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. 2025 Jun 4:15:1598069.
doi: 10.3389/fonc.2025.1598069. eCollection 2025.

Survival prognosis evaluation in advanced breast cancer patients: a study on the application of the advanced lung cancer inflammation index

Chunfeng Liang #  1 , Chunyan Yang #  1 , Qiujiao Yang  1 , Yuchen Tang  1 , Wenhai Zhang  1 , Qixing Tan  1 , Qinghong Qin  1
Affiliations

Survival prognosis evaluation in advanced breast cancer patients: a study on the application of the advanced lung cancer inflammation index

Chunfeng Liang et al. Front Oncol. .

Abstract

Background: Inflammation and nutritional status play critical roles in tumor initiation and progression. Advanced Lung Cancer Inflammation Index (ALI) has gained widespread attention as a novel biomarker for cancer prognosis evaluation.

Methods: This retrospective study analyzed 163 advanced breast cancer patients with distant metastasis (Guangxi Medical University Cancer Hospital, 2016-2023). Patients were stratified into high-ALI (n=64) and low-ALI (n=99) groups via K-means clustering. Kaplan-Meier survival curves with log-rank testing were used to assess survival differences, while Cox proportional hazards models were employed to evaluate the independent prognostic value of ALI. The predictive performance of ALI was assessed using time-dependent ROC curves.

Results: High ALI correlated with superior overall survival (log-rank p=0.0024) [HR=2.493 (95%CI 1.350-4.606) p = 0.004]. Multivariate analysis confirmed ALI as an independent prognostic factor (HR=0.39, 95% CI 0.16-0.95, p=0.037). ALI demonstrated stable predictive accuracy with 3-year AUC=0.645 and 5-year AUC=0.650 (C-index=0.65). Subgroup analyses confirmed prognostic consistency across clinical characteristics (p-interaction>0.05).

Conclusion: ALI is an independent prognostic factor for advanced breast cancer patients with good predictive ability. It provides an important supplementary prognostic marker for clinical practice and can help optimize personalized treatment strategies.

Keywords: advanced breast cancer; advanced lung cancer inflammation index (ALI); inflammation; nutritional status; survival prognosis.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Kaplan-Meier analysis of overall survival (OS) between low-ALI and high-ALI groups.
Figure 2
Figure 2
Restricted cubic spline analysis showing the relationship between ALI and survival risk in patients with advanced breast cancer.
Figure 3
Figure 3
(A) ROC curves for 3-year and 5-year survival prediction in patients with advanced breast cancer, with the area under the curve (AUC) for each time point shown. (B) C-index curve illustrating the relationship between ALI and survival time in patients with advanced breast cancer.
Figure 4
Figure 4
Forest plot of subgroup analysis showing survival outcomes by age, molecular subtype, and treatment modality (surgery, radiotherapy, chemotherapy, etc.) in patients with advanced breast cancer. *adjusted for age, insurance, hypertension, diabetes, marital status, education, location, and menstrual status, pathological, histological grade, subtype, tumor, lymph node, metastatic, Ki 67, surgery, radiation, and chemotherapy.
See this image and copyright information in PMC

References

    1. Cancer Today .Global Cancer Observatory (2024). Available online at: https://gco.iarc.fr/en (Accessed September 15, 2024).
    1. Lei S, Zheng R, Zhang S, Chen R, Wang S, Sun K, et al. Breast cancer incidence and mortality in women in China: temporal trends and projections to 2030. Cancer Biol Med. (2021) 18:900–9. doi: 10.20892/j.issn.2095-3941.2020.0523 - DOI - PMC - PubMed
    1. Ko NY, Hong S, Winn RA, Calip GS. Association of insurance status and racial disparities with the detection of early-stage breast cancer. JAMA Oncol. (2020) 6(3):385–92. doi: 10.1001/jamaoncol.2019.5672 - DOI - PMC - PubMed
    1. Fields BKK, Joe BN. Screening breast MRI effectively detects early-stage breast cancer in high-risk patients without prior history of breast cancer. Radiology: Imaging Cancer. (2024) 6(2):e249005. doi: 10.1148/rycan.249005 - DOI - PMC - PubMed
    1. Kopans DB. Beyond randomized controlled trials. Cancer. (2002) 94:580–1. doi: 10.1002/cncr.10220 - DOI - PubMed

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