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Query: UMLS:C0026764 (multiple myeloma)
 36,148 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

In a group of 136 completely followed up patients with multiple myeloma, the prognostic significance of the immunological myeloma types, of 20 different single prognostic factors, of 15 clinical staging systems, and of 6 morphological classifications was retrospectively investigated by means of the calculation of mean survivals, survival curves, and responses to chemotherapy. A univariate analysis was employed in order to correlate each prognostic parameter at presentation with the survival in the whole group; a multivariate analysis according to the Cox's hazards regression model was used in order to select the most powerful prognostic variables. The patients were grouped according to the myeloma immunological types, to the mean value of each single prognostic factor, and to each stage of the clinical and morphological systems. Causes of death were also related to immunological multiple myeloma types. All single variables, except age and serum calcium, presented a significant relationship with the survival, even if at different significance levels. Cox's regression model selected among them, serum levels of beta 2-microglobulin, percentage of bone marrow plasma cells, hemoglobinemia, lytic bone lesions, and Bence-Jones proteinuria as the most significant factors related to survival. Each clinical and morphological staging system divided groups of patients with significant differences in mean survivals, or in survival curves, or in response to therapy. Multiple myeloma type IgA and micromolecular, with Bence-Jones proteinuria, and type lambda were associated with a poor prognosis, with low therapeutical response, and with the development of fatal renal failure. All these parameters, together with new prognostic factors, are useful in the prognostic evaluation, and, when applied in different steps of the diagnosis and the therapy, allow of studying the clinical course of multiple myeloma under different perspectives, in order to have a more complete picture of the disease and of the single patient.
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PMID:Classification and prognostic evaluation in multiple myeloma. A retrospective study of relationship of survivals and responses to chemotherapy to immunological types, 20 single prognostic factors, 15 clinical staging systems, and 6 morphological classifications. 192 60

The prognostic value of the multiple myeloma (MM) immunological type, of 20 different single prognostic variables, of 11 clinical staging systems, and of 6 morphological classification systems was evaluated in 121 patients (71 males and 50 females, 75 MM IgG, 26 MM IgA, and 20 MM micromolecular), who were followed from diagnosis to demise. The values of the prognostic variables related to diagnosis were correlated with survival by means of univariate analysis; multivariate analysis according to Cox's model was employed to select highly-significant parameters correlated with survival among these variables. Every patient was retrospectively staged according to each clinical and morphological system. Mean survivals were computed for each group on the basis of immunological type, mean value of each prognostic factor, clinical and morphological stage. Survival curves were computed and compared. All prognostic parameters showed a significant relationship with survival, even though p-value differed. Multivariate analysis according to Cox's model has indicated the following variables as significantly correlated with survival: bone marrow plasma cell percentage, degree of lytic bone lesions, hemoglobinemia value, and serum levels of beta 2-microglobulin. Each clinical and morphological staging system, as well as immunological types and mean value of single prognostic parameters, have divided patients into separate groups with significant differences in mean survival and in survival curves. All of these factors could be taken into account for correct prognostic evaluation, and, if they were applied in different steps of diagnosis and therapy, it would be possible to study the MM patient under different perspectives, in order to have a more complete picture of the disease and of the patient.
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PMID:[Prognostic evaluation in multiple myeloma. Relationship between immunological types, single prognostic factors, clinical staging systems, morphological classification systems and survival]. 228 22

The relationship between initial percentage of bone marrow plasma cells and survival was studied in a group of 70 patients affected with multiple myeloma. All patients had a complete follow-up. The initial percentage of plasma cells shows a highly significant correlation with survival. Moreover, the percentage of bone marrow plasma cells is also correlated with the levels of hemoglobinemia and serum or urinary monoclonal component. The patients were divided in three groups according to the percentage of bone marrow plasma cells: group A: less than 20%; group B: 21-40%; group C: greater than 41%. The mean survival times of these three groups are significantly different, as well as their survival curves. The initial percentage of plasma cells in bone marrow is an useful parameter for estimating survival and predicting prognosis, and it can be an additional factor in the clinical staging of multiple myeloma, while the effectiveness of therapy can be monitored by sequential bone marrow aspirates.
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PMID:[Prognostic value of the ratio of bone marrow plasma cells in multiple myeloma]. 232 Feb 80

A new simple scoring staging system was developed and evaluated in 121 cases of multiple myeloma, followed from first diagnosis to demise. A score of 1 was assigned to each of the following features: bone marrow plasma cells more than 30%, hemoglobinemia less than 11 g/dl, lytic bone lesions of degrees 2-3, presence of Bence Jones proteinuria and serum beta 2-microglobulin levels higher than 8.0 micrograms/ml. Therefore, the score for each patient ranged from 0 to 5, corresponding to six risk classes: score 0 = class I; score 1 = class II; score 2 = class III; score 3 = class IV; score 4 = class V; score 5 = class VI. Since no differences in mean survivals and in survival curves were found between classes I and II, between classes III and IV and between classes V and VI, three stages could be devised: stage A (good prognosis) corresponding to classes I and II; stage B (intermediate prognosis) corresponding to classes III and IV; stage C (poor prognosis) corresponding to classes V and VI. Significant differences were found among the three stages regarding mean survivals, survival curves, and response to treatment. This scoring staging system is very simple in its formulation; only five routine parameters and no calculations are necessary for obtaining a score and consequently a stage for each patient. Moreover, the system can identify categories of multiple myeloma patients with homogeneous characteristics since it appears to be correlated with response to treatment and survival.
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PMID:[Proposal of a new staging system using scoring of multiple myeloma]. 263 28

The pretreatment characteristics of 210 patients with multiple myeloma, observed between 1980 and 1994, were evaluated as potential prognostic factors for survival. Multivariate analysis according to Cox's proportional hazard model identified in the 160 dead patients with myeloma, among 26 different single prognostic variables, the following factors in order of importance: beta 2-microglobulin; bone marrow plasma cell percentage, hemoglobinemia, degree of lytic bone lesions, serum creatinine, and serum albumin. By analysis of these variables a prognostic index (PI), that considers the regression coefficients derived by Cox's model of all significant factors, was obtained. Using this it was possible to separate the whole patient group into three stages: stage I (PI < 1.485, 67 patients), stage II (PI: 1.485-2.090, 76 patients), and stage III (PI > 2.090, 67 patients), with a median survivals of 68, 36 and 13 months (P < 0.0001), respectively. Also the responses to therapy (P < 0.0001) and the survival curves (P < 0.00001) presented significant differences among the three subgroups. Knowledge of these factors could be of value in predicting prognosis and in planning therapy in patients with multiple myeloma.
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PMID:Prognostic factors in multiple myeloma: selection using Cox's proportional hazard model. 867 29