ArticleTranslational oncology2026
An unfavorable biologic profile associated with decreased overall survival and cancer-specific survival in non-metastatic breast cancer: A latent class analysis.
Article in Translational oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundChronological age is an imperfect proxy for risk assessment in geriatric oncology. There is an urgent need for an objective, easily measurable biological aging signature to refine patient stratification and personalize therapeutic decisions.
methodsWe analyzed a panel of seven aging-related biomarkers (including markers of inflammation, anabolic reserve, and telomere status) in 244 nonmetastatic breast cancer patients from two age groups ("Old", ≥70 years, N = 162; "Young", ≤60 years, N = 82). We used Latent Class Analysis (LCA) to integrate these markers and identify distinct biological risk profiles. These profiles were then evaluated for their association with Overall Survival (OS) and Cancer-Specific Death (CSD) via Competing Risk Analysis.
resultsLCA identified two patient profiles. The Unfavorable Biologic Profile (56.1% of the cohort) was defined by a triad of high MCP-1, high Chitinase activity, and low IGF-1. This profile was strongly associated with poorer OS (Age-adjusted HR=1.82, p = 0.018). Crucially, 15% of chronologically "Young" patients were assigned to this high-risk profile, while 23% of "Old" patients were assigned to the Favorable Profile. Furthermore, the Unfavorable Profile was more strongly and specifically associated with CSD (Subdistribution HR: 2.05, p = 0.012) than with Non-Cancer Death.
conclusionOur results delineate an unfavorable, trans-chronological biological profile that identifies patients with low host reserve, largely driven by inflammaging and catabolism. This integrated signature provides a robust, objective screening tool to identify biologically frail patients, validating the need for Comprehensive Geriatric Assessment (CGA) and biomarker-guided therapeutic de-escalation (e.g., avoiding adjuvant chemotherapy) to improve individualized outcomes in oncology.
trial registrationBS32220096117.
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