The Era of Radiogenomics in Precision Medicine: An Emerging Approach to Support Diagnosis, Treatment Decisions, and Prognostication in Oncology

With the rapid development of new technologies, including artificial intelligence and genome sequencing, radiogenomics has emerged as a state-of-the-art science in the field of individualized medicine. Radiogenomics combines a large volume of quantitative data extracted from medical images with individual genomic phenotypes and constructs a prediction model through deep learning to stratify patients, guide therapeutic strategies, and evaluate clinical outcomes. Recent studies of various types of tumors demonstrate the predictive value of radiogenomics. And some of the issues in the radiogenomic analysis and the solutions from prior works are presented. Although the workflow criteria and international agreed guidelines for statistical methods need to be confirmed, radiogenomics represents a repeatable and cost-effective approach for the detection of continuous changes and is a promising surrogate for invasive interventions. Therefore, radiogenomics could facilitate computer-aided diagnosis, treatment, and prediction of the prognosis in patients with tumors in the routine clinical setting. Here, we summarize the integrated process of radiogenomics and introduce the crucial strategies and statistical algorithms involved in current studies

Triplet Chemotherapy (FOLFOXIRI) Plus Bevacizumab Versus Doublet Chemotherapy (FOLFOX/FOLFIRI) Plus Bevacizumab in Conversion Therapy for Metastatic Colorectal Cancer: a Meta-Analysis

Background/Aims: Conversion therapy can convert unresectable metastatic colorectal cancer (mCRC) into resectable. However, the optimal conversion regimen was not yet defined. This meta-analysis aimed to compare the efficacy and safety of the triplet chemotherapy (FOLFOXIRI) plus bevacizumab (Bev) with doublet chemotherapy (FOLFOX/FOLFIRI) plus Bev in conversion therapy. Methods: Randomized controlled trials (RCTs) from databases, including Pubmed, EMBASE, Cochrane clinical trials, clinicaltrial.gov and some conferences, were searched from the inception to November 2017. The R0 resection, objective response rate (ORR), progression-free survival (PFS), overall survival (OS) and the incidence of adverse events were pooled with the use of hazard ratio (HR) or risk ratio (RR). Results: Four RCTs with 1013 patients were included. FOLFOXIRI plus Bev regimen significantly improved the overall R0 resection rate (RR 1.41, 95% confidence interval (CI) 1.07-1.85, I2=37%), liver R0 resection rate (RR 2.28, 95% CI 1.34-3.89, I2=0%), ORR (RR 1.20, 95% CI 1.09-1.32, I2=0%), PFS (HR 0.72, 95% CI 0.62-0.84, I2=36%) and OS (HR 0.80, 95% CI 0.66-0.97, I2=0%). There was no significant difference in any Grade≥3 adverse event (RR 1.08, 95% CI 0.99-1.17, I2=0%) between two regimens. FOLFOXIRI-Bev was associated with a higher risk of neutropenia (RR 1.77, 95% CI 1.13-2.79, I2=68%) and diarrhea (RR 1.65, 95% CI 1.17-2.32, I2=0%). Conclusions: Triplet chemotherapy plus Bev significantly improved the R0 resection rates, ORR, PFS and OS in comparison with doublet chemotherapy plus Bev in conversion therapy for mCRC patients, with a higher risk of neutropenia and diarrhea