Application value of nomogram and prognostic factors of gastric cancer patients who underwent D2 radical lymphadenectomy

Mu, Guang-Chuan; Huang, Yuan; Liu, Zhiming; Wu, Xianghua; Qin, Xin‐Gan; Chen, Zhibai

doi:10.1186/s12876-019-1098-6

Cited by 12 publications

(15 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…More recently, efforts have increasingly focused on developing improved prognostic systems to offer a more accurate prediction of long-term prognosis and risk of recurrence [15,16]. In particular, nomograms have been increasingly adopted within the oncological field for a variety of tumors.…”

Section: Introductionmentioning

confidence: 99%

A nomogram to predict overall survival and disease-free survival after curative-intent gastrectomy for gastric cancer

et al. 2021

View full text Add to dashboard Cite

An individual prediction of DFS and OS may be useful after surgery for gastric cancer to inform patients and to guide the clinical management. Patients who underwent curative-intent resection for gastric cancer between January 2010 and May 2020 at a single Italian institution were identified. Variables associated with OS and DFS were recorded and analysed according to univariable and multivariable Cox models. Nomograms predicting OS and DFS were built according to variables resulting from multivariable Cox models. Discrimination ability was calculated using the Harrell’s Concordance Index. Overall, 168 patients underwent curative-intent resection. Nomograms to predict OS were developed including age, tumor size, tumor location, T stage, N stage, M stage and post-operative complications, while nomogram to predict DFS includes Lauren classification, and lymph node ratio (LNR). On internal validation, both nomograms demonstrated a good discrimination with a Harrell’s C-index of 0.77 for OS and 0.71 for DFS. The proposed nomogram to predict DFS and OS after curative-intent surgery for gastric cancer showed a good discrimination on internal validation, and may be useful to guide clinician decision-making, as well help identify patients with high-risk of recurrence or with a poor estimated survival.

show abstract

Section: Introductionmentioning

confidence: 99%

A nomogram to predict overall survival and disease-free survival after curative-intent gastrectomy for gastric cancer

et al. 2021

View full text Add to dashboard Cite

show abstract

“…LN metastasis is involved in GC prognostic outcomes [ 2 , 3 ]. Precise preoperative determination of LN involvement in GC is pivotal for clinical decision-making.…”

Section: Discussionmentioning

confidence: 99%

“…Globally, gastric cancer (GC) is the 5th most prevalent cancer type and the 3rd highest cause of cancer-associated mortalities [ 1 ]. Some studies demonstrated that Lymph node (LN) metastasis is an independent risk index for poor prognosis of GC [ 2 , 3 ]. Precise and exact preoperative identification of LN involvement is important in informing therapeutic decisions for GC patients [ 4 , 5 ].…”

Section: Introductionmentioning

confidence: 99%

A genomic-clinicopathologic Nomogram for the preoperative prediction of lymph node metastasis in gastric cancer

et al. 2021

View full text Add to dashboard Cite

Background Preoperative evaluation of lymph node (LN) state is of pivotal significance for informing therapeutic decisions in gastric cancer (GC) patients. However, there are no non-invasive methods that can be used to preoperatively identify such status. We aimed at developing a genomic biosignature based model to predict the possibility of LN metastasis in GC patients. Methods We used the RNA profile retrieving strategy and performed RNA expression profiling in a large GC cohort (GSE62254, n = 300) from Gene Expression Ominus (GEO). In the exploratory stage, 300 GC patients from GSE62254 were involved and the differentially expressed RNAs (DERs) for LN-status were determined using the R software. GC samples in GSE62254 were randomly allocated into a learning set (n = 210) and a verification set (n = 90). By using the Least absolute shrinkage and selection operator (LASSO) regression approach, a set of 23-RNA signatures were established and the signature based nomogram was subsequently built for distinguishing LN condition. The diagnostic efficiency, as well as the clinical performance of this model were assessed using the decision curve analysis (DCA). Metascape was used for bioinformatic analysis of the DERs. Results Based on the genomic signature, we established a nomogram that robustly distinguished LN status in the learning (AUC = 0.916, 95% CI 0.833–0.999) and verification sets (AUC = 0.775, 95% CI 0.647–0.903). DCA demonstrated the clinical value of this nomogram. Functional enrichment analysis of the DERs was performed using bioinformatics methods which revealed that these DERs were involved in several lymphangiogenesis-correlated cascades. Conclusions In this study, we present a genomic signature based nomogram that integrates the 23-RNA biosignature based scores and Lauren classification. This model can be utilized to estimate the probability of LN metastasis with good performance in GC. The functional analysis of the DERs reveals the prospective biogenesis of LN metastasis in GC.

show abstract

“…LN metastasis is among the primary conditions that in uence the prognosis of GC [2,3]. Precise preoperative determination of LN participation in GC is pivotal for clinical decision-making.…”

Section: Discussionmentioning

confidence: 99%

“…Gastric cancer (GC) constitutes the 5th most frequent cancer and the 3rd top cause of cancer-associated mortality globally [1]. Some studies demonstrated that LN metastasis is an independent risk index for poor prognosis of GC [2,3]. Precise and exact preoperative identi cation of LN involvement is of vital signi cance for treatment strategy decisions in patients with GC [4,5].…”

Section: Introductionmentioning

confidence: 99%

A Genomic-Clinicopathologic Nomogram for the Preoperative Prediction of Lymph Node Metastasis in Gastric Cancer

Zhong

Xuan

Qian

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Preoperative evaluation of the lymph node (LN) state is of pivotal significance for therapy strategy decisions in gastric cancer (GC) patients. However, there is lack of noninvasive method that can identify such status preoperatively. We aimed at developing a genomic biosignature based model to forecast the possibility of LN metastasis in GC patients.Methods: We employed the RNA profile retrieving strategy and conducted RNA expression profiling in a large GC cohort (GSE62254, n = 300) from Gene Expression Ominus (GEO). In the exploratory stage, 300 GC patients from GSE62254 were involved and the differentially expressed RNAs (DERs) for LN-status were determined using R software. The GC samples in GSE62254 were randomly divided into a learning set (n = 210) and a verification set (n = 90). By performing the Least absolute shrinkage and selection operator (LASSO) regression approach, a set of 23-RNA signature was established and the signature based nomogram was subsequently built for distinguishing LN condition. The diagnostic effectiveness of this model was assessed, as well as the clinical performance subsequently assessed using the decision curve analysis (DCA). Metascape was used for bioinformatic analysis of the DERsResults: Based on this genomic signature, we established a nomogram which robustly distinguished LN status in the learning (AUC = 0.916, 95% CI 0.833–0.999) and verification sets (AUC = 0.775, 95% CI 0.647–0.903). DCA demonstrated the clinical value of this nomogram. Functional enrichment analysis of the DERs was conducted using bioinformatics methods which posited that these DERs were involved with several lymphangiogenesis-correlated cascades.Conclusions: Here, we present a genomic signature based nomogram that integrates the 23-RNA biosignature based scores and Lauren classification. This model can be readily utilized to estimate the possibility of LN metastasis with good performance in GC. The uncovering of the DERs reveals the prospective biogenesis of LN metastasis in GC.

show abstract

Application value of nomogram and prognostic factors of gastric cancer patients who underwent D2 radical lymphadenectomy

Cited by 12 publications

References 16 publications

A nomogram to predict overall survival and disease-free survival after curative-intent gastrectomy for gastric cancer

A nomogram to predict overall survival and disease-free survival after curative-intent gastrectomy for gastric cancer

A genomic-clinicopathologic Nomogram for the preoperative prediction of lymph node metastasis in gastric cancer

A Genomic-Clinicopathologic Nomogram for the Preoperative Prediction of Lymph Node Metastasis in Gastric Cancer

Contact Info

Product

Resources

About