Prognostic significance of serum tumor marker normalization in the perioperative period for patients with advanced gastric cancer

Hu, Can; Zhang, Yanqiang; Xu, Jia; Chen, Wujie; Yu, Pengcheng; Wang, Yi; Bao, Zhehan; Zhang, Ruolan; Cheng, Xiangdong

doi:10.21037/atm-22-109

Cited by 10 publications

(9 citation statements)

References 12 publications

(10 reference statements)

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“…While surgery remains the primary treatment for GC, radical gastrectomy is only suitable for patients diagnosed with early GC. Unfortunately, 50–60% of patients are typically diagnosed in advanced stages, with invasion or metastasis 2 . After radical surgery, patients with locally advanced gastric cancer (LAGC), which refers to the stage between early GC and advanced GC, face high rates of distant metastasis and local recurrence, ranging from 40 to 51% 3 .…”

Section: Introductionmentioning

confidence: 99%

Deep learning radio-clinical signature for predicting neoadjuvant chemotherapy response and prognosis from pretreatment CT images of locally advanced gastric cancer patients

Chen

et al. 2023

International Journal of Surgery

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Background: Early noninvasive screening of patients who would benefit from neoadjuvant chemotherapy (NCT) is essential for personalized treatment of locally advanced gastric cancer (LAGC). The aim of this study was to identify radio-clinical signatures from pretreatment oversampled computed tomography (CT) images to predict the response to NCT and prognosis of LAGC patients. Methods: LAGC patients were retrospectively recruited from six hospitals from January 2008 to December 2021. An SE-ResNet50-based chemotherapy response prediction system was developed from pretreatment CT images preprocessed with an imaging oversampling method (i.e. DeepSMOTE). Then, the deep learning (DL) signature and clinic-based features were fed into the deep learning radio-clinical signature (DLCS). The predictive performance of the model was evaluated based on discrimination, calibration, and clinical usefulness. An additional model was built to predict overall survival (OS) and explore the survival benefit of the proposed DL signature and clinicopathological characteristics. Results: A total of 1060 LAGC patients were recruited from six hospitals; the training cohort (TC) and internal validation cohort (IVC) patients were randomly selected from center I. An external validation cohort (EVC) of 265 patients from five other centers was also included. The DLCS exhibited excellent performance in predicting the response to NCT in the IVC [area under the curve (AUC), 0.86] and EVC (AUC, 0.82), with good calibration in all cohorts ( P >0.05). Moreover, the DLCS model outperformed the clinical model ( P <0.05). Additionally, we found that the DL signature could serve as an independent factor for prognosis [hazard ratio (HR), 0.828, P =0.004]. The concordance index (C-index), integrated area under the time-dependent ROC curve (iAUC), and integrated Brier score (IBS) for the OS model were 0.64, 1.24, and 0.71 in the test set. Conclusion: The authors proposed a DLCS model that combined imaging features with clinical risk factors to accurately predict tumor response and identify the risk of OS in LAGC patients prior to NCT, which can then be used to guide personalized treatment plans with the help of computerized tumor-level characterization.

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Section: Introductionmentioning

confidence: 99%

Deep learning radio-clinical signature for predicting neoadjuvant chemotherapy response and prognosis from pretreatment CT images of locally advanced gastric cancer patients

Chen

et al. 2023

International Journal of Surgery

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“…As an easily accessible clinical examination, CA125 also played a key role in the diagnosis of gastrointestinal malignant tumors [ 18 , 19 ]. Studies have shown that CA125 level was a predictive factor of peritoneal metastases in gastric cancer [ 20 , 21 ] and normalization of CA125 was relevant with better survival [ 22 ]. Thus, we assumed that CA125 level has an impact on the prognosis of GIST patients.…”

Section: Discussionmentioning

confidence: 99%

Prognostic significance of serum CA125 in the overall management for patients with gastrointestinal stromal tumors

et al. 2023

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Background Carbohydrate antigen 125 (CA125) is elevated as a tumor marker in many carcinomas, but its association with gastrointestinal stromal tumor (GIST) has received less attention. This study intends to evaluate whether CA125 level can predict tumor progression and overall survival (OS) of GIST patients. Methods We retrospectively analyzed the clinical data and follow-up records of GIST patients who underwent surgical resection in Nanjing Drum Tower Hospital from August 2010 to December 2020. All patients were classified according to serum CA125 level. The relationship between CA125 and clinical outcomes was then examined. Results A total of 406 GIST patients were enrolled in this study, among which 46 patients had preoperative elevated serum CA125 level and 13 patients with high CA125 level both preoperative and postoperative were observed. Preoperative CA125 concentration was significantly related to rupture status, resection style, tumor site, tumor size, mitotic index, NIH risk grade and c-kit exons. According to Kaplan–Meier curve analysis, high expression of postoperative CA125 was significantly correlated with worse progression-free survival (PFS) and OS among patients with preoperative elevated CA125 level. Ultimately, Cox proportional regression model analysis revealed that increase of preoperative and concurrent postoperative CA125 concentration was an independent predictive factor for PFS. Conclusions The concurrent abnormality of serum CA125 before and after operation was an independent risk factor for GIST progression, suggesting its significance as a serum biomarker in the overall management of GIST patients.

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“…Moreover, Hu et al . [36]. found that the tumor markers before and after neoadjuvant chemotherapy have a discriminatory ability for patients with GC, and the normalization of tumor markers was associated with better survival.…”

Section: Discussionmentioning

confidence: 99%

A radiomics nomogram based on 18F-FDG PET/CT and clinical risk factors for the prediction of peritoneal metastasis in gastric cancer

Xie¹,

Xue²,

Bian³

et al. 2023

Nuclear Medicine Communications

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Purpose Peritoneal metastasis (PM) is usually considered an incurable factor of gastric cancer (GC) and not fit for surgery. The aim of this study is to develop and validate an 18F-FDG PET/CT-derived radiomics model combining with clinical risk factors for predicting PM of GC. Method In this retrospective study, 410 GC patients (PM − = 281, PM + = 129) who underwent preoperative 18F-FDG PET/CT images from January 2015 to October 2021 were analyzed. The patients were randomly divided into a training cohort (n = 288) and a validation cohort (n = 122). The maximum relevance and minimum redundancy (mRMR) and the least shrinkage and selection operator method were applied to select feature. Multivariable logistic regression analysis was preformed to develop the predicting model. Discrimination, calibration, and clinical usefulness were used to evaluate the performance of the nomogram. Result Fourteen radiomics feature parameters were selected to construct radiomics model. The area under the curve (AUC) of the radiomics model were 0.86 [95% confidence interval (CI), 0.81–0.90] in the training cohort and 0.85 (95% CI, 0.78–0.92) in the validation cohort. After multivariable logistic regression, peritoneal effusion, mean standardized uptake value (SUVmean), carbohydrate antigen 125 (CA125) and radiomics signature showed statistically significant differences between different PM status patients(P < 0.05). They were chosen to construct the comprehensive predicting model which showed a performance with an AUC of 0.92 (95% CI, 0.89–0.95) in the training cohort and 0.92 (95% CI, 0.86–0.98) in the validation cohort, respectively. Conclusion The nomogram based on 18F-FDG PET/CT radiomics features and clinical risk factors can be potentially applied in individualized treatment strategy-making for GC patients before the surgery.

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Prognostic significance of serum tumor marker normalization in the perioperative period for patients with advanced gastric cancer

Cited by 10 publications

References 12 publications

Deep learning radio-clinical signature for predicting neoadjuvant chemotherapy response and prognosis from pretreatment CT images of locally advanced gastric cancer patients

Deep learning radio-clinical signature for predicting neoadjuvant chemotherapy response and prognosis from pretreatment CT images of locally advanced gastric cancer patients

Prognostic significance of serum CA125 in the overall management for patients with gastrointestinal stromal tumors

A radiomics nomogram based on 18F-FDG PET/CT and clinical risk factors for the prediction of peritoneal metastasis in gastric cancer

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