Abstract
Neoadjuvant therapies have been shown to decrease tumor burden, increase resection rate, and improve the outcomes among patients with locally advanced gastric cancer (GC). However, not all patients are equally responsive; therefore, differentiating potential respondents from nonrespondents is clinically important. To use pretreatment computed tomography (CT)-pixelated feature-difference extraction techniques to identify diagnostically relevant features that could predict patients' response to neoadjuvant chemotherapy at diagnosis. This multicenter cohort study included patients with locally advanced GC who were treated from January 2010 to July 2017 at 2 hospitals in southern China (training cohort) and 1 hospital in northern China (external validation cohort). Their clinicopathological data, pretreatment CT images, and pathological reports were retrieved and analyzed. Data analysis was conducted from December 2017 to May 2021. All patients underwent 2 to 4 cycles of fluorouracil in combination with a platinum-based neoadjuvant chemotherapy regimen. All gastrectomies were performed according to the Japanese Classification of Gastric Carcinoma (14th edition) guidelines. Reliability of clinicopathological and radiomics-based features were assessed with area under receiver operating characteristic curve (AUC) and Mann-Whitney U test. A total of 323 patients (242 [74.9%] men; median [range] age, 58 [24-82] years) were included in the study, with 250 patients (77.4%) in the training cohort and 73 (22.6%) in the validation cohort. The baseline pretreatment characteristics of the training and validation cohorts were well-balanced. The number of respondents in the training and validation cohort was 122 (48.8%) and 40 (54.8%), respectively, and the number of nonrespondents was 128 (51.2%) and 33 (45.2%), respectively. No clinicopathological variables were significantly associated with treatment response. Using radiomics, 20 low-intercorrelated features from a total of 7477 features were used to construct a radiomics signature that demonstrated significant association with treatment response. Good discrimination performance of the radiomics signature for predicting treatment response in the training (AUC, 0.736; 95% CI, 0.675-0.798) and external validation (AUC, 0.679; 95% CI, 0.554-0.803) cohorts was observed. Decision curve analysis confirmed the clinical utility of the radiomics signature. In this study, the proposed radiomics signature showed potential as a clinical aid for predicting the response of patients with locally advanced GC before treatment, thereby allowing timely planning for effective treatments for potential nonrespondents.
Highlights
Gastric cancer (GC) is a highly heterogeneous disease associated with a high mortality rate.[1]
The main inclusion criteria were (1) biopsy-proven gastric adenocarcinoma; (2) nonmetastatic locally advanced GC determined by pretreatment computed tomography (CT) examination or laparoscopic laparotomy; and (3) gastrectomy procedure after completion of neoadjuvant chemotherapy, after which tumor response was confirmed by postoperative pathologic examination
Our analyses showed that no patient characteristics were associated with neoadjuvant chemotherapy response, including commonly used clinical, serological, and radiographic variables, such as age, carcinoembryonic antigen level, CA199 level, CA724 level, tumor location, clinical tumor stage, clinical node stage, and clinical TNM stage in both the training and validation cohorts
Summary
Gastric cancer (GC) is a highly heterogeneous disease associated with a high mortality rate.[1] multimodal treatments, such as gastrectomies followed by adjuvant chemotherapy (the standard of care especially in Asian countries),[2] have improved patients’ survival outcomes,[3] benefits for locally advanced cases have been modest. The addition of neoadjuvant therapies to standard treatment has led to an increase in pathological complete remission (pCR) and pathological partial remission (pPR) rates of the tumor, an increase in resection rates, and improvements in survival outcomes.[4,5,6,7] neoadjuvant therapy is being increasingly used outside clinical trial settings. Considering that pCR and pPR are confirmed through invasive histopathological interventions and mostly after surgery, creating an alternative, noninvasive method remains a major challenge. Conventional and multicombinative radiographic approaches have been explored, but their accuracies have been limited.[8,9] On the other hand, molecular biomarkers, including serologic and radiographic markers, have shown promising results, but none have been prospectively validated for routine clinical use.[10,11]
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