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pubmed:abstractText |
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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