D Hasenclever1, V Diehl. 1. Institute of Medical Informatics, Statistics and Epidemiology, University of Leipzig, Germany.
Abstract
BACKGROUND: Two thirds of patients with advanced Hodgkin's disease are cured with current approaches to treatment. Prediction of the outcome is important to avoid overtreating some patients and to identify others in whom standard treatment is likely to fail. METHODS: Data were collected from 25 centers and study groups on a total of 5141 patients treated with combination chemotherapy for advanced Hodgkin's disease, with or without radiotherapy. The data included the outcome and 19 demographic and clinical characteristics at diagnosis. The end point was freedom from progression of disease. Complete data were available for 1618 patients; the final Cox model was fitted to these data. Data from an additional 2643 patients were used for partial validation. RESULTS: The prognostic score was defined as the number of adverse prognostic factors present at diagnosis. Seven factors had similar independent prognostic effects: a serum albumin level of less than 4 g per deciliter, a hemoglobin level of less than 10.5 g per deciliter, male sex, an age of 45 years or older, stage IV disease (according to the Ann Arbor classification), leukocytosis (a white-cell count of at least 15,000 per cubic millimeter), and lymphocytopenia (a lymphocyte count of less than 600 per cubic millimeter, a count that was less than 8 percent of the white-cell count, or both). The score predicted the rate of freedom from progression of disease as follows: 0, or no factors (7 percent of the patients), 84 percent; 1 (22 percent of the patients), 77 percent; 2 (29 percent of the patients), 67 percent; 3 (23 percent of the patients), 60 percent; 4 (12 percent of the patients), 51 percent; and 5 or higher (7 percent of the patients), 42 percent. CONCLUSIONS: The prognostic score we developed may be useful in designing clinical trials for the treatment of advanced Hodgkin's disease and in making individual therapeutic decisions, but a distinct group of patients at very high risk could not be identified on the basis of routinely documented demographic and clinical characteristics.
BACKGROUND: Two thirds of patients with advanced Hodgkin's disease are cured with current approaches to treatment. Prediction of the outcome is important to avoid overtreating some patients and to identify others in whom standard treatment is likely to fail. METHODS: Data were collected from 25 centers and study groups on a total of 5141 patients treated with combination chemotherapy for advanced Hodgkin's disease, with or without radiotherapy. The data included the outcome and 19 demographic and clinical characteristics at diagnosis. The end point was freedom from progression of disease. Complete data were available for 1618 patients; the final Cox model was fitted to these data. Data from an additional 2643 patients were used for partial validation. RESULTS: The prognostic score was defined as the number of adverse prognostic factors present at diagnosis. Seven factors had similar independent prognostic effects: a serum albumin level of less than 4 g per deciliter, a hemoglobin level of less than 10.5 g per deciliter, male sex, an age of 45 years or older, stage IV disease (according to the Ann Arbor classification), leukocytosis (a white-cell count of at least 15,000 per cubic millimeter), and lymphocytopenia (a lymphocyte count of less than 600 per cubic millimeter, a count that was less than 8 percent of the white-cell count, or both). The score predicted the rate of freedom from progression of disease as follows: 0, or no factors (7 percent of the patients), 84 percent; 1 (22 percent of the patients), 77 percent; 2 (29 percent of the patients), 67 percent; 3 (23 percent of the patients), 60 percent; 4 (12 percent of the patients), 51 percent; and 5 or higher (7 percent of the patients), 42 percent. CONCLUSIONS: The prognostic score we developed may be useful in designing clinical trials for the treatment of advanced Hodgkin's disease and in making individual therapeutic decisions, but a distinct group of patients at very high risk could not be identified on the basis of routinely documented demographic and clinical characteristics.
Authors: I Ionescu; P Brice; D Simon; A Guermazi; T Leblanc; P Rousselot; D Gossot; V Meignin; C Gisselbrecht; J D Rain Journal: Med Oncol Date: 2000-05 Impact factor: 3.064
Authors: Anas Younes; Yasuhiro Oki; Peter McLaughlin; Amanda R Copeland; Andre Goy; Barbara Pro; Lei Feng; Ying Yuan; Hubert H Chuang; Homer A Macapinlac; Fredrick Hagemeister; Jorge Romaguera; Felipe Samaniego; Michelle A Fanale; Bouthaina Shbib Dabaja; Maria A Rodriguez; Nam Dang; Larry W Kwak; Sattva S Neelapu; Luis E Fayad Journal: Blood Date: 2012-02-27 Impact factor: 22.113
Authors: Luis F Porrata; Kay Ristow; Joseph P Colgan; Thomas M Habermann; Thomas E Witzig; David J Inwards; Stephen M Ansell; Ivana N Micallef; Patrick B Johnston; Grzegorz S Nowakowski; Carrie Thompson; Svetomir N Markovic Journal: Haematologica Date: 2011-10-11 Impact factor: 9.941