Providing Patients with Locally Advanced Cervical Cancer Access to Brachytherapy: Experience from a Referral Network for Women Treated in Overseas France.

Abstract

Simple SummaryAccess to image-guided adaptive brachytherapy (IGABT) is limited in many regions in the world, thus leading to treatment care disparities. The aim of our retrospective study was to report the experience of a referral network for women with locally advanced cervical cancer (LACC) between radiotherapy facilities in Overseas France and our institution. This series of 64 patients shows the feasibility of a referral process for women with LACC who require IGABT with estimated probabilities of LC, progression-free survival, and overall survival (OS) of 94.6% (95% CI: 88.9–100.0%), 72.7% (95% CI: 61.1–86.5%), and 82.5% (95% CI: 72.0–94.5%). However, the centralization of this advanced technique to expert centers requires a well-defined workflow and appropriate dimensioning of resources to minimize overall treatment time.Image-guided adaptive brachytherapy (IGABT) is part of the standard of care for locally advanced cervical cancer (LACC). Access to IGABT is limited in many regions, thus leading to treatment care disparities. We report the experience of a referral network for women with LACC between radiotherapy facilities in Overseas France and Gustave Roussy. This is a retrospective review of patients with LACC referred to Gustave Roussy, for pulsed-dose-rate (PDR) image-guided adaptive BT after initial radiation therapy in the French overseas between 2014 and 2021. Sixty-four patients were eligible to receive IGABT. Overall treatment time (OTT) was 60.5 days (IQR: 51–68.5). The median follow-up time was 17 months. At two years, estimated probabilities of LC, progression-free survival, and overall survival (OS) were 94.6% (95% CI: 88.9–100.0%), 72.7% (95% CI: 61.1–86.5%), and 82.5% (95% CI: 72.0–94.5%). In multivariable analysis, a D90CTVHR < 85GyEQD2 and a CTVHR volume > 40 cm3 were significant for poorer PFS (p = 0.001 and p = 0.009, respectively) and poorer OS (p = 0.004 and p = 0.004). The centralization of this advanced technique to expert centers requires a well-defined workflow and appropriate dimensioning of resources to minimize OTT.