A grading system for predicting the prognosis of gastric cancer with liver metastasis

Comprehensive treatment focusing on transarterial chemoembolization for postoperative liver metastasis in gastric cancer patients

OBJECTIVE

To investigate the clinical efficacy of comprehensive treatment focusing on transarterial chemoembolization (TACE) for postoperative liver metastasis in patients with gastric cancer and analyze the factors influencing prognosis.

METHODS

A retrospective study was conducted on 116 patients who developed liver metastasis after gastric cancer surgery and were admitted to Gansu Provincial Cancer Hospital between January 2018 and February 2020. The observation group, consisting of 62 patients, received TACE with fluorouracil (FU) + irinotecan (CPT-11) + oxaliplatin (OXA) and moderate lipiodol embolization. The control group, consisting of 54 patients, received systemic S-1 and Oxaliplatin regimen (SOX) alone. The clinical efficacy and incidence of adverse reactions were compared between the two groups. Liver function indicators, tumor markers, and immunoglobulin changes were analyzed in both groups. The 2-year survival rate of patients was analyzed using the Kaplan-Meier (K-M) curve. Lasso-Cox regression was used to identify independent prognostic factors affecting the 2-year survival rate. A Nomogram model was constructed to predict outcomes.

RESULTS

The overall clinical efficacy (P = 0.001) and objective response rate (ORR) (P = 0.001) were significantly lower in the control group compared to the observation group. No significant differences were found in ALT and AST changes between the two groups (P > 0.05). Post-treatment, CEA and CA19-9 levels were significantly lower, and IgG and IgM levels were significantly higher in the observation group (P < 0.001). There was no significant difference in the incidence of adverse reactions (P > 0.05). Lasso-Cox regression identified treatment plan, pathological differentiation, degree of liver metastasis, and pre-treatment CEA as independent prognostic factors for 2-year survival. Based on these, a Nomogram model was constructed. In the training group, the model had AUC values over 0.8 for 1- and 2-year survival rates, and in the validation group, the AUC was 0.765 and 0.687, respectively, indicating good predictive performance.

CONCLUSION

Compared to the conventional SOX regimen, comprehensive treatment focusing on TACE embolization for postoperative liver metastasis in gastric cancer is more effective and can improve survival rates.

Application of Survival Quilts for prognosis prediction of gastrectomy patients based on the Surveillance, Epidemiology, and End Results database and China National Cancer Center Gastric Cancer database

Objective

Accurate prognosis prediction is critical for individualized-therapy making of gastric cancer patients. We aimed to develop and test 6-month, 1-, 2-, 3-, 5-, and 10-year overall survival (OS) and cancer-specific survival (CSS) prediction models for gastric cancer patients following gastrectomy.

Methods

We derived and tested Survival Quilts, a machine learning-based model, to develop 6-month, 1-, 2-, 3-, 5-, and 10-year OS and CSS prediction models. Gastrectomy patients in the development set (n = 20,583) and the internal validation set (n = 5,106) were recruited from the Surveillance, Epidemiology, and End Results (SEER) database, while those in the external validation set (n = 6,352) were recruited from the China National Cancer Center Gastric Cancer (NCCGC) database. Furthermore, we selected gastrectomy patients without neoadjuvant therapy as a subgroup to train and test the prognostic models in order to keep the accuracy of tumor-node-metastasis (TNM) stage. Prognostic performances of these OS and CSS models were assessed using the Concordance Index (C-index) and area under the curve (AUC) values.

Results

The machine learning model had a consistently high accuracy in predicting 6-month, 1-, 2-, 3-, 5-, and 10-year OS in the SEER development set (C-index = 0.861, 0.832, 0.789, 0.766, 0.740, and 0.709; AUC = 0.784, 0.828, 0.840, 0.849, 0.869, and 0.902, respectively), SEER validation set (C-index = 0.782, 0.739, 0.712, 0.698, 0.681, and 0.660; AUC = 0.751, 0.772, 0.767, 0.762, 0.766, and 0.787, respectively), and NCCGC set (C-index = 0.691, 0.756, 0.751, 0.737, 0.722, and 0.701; AUC = 0.769, 0.788, 0.790, 0.790, 0.787, and 0.788, respectively). The model was able to predict 6-month, 1-, 2-, 3-, 5-, and 10-year CSS in the SEER development set (C-index = 0.879, 0.858, 0.820, 0.802, 0.784, and 0.774; AUC = 0.756, 0.827, 0.852, 0.863, 0.874, and 0.884, respectively) and SEER validation set (C-index = 0.790, 0.763, 0.741, 0.729, 0.718, and 0.708; AUC = 0.706, 0.758, 0.767, 0.766, 0.766, and 0.764, respectively). In multivariate analysis, the high-risk group with risk score output by 5-year OS model was proved to be a strong survival predictor both in the SEER development set (hazard ratio [HR] = 14.59, 95% confidence interval [CI]: 1.872-2.774, P < 0.001), SEER validation set (HR = 2.28, 95% CI: 13.089-16.293, P < 0.001), and NCCGC set (HR = 1.98, 95% CI: 1.617-2.437, P < 0.001). We further explored the prognostic value of risk score resulted 5-year CSS model of gastrectomy patients, and found that high-risk group remained as an independent CSS factor in the SEER development set (HR = 12.81, 95% CI: 11.568-14.194, P < 0.001) and SEER validation set (HR = 1.61, 95% CI: 1.338-1.935, P < 0.001).

Conclusion

Survival Quilts could allow accurate prediction of 6-month, 1-, 2-, 3-, 5-, and 10-year OS and CSS in gastric cancer patients following gastrectomy.

Risk stratification in gastric cancer lung metastasis: Utilizing an overall survival nomogram and comparing it with previous staging

BACKGROUND

Gastric cancer (GC) is prevalent and aggressive, especially when patients have distant lung metastases, which often places patients into advanced stages. By identifying prognostic variables for lung metastasis in GC patients, it may be possible to construct a good prediction model for both overall survival (OS) and the cumulative incidence prediction (CIP) plot of the tumour.

AIM

To investigate the predictors of GC with lung metastasis (GCLM) to produce nomograms for OS and generate CIP by using cancer-specific survival (CSS) data.

METHODS

Data from January 2000 to December 2020 involving 1652 patients with GCLM were obtained from the Surveillance, epidemiology, and end results program database. The major observational endpoint was OS; hence, patients were separated into training and validation groups. Correlation analysis determined various connections. Univariate and multivariate Cox analyses validated the independent predictive factors. Nomogram distinction and calibration were performed with the time-dependent area under the curve (AUC) and calibration curves. To evaluate the accuracy and clinical usefulness of the nomograms, decision curve analysis (DCA) was performed. The clinical utility of the novel prognostic model was compared to that of the 7th edition of the American Joint Committee on Cancer (AJCC) staging system by utilizing Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI). Finally, the OS prognostic model and Cox-AJCC risk stratification model modified for the AJCC system were compared.

RESULTS

For the purpose of creating the OS nomogram, a CIP plot based on CSS was generated. Cox multivariate regression analysis identified eleven significant prognostic factors (P < 0.05) related to liver metastasis, bone metastasis, primary site, surgery, regional surgery, treatment sequence, chemotherapy, radiotherapy, positive lymph node count, N staging, and time from diagnosis to treatment. It was clear from the DCA (net benefit > 0), time-dependent ROC curve (training/validation set AUC > 0.7), and calibration curve (reliability slope closer to 45 degrees) results that the OS nomogram demonstrated a high level of predictive efficiency. The OS prediction model (New Model AUC = 0.83) also performed much better than the old Cox-AJCC model (AUC difference between the new model and the old model greater than 0) in terms of risk stratification (P < 0.0001) and verification using the IDI and NRI.

CONCLUSION

The OS nomogram for GCLM successfully predicts 1- and 3-year OS. Moreover, this approach can help to appropriately classify patients into high-risk and low-risk groups, thereby guiding treatment.

A bibliometric analysis of gastric cancer liver metastases: advances in mechanisms of occurrence and treatment options

BACKGROUND

Gastric cancer (GC) is the fifth most commonly diagnosed cancer worldwide, and its poor prognosis is predominantly attributed to distant metastasis. Liver is the primary site of GC metastasis. However, there is no universally approved treatment regimen for liver metastasis in GC. The aim of this article is to review the current research status and trends of liver metastasis of gastric cancer worldwide.

METHODS

We utilized the Web of Science Core Collection database to identify articles on liver metastasis from GC published between 2000 and 2022. We used bibliometric methods to analyze authors, institutions, countries, journals, and references through CiteSpace and VOSviewer. A total of 1,003 articles were included in this study.

RESULTS

Japan published the most articles in the field, followed by China. Nagoya University is the leading institution in the field of liver metastases in GC. Yasuhiro Kodera from Japan has made significant achievements in this area. We identified Gastric Cancer to be the most influential journal in this field. Using cluster analysis, the keywords were divided into four major clusters:(1) the molecular mechanism of gastric cancer liver metastasis (2) prognosis (3) liver resection (4) chemotherapy.

CONCLUSION

Our study systematically summarizes the results of gastric cancer liver metastasis research from 2000 to 2022 and describes and predicts research hotspots and trends on a global scale. Research on the molecular mechanisms of gastric cancer liver metastasis will become a hot topic in the future, and the expansion of the surgical treatment scope and the advancement of translational therapy will benefit more patients.

Analysis of Related Risk Factors and Prognostic Factors of Gastric Cancer with Liver Metastasis: A SEER and External Validation Based Study

Background

Gastric cancer (GC) has a poor prognosis, particularly in patients with liver metastasis (LM). This study aims to identify relevant factors associated with the occurrence of LM in GC patients and factors influencing the prognosis of gastric cancer with liver metastasis (GCLM) patients, in addition to developing diagnostic and prognostic nomograms specifically.

Patients and Methods

Overall, 6184 training data were from the Surveillance, Epidemiology, and End Results (SEER) database from 2011 to 2015. 1527 validation data were from our hospital between January 2018 and December 2022. Logistic regression was used to identify the risk factors associated with the occurrence of LM in GC patients, Cox regression was used to confirm the prognostic factors of GCLM patients. Two nomogram models were established to predict the risk and overall survival (OS) of patients with GCLM. The performance of the two models was evaluated using the area under the curve (AUC), concordance index (C-index), and calibration curves.

Results

A nomogram included five independent factors from multivariate logistic regression: sex, lymph node removal, chemotherapy, T stage and N stage were constructed to calculate the possibility of LM. Internal and external verifications of AUC were 0.786 and 0.885, respectively. The other nomogram included four independent factors from multivariate Cox regression: surgery at primary site, surgery at other site, chemotherapy, and N stage were constructed to predict OS. C-index for internal and external validations were 0.714 and 0.702, respectively, and the calibration curves demonstrated the robust discriminative ability of the models.

Conclusion

Based on the SEER database and validation data, we defined effective nomogram models to predict risk and OS in patients with GCLM. They have important value in clinical decision-making and personalized treatment.

Usefulness of [68Ga]FAPI-04 and [18F]FDG PET/CT for the detection of primary tumour and metastatic lesions in gastrointestinal carcinoma: a comparative study

OBJECTIVE

To assess and compare the diagnostic performance of gallium-68-labelled fibroblast activation protein inhibitor ([⁶⁸Ga]FAPI-04) and fluorine-18 fluorodeoxyglucose ([¹⁸F]FDG) positron emission tomography/computed tomography (PET/CT) in gastrointestinal cancer.

METHODS

Fifty-one patients who underwent both [¹⁸F]FDG and [⁶⁸Ga]FAPI-04 PET/CT for initial staging or restaging were enrolled. Histopathological findings, typical radiological appearances, and clinical imaging follow-up were used as the reference standard. The diagnostic performance of the two tracers was calculated and compared. The maximum standardised uptake value (SUVmax), mean SUV (SUVmean), tumour-to-mediastinal blood pool ratio (TBR), and tumour-to-liver ratio (TLR) of primary and metastatic lesions were measured and compared between two imaging modalities.

RESULTS

In patient-based analysis, [⁶⁸Ga]FAPI-04 showed much better diagnostic sensitivity than [¹⁸F]FDG in detecting primary tumour (94.44% [17/18] vs. 61.11% [11/18]), postoperative recurrence and metastases (95.65% [22/23] vs. 69.57% [16/23]), and peritoneal carcinomatosis (100% [28/28] vs. 60.71% [17/28]) (all p < 0.05). In lesion-based analysis, [⁶⁸Ga]FAPI-04 showed higher sensitivity than [¹⁸F]FDG for detecting lymph node metastases. In peritoneal carcinomatosis, the median SUVmax (12.12 vs. 7.18) and SUVmean (6.84 vs. 4.11) with [⁶⁸Ga]FAPI-04 were significantly higher than those with [¹⁸F]FDG (all p < 0.005). The TBR and TLR of [⁶⁸Ga]FAPI-04 were significantly higher than those of [¹⁸F]FDG for detecting primary tumour, lymph node, liver, and peritoneal metastases (all p < 0.005). Therapeutic management changed in 13 patients according to [⁶⁸Ga]FAPI-04 PET/CT compared with conventional imaging.

CONCLUSIONS

[⁶⁸Ga]FAPI-04 is superior to [¹⁸F]FDG PET/CT for detecting primary tumour, postoperative recurrence and metastasis, and peritoneal carcinomatosis in gastrointestinal cancer.

KEY POINTS

• [⁶⁸Ga]FAPI-04 PET/CT showed significantly higher sensitivity than [¹⁸F]FDG PET/CT in the detection of primary tumour and postoperative recurrence and metastasis in patients with gastrointestinal carcinoma. • [⁶⁸Ga]FAPI-04 PET/CT had obvious advantages over [¹⁸F]FDG PET/CT in the detection of peritoneal carcinomatosis from gastrointestinal carcinoma with a much higher FAPI uptake value, TBR, and TLR. • Although the median SUVmax and SUVmean of [⁶⁸Ga]FAPI-04 were similar to those of [¹⁸F]FDG for the primary tumour, lymph node metastases, and liver metastases in gastrointestinal carcinoma, the TBR and TLR of the SUVmax and SUVmean were significantly higher on [⁶⁸Ga]FAPI-04 PET/CT, causing the lesions to be displayed more clearly.