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Prognostic factors and classification in multiple myeloma.

Analyses of prognostic factors have allowed the design of staging systems in different haematological disorders. In a series of 220 patients with multiple myeloma, univariate analysis showed that nine parameters had a significant adverse effect on survival; poor performance status (Karnowsky scaling...

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Autores principales: San Miguel, J. F., Sànchez, J., Gonzalez, M.
Formato: Texto
Lenguaje:English
Publicado: Nature Publishing Group 1989
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2246952/
https://www.ncbi.nlm.nih.gov/pubmed/2757917
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author San Miguel, J. F.
Sànchez, J.
Gonzalez, M.
author_facet San Miguel, J. F.
Sànchez, J.
Gonzalez, M.
author_sort San Miguel, J. F.
collection PubMed
description Analyses of prognostic factors have allowed the design of staging systems in different haematological disorders. In a series of 220 patients with multiple myeloma, univariate analysis showed that nine parameters had a significant adverse effect on survival; poor performance status (Karnowsky scaling system less than 70%), infections before diagnosis, renal impairment (assessed either by creatinine clearance greater than 2 mg dl-1 or urea greater than 40 mg dl-1), serum calcium (greater than 10 mg dl-1), severe anaemia (less than 8.5 g dl-1), the presence of Bence-Jones proteinuria, failure to achieve complete remission, more than 40% plasma cells in bone marrow and a low paraprotein index (monoclonal component/% plasma cells: P less than 0.09). In addition, this index correlated significantly with all the other prognostic factors except performance status. The best combination of disease characteristics selected by means of the Cox regression proportional hazards method were performance status and creatinine levels. Additionally, by factor analysis of principal components we obtained a regression equation that included creatinine levels, haemoglobin, performance status and paraprotein index. Using this it was possible to separate the series of patients into three risk categories: A (65 patients), B (69 patients) and C (65 patients) with a median survival of 41, 24 and 12 months, respectively. The model provided similar results to those of the British Medical Research Council, whereas the staging systems proposed by Durie and Salmon, Merlin et al. and Carbone et al. had a lower discriminant value in our series.
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spelling pubmed-22469522009-09-10 Prognostic factors and classification in multiple myeloma. San Miguel, J. F. Sànchez, J. Gonzalez, M. Br J Cancer Research Article Analyses of prognostic factors have allowed the design of staging systems in different haematological disorders. In a series of 220 patients with multiple myeloma, univariate analysis showed that nine parameters had a significant adverse effect on survival; poor performance status (Karnowsky scaling system less than 70%), infections before diagnosis, renal impairment (assessed either by creatinine clearance greater than 2 mg dl-1 or urea greater than 40 mg dl-1), serum calcium (greater than 10 mg dl-1), severe anaemia (less than 8.5 g dl-1), the presence of Bence-Jones proteinuria, failure to achieve complete remission, more than 40% plasma cells in bone marrow and a low paraprotein index (monoclonal component/% plasma cells: P less than 0.09). In addition, this index correlated significantly with all the other prognostic factors except performance status. The best combination of disease characteristics selected by means of the Cox regression proportional hazards method were performance status and creatinine levels. Additionally, by factor analysis of principal components we obtained a regression equation that included creatinine levels, haemoglobin, performance status and paraprotein index. Using this it was possible to separate the series of patients into three risk categories: A (65 patients), B (69 patients) and C (65 patients) with a median survival of 41, 24 and 12 months, respectively. The model provided similar results to those of the British Medical Research Council, whereas the staging systems proposed by Durie and Salmon, Merlin et al. and Carbone et al. had a lower discriminant value in our series. Nature Publishing Group 1989-01 /pmc/articles/PMC2246952/ /pubmed/2757917 Text en https://creativecommons.org/licenses/by/4.0/This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/.
spellingShingle Research Article
San Miguel, J. F.
Sànchez, J.
Gonzalez, M.
Prognostic factors and classification in multiple myeloma.
title Prognostic factors and classification in multiple myeloma.
title_full Prognostic factors and classification in multiple myeloma.
title_fullStr Prognostic factors and classification in multiple myeloma.
title_full_unstemmed Prognostic factors and classification in multiple myeloma.
title_short Prognostic factors and classification in multiple myeloma.
title_sort prognostic factors and classification in multiple myeloma.
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2246952/
https://www.ncbi.nlm.nih.gov/pubmed/2757917
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