516 Background: 90Y loaded microsphere SIRT (radioembolization) is a treatment option in advanced HCC. However, no personalized dosimetric endpoints are currently used. The goal of this study was to compare the efficacy of 90Y loaded glass microsphere SIRT in HCC using a standard versus a personalized dosimetric approach. Methods: DOSISPHERE-01 was a multicenter, randomized phase 2 trial in unresectable HCC patients with at least one tumor ≥7cm. Treatment arm was randomly assigned (1:1) to standard dosimetry arm (SDA), with a goal to deliver 120±20Gy to the treated volume or to personalized dosimetry arm (PDA) with a goal to deliver at least 205Gy to the index lesion. The primary endpoint was the response rate (RR) of the index lesion according to EASL criteria. Secondary endpoints included dose response evaluation, safety and overall survival (OS). Results: Sixty HCC patients were randomized (PDA 31, SDA 29, intent to treat population-ITTP-), and 56 treated (28 in each arm). RR was significantly increased in the PDA versus the SDA, in the ITTP, respectively 64.5% versus 31% (p=0.0095) as in the safety population -SP- (treatment effectively received, personalized 35, standard 21), respectively 74.3% versus 14.3% (p<0.0001). Median OS was significantly increased in the PDA versus the SDA, in the ITTP, respectively 26.7m (CI 95%:11.7-NR) versus 10.6m (CI 95%:6-16.8), p=0.0096, HR=0.421 (95%CI:0.215-0.826), p=0.0119, as in the SP, respectively 26.7m (CI 95%:11.7- NR) versus 9.5m (CI 95%:4.8-14.9), p=0.0015, HR=0.342 (95%CI:0.171-0.683), p=0.0023. Median OS was 26.7m (CI 95%:13.5-NR) versus 6.0m (CI 95%:3.8-14.9) for the patients who received a tumor dose ≥205 Gy or <205 Gy respectively, p=0.0106, HR=0.336 (95%CI:0.154-0.735), p=0.0063. Treatment-related clinically relevant hepatic ≥grade 3 AEs were observed in 5.7% and 14.2% of the patients of the PDA and SDA arms, respectively, (p=ns). Conclusions: MAA SPECT/CT based personalized dosimetry is safe and dramatically increased RR and OS of HCC patients. These results question the interpretation of all phase 3 trials of SIRT designed without personalized dosimetry in HCC. Clinical trial information: 2015-A00894-45.
9535 Background: Molecular characterization of metastatic lung adenocarcinomas is mandatory but might be hampered by the quantity of tissue, restricted access to molecular platforms or limited economical resources. Our aim was to develop a tool supported by the hypothesis that radiological patterns of pts could help predict the rate of positivity of the most common oncogenic drivers. Methods: We defined an algorithm based on a molecularly defined cohort of 656 pts with stage IV lung adenocarcinoma. Two radiologists centrally reviewed the baseline imaging. Clinical data were retrospectively collected. There were 135 EGFR mutations, 81 ALK fusions, 47 BRAF mutations, 141 KRAS mutations, and 146 pan-negative tumors for these 4 oncogenic drivers. Univariate correlation analyses were performed to define an algorithm predicting the molecular testing positivity based on the metastatic pattern. Subsequently, an online tool was developed. This study was approved by our institutional review board. Results: Metastatic patterns correlated with the genomic drivers when compared to the pan-negative group. In the EGFR group, pleural metastases were more frequent (32% vs. 20%; p = 0.021), whereas adrenal and node metastases less frequent (6% vs.23%; p < 0.001 and 11% vs. 23% respectively; p = 0.011). In the ALK group, there were more brain and lung metastases (respectively 42% vs. 29%; p = 0.043 and 37% vs. 24% respectively; p = 0.037). In the BRAF group, pleural and pericardial metastases were more common (47% vs. 20%; p < 0.001 and 11% vs. 3% respectively; p = 0.04) and bone metastases less common (21% vs. 42%; p = 0.011). Lymphangitis was more frequent in EGFR, ALK and BRAF groups (6%, 7% and 15% vs. 1%; p = 0,016, p = 0,009 and p < 0,001 respectively). A free online access to the algorithm is now available after registration at http//tactic-ct.fr. Physicians enter age, sex, smoking status and the sites of metastases at diagnosis (present/absent/unknown). A mutation score is calculated, reflecting the % of chance to find an oncogenic driver. On the website, contributors can also enter new cases and an artificial intelligence will refine the algorithm and expand the number of oncogenic drivers. Conclusions: Our free access tool allows establishing a hierarchy in the molecular testing based on simple clinical and radiological information. Continual learning from new cases entered in the database will increase the sensitivity of the tool. This tool might save time, tumor tissue, economical resources and accelerate access to personalized treatment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.