scholarly journals Clinical scoring system for the prediction of survival of patients with advanced gastric cancer

ESMO Open ◽  
2020 ◽  
Vol 5 (2) ◽  
pp. e000670 ◽  
Author(s):  
Jinchul Kim ◽  
Jung Yong Hong ◽  
Seung Tae Kim ◽  
Se Hoon Park ◽  
Se Yong Jekal ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Advanced Gastric Cancer ◽  
Scoring System ◽  
Cox Regression ◽  
Laboratory Data ◽  
Discrimination Performance ◽  
Validation Dataset ◽  
Homogeneous Population ◽  
Scoring Model

ObjectiveIn this study, we established a risk scoring system using easily obtained clinical characteristics at the time of initiating palliative chemotherapy to predict accurate overall survival of patients with advanced gastric cancer after first-line treatment with fluoropyrimidine–platinum combination chemotherapy.MethodsA total of 1733 patients treated at the Samsung Medical Center, Korea were included in the study, and clinicopathological and laboratory data were retrospectively analysed. The dataset was split into a training set (n=1156, 67%) and a validation set (n=577, 33%). Top-ranked variables were identified using the random forest survival algorithm and integrated into a Cox regression model, thereby constructing the scoring system for predicting the overall survival of patients with advanced gastric cancer.ResultsThe following five variables were finally included in the scoring system: serum neutrophil–lymphocyte ratio, alkaline phosphatase level, albumin level, performance status and histologic differentiation. The scoring system determined four distinct risk groups in the validation dataset with median overall survival of 17.1 months (95% CI=14.9 to 20.5 months), 12.9 months (95% CI=11.4 to 14.6 months), 8.1 months (95% CI=5.3 to 12.3 months) and 3.9 months (95% CI=1.5 to 8.2 months), respectively. The area under the curve to estimate the discrimination performance of the scoring system was 66.1 considering 1 year overall survival.ConclusionsWe developed a simple and clinically useful predictive scoring model in a homogeneous population with advanced gastric cancer treated with fluoropyrimidine-containing and platinum-containing chemotherapy. However, additional independent validation will be required before the scoring model can be used commonly.

A clinical scoring system for survival prediction in advanced gastric cancer.

2020 ◽  
Vol 38 (4_suppl) ◽  
pp. 436-436
Author(s):  
Jinchul Kim ◽  
Ja Hyun Yeo ◽  
Jung Yong Hong ◽  
Seung Tae Kim ◽  
Se Hoon Park ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Advanced Gastric Cancer ◽  
Scoring System ◽  
Cox Regression ◽  
Discrimination Performance ◽  
Validation Dataset ◽  
Survival Prediction ◽  
Scoring Model ◽  
Neutrophil Lymphocyte Ratio

436 Background: We established a scoring system using easily approachable clinical characteristics at the timing of initiating palliative chemotherapy to achieve accurate overall survival prediction to first-line treatment consisting of fluoropyrimidines in patients with advanced gastric cancer. Methods: A total of 1,733 patients were included in the study. The dataset was split into a training (n=1156, 67%) and validation set (n=577, 33%). Top-ranked variables were identified using the Random Forest for Survival algorithm and analyzed into a Cox regression model, thereby constructing the scoring system for predicting overall survival of advanced gastric cancer. Results: Five variables were finally included in the scoring system: serum neutrophil-lymphocyte ratio, alkaline phosphatase, albumin level, performance status, and histologic differentiation. The scoring system determined four distinct risk groups in validation dataset with median overall survival of 17.1 month (95% confidence interval [CI] = 14.9 to 20.5 month), 12.9 month (95% CI = 11.4 to 14.6 month), 8.1 month (95% CI = 5.3 to 12.3 month), and 3.9 month (95% CI = 1.5 to 8.2 month), respectively. AUC to estimate discrimination performance of the scoring system was 66.1 for one-year overall survival. Conclusions: We developed a simple and clinically useful predictive scoring model in a relatively homogenous population who initiate fluoropyrimidine-containing chemotherapy in advanced gastric cancer. Generalized application of the scoring model will require additional independent validation. [Table: see text]

A Simple Scoring Model Predicting the Outcome of COVID-19 Patients: Tanta COVID score

2021 ◽  
Vol 21 ◽  
Author(s):  
Mohammed Elhendawy ◽  
Ferial El-Kalla ◽  
Sherief Abd-Elsalam ◽  
Dalia ElSharawy ◽  
Shaimaa S Soliman ◽  
...  
Keyword(s):  
Scoring System ◽  
Model Building ◽  
Cox Regression ◽  
Laboratory Data ◽  
Discrimination Performance ◽  
University Hospital ◽  
Severe Illness ◽  
Health Providers ◽  
Scoring Model ◽  
Increased Risk

Background & Aim: COVID-19 is a worldwide pandemic with high rates of morbidity and mortality, and an uncertain prognosis leading to an increased risk of infection in health providers and limited hospital care capacities. In this study, we have proposed a predictive, interpretable prognosis scoring system with the use of readily obtained clinical, radiological and laboratory characteristics to accurately predict worsening of the condition and overall survival of patients with COVID -19. Methods: This is a single-center, observational, prospective, cohort study. A total of 347 patients infected with COVID-19 presenting to the Tanta university hospital, Egypt, were enrolled in the study, and clinical, radiological and laboratory data were analyzed. Top-ranked variables were identified and selected to be integrated into a Cox regression model, building the scoring system for accurate prediction of the prognosis of patients with COVID-19. Results: The six variables that were finally selected in the scoring system were lymphopenia, serum CRP, ferritin, D-Dimer, radiological CT lung findings and associated chronic debilitating disease. The scoring system discriminated risk groups with either mild disease or severe illness characterized by respiratory distress (and also those with hypoxia and in need for oxygen therapy or mechanical ventilation) or death. The area under the curve to estimate the discrimination performance of the scoring system was more than 90%. Conclusion: We proposed a simple and clinically useful predictive scoring model for COVID-19 patients. However, additional independent validation will be required before the scoring model can be used commonly.

scholarly journals Combined Neutrophil-to-Lymphocyte and Platelet-Volume-to-Platelet Ratio (NLR and PVPR Score) Represents a Novel Prognostic Factor in Advanced Gastric Cancer Patients

2021 ◽  
Vol 10 (17) ◽  
pp. 3902
Author(s):  
Kamil Konopka ◽  
Agnieszka Micek ◽  
Sebastian Ochenduszko ◽  
Joanna Streb ◽  
Paweł Potocki ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Advanced Gastric Cancer ◽  
Cancer Patients ◽  
Inflammatory Markers ◽  
Cox Regression ◽  
Risk Of Death ◽  
Immune System Activation ◽  
Increased Risk ◽  
Gastric Cancer Patients

Background: Chemotherapy is a cornerstone of treatment in advanced gastric cancer (GC) with a proven impact on overall survival, however, reliable predictive markers are missing. The role of various inflammatory markers has been tested in gastric cancer patients, but there is still no general consensus on their true clinical applicability. High neutrophil-to-lymphocyte (NLR) and low (medium)-platelets-volume-to-platelet ratio (PVPR) are known markers of unspecific immune system activation, correlating significantly with outcomes in advanced GC patients. Methods: Metastatic GC patients (N:155) treated with chemotherapy +/− trastuzumab were enrolled in this retrospective study. Pre-treatment NLR and PVPR, as well as other inflammatory markers were measured in peripheral blood. Univariate Cox regression was conducted to find markers with a significant impact on overall survival (OS) and progression-free survival (PFS). Spearman correlation and Cohen’s kappa was used to analyze multicollinearity. Multiple multivariable Cox regression models were built to study the combined impact of NLR and PVPR, as well as other known prognostic factors on OS. Results: Elevated NLR was significantly associated with increased risk of death (HR = 1.95; 95% CI: 1.17–3.24), and lower PVPR was significantly associated with improved outcomes (HR = 0.53; 95% CI: 0.32–0.90). A novel inflammatory marker, based on a combination of NLR and PVPR, allows for the classification of GC patients into three prognostic groups, characterized by median OS of 8.4 months (95% CI 5.8–11.1), 10.5 months (95% CI 8.8–12.1), and 15.9 months (95% CI 13.5–18.3). Conclusion: The NLR and PVPR score (elevated NLR and decreased PVPR) is a marker of detrimental outcome of advanced GC patients treated with chemotherapy.

scholarly journals A radiomics-based model for predicting prognosis of locally advanced gastric cancer in the preoperative setting

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jaeseung Shin ◽  
Joon Seok Lim ◽  
Yong-Min Huh ◽  
Jie-Hyun Kim ◽  
Woo Jin Hyung ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Advanced Gastric Cancer ◽  
Cox Regression ◽  
Characteristic Curve ◽  
External Validation ◽  
Locally Advanced ◽  
Clinical Model ◽  
Locally Advanced Gastric Cancer ◽  
Contrast Enhanced Ct ◽  
Preoperative Ct

AbstractThis study aims to evaluate the performance of a radiomic signature-based model for predicting recurrence-free survival (RFS) of locally advanced gastric cancer (LAGC) using preoperative contrast-enhanced CT. This retrospective study included a training cohort (349 patients) and an external validation cohort (61 patients) who underwent curative resection for LAGC in 2010 without neoadjuvant therapies. Available preoperative clinical factors, including conventional CT staging and endoscopic data, and 438 radiomic features from the preoperative CT were obtained. To predict RFS, a radiomic model was developed using penalized Cox regression with the least absolute shrinkage and selection operator with ten-fold cross-validation. Internal and external validations were performed using a bootstrapping method. With the final 410 patients (58.2 ± 13.0 years-old; 268 female), the radiomic model consisted of seven selected features. In both of the internal and the external validation, the integrated area under the receiver operating characteristic curve values of both the radiomic model (0.714, P < 0.001 [internal validation]; 0.652, P = 0.010 [external validation]) and the merged model (0.719, P < 0.001; 0.651, P = 0.014) were significantly higher than those of the clinical model (0.616; 0.594). The radiomics-based model on preoperative CT images may improve RFS prediction and high-risk stratification in the preoperative setting of LAGC.

scholarly journals Identification of the angiogenesis related genes for predicting prognosis of patients with gastric cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sheng Zheng ◽  
Zizhen Zhang ◽  
Ning Ding ◽  
Jiawei Sun ◽  
Yifeng Lin ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
High Efficiency ◽  
Cox Regression ◽  
Risk Group ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Lasso Regression ◽  
Sequencing Data ◽  
Cox Regression Analysis

Abstract Introduction Angiogenesis is a key factor in promoting tumor growth, invasion and metastasis. In this study we aimed to investigate the prognostic value of angiogenesis-related genes (ARGs) in gastric cancer (GC). Methods mRNA sequencing data with clinical information of GC were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The differentially expressed ARGs between normal and tumor tissues were analyzed by limma package, and then prognosis‑associated genes were screened using Cox regression analysis. Nine angiogenesis genes were identified as crucially related to the overall survival (OS) of patients through least absolute shrinkage and selection operator (LASSO) regression. The prognostic model and corresponding nomograms were establish based on 9 ARGs and verified in in both TCGA and GEO GC cohorts respectively. Results Eighty-five differentially expressed ARGs and their enriched pathways were confirmed. Significant enrichment analysis revealed that ARGs-related signaling pathway genes were highly related to tumor angiogenesis development. Kaplan–Meier analysis revealed that patients in the high-risk group had worse OS rates compared with the low-risk group in training cohort and validation cohort. In addition, RS had a good prognostic effect on GC patients with different clinical features, especially those with advanced GC. Besides, the calibration curves verified fine concordance between the nomogram prediction model and actual observation. Conclusions We developed a nine gene signature related to the angiogenesis that can predict overall survival for GC. It’s assumed to be a valuable prognosis model with high efficiency, providing new perspectives in targeted therapy.

scholarly journals Efficacy and Safety of FLOT regimen vs. DCF, FOLFOX, and ECF regimens as Perioperative Chemotherapy Treatments for Resectable Gastric Cancer Patients

2021 ◽  
Author(s):  
Pegah Farrokhi ◽  
Alireza Sadeghi ◽  
Mehran sharifi ◽  
Payam Dadvand ◽  
Rachel Riechelmann ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Cox Regression ◽  
Progression Free Survival ◽  
R0 Resection ◽  
P Value ◽  
Perioperative Chemotherapy ◽  
Resectable Gastric Cancer ◽  
Gastric Cancer Patients

AbstractAimThis study aimed to evaluate and compare the efficacy and toxicity of common regimens used as perioperative chemotherapy including ECF, DCF, FOLFOX, and FLOT to identify the most effective chemotherapy regimen with less toxicity.Material and MethodsThis retrospective cohort study was based on 152 eligible gastric cancer patients recruited in a tertiary oncology hospital in Isfahan, Iran (2014-2019). All resectable gastric cancer patients who had received one of the four chemotherapy regimens including ECF, DCF, FOLFOX, or FLOT, and followed for at least one year (up to five years) were included. The primary endpoint of this study was Overall Survival (OS), Progression-Free Survival (PFS), Overall Response Rate (ORR), and R0 resection. We also considered toxicity according to CTCAE (v.4.0) criteria as a secondary endpoint. Cox -regression models were used applied to estimate OS and PFS time, controlled for relevant covariates.ResultsOf included patients, 32(21%), 51(33.7%), 37(24.3%), and 32(21%) had received ECF, DCF, FOLFOX and FLOT, respectively. After the median 25 months follow-up, overall survival was higher with the FLOT regimen in comparison with other regimens (hazard ratio [HR] = 0. 052). The median OS of the FLOT regimen was not reachable in Kaplan-Meier analysis and the median OS was 28, 26, and 23 months for DCF, FOLOFX, and ECF regimens, respectively. On the other hand, a median PFS of 25, 17, 15, and 14 months was observed for FLOT, DCF, FOLFOX, and ECF regimens, respectively (Log-rank = 0. 021). FLOT regimen showed 84. 4% ORR which was notably higher than other groups (p-value<0. 01).ConclusionsFor resectable gastric cancer patients, the perioperative FLOT regimen seemed to lead to a significant improvement in patients’ OS and PFS in comparison with ECF, DCF, and FOLFOX regimens. As such, the FLOT regimen could be considered as the optimal option for managing resectable gastric cancer patients.

Overexpression of a novel oncogene Cadherin 6 correlates with tumor progression and poor prognosis in gastric cancer

2021 ◽  
Author(s):  
Zongxian Zhao ◽  
Shuliang Li ◽  
Shilong Li ◽  
Jun Wang ◽  
Hai Lin ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Roc Curve ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
Expression Level ◽  
Diagnostic Efficiency ◽  
Gastric Tissue ◽  
Diagnosis And Prognosis ◽  
T Classification

Abstract BackgroundGastric cancer (GC) is one of the most common and fatal cancers worldwide and effective biomarkers aids in GC management and prognosis. Hence, we explored the role and function of cadherin 6 (CDH6) in diagnosis and prognosis of gastric cancer. MethodsThe expression level of CDH6 in GC tissue and normal gastric tissue were analyzed using multiple public databases. Gene set enrichment analysis (GSEA) was performed using The Cancer Genome Atlas dataset (TCGA). The diagnostic efficiency of CDH6 expression in GC patients was determined through receiver operating characteristic (ROC) curve analysis. The associations between clinical variables and expression of CDH6 were evaluated statistically and the prognostic factors for overall survival were analyzed by univariate and multivariate Cox regression. Forty-four GC tissues, corresponding adjacent normal tissues (n=20), and detailed clinical information were collected from Tianjin Medical University General Hospital, CDH6 expression level was detected for further validation. ResultsCDH6 was upregulated in GC samples compared with normal gastric tissue, and GSEA identified the citrate cycle tricarboxylic (TCA) cycle, extracellular matrix (ECM) receptor interaction, glyoxylate and dicarboxylate metabolism oxidative phosphorylation, and pentose phosphate pathway as differentially enriched in GCs. According to the area under the ROC curve (AUC) (AUC=0.829 in TCGA and 0.966 in GSE54129), CDH6 had high diagnostic efficiency. Patients with high expression of CDH6 was associated with higher T classification and worse prognoses than those with low CDH6 expression in GC. Univariate and multivariate Cox regression analysis showed that CDH6 was an independent risk factor for overall survival (univariate: HR = 1.305, P = 0.002, multivariate: HR = 1.481, P < 0.001). ConclusionCDH6 was upregulated in GC and high CDH6 expression indicated higher T classification and worse prognoses. CDH6 could be a potentially independent molecular biomarker for diagnosis and prognosis of GC.

scholarly journals Hyperprogressive disease during nivolumab or irinotecan treatment in patients with advanced gastric cancer

ESMO Open ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. e000488 ◽  
Author(s):  
Masahiko Aoki ◽  
Hirokazu Shoji ◽  
Kengo Nagashima ◽  
Hiroshi Imazeki ◽  
Takahiro Miyamoto ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Advanced Gastric Cancer ◽  
Survival Benefit ◽  
Poor Prognosis ◽  
Tumour Growth ◽  
Progression Free Survival ◽  
Free Survival ◽  
Prior Therapy ◽  
Hyperprogressive Disease

BackgroundNivolumab showed a survival benefit for advanced gastric cancer (AGC). However, an acceleration of tumour growth during immunotherapy, (hyperprogressive disease, HPD) has been reported in various cancers. This study reviewed the HPD in patients with AGC treated with nivolumab or irinotecan.MethodsThe subjects of this retrospective study were patients with AGC with measurable lesions, and their tumour growth rates (TGR) during nivolumab or irinotecan were compared with those during prior therapy. HPD was defined as an increase in TGR more than twofold.Results34 and 66 patients received nivolumab and irinotecan in third or later line between June 2009 and September 2018 at our hospital; 22 patients receiving nivolumab had prior treatment with irinotecan, and one patient received irinotecan after nivolumab. Nivolumab and irinotecan showed no differences in disease control rates (38.2% and 34.8%) and in progression-free survival (PFS) (HR 1.1, 95% CI 0.7 to 1.6, p=0.802). The incidence of HPD was slightly higher after nivolumab (29.4%) than after irinotecan (13.5%) (p=0.0656), showing no differences in background between the patients with and without HPD. Compared between HPD and PD other than HPD after nivolumab, the HRs for PFS and overall survival (OS) were 1.1 (95% CI 0.5 to 2.7; p=0.756), and 2.1 (95% CI 0.7 to 5.8; p=0.168), but such clear difference in OS was not observed after irinotecan.ConclusionsHPD was observed more frequently after nivolumab compared with irinotecan, which was associated with a poor prognosis after nivolumab but not so clearly after irinotecan.

Sign in / Sign up

Export Citation Format

Share Document