Abstract

ObjectiveThe existing Central Nervous System-International Prognostic Index (CNS-IPI) provides insufficient guidance for predicting central nervous system (CNS) relapse in individuals with primary breast diffuse large B-cell lymphoma (DLBCL). This retrospective cohort study sought to examine the potential of the stage-modified IPI in predicting CNS relapse within this specific patient population. Patients and methodsWe examined the baseline characteristics of 76 consecutive patients diagnosed with primary breast DLBCL, calculating the stage-modified IPI score for each individual. Utilizing a competing risk regression (CRR) model, we conducted both univariate and multivariate analyses to explore the relationship between potential prognostic factors and the occurrence of CNS relapse. ResultsIn our cohort, the rates of CNS disease at 2 and 5 years since the diagnosis of primary breast DLBCL are 3.9% and 7.8%, respectively. Among patients experiencing CNS relapse, 80% presented with a parenchymal brain mass. Individuals with a high stage-modified IPI score (1–3 points) had a significantly higher incidence of CNS relapse (p = 0.031), a shorter time from the initial diagnosis of primary breast DLBCL to the first CNS relapse (p = 0.010), as well as relapse at any site (p = 0.012), compared to those with a low score (0 points). Univariate analysis identified stage (Hazard Ratio (HR): 4.098, p = 0.024), stage-modified IPI score (HR: 11.582, p = 0.012), and radiation therapy (HR: 5.784, p = 0.026) as significant risk factors. In multivariate analysis, in addition to radiation therapy (HR: 7.258, p = 0.012), the stage-modified IPI score (1–3 points versus 0 points) emerged as an independent and reliable predictor for CNS relapse (HR: 12.945, p = 0.016). ConclusionOur study underscores the significance of stage-modified IPI scores in predicting CNS relapse for patients with primary breast DLBCL. Validation of these findings through further research is essential, along with exploring potential prevention and intervention approaches.

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