Objective: Prognostic nutritional index (PNI) is a comprehensive reflection of the nutritional and immune status of the patient, which is closely related to the ability of the organism to clear tumor cells and reduce local recurrence. Several findings suggested that PNI was a prognostic indicator for breast cancer, but the conclusions were conflicting. We aimed to comprehensively elucidate the prognostic value of PNI in breast cancer patients.
Methods: Relevant studies in PubMed, Embase, Cochrane Library, and Web of Science databases were searched through March 2023. Data extraction and literature quality assessment of the screened studies were performed. The associations between PNI and overall survival (OS), disease-free survival (DFS), and progression-free survival (PFS) in breast cancer patients who received clinical treatment were assessed by hazard ratios () and 95% confidence intervals ().
Results: A total of 7 studies involving 2212 patients met the inclusion criteria. High PNI was a favorable independent predictor of prolonged OS and PFS after clinical treatment in breast cancer patients compared to low PNI (for OS: = .38, 95% .31 ∼ .46, < .001; for DFS: = .32, 95% .19 ∼ .51, < .001). In subgroup analysis, high PNI was a prognostic factor for extended DFS in the context of a study sample size ≥300 ( = .39, 95% .28 ∼ .54, < .001) and patients not receiving neoadjuvant chemotherapy ( = .51, 95% .37 ∼ .70, < .001).
Conclusion: The PNI has a significant correlation with the prognosis of breast cancer patients. We suggest that individualized targeted treatment and long-term surveillance should be implemented for patients with different levels of PNI.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1177/00031348231191200 | DOI Listing |
East Mediterr Health J
December 2024
Department of Radiology, King Abdulaziz University, Jeddah, Saudi Arabia.
Background: Breast cancer is often thought to occur at a younger age among Arab women based on the mean or median age at diagnosis, or the proportion of women diagnosed with breast cancer at a young age.
Objective: To compare age-specific breast cancer incidence rates among women from selected Arab countries with selected high- and middle-income countries.
Methods: We examined population-based, age-specific, national or regional breast cancer incidence data for 2008-2012 and 2013-2017 from Australia, Brazil, Canada, Germany, Japan, United Kingdom, and United States of America, and compared them with data from Algeria, Bahrain, Jordan, Kuwait, Morocco, Qatar, and Saudi Arabia.
Pharm Dev Technol
January 2025
Department of Pharmacy, School of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian 116029, China.
In this paper, the pH-sensitive targeting functional material NGR-poly(2-ethyl-2-oxazoline)-cholesteryl methyl carbonate (NGR-PEtOz-CHMC, NPC) modified quercetin (QUE) liposomes (NPC-QUE-L) was constructed. The structure of NPC was confirmed by infrared spectroscopy (IR) and nuclear magnetic resonance hydrogen spectrum (H-NMR). Pharmacokinetic results showed that the accumulation of QUE in plasma of the NPC-QUE-L group was 1.
View Article and Find Full Text PDFJ Med Econ
January 2025
UNESCO-TWAS, The World Academy of Sciences, Trieste, Italy.
Aim: Dynamic cancer control is a current health system priority, yet methods for achieving it are lacking. This study aims to review the application of system dynamics modeling (SDM) on cancer control and evaluate the research quality.
Methods: Articles were searched in PubMed, Web of Science, and Scopus from the inception of the study to November 15th, 2023.
Int J Surg
January 2025
Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China.
Detection of biomarkers of breast cancer incurs additional costs and tissue burden. We propose a deep learning-based algorithm (BBMIL) to predict classical biomarkers, immunotherapy-associated gene signatures, and prognosis-associated subtypes directly from hematoxylin and eosin stained histopathology images. BBMIL showed the best performance among comparative algorithms on the prediction of classical biomarkers, immunotherapy related gene signatures, and subtypes.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!