ArticleCancer management and research2026
Ki-67 and Platelet-to-Lymphocyte Ratio (PLR) as Predictors of Progression-Free Survival in Metastatic Breast Cancer Receiving CDK4/6 Inhibitors: Clinical Implications.
Article in Cancer management and research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: We aimed to investigate the prognostic power of Platelet-to-Lymphocyte Ratio (PLR) and Ki-67 index in predicting progression-free survival (PFS) in patients with metastatic HR+/HER2- breast cancer treated with CDK4/6 inhibitors. Materials and Methods: In this retrospective study, 121 patients who received CDK4/6 inhibitors (palbociclib, ribociclib) at the Department of Medical Oncology, Dokuz Eylul University, between January 2015 and January 2025, were analyzed. PLR was calculated using baseline complete blood count parameters. The optimal cut-off value of 168.37 was determined using ROC analysis, and patients were stratified into low and high PLR groups. Survival analyses were performed using the Kaplan-Meier method and Cox regression. Results: A lower progression rate was observed in the high PLR group (p=0.01), although PLR was not identified as an independent prognostic factor for PFS in multivariate analysis. Patients with lung metastases showed a higher proportion of low PLR (p=0.04).Although PLR was associated with PFS in univariate analysis, it did not retain independent prognostic significance in multivariate analysis.Conversely, Ki-67 was significantly associated with shorter PFS in both univariate (p<0.001) and multivariate analyses (p=0.007). Conclusion: While PLR did not independently predict survival outcomes, it may provide complementary information regarding metastatic distribution and disease behavior. Ki-67 remains a strong and independent prognostic marker for PFS in metastatic HR+/HER2- breast cancer. Our findings indicate that Ki-67 is the strongest and most consistent independent prognostic marker in this patient population.
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