Variation in practice in endometrial cancer and potential for improved care and equity through molecular classification

Abstract

Objectives: We measured the variation in practice across all aspects of endometrial cancer (EC) management and assessed the potential impact of implementation of molecular classification.

Methods: Centers from across Canada provided representative tumor samples and clinical data, including preoperative workup, operative management, hereditary cancer program (HCP) referrals, adjuvant therapy, surveillance and outcomes, for all EC patients diagnosed in 2016. Tumors were classified into the four ProMisE molecular subtypes.

Results: A total of 1336 fully evaluable EC patients were identified from 10 tertiary cancer centers (TC; n = 1022) and 19 community centers (CC; n = 314). Variation of surgical practice across TCs was profound (14-100%) for lymphadenectomy (LND) (mean 57% Gr1/2, 82% Gr3) and omental sampling (20% Gr1/2, 79% Gr3). Preoperative CT scans were inconsistently obtained (mean 32% Gr1/2, 51% Gr3) and use of adjuvant chemo or chemoRT in high risk EC ranged from 0-55% and 64-100%, respectively. Molecular subtyping was performed retrospectively and identified 6% POLEmut, 28% MMRd, 48% NSMP and 18% p53abn ECs, and was significantly associated with survival. Within patients retrospectively diagnosed with MMRd EC only 22% had been referred to HCP. Of patients with p53abn EC, LND and omental sampling was not performed in 21% and 23% respectively, and 41% received no chemotherapy. Comparison of management in 2016 with current 2020 ESGO/ESTRO/ESP guidelines identified at least 26 and 95 patients that would have been directed to less or more adjuvant therapy, respectively (10% of cohort).

Conclusion: Molecular classification has the potential to mitigate the profound variation in practice demonstrated in current EC care, enabling reproducible risk assessment, guiding treatment and reducing health care disparities.

Keywords: Adjuvant therapy; Endometrial cancer; Hereditary cancer testing; Lymph node assessment; Molecular classification.