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Updated: Jul 28, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Predicting the prognosis of breast cancer patients by using pan-immune-inflammation value: a systematic review and
Patricia Diana Prasetiyo1, Alif Rizky Soeratman2, Bernard Agung Baskoro3
1Department of Pathology, Faculty of Medicine, Pelita Harapan University, Tangerang, 15811, Banten, Indonesia. drpdiana@yahoo.com.
Abstract:
Available evidence has unequivocally established the significance of inflammation in the onset and advancement of cancer. Pan-immune-inflammation value (PIV) is an evaluation method that incorporates the role of different white blood cells (WBC) subsets to predict the progression of cancer. The main aim of this study is to assess the feasibility of the PIV score in predicting prognosis among women with breast cancer. A thorough search was performed on the Scopus, Europe PMC, Cochrane Library, and Medline databases up until September 25th, 2024, employing a combination of pertinent keywords. This investigation includes paper that explores the connection of PIV and survival in breast neoplasm. We utilized random-effects models to assess the hazard ratio (HR) and report the results together with their respective 95% confidence intervals (CI). Sixteen papers were chosen for analysis. The findings of our meta-analysis from multivariate data indicated that breast cancer patients who possessed high PIV score had a higher risk of shorter overall survival (OS) (HR 2.22; 95% CI 1.60-3.07, p < 0.00001, I2 = 55%), poorer progression-free survival (PFS) (HR 1.58; 95% CI 1.16-2.15, p = 0.003, I2 = 53%), and lower likelihood of achieving pathological complete response (pCR) (HR 0.45; 95% CI 0.27-0.75, p = 0.002, I2 = 47%) than those with low PIV score. The present review indicates the prognostic ability of PIV score in forecasting the prognosis of breast cancer patients.
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