Prognostic Biomarkers in Cancer Survival Analysis
Summary
Prognostic biomarkers are measurable indicators that inform on the likely trajectory of a patient’s cancer, guiding risk stratification and therapeutic decision-making. These markers span molecular alterations, circulating proteins, immune cell ratios and composite scores derived from routine laboratory tests. Survival analysis techniques, such as Kaplan-Meier estimation and Cox proportional hazards modelling, quantify associations between biomarker levels and outcomes including overall survival and disease-free survival. Recent advances in genomics and proteomics have enabled the identification of novel signatures from tumour tissue and peripheral blood, while machine-learning approaches are being deployed to refine multivariate prognostic models. Composite indices—such as ratios of neutrophils to lymphocytes or albumin to fibrinogen—offer inexpensive, readily accessible metrics that reflect tumour biology and systemic inflammation. Rigorous validation across diverse cohorts remains essential to establish clinical utility. As precision oncology evolves, integration of established clinical variables with emerging biomarkers promises to enhance individualised prognosis, optimise therapeutic sequencing and ultimately improve patient outcomes on a global scale.
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Prognostic Biomarkers in Cancer Survival Analysis publication trend
The graph below shows the total number of articles in prognostic biomarkers in cancer survival analysis across all publications each year (not limited to Nature Index journals).
Technical terms
Prognostic biomarker: A biological measure that provides information on the likely course or outcome of disease in an individual.
Hazard ratio (HR): A statistic representing the relative risk of an event occurring in one group compared with another over time.
Overall survival (OS): The period from diagnosis or initiation of treatment to death from any cause.
Disease-free survival (DFS): The interval during which a patient remains free from detectable disease following treatment.
Cox proportional hazards model: A regression method used to assess the impact of variables on the time until an event of interest.
References
- Association between glucose to lymphocyte ratio and prognosis in patients with solid tumors. Frontiers in Immunology (2024).
- Prognostic values of the prognostic nutritional index, geriatric nutritional risk index, and systemic inflammatory indexes in patients with stage IIB–III cervical cancer receiving radiotherapy. Frontiers in Nutrition (2023).
- Prognostic role of lymphocyte to monocyte ratio for patients with cancer: evidence from a systematic review and meta-analysis. Oncotarget (2016).
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