Analysis of survival differences in advanced triple-negative breast cancer: a real-world study.

BACKGROUND

Advanced triple-negative breast cancer (aTNBC) has a poor prognosis, and there is a dearth of relevant real-world research data. This study is aimed at analyzing the survival outcomes and subgroup characteristics of aTNBC in the first-line treatment stage, providing data support for clinical treatment decisions.

METHODS

A retrospective analysis was conducted on 215 patients with aTNBC who received first-line salvage treatment at Shandong Cancer Hospital from January 2018 to March 2023 (74 patients of metastatic breast cancer [dnMBC] and 141 patients of recurrent metastatic breast cancer [rMBC]). Progression-free survival (PFS) and overall survival (OS) were assessed using the Kaplan-Meier method, and hazard ratio (HR) were calculated using the Cox regression model. Spearman correlation analysis was used to evaluate the relationship between PFS and OS.

RESULTS

The median PFS for aTNBC patients during the first-line treatment phase was 8.40 months (95% CI: 7.56-9.24 months), while the median OS was 23.87 months (95% CI: 20.53-27.21 months). Multivariate Cox regression and interaction analyses identified several independent prognostic factors affecting PFS, including dnMBC, platinum-containing regimen, immunotherapy, and local treatment of metastasis. For OS, independent prognostic factors included dnMBC, G3, and platinum-containing regimen. Additional survival analysis showed that the risk of disease progression and death was significantly lower in dnMBC patients compared to rMBC patients (PFS: HR = 0.70, 95% CI: 0.51-0.95, = 0.025; OS: HR = 0.65, 95% CI: 0.45-0.95, = 0.023). Furthermore, in both groups, PFS and OS were positively correlated ( = 0.54; = 0.58).

CONCLUSION

In patients with aTNBC, those with dnMBC demonstrate a more pronounced survival benefit, with this advantage being consistent across various clinicopathological parameters. Therefore, stratifying patients by metastatic category in clinical trials may improve evaluation of treatment efficacy and support more individualized patient management.