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  • Title: A comparison of proliferation markers and their prognostic value for women with endometrial carcinoma. Ki-67, proliferating cell nuclear antigen, and flow cytometric S-phase fraction.
    Author: Nordström B, Strang P, Bergström R, Nilsson S, Tribukait B.
    Journal: Cancer; 1996 Nov 01; 78(9):1942-51. PubMed ID: 8909315.
    Abstract:
    BACKGROUND: The understanding of proliferation is a central issue in oncology. Several methods exist for the assessment of the growth fraction and cell-cycle time, but comparative studies that give the clinician advice about the most reliable use of new markers are few. The aim of the current study was to perform methodologic, descriptive, comparative, and prognostic studies of Ki-67, proliferating cell nuclear antigen (PCNA), and flow cytometric S-phase fraction (SPF) in endometrial carcinoma. METHODS: The expression of Ki 67 (n = 175) and PCNA (n = 146) were studied immunohistochemically; and the SPF (n = 297) by flow cytometry. The median follow-up time was 78 months. RESULTS: Neither Ki-67 nor PCNA had any correlation to either the stage or the histopathologic subtype of the tumors, but they were covariant with the histopathologic grade (P < 0.05). There was an interrelationship between Ki-67 and PCNA (P < 0.001), and both were associated with the size of the SPF (P < 0.0001 and P < 0.05, respectively). Mean SPF was high in advanced stages and strongly associated with histopathologic subtype (P < 0.0001) and ploidy (P < 0.0001). Tumors with strong Ki-67 expression were more often aneuploid (P < 0.01). In initial analyses, Ki-67 and SPF were predictors of poor survival (P < 0.05 and P < 0.001, respectively), whereas PCNA was not. When SPF was added to a comprehensive multivariate model, Ki-67 provided no further prognostic information, whereas SPF remained a powerful predictor of survival. CONCLUSIONS: Ki-67 and, to a lesser extent, PCNA, give approximate estimates of the growth fraction, whereas SPF only reflects the proportion of cells in S-phase. However, SPF is by far the strongest predictor of survival.
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