Development and Validation of a Prognostic Nomogram for Gastric Signet Ring Cell Carcinoma: A Multicenter Population-Based Study

Zhang, Shuairan; Liu, Yang; Jiao, Zihan; Li, Zenan; Wang, Jin; Li, Ce; Qu, Xiujuan; Xu, Ling

doi:10.3389/fonc.2021.603031

Cited by 10 publications

(6 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, there are also studies reporting that histological grade is not a prognostic factor in signet-ring cell gastric carcinomas. 18 In our study, we observed that high histological grade, depth of infiltration, and lymph node metastasis adversely affected the mean survival.…”

Section: Discussionmentioning

confidence: 61%

Factors affecting prognosis in signet ring cell gastric cancers with expanded lymph node dissection; high volume centre experience

2022

View full text Add to dashboard Cite

Background: Signet ring cell gastric cancer differs from gastric adenocarcinoma in terms of demographic and clinical features, age, gender, tumour grade and stage. In this study, we aimed to evaluate the clinical features and overall survival of gastric signet ring cell carcinoma and the prognostic factors affecting survival.Methods: We analysed 138 patients who were operated on with the diagnosis of signet ring cell gastric cancer. The univariant and multivariate hazard ratios of these parameters were analysed and the factors affecting the long-term average survival outcomes were investigated.Results: We performed Cox regression univariate analysis to investigate the effects of clinicopathological factors on mean survival follow-up in signet ring cell gastric cancer. As age increases, the mean survival follow-up period decreases. This relationship is also statistically significant. Mean survival follow-up for the open technique was lower than for laparoscopic procedures. The mean survival follow-up time of patients with positive perineural invasion (PNI) and lymphovascular invasion (LVI) is lower than patients with negative LVI and PNI. We did not find a significant relationship between the hazard ratios (HRs) of tumour markers and systemic inflammatory response parameters. However, we found a significant relationship between the increase in fibrinogen value and HR.Conclusions: We investigated the clinicopathological features of nonmetastatic signet ring cell gastric carcinomas and identified predictors of long survival. Age, lymphovascular and perineural invasion, open surgery, higher tumor infiltration, and lymph node involvement were independent predictors of shorter survival times in nonmetastatic signet ring cell gastric cancers.

show abstract

Section: Discussionmentioning

confidence: 61%

Factors affecting prognosis in signet ring cell gastric cancers with expanded lymph node dissection; high volume centre experience

2022

View full text Add to dashboard Cite

show abstract

“…The studies carried out by Wang et al, Zhang et al, and Guo et al also had similar problems [ 13 , 14 , 28 ]. Wei et al collected 1,030 patients from the SEER database and constructed CSS prognostic model.…”

Section: Discussionmentioning

confidence: 88%

“…Accurate prediction is essential for the survival of patients with nonmetastatic GSRC and medical decisionmaking. Previous regression analysis-based models have been developed to predict the survival of patients with non-metastatic GSRC [13][14][15]. Nonetheless, these models are commonly based on the assumption that each parameter, and the survival outcomes of GSRC were linear dependent (regression model).…”

Section: Introductionmentioning

confidence: 99%

Predicting Overall Survival in Patients with Nonmetastatic Gastric Signet Ring Cell Carcinoma: A Machine Learning Approach

Chen

Lin

et al. 2022

Computational and Mathematical Methods in Medicine

View full text Add to dashboard Cite

Background and Aims. Accurate prediction is essential for the survival of patients with nonmetastatic gastric signet ring cell carcinoma (GSRC) and medical decision-making. Current models rely on prespecified variables, limiting their performance and not being suitable for individual patients. Our study is aimed at developing a more precise model for predicting 1-, 3-, and 5-year overall survival (OS) in patients with nonmetastatic GSRC based on a machine learning approach. Methods. We selected 2127 GSRC patients diagnosed from 2004 to 2014 from the Surveillance, Epidemiology, and End Results (SEER) database and then randomly partitioned them into a training and validation cohort. We compared the performance of several machine learning-based models and finally chose the eXtreme gradient boosting (XGBoost) model as the optimal method to predict the OS in patients with nonmetastatic GSRC. The model was assessed using the receiver operating characteristic curve (ROC). Results. In the training cohort, for predicting OS rates at 1-, 3-, and 5-year, the AUCs of the XGBoost model were 0.842, 0.831, and 0.838, respectively, while in the testing cohort, the AUCs of 1-, 3-, and 5-year OS rates were 0.749, 0.823, and 0.829, respectively. Besides, the XGBoost model also performed better when compared with the American Joint Committee on Cancer (AJCC) stage. The performance for this model was stably maintained when stratified by age and ethnicity. Conclusion. The XGBoost-based model accurately predicts the 1-, 3-, and 5-year OS in patients with nonmetastatic GSRC. Machine learning is a promising way to predict the survival outcomes of tumor patients.

show abstract

“…From the current researches on SRCC, it is known that a variety of prognostic factors can affect the survival rate of SRCC patients: age, tumor size, tumor stage, radiotherapy, chemotherapy, and surgical resection [ 9 , 10 ]. Among these factors, surgical resection is the most effective treatment for SRCC patients [ 8 ].…”

Section: Discussionmentioning

confidence: 99%

A population-based predictive model to identify patients with signet ring cell carcinoma of the stomach who are most suitable for primary tumor resection

Zou

Gan

et al. 2022

World J Surg Onc

View full text Add to dashboard Cite

Background Though the survival benefit of primary tumor operation for patients with signet ring cell carcinoma of the stomach is known, the specific characteristics of those patients who would profit from the operation are yet to be determined. To this end, a predictive model was developed to identify the conjecture that the survival profit from primary tumor operation would only be obtained by patients. Method The clinical data of the patients with signet ring cell carcinoma of the stomach were obtained from the Surveillance, Epidemiology, and End Results database, and then divided into operation and no-operation groups based on whether the patients underwent the primary tumor operation. To remove the confounding factors, propensity score matching was employed, and it was hypothesized that the patients who had been operated on and lived a longer life than the median cancer-specific survival time of those who hadn’t must have profited from the surgery. To discuss the independent factors of cancer-specific survival time in the beneficial group and the non-beneficial group, the Cox model was used, and based on the various vital predictive factors, a nomogram was drawn using logistic regression. Result The number of eligible patients was 12,484, with 43.9% (5483) of them having received surgery. After employing propensity score matching, the cancer-specific survival time of the operation group was found to be apparently longer (median: 21 vs. 5 months; p < 0.001) than the no-operation group. In the operation group, 4757 (86.7%) of the patients lived longer than five months (beneficial group). The six indexes (beneficial and non-beneficial group) included gender, age, Tumor Node Metastasis stage, histologic type, differentiation grade, and tumor position, and were used as predictors to draw the nomogram. The nomogram was used to divide the patients who had taken operations into two groups: the beneficial operation group and the non-beneficial operation group. The beneficial operation group, it was found, survived longer than the non-beneficial operation group (median cancer-specific survival time: 28 vs. 3 months, p < 0.001). Moreover, there was we could tell little difference in survival between the two groups (median cancer-specific survival time: 3 vs. 5 months). Conclusions The predictive model created to select suitable candidates for surgical treatment from patients with signet ring carcinoma of the stomach could be adopted to identify certain patients benefiting from the primary tumor operation.

show abstract

Development and Validation of a Prognostic Nomogram for Gastric Signet Ring Cell Carcinoma: A Multicenter Population-Based Study

Cited by 10 publications

References 34 publications

Factors affecting prognosis in signet ring cell gastric cancers with expanded lymph node dissection; high volume centre experience

Factors affecting prognosis in signet ring cell gastric cancers with expanded lymph node dissection; high volume centre experience

Predicting Overall Survival in Patients with Nonmetastatic Gastric Signet Ring Cell Carcinoma: A Machine Learning Approach

A population-based predictive model to identify patients with signet ring cell carcinoma of the stomach who are most suitable for primary tumor resection

Contact Info

Product

Resources

About