Hacene K, Desplaces A, Brunet M, Lidereau R, Bourguignat A, Oglobine J. Competitive prognostic value of clinicopathologic and bioimmunologic factors in primary breast cancer.
Cancer 1986;
57:245-50. [PMID:
3484657 DOI:
10.1002/1097-0142(19860115)57:2<245::aid-cncr2820570210>3.0.co;2-2]
[Citation(s) in RCA: 14] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Fourteen clinical, pathologic, and pretreatment bioimmunologic variables were evaluated for their significance in predicting the survival or the length of disease-free interval of 55 patients with primary breast cancer. The variables studied were: patient age; clinical stage of disease according to the International Union Against Cancer TNM classification; number of involved nodes; sedimentation rate; peripheral lymphocyte, leucocyte, and monocyte counts; serum levels of immunoglobulins IgG, IgA, and IgM; percentages of E-, "active" E-, and EAC-rosettes; and finally, the lymphoblastic transformation test value (PHA-LTT). A multivariate analysis using the Cox proportional hazards regression model was carried out, in a stepwise manner, to identify those variables most highly related to survival or to the length of disease-free interval. The Cox analysis showed that clinical stage, number of involved nodes, percentage of EAC-rosettes, sedimentation rate, and T-lymphocyte reactivity, (i.e., the T-lymphocyte sensitivity to PHA, expressed as the ratio between the PHA-LTT in counts per minute and the percentage of E-rosettes) were the significant prognostic factors for survival, whereas the number of involved nodes and the sedimentation rate were independent of importance in predicting the length of disease-free interval. The results obtained from this analysis proved the importance of some immunologic parameters in the estimation of prognosis. In addition, a prognostic score for summarizing multiple factors with potential use in stratification was derived from the multivariate analysis.
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