shanafelt; Daniel L Van Dyke; Sameer A Parikh Journal: Am J Hematol Date: 2019-01-08 Impact factor: 10.047
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Authors: Panagiotis Baliakas; Sabine Jeromin; Michalis Iskas; Anna Puiggros; Karla Plevova; Florence Nguyen-Khac; Zadie Davis; Gian Matteo Rigolin; Andrea Visentin; Aliki Xochelli; Julio Delgado; Fanny Baran-Marszak; Evangelia Stalika; Pau Abrisqueta; Kristina Durechova; George Papaioannou; Virginie Eclache; Maria Dimou; Theodoros Iliakis; Rosa Collado; Michael Doubek; M Jose Calasanz; Neus Ruiz-Xiville; Carolina Moreno; Marie Jarosova; Alexander C Leeksma; Panayiotis Panayiotidis; Helena Podgornik; Florence Cymbalista; Achilles Anagnostopoulos; Livio Trentin; Niki Stavroyianni; Fred Davi; Paolo Ghia; Arnon P Kater; Antonio Cuneo; Sarka Pospisilova; Blanca Espinet; Anastasia Athanasiadou; David Oscier; Claudia Haferlach; Kostas Stamatopoulos Journal: Blood Date: 2019-01-02 Impact factor: 22.113