Margin of Error: The Emerging Role of Field Cancerization in Predicting Recurrence Risk of Ductal Carcinoma In Situ

TL;DR

This paper explores how field cancerization can improve predicting recurrence risk in ductal carcinoma in situ, moving beyond traditional margin-based models.

Contribution

The paper introduces field cancerization as a novel framework for understanding and predicting DCIS recurrence.

Findings

Conventional methods for predicting DCIS recurrence are limited and often inaccurate.

Field cancerization offers a dynamic model for assessing recurrence risk based on patient-specific biomarkers.

The paper highlights the need for multivariable models that include field biomarkers for better patient management.

Abstract

Although ductal carcinoma in situ (DCIS) diagnoses continue to climb, patient management remains constrained by limitations in recurrence prediction. Conventional histopathology and existing prognostic parameters often inadequately predict local recurrence, leading to over- or under-treatment. Additionally, discourse remains over the clinical implications of margin width as a measure of recurrence risk, demonstrating the limitations of a margin-based model, and motivating our proposal that recurrence risk is dynamic and should be defined by patient-specific, spatially resolved diagnostic biomarkers. This review introduces field cancerization as a framework that may illuminate mechanisms underlying DCIS ipsilateral recurrence and improve clinical decision-making. We propose that the potential drivers of ductal field cancerization span two stages: pre-tumorigenesis and post-tumorigenesis. Pre-tumorigenic events include non-biological and biological exposome factors. Post-tumorigenic drivers include intratumoral and microenvironment-mediated remodeling of adjacent tissues that promote malignancy. This review bridges stage-specific molecular mechanisms to potentially actionable strategies for DCIS patient management—particularly margin assessment and recurrence risk prognostication—while highlighting the critical unmet need to identify biomarkers that measure high-risk field changes. We also emphasize the need to move beyond lesion-centric management toward multivariable prognostic models that include distance-mapped field biomarkers, enabling more precise surgery, improved selection of adjuvant therapy, and safer de-escalation for low-risk patients.

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