Tumor Budding, Poorly Differentiated Clusters, and Stroma Percentage in Uterine Endometrioid Carcinomas Are Morphologic Findings Associated With Adverse Clinical Outcomes.

Publication/Presentation Date

1-1-2025

Abstract

Uterine endometrioid carcinoma (UEC) has well-defined morphologic features that carry prognostic significance and guide treatment. In addition to the well-known features, tumor budding (TB), poorly differentiated clusters (PDCs), and amount of stroma within the invasive front are associated with a poor prognostic outcome in many carcinomas. Here, we evaluate TB, PDCs, and the stroma percentage in UEC and correlate these findings with morphologic features known to be associated with a poor clinical outcome and with recurrence-free survival (RFS). We performed a retrospective search of our institution's EMR for cases of hysterectomy for UEC. We collected clinical data including disease recurrence, death, and data associated with poor patient outcomes. Cases were evaluated for TB, PDCs, and percent stroma by 2 pathologists. Ten 20× fields were examined, and the one with the most PDCs and TB was evaluated. Percent stroma was evaluated in a ×10 field of tumor at the area of deepest invasion. Less than 10% stroma was defined as stroma poor, and >10% stroma was defined as stroma rich. Statistical testing and analysis were conducted, and P-value was set at 0.05. One hundred thirteen cases were evaluated. Decreased RFS was seen with TB (P=0.03), at least 5 PDCs (P=0.01), and stroma-rich tumors (P=0.043). This study shows a statistically significant association between TB presence, at least 5 PDCs, stroma-rich tumors, and decreased RFS in UEC. We conclude that TB, PDCs and stromal evaluation are strong independent prognostic indicators in UEC and provide additional value to the currently used morphologic assessment of UEC.

Volume

44

Issue

1

First Page

49

Last Page

55

ISSN

1538-7151

Disciplines

Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods

PubMedID

39661577

Department(s)

Administration and Leadership

Document Type

Article

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