Survival after Gastrectomy in Node-Negative Gastric Cancer: A Review and Meta-Analysis of Prognostic Factors

Zhou, Yanming; Yu, Feng; Wu, Lupeng; Ye, Feng; Zhang, Leilei; Li, Yumin

doi:10.12659/msm.893856

Cited by 17 publications

(11 citation statements)

References 37 publications

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“…This can be regarded as indirect evidence for their predictive power in gastric cancer prognosis. Direct evidence, i.e., magnitude of their association with the outcome, such as hazard ratio, can be found in previous systematic reviews and meta-analyses [46, 47]. Therefore, we suggest that future model development, if necessary, to build upon these existing evidence.…”

Section: Discussionmentioning

confidence: 79%

Prognostic Models for Predicting Overall Survival in Patients with Primary Gastric Cancer: A Systematic Review

Feng

May

Ingle

et al. 2019

BioMed Research International

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Background. This study was designed to review the methodology and reporting of gastric cancer prognostic models and identify potential problems in model development. Methods. This systematic review was conducted following the CHARMS checklist. MEDLINE and EMBASE were searched. Information on patient characteristics, methodological details, and models’ performance was extracted. Descriptive statistics was used to summarize the methodological and reporting quality. Results. In total, 101 model developments and 32 external validations were included. The median (range) of training sample size, number of death, and number of final predictors were 360 (29 to 15320), 193 (14 to 9560), and 5 (2 to 53), respectively. Ninety-one models were developed from routine clinical data. Statistical assumptions were reported to be checked in only nine models. Most model developments (94/101) used complete-case analysis. Discrimination and calibration were not reported in 33 and 55 models, respectively. The majority of models (81/101) have never been externally validated. None of the models have been evaluated regarding clinical impact. Conclusions. Many prognostic models have been developed, but their usefulness in clinical practice remains uncertain due to methodological shortcomings, insufficient reporting, and lack of external validation and impact studies. Impact. Future research should improve methodological and reporting quality and emphasize more on external validation and impact assessment.

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Section: Discussionmentioning

confidence: 79%

Prognostic Models for Predicting Overall Survival in Patients with Primary Gastric Cancer: A Systematic Review

Feng

May

Ingle

et al. 2019

BioMed Research International

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“…Previous reports consistently found that the depth of invasion was an independent predictor in node-negative GC that included early gastric cancer (EGC) [7] . Furthermore, there is no consensus about other clinicopathologic factors of the prognostic signi cance, including patient gender, age, tumor location, tumor size, histological grading, Lauren type and Lymphatic vessel invasion [8,9] . In addition, little is known about the recurrent patterns of node-negative AGC after D2 curative resection.…”

Section: Introductionmentioning

confidence: 99%

Recurrence in node-negative advanced gastric cancer with novel clinical and pathologic findings

Chen¹,

Xu²,

J³

et al. 2020

Preprint

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Abstract Background Node-negative gastric cancer patients carry a better prognosis than node-positive. However, a subset of these patients eventually died due to the high recurrence rate of recurrence. This study investigated the clinic-pathologic factors for recurrent patterns and prognosis. Methods The detailed medical records of 947 gastric cancer patients who underwent gastrectomy from the prospectively collected database of the Gastrointestinal Surgery Department of the First Affiliated Hospital of Zhejiang Chinese Medical University From January 2012 to December 2014 were analyzed retrospectively. Results Tumor size, tumor invasion, histological grading were the predictive factors for locoregional recurrence. Tumor invasion, histological grading, Lauren type and lymphatic vessel invasion resulted significantly in predicting peritoneal recurrence. Two parameters, tumor invasion and lymphatic vessel invasion, were significantly associated with hematogenous spread. The combinatorial biomarker of positive for both Ki67 and P53 was significantly associated with recurrence-free survival (RFS) (P = 0.037). Histological grading (P = 0.020), tumor invasion (P = 0.007) and lymphatic vessel invasion (P = 0.012) were independent factors related to overall survival (OS) in node-negative advanced gastric cancer patients. Conclusion The reported clinicopathologic factors for different recurrence patterns and the prognostic factors of RFS and OS should be considered to guide clinicians choose appropriate postoperative treatment strategy and construct individual follow-up schedule to improve prognosis of node-negative gastric cancer.

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“…The TNM classification consists of tumor depth, nodal and distant metastasis with distant metastasis as the strongest prognostic marker [ 4 ]. The classification also includes peritumoral lymphatic and venous invasions, which are linked to aggressive tumor behavior in gastric cancer [ 5 , 6 ]. Additional biomolecular prognostic markers are currently being investigated by several clinical researchers.…”

Section: Introductionmentioning

confidence: 99%

Expression of gremlin1 in gastric cancer and its clinical significance

et al. 2018

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As an antagonist of bone morphogenetic proteins (BMPs), 2, 4 and 7, gremlin1 plays a role in regulating organogenesis, tissue differentiation and angiogenesis. However, there is little information regarding gremlin1 in gastrointestinal cancer. We attempted to clarify how gremlin1 expression affects the clinical features and biological properties of gastric cancer. A total of 232 gastric cancer patients who received R0 gastrectomy at Kagoshima University Hospital were enrolled. Gremlin1 expression in gastric cancer was detected by immunohistochemical and western blotting methods. Correlations between clinicopathological parameters and gremlin1 expression were analyzed. Gremlin1 was identified in the cytoplasm and nucleus of all gastric cancer cell lines and some regions of surgical specimens of gastric cancer. One hundred and seventeen of the 232 patients (50.4%) were classified as gremlin1-positive based on gremlin1 expression. Gremlin1 positivity was correlated with shallower tumor depth, smaller tumor size, less nodal involvement and vessel invasion (p < 0.05). The 5-year survival rate of the gremlin1-positive group was 81%, which was significantly higher than the gremlin1-negative group (p < 0.01). Multivariate analysis revealed that gremlin1 was not selected as an independent prognostic marker. Gremlin1 expression in gastric cancer may be a useful prognostic marker that is involved with the BMP signaling pathway. Furthermore, gremlin1 may have clinical use as a diagnostic and treatment tool.

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Survival after Gastrectomy in Node-Negative Gastric Cancer: A Review and Meta-Analysis of Prognostic Factors

Cited by 17 publications

References 37 publications

Prognostic Models for Predicting Overall Survival in Patients with Primary Gastric Cancer: A Systematic Review

Prognostic Models for Predicting Overall Survival in Patients with Primary Gastric Cancer: A Systematic Review

Recurrence in node-negative advanced gastric cancer with novel clinical and pathologic findings

Expression of gremlin1 in gastric cancer and its clinical significance

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