FIGO 2018 Versus Ontogenetic Staging for Locally Advanced Cervical Cancer: An International Multicenter Cohort Study Comparing the Two Classifications and Their Prognostic Implications

FIGO 2018 分期与局部晚期宫颈癌的个体发育分期:一项国际多中心队列研究比较了两种分期方法及其预后意义

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Abstract

BACKGROUND/OBJECTIVE: The aim of this study was to compare two different staging systems (FIGO 2018 and ontogenetic staging) for cervical cancer in a locally advanced setting and to determine which one provides better prognostic stratification and a stronger association with oncological outcomes. METHODS: A multicenter retrospective cohort study was conducted in patients with cervical cancer (FIGO 2018 stages IIB-IVA) primarily treated with chemoradiotherapy. The primary endpoint was the difference in accuracy for predicting cancer-specific survival at 3 years between the ontogenetic tumor staging system and the FIGO 2018 staging system. Secondary endpoints assessed the same difference in prognostic power with respect to recurrence-free survival and overall survival. RESULTS: Of 341 patients with locally advanced cervical cancer, the ontogenetic tumor staging system demonstrated superior prognostic performance compared to the FIGO 2018 system. The ontogenetic system showed clear separation of Kaplan-Meier curves for recurrence-free, overall, and cancer-specific survival, unlike the overlapping FIGO 2018 survival curves. Multivariable Cox models controlling clinicopathological factors revealed a progressive, significant worsening of cancer-specific survival across ontogenetic tumor (oT) stages, which was not observed with FIGO staging. Formal comparisons using Harrell's C-index, time-dependent areas under the curve (AUC), and Akaike's information criterion confirmed the ontogenetic model's significantly better discriminative ability and fit. Furthermore, ontogenetic staging provided significant risk stratification within the FIGO IIIC nodal-positive group and among patients with parametrial invasion, demonstrating its refined prognostic utility. CONCLUSIONS: Ontogenetic tumor staging can be effectively applied using imaging alone and was superior to the FIGO 2018 classification in this study.

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