Abstract 53P
Background
Bevacizumab has significantly improved the resectability, response rate and survival of patients with RAS-mutant colorectal cancer liver metastases (CRLM). However, more than half of these patients were insensitive to bevacizumab therapy. Identification of patients who are sensitive to bevacizumab therapy may improve the response rate and reduce adverse events. In this study, we aimed to construct and validate a PET/CT deep radiomics signature to predict bevacizumab efficacy in initially unresectable RAS-mutant CRLM patients.
Methods
We retrospectively collected 208 RAS-mutant CRLM patients. Training cohort (n=74) included the members of armA (mFOLFOX plus bevacizumab) from the BECOME study (NCT01972490). Internal validation cohort (n=65) and external validation cohort (n=29) were collected, during January 2018 to December 2018, from the consecutive bevacizumab-treated RAS-mutant CRLM patients of Shanghai Zhongshan Hospital and First Hospital of Wenzhou, respectively. In order to exclude the effect of chemotherapy alone, a negative validation cohort (n=40) enrolled the members of armB (mFOLFOX alone) from the BECOME study. The PET/CT image features were extracted using a deep learning signature, and we converted them into a multi-scale representation by a Gaussian mixture model. This representation was further combined with relevant clinical factors to form the final radiomics signature.
Results
Our deep radiomics signature fitted well in the training cohort (AUC 0.982 [0.926-1.0]). As for internal validation cohort, our signature achieved a promising performance in predicting bevacizumab sensitivity (AUC 0.846 [0.794-0.869], sensitivity 0.752 [0.723-0.794], specificity 0.776 [0.743-0.814]), and the external validation cohort shows a similar outcome (AUC 0.768 [0.732-0.846], sensitivity 0.684 [0.647-0.734], specificity 0.696 [0.645-0.751]). But for the negative validation cohort, our signature failed with chemotherapy (AUC of 0.534 [0.467-0.592]).
Conclusions
A baseline PEC/CT deep radiomics signature was constructed and was able to specifically identify bevacizumab-sensitive RAS-mutant CRLM patients. This tool deserves to be validated by further prospective study.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Fujian Provincial Health Commission Project (2021GGB032) and National Natural Science Foundation of China (82072653).
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
79P - Outcomes by baseline liver function in patients with unresectable hepatocellular carcinoma treated with tremelimumab and durvalumab in the phase III HIMALAYA study
Presenter: Arndt Vogel
Session: Poster viewing 02
82P - A randomized controlled, open-label, adaptive phase III clinical trial to evaluate safety and efficacy of EndoTAG-1 plus gemcitabine versus gemcitabine alone in patients with measurable locally advanced and/or metastatic adenocarcinoma of the pancreas after FOLFIRINOX
Presenter: Muh-Hwan Su
Session: Poster viewing 02
83P - Impact of viral aetiology in the phase III HIMALAYA study of tremelimumab (T) plus durvalumab (D) in unresectable hepatocellular carcinoma (uHCC)
Presenter: Stephen Chan
Session: Poster viewing 02
84P - Atezolizumab plus bevacizumab versus lenvatinib for unresectable hepatocellular carcinoma: A large real life worldwide population
Presenter: Margherita Rimini
Session: Poster viewing 02
86P - Outcomes by primary tumour location in patients with advanced biliary tract cancer treated with durvalumab or placebo plus gemcitabine and cisplatin in the phase III TOPAZ-1 study
Presenter: Aiwu Ruth He
Session: Poster viewing 02
87P - Socio-demographic disparities in esophageal cancer: A SEER analysis
Presenter: Beas Siromoni
Session: Poster viewing 02
88P - Sintilimab plus anlotinib as second-line therapy for metastatic or recurrent gallbladder carcinoma (GBC): A single-arm, phase II study
Presenter: Qingbao Cheng
Session: Poster viewing 02