Related Experiment Video
Updated: May 7, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Quantification of residual risk of relapse in breast cancer patients optimally treated
Maria Vittoria Dieci1, Monica Arnedos, Suzette Delaloge
1INSERM Unit U981 and Breast Cancer Unit, Department of Medical Oncology, Gustave Roussy Institute, Villejuif, France.
Abstract:
Despite remarkable improvements in breast cancer survival in the last decades, a proportion of patients still relapse after treatment for early disease. Different prognostic parameters may permit to roughly quantify the residual risk of relapse after (neo)adjuvant therapy. They include: tumor stage and classical molecular features at baseline, newly proposed prognosticators (such as tumor-infiltrating lymphocytes and integrated genomic tools) and the evaluation of tumor response after primary systemic therapy. However, the performance of these factors is still suboptimal and should be improved. Further research aimed to discover new possible prognostic factors in patients who received optimal systemic therapy is needed. Moreover, to exploit at the best the potential of each of these parameters, they should be integrated into algorithms to guide treatment decisions and to select those patients who may deserve the inclusion in clinical trials.
Related Concept Videos
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Cancer Survival Analysis
Assumptions of Survival Analysis
Actuarial Approach
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Relative Risk
Kaplan-Meier Approach
