Molecular Classification Provides Better Prognostication in Endometrial Cancer

Incorporating molecular classification in endometrial cancer staging allows for better prognostication, according to research published in Gynecologic Oncology.

Researchers found that incorporating molecular classification into the International Federation of Gynecology and Obstetrics (FIGO) 2023 staging system allowed for more accurate prognostication than the FIGO2008 system or the FIGO2023 system without molecular classification.

The researchers compared the 3 staging systems — FIGO2023 with molecular classification (FIGO2023_m), FIGO2008, and FIGO2023 — in 265 patients who were diagnosed with endometrial cancer and underwent surgery at a single center between 1997 and 2019.

The proportion of patients with stage I, II, and III disease differed across the 3 systems. The distribution of staging according to each system can be seen in the table below.

Distribution of Disease Stages Across FIGO Systems
	FIGO2008	FIGO2023	FIGO2023m
Stage I	140 (52.8%)	83 (31.3%)	98 (37.0%)
Stage IA	99	67	55
Stage IAm			29
Stage IB	41	16	14
Stage II	21 (7.9%)	82 (30.9%)	67 (25.3%)
Stage IIA		11	10
Stage IIB		9	6
Stage IIC		62	32
Stage IICm			19
Stage III	79 (29.8%)	75 (28.3%)	75 (28.3%)
Stage IV	25 (9.4%)	25 (9.4%)	25 (9.4%)

The researchers noted that the differences across the staging systems were reflected in the overall survival (OS) outcomes of patients with stage I and II disease.

The 5-year OS rate was better among patients with stage I disease per FIGO2023_m than among those with stage I disease per FIGO2008 or FIGO2023 — 95.5%, 92.4%, and 92.2%, respectively.

The researchers attributed this finding to the downstaging of POLE-EDM endometrial cancer to stage IA_m. POLE-EDM was defined as an oncogenic/pathogenic, nonsense, and in-frame deletion variant within the exonuclease domain of POLE that appeared as a somatic hotspot, the researchers explained.

The researchers also found that the 5-year OS rate was worse among patients with stage II disease per FIGO2023_m than among those with stage II disease per FIGO2008 or FIGO2023 —  89.1%, 95.2%, and 93.6%, respectively.

Here, the difference between FIGO2008 and FIGO2023 was primarily caused by the upstaging of 7 patients to stage IIB and 51 patients to stage IIC, according to the researchers. The difference between FIGO2023 and FIGO2023_m was attributed to the upstaging of 4 patients to stage IIC with p53 abnormalities.

Among patients with stage IIIC disease per FIGO2023_m, p53 abnormalities were associated with significantly worse OS. The 5-year OS rate was 24.3% in patients with p53 abnormalities and 83.7% in patients with wild-type p53 (P =.0005).

The researchers noted that relapse-free survival curves followed a similar trend as the OS curves.

The researchers also used Harrell’s C statistic (C-index) and Akaike’s information criterion (AIC) to assess the predictive capability and accuracy of the 3 models. A higher C-index value suggests better predictive capability, and a lower AIC value suggests a more accurate model.

FIGO2023_m had a lower AIC value (455.9) than FIGO2023 (459.2) or FIGO2008 (457.9). FIGO2023_m also had a higher C-index for OS (0.768) than FIGO2023 (0.743) or FIGO2008 (0.740). Results were similar for relapse-free survival (C-index, 0.749, 0.743, 0.711, respectively).

The researchers concluded that the prognostic value of FIGO2023_m was superior to that of FIGO2008 and FIGO2023 because FIGO2023_m accounts for the presence of POLE-EDM and p53 abnormalities.

“When feasible, molecular subtypes can be included in the staging criteria to allow for a better prediction of prognosis,” the researchers wrote. “The development of a method to check POLE status that is widely available in hospitals around the world is necessary.”

Reference

Kobayashi-Kato M, Fujii E, Asami Y, et al. Utility of the revised FIGO2023 staging with molecular classification in endometrial cancer. Gynecologic Oncology. Published online September 23, 2023. Doi:10.1016/j.ygyno.2023.09.011

This article originally appeared on Cancer Therapy Advisor