Dataset Information

Neoadjuvant chemotherapy for advanced gastric cancer: a meta-analysis.

ABSTRACT: To study the value of neoadjuvant chemotherapy (NAC) for advanced gastric cancer by performing a meta-analysis of the published studies.All published controlled trials of NAC for advanced gastric cancer vs no therapy before surgery were searched. Studies that included patients with metastases at enrollment were excluded. Databases included Cochrane Library of Clinical Comparative Trials, MEDLINE, Embase, and American Society of Clinical Oncology meeting abstracts from 1978 to 2010. The censor date was up to April 2010. Primary outcome was the odds ratio (OR) for improving overall survival rate of patients with advanced gastric cancer. Secondary outcome was the OR for down-staging tumor and increasing R0 resection in patients with advanced gastric cancer. Safety analyses were also performed. All calculations and statistical tests were performed using RevMan 5.0 software.A total of 2271 patients with advanced gastric cancer enrolled in 14 trials were divided into NAC group (n = 1054) and control group (n = 1217). The patients were followed up for a median time of 54 mo. NAC significantly improved the survival rate [OR = 1.27, 95% confidence interval (CI): 1.04-1.55], tumor stage (OR = 1.71, 95% CI: 1.26-2.33) and R0 resection rate (OR = 1.51, 95% CI: 1.19-1.91) of patients with advanced gastric cancer. No obvious safety concerns were raised in these trials.NAC can improve tumor stage and survival rate of patients with advanced gastric cancer with a rather good safety.

SUBMITTER: Li W

PROVIDER: S-EPMC2992682 | biostudies-other | 2010 Nov

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Neoadjuvant chemotherapy for advanced gastric cancer: a meta-analysis.

Li Wei W Qin Jing J Sun Yi-Hong YH Liu Tian-Shu TS

World journal of gastroenterology 20101101 44

<h4>Aim</h4>To study the value of neoadjuvant chemotherapy (NAC) for advanced gastric cancer by performing a meta-analysis of the published studies.<h4>Methods</h4>All published controlled trials of NAC for advanced gastric cancer vs no therapy before surgery were searched. Studies that included patients with metastases at enrollment were excluded. Databases included Cochrane Library of Clinical Comparative Trials, MEDLINE, Embase, and American Society of Clinical Oncology meeting abstracts from ...[more]

PMID: 21105197

Similar Datasets

Project description:BackgroundSerum tumor markers including AFU, AFP, CEA, CA199, CA125 and CA724, are of great importance in the diagnosis, prognostic prediction and recurrence monitoring of gastrointestinal malignancies. However, their significance in gastric cancer (GC) patients with neoadjuvant therapy (NCT) is still uncertain. The aim of this study was to evaluate the predictive value of these six tumor markers in locally advanced GC patients who underwent NCT and curative surgery.MethodsIn total, 290 locally advanced GC patients who underwent NCT and D2 radical gastrectomy were retrospectively analyzed. Data on their tumor markers before (pre-) and after (post-) NCT and pathological characteristics were extracted from the database of our hospital. The optimal cutoff values of the six tumor markers were calculated by the ROC curve and Youden index. Their predictive significance was analyzed and survival curves for overall survival (OS) were obtained by the Kaplan-Meier method. Associations between categorical variables were explored by the chi-square test or Fisher's exact test. Multivariate analyses were performed by the Cox regression model.ResultsPre- and post-CA199, -CA125 and -CA724 could predict overall survival (all P < 0.05), but only the change (diff-) of CA199 was related to prognosis (P = 0.05). In the multivariable analysis, pre- (P = 0.014) and post-CA724 (P = 0.036) remained significant, though diff-CA724 was not an independent prognostic factor (P = 0.581). In addition, pre- and post-CA199, -CA125 and -CA724 were associated with lymph node metastasis (N- vs N+) and pathological stage (I-II vs III) (all P < 0.05). Moreover, post-CA724 was related to the vascular or lymphatic invasion (P = 0.019), while pre-CA724 was not (P = 0.082). However, AFU, AFP and CEA showed no association with survival (P > 0.05).ConclusionsCA724 is an independent factor for prognosis and could be used to predict ypN and ypTNM stage in locally advanced GC patients undergoing NCT and curative resection.

Project description:ObjectivesTo develop and evaluate machine learning models using baseline and restaging computed tomography (CT) for predicting and early detecting pathological downstaging (pDS) with neoadjuvant chemotherapy in advanced gastric cancer (AGC).MethodsWe collected 292 AGC patients who received neoadjuvant chemotherapy. They were classified into (a) primary cohort (206 patients with 3-4 cycles chemotherapy) for model development and internal validation, (b) testing cohort I (46 patients with 3-4 cycles chemotherapy) for evaluating models' predictive ability before and after the complete course, and (c) testing cohort II (n = 40) for model evaluation on its performance at early treatment. We extracted 1,231 radiomics features from venous phase CT at baseline and restaging. We selected radiomics models based on 28 cross-combination models and measured the areas under the curve (AUC). Our prediction radiomics (PR) model is designed to predict pDS outcomes using baseline CT. Detection radiomics (DR) model is applied to restaging CT for early pDS detection.ResultsPR model achieved promising outcomes in two testing cohorts (AUC 0.750, p = .009 and AUC 0.889, p = .000). DR model also showed a good predictive ability (AUC 0.922, p = .000 and AUC 0.850, p = .000), outperforming the commonly used RECIST method (NRI 39.5% and NRI 35.4%). Furthermore, the improved DR model with averaging outcome scores of PR and DR models showed boosted results in two testing cohorts (AUC 0.961, p = .000 and AUC 0.921, p = .000).ConclusionsCT-based radiomics models perform well on prediction and early detection tasks of pDS and can potentially assist surgical decision-making in AGC patients.Key points• Baseline contrast-enhanced computed tomography (CECT)-based radiomics features were predictive of pathological downstaging, allowing accurate identification of non-responders before therapy. • Restaging CECT-based radiomics features were predictive to achieve pDS after and even at an early stage of neoadjuvant chemotherapy. • Combination of baseline and restaging CECT-based radiomics features was promising for early detection and preoperative evaluation of pathological downstaging of AGC.

Dataset Information

Neoadjuvant chemotherapy for advanced gastric cancer: a meta-analysis.

Publications

Neoadjuvant chemotherapy for advanced gastric cancer: a meta-analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets