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Flow cytometry in primary breast cancer: improving the prognostic value of the fraction of cells in the S-phase by optimal categorisation of cut-off levels.

The use of continuous prognostic variables is clinically impractical, and arbitrarily chosen cut-off points can result in a loss of prognostic information. Here we report findings from a study of primary breast cancer, showing how the prognostic value of the fraction of cells in the S-phase of the c...

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Detalles Bibliográficos
Autores principales: Sigurdsson, H., Baldetorp, B., Borg, A., Dalberg, M., Fernö, M., Killander, D., Olsson, H., Ranstam, J.
Formato: Texto
Lenguaje:English
Publicado: Nature Publishing Group 1990
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1971535/
https://www.ncbi.nlm.nih.gov/pubmed/2245171
Descripción
Sumario:The use of continuous prognostic variables is clinically impractical, and arbitrarily chosen cut-off points can result in a loss of prognostic information. Here we report findings from a study of primary breast cancer, showing how the prognostic value of the fraction of cells in the S-phase of the cell cycle (SPF), as measured by flow cytometry, can be affected by the SPF cut-off level(s) adopted. It was possible to evaluate the SPF in 566 (94%) of 603 consecutive cases where fresh frozen specimens were available in a tumour bank at our department. Clinically, all patients were without distant spread at the time of diagnosis, and the median duration of follow-up was 4 years. Using different survival end-points and chi 2 values for each cut-off level, two optimal cut-off points, at the 7% and 12% levels, were consistently obtained for the SPF. Furthermore, both disease-free survival and the relative risk of recurrence exhibited a non-linear relationship with SPF values; the curves implied that the prognosis was better among patients with SPF values about 2-5% than in patients with lower SPF values (parabolic shape), though the relationship with higher SPF values approached linearity. The non-linearity of the curves is incompatible with the general use of the median SPF as a prognostic cut-off value. An alternative procedure might be to use two cut-off levels, one to distinguish patients with the lowest SPF values (i.e. within the parabolic survival curve) from those with higher values (i.e. with a survival curve approaching linearity), the other to distinguish between patients with intermediate SPF values and those with high values (i.e. within the almost linear part of the survival curve). The 7% and 12% obtained here would be suitable for this purpose. We conclude that prognostic information can be gained by dividing the SPF into three prognostic categories (less than 7.0%, 7.0-11.9% and greater than or equal to 12%), instead of using the median SPF level.