Grant Number:	1R01CA303112-01A1 Interpret this number
Primary Investigator:	Plichta, Jennifer
Organization:	Duke University
Project Title:	Post-Recurrence Survival in Patients with Recurrent Breast Cancer: Identifying Key Predictors and Standardizing Assessments
Fiscal Year:	2026

PROJECT SUMMARY Nearly one-third of women diagnosed with early-stage breast cancer in the United States every year will go on to develop recurrence (recurrent breast cancer, RBC) after initial treatment. Moreover, these recurrences are frequently accompanied by distant metastases, and too often prove fatal for the patient. Prognosis for patients with RBC varies widely and depends on a multitude of factors. Indeed, similar to prognosis for a primary (first) breast cancer diagnosis, factors associated with survival outcomes for RBC include tumor size, nodal status, distant metastasis, tumor grade, biomarker status, and genomic assays. For primary breast cancer, these factors serve as the basis for the cancer staging guidelines put forth by the American Joint Committee on Cancer, which translates into a patient being assigned a prognostic stage at the time of their initial diagnosis (i.e Stage I, II, III, or IV). However, despite the similarity of prognostic criteria to primary breast cancer, and clear clinical benefits and utility of cancer staging systems, no prognostic staging system currently exists for RBC, severely limiting providers when discussing prognosis and making recommendations with patients. This proposal will address this critical gap in clinical care by creating the first prognostic classificationsystemfor patients with RBC. Working together with our Community Advisory Board throughout the duration of this proposal, we will develop a multi- institutional, tumor registry based on a retrospective observational cohort utilizing multiple data sources from 6 major sites across the US. This database will be the first of its kind for RBC and will contain sufficient granular clinical details of disease (e.g., type of breast cancer, stage, tumor size/location, etc.) and treatment for accurate prognostic staging. Next, leveraging this tumor registry, we will identify the variables with the greatest impact on survival, and then use the variables to develop a novel prognostic classification system. Finally, we will create a web-based clinical support tool based on the new prognostic classification system and assess the acceptability of the classification system by surveying clinicians and patients. Completion of this work will provide the field with a first-of-its-kind, validated, prognostic classification system for patients with RBC. This prognostic classification system will improve treatment approaches for RBC by allowing a more accurate and precise assessment of a patient’s disease trajectory.