Abstract PS6-57: Association of the prognostic nutritional index and survival of patients with breast cancer in a third-level care hospital in Mexico

Abstract

Introduction. The prognostic nutritional index (PNI) is a convenient and accessible tool that reflects the nutritional and immunological conditions of patients with solid tumors. PNI is calculated based on the total lymphocyte count and serum albumin level. There is not an optimal well established cutoff value. Low PNI has been associated with lower overall and disease-free survival (OS and DFS) in breast cancer patients, however, there is no information regarding this prognostic value in patients from Mexico. The aim of this study was to analyze the association between PNI and survival of breast cancer patients from Mexico. Methods. We retrospectively analyzed medical records of patients with histologically confirmed breast cancer treated at Medica Sur Oncology Center in Mexico City between January 2008 to December 2019. PNI was calculated using the following formula: 10 × serum albumin value (g/dL) + 0.005 × total lymphocyte count (mm3). Receiver operating characteristic (ROC) curve analysis was performed to determine the optimal PNI cutoff value. The primary endpoint was OS. The secondary endpoint was DFS. Statistical analysis was performed with SPSS v25, the associations between PNI and clinicopathologic characteristics were analyzed using Pearson's χ2 test, survival curves were calculated with Kaplan-Meier method, and comparison among groups with log-rank. Proportional Cox model was used to perform multivariate analysis. A p value <0.05 was significant. Results. A total of 110 patients were included in the analysis, and classified into two groups: low and high PNI (ROC curve analysis showed an optimal cutoff value of 32.1). Median follow-up was 65 months. Mean PNI at diagnosis was 39.3 (SD 6.7). All patients had infiltrating ductal carcinoma, 15.5% had metastatic disease, 18.2% had triple negative breast cancer, 23.6% had HER 2 overexpression, and around 51% where positive for hormone receptors. Mean PNI in patients with locally advanced disease was significantly lower than in patients with localized disease, (p= 0.044), no other statistically significant associations were found between mean PNI and clinical characteristics. Median OS was not reached in the high PNI group vs 48.5 months (mo) in the low PNI group, while 5 -year OS rates were 89% and 41%, respectively (p= 0.03). The high PNI group had better DFS than the low PNI group (median DFS 65 mo vs 22.5 mo, 5-year DFS rates 65% vs 45% (p = 0.024). In univariate and multivariate analysis, triple negative histological subtype and low PNI were independent prognostic indicators for poor survival. Conclusion. High PNI in breast cancer patients is associated with superior DFS and OS. PNI is an independent prognostic factor for DFS and OS. PNI is an accessible prognosis factor that uses only regular laboratory assessment in patients with cancer. Citation Format: Pamela Denisse Soberanis-Piña, Edgar Varela-Santoyo, Andres Mauricio Arroyave-Ramirez, Hector Hugo Buerba-Vieregge, Daniel Motola-Kuba. Association of the prognostic nutritional index and survival of patients with breast cancer in a third-level care hospital in Mexico [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS6-57.

Low pretreatment prognostic nutritional index predicts poor survival in breast cancer patients: A meta-analysis

“…Flow chart diagram of study selection was shown in Fig 1 . Eight studies with 2322 patients were finally included in this meta-analysis [3,[8][9][10][15][16][17][18]. And all these studies were scored 6 or above after careful evaluation with the Newcastle-Ottawa Scale (NOS).…”

The role of nutrition-based index in predicting survival of breast cancer patients: A systematic review and meta-analysis

“…First, Hu G et al [ 45 ] conducted an earlier meta-analysis that included a total of 8 studies, with information on 6 studies that focused on OS analysis and 5 studies that focused on DFS analysis. Of these 8 studies, there was 1 study by Soberanis-Pina PD et al [ 46 ], which was published in the form of an abstract. Although listed in the table of characteristics of the included studies, the study by Soberanis-Pina PD et al [ 46 ] was not discussed further at all nor included in the meta-analysis.…”

“…Of these 8 studies, there was 1 study by Soberanis-Pina PD et al [ 46 ], which was published in the form of an abstract. Although listed in the table of characteristics of the included studies, the study by Soberanis-Pina PD et al [ 46 ] was not discussed further at all nor included in the meta-analysis. There is no clear reason why one study in the form of an abstract was still included.…”