A New Metastatic Lymph Node Classification-based Survival Predicting Model in Patients With Small Bowel Adenocarcinoma: A Derivation and Validation Study

Yang

et al. 2019

Preprint

Background: Surgery is the only way to cure gastric adenocarcinoma (GAC), and chemotherapy is the basic adjuvant management for GAC. A prognostic model for predicting the individual disease-specific survival (DSS) rates of GAC patients who receive surgery and chemotherapy has not been established. Objective: We aimed to establish a survival nomogram for GAC patients who receive surgery and chemotherapy. Methods: We identified 5764 GAC patients who had received surgery and chemotherapy from the SEER (Surveillance, Epidemiology, and End Results) database. Approximately 80% (n=4034) of the included patients were randomly assigned to the training set, and the remaining patients (n=1729) were assigned to the external validation set. Nomogram was established by the training set and validated by the validation set. Results: Based on the results of a multivariate analysis, a nomogram was developed that encompassed age at diagnosis, number of regional lymph nodes examined, number of positive regional lymph nodes, sex, race, grade, derived AJCC stage, summary stage, and radiotherapy status. The C-index (Harrell's concordance index) of the model was higher than that of the traditional seventh AJCC staging system (0.707 vs 0.661). Calibration plots of the nomogram showed that the probability of DSS optimally corresponded to the survival rate.Integrated discrimination improvement (IDI) and categorical net reclassification improvement (NRI) showed visible improvement. IDI for 3-, 5-and 10-year DSS were 0.058, 0.059 and 0.058, respectively (P>0.05), and NRI for 3-, 5-and 10-year DSS were 0.380 (95% CI=0.316-0.470), 0.407 (95% CI=0.350-0.505), and 0.413 (95% CI=0.336-0.519), respectively. Decision curve analysis supported that the constructed nomogram was superior to the AJCC staging system. Conclusion: The proposed nomogram provides more-reliable DSS predictions for GAC patients who receive surgery and chemotherapy in the general population. According to validation, the new nomogram will be beneficial in facilitating individualized survival predictions and useful when performing clinical decision-making for GAC patients who receive surgery and chemotherapy.

Section: Discussionsupporting

confidence: 68%

Nomogram for predicting the survival of gastric adenocarcinoma patients who receive surgery and chemotherapy

Yang

et al. 2019

Preprint

“…The NRI and IDI are more sensitive indicators than the C-index, and the NRI indicated that the proposed model reclassified the risk probabilities better than did the AJCC staging system, while the IDI demonstrated the superior ability of the constructed nomogram to distinguish cases compared with the AJCC staging system. Numerous previous studies have found benefits of applying DCA (29)(30)(31)(32)(33), and the results of the current study showed that the 3-, 5-, and 10year DCA curves displayed net benefits larger than those of the AJCC staging system, both in the training set and validation set (Figure 4).…”

Section: Discussionsupporting

confidence: 63%

Nomogram for predicting the survival of gastric adenocarcinoma patients who receive surgery and chemotherapy

Yang

et al. 2019

Preprint

Background: Surgery is the only way to cure gastric adenocarcinoma (GAC), and chemotherapy is the basic adjuvant management for GAC. A significant prognostic nomogram for predicting the respective disease-specific survival (DSS) rates of GAC patients who receive surgery and chemotherapy has not been established.Objective: We were planning to establish a survival nomogram model for GAC patients who receive surgery and chemotherapy. Methods: We identified 5764 GAC patients who had received surgery and chemotherapy from the record of Surveillance, Epidemiology, and End Results (SEER ) database. About 70% ( n =4034) of the chosen GAC patients were randomly assigned to the training set, and the rest of the included ones ( n =1729) were assigned to the external validation set. A prognostic nomogram was constructed by the training set and the predictive accuracy of it was validated by the validation set. Results: Based on the outcome of a multivariate analysis of candidate factors, a nomogram was developed that encompassed age at diagnosis, number of regional lymph nodes examined after surgery, number of positive regional lymph nodes , sex , race, grade, derived AJCC stage, summary stage , and radiotherapy status. The C-index (Harrell’s concordance index) of the nomogram model was some larger than that of the traditional seventh AJCC staging system (0.707 vs 0.661). Calibration plots of the constructed nomogram displayed that the probability of DSS commendably accord with the survival rate. Integrated discrimination improvement (IDI) revealed obvious increase and categorical net reclassification improvement (NRI) showed visible enhancement. IDI for 3-, 5- and 10- year DSS were 0.058, 0.059 and 0.058, respectively ( P >0.05), and NRI for 3-, 5- and 10- year DSS were 0.380 (95% CI=0.316–0.470), 0.407 (95% CI=0.350–0.505), and 0.413 (95% CI=0.336–0.519), respectively. Decision curve analysis (DCA) proved that the constructed nomogram was preferable to the AJCC staging system. Conclusion: The constructed nomogram supplies more credible DSS predictions for GAC patients who receive surgery and chemotherapy in the general population. According to validation, the new nomogram will be beneficial in facilitating individualized survival predictions and useful when performing clinical decision-making for GAC patients who receive surgery and chemotherapy.

“…Up to now, the American Joint Committee on Cancer (AJCC) staging system has always been broadly adopted for cancer management, including BC . However, the current TNM Classification method cannot perfectly provide accurate information to predict patients’ prognosis . Then some patients with BC received unnecessary or excessive medication, while others may be faced with recurrence or metastasis due to lack of appropriate treatment .…”

Section: Introductionmentioning

confidence: 99%

Identification of a 4‐mRNA metastasis‐related prognostic signature for patients with breast cancer

Xie

J Cellular Molecular Medi

Shi

et al. 2018

Metastasis‐related mRNAs have showed great promise as prognostic biomarkers in various types of cancers. Therefore, we attempted to develop a metastasis‐associated gene signature to enhance prognostic prediction of breast cancer (BC) based on gene expression profiling. We firstly screened and identified 56 differentially expressed mRNAs by analysing BC tumour tissues with and without metastasis in the discovery cohort (GSE102484, n = 683). We then found 26 of these differentially expressed genes were associated with metastasis‐free survival (MFS) in the training set (GSE20685, n = 319). A metastasis‐associated gene signature built using a LASSO Cox regression model, which consisted of four mRNAs, can classify patients into high‐ and low‐risk groups in the training cohort. Patients with high‐risk scores in the training cohort had shorter MFS (hazard ratio [HR] 3.89, 95% CI 2.53‐5.98; P < 0.001), disease‐free survival (DFS) (HR 4.69, 2.93‐7.50; P < 0.001) and overall survival (HR 4.06, 2.56‐6.45; P < 0.001) than patients with low‐risk scores. The prognostic accuracy of mRNAs signature was validated in the two independent validation cohorts (GSE21653, n = 248; GSE31448, n = 246). We then developed a nomogram based on the mRNAs signature and clinical‐related risk factors (T stage and N stage) that predicted an individual's risk of disease, which can be assessed by calibration curves. Our study demonstrated that this 4‐mRNA signature might be a reliable and useful prognostic tool for DFS evaluation and will facilitate tailored therapy for BC patients at different risk of disease.