ArticleScientific reports2024
Pan-immune-inflammation value and survival in patients with breast cancer from a Peruvian reference hospital.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predicting the prognosis of breast cancer patients by using pan-immune-inflammation value: a systematic review and meta-analysis.Scientific reports · 2025Pooled it
- Integrating pan-immune-inflammation value into personalized survival prediction of nasopharyngeal carcinoma: a large-scale long-term retrospective study.BMC cancer · 2025Article
- Pan-immune-inflammation value and mortality in the US adult MASLD: a nonlinear NHANES analysis.BMC gastroenterology · 2025Article
- Pan-Immune-Inflammation Value as a Prognostic Biomarker for Hepatocellular Carcinoma Patients Undergoing Hepatectomy.Journal of inflammation research · 2025Article
- High Pan-Immune Inflammation Values are Associated with Prolonged Length of Hospital Stay in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease.International journal of general medicine · 2025Article
- Pan-immune-inflammation value as a novel predictor of pathological response to neoadjuvant chemotherapy combined with anti-PD-1 therapy in esophageal squamous cell carcinoma: a multicenter real-world retrospective clinical study.Therapeutic advances in medical oncology · 2025Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The pan-immune-inflammation value (PIV), calculated as (neutrophil × platelet × monocyte)/lymphocyte count, may be useful for estimating survival in breast cancer patients. To determine the prognostic value of PIV for overall survival in breast cancer patients in Lima, Peru. A retrospective cohort study was conducted. 97 breast cancer patients diagnosed between January 2010 and December 2016 had their medical records analyzed. The primary dependent variable was overall survival, and the key independent variable was the PIV, divided into high (≥ 310) and low (< 310) groups. Patient data included demographics, treatment protocols and other clinical variables. Statistical analysis involved Kaplan-Meier survival curves and Cox proportional hazards modeling. Patients with a PIV ≥ 310 had significantly lower 5-year survival functions (p = 0.004). Similar significant differences in survival were observed for clinical stage III-IV (p = 0.015), hemoglobin levels < 12 mg/Dl (p = 0.007), histological grade (p = 0.019), and nuclear grade (p < 0.001); however, molecular classification did not show a significant survival difference (p = 0.371). The adjusted Hazard Ratios showed that PIV ≥ 310 was significantly associated with poor outcome (5.08, IC95%: 1.52-16.92). While clinical stage and hemoglobin levels were associated with survival in the unadjusted model. These factors did not maintain significance after adjustment. PIV is an independent predictor of reduced survival in Peruvian breast cancer patients.
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