Predictive Factors for Metachronous Gastric Cancer in High-Risk Patients after Successful Helicobacter pylori Eradication

Digestion ◽  
2008 ◽  
Vol 78 (2-3) ◽  
pp. 113-119 ◽  
Author(s):  
Akiko Shiotani ◽  
Noriya Uedo ◽  
Hiroyasu Iishi ◽  
Yamanaka Yoshiyuki ◽  
Manabu Ishii ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Helicobacter Pylori ◽  
High Risk ◽  
Predictive Factors ◽  
High Risk Patients ◽  
Risk Patients ◽  
Metachronous Gastric Cancer

scholarly journals Accuracy of upper endoscopies with random biopsies to identify patients with gastric premalignant lesions who can safely be exempt from surveillance

2021 ◽  
Vol 24 (3) ◽  
pp. 680-690
Author(s):  
Michiel C. Mommersteeg ◽  
Stella A. V. Nieuwenburg ◽  
Wouter J. den Hollander ◽  
Lisanne Holster ◽  
Caroline M. den Hoed ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
High Risk ◽  
Low Risk ◽  
Premalignant Lesions ◽  
High Risk Patients ◽  
European Guidelines ◽  
Progression Of Disease ◽  
Risk Patients ◽  
Progression Risk

Abstract Introduction Guidelines recommend endoscopy with biopsies to stratify patients with gastric premalignant lesions (GPL) to high and low progression risk. High-risk patients are recommended to undergo surveillance. We aimed to assess the accuracy of guideline recommendations to identify low-risk patients, who can safely be discharged from surveillance. Methods This study includes patients with GPL. Patients underwent at least two endoscopies with an interval of 1–6 years. Patients were defined ‘low risk’ if they fulfilled requirements for discharge, and ‘high risk’ if they fulfilled requirements for surveillance, according to European guidelines (MAPS-2012, updated MAPS-2019, BSG). Patients defined ‘low risk’ with progression of disease during follow-up (FU) were considered ‘misclassified’ as low risk. Results 334 patients (median age 60 years IQR11; 48.7% male) were included and followed for a median of 48 months. At baseline, 181/334 (54%) patients were defined low risk. Of these, 32.6% were ‘misclassified’, showing progression of disease during FU. If MAPS-2019 were followed, 169/334 (51%) patients were defined low risk, of which 32.5% were ‘misclassified’. If BSG were followed, 174/334 (51%) patients were defined low risk, of which 32.2% were ‘misclassified’. Seven patients developed gastric cancer (GC) or dysplasia, four patients were ‘misclassified’ based on MAPS-2012 and three on MAPS-2019 and BSG. By performing one additional endoscopy 72.9% (95% CI 62.4–83.3) of high-risk patients and all patients who developed GC or dysplasia were identified. Conclusion One-third of patients that would have been discharged from GC surveillance, appeared to be ‘misclassified’ as low risk. One additional endoscopy will reduce this risk by 70%.

scholarly journals A Tumor Progression Related 7-Gene Signature Indicates Prognosis and Tumor Immune Characteristics of Gastric Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Fen Liu ◽  
Zongcheng Yang ◽  
Lixin Zheng ◽  
Wei Shao ◽  
Xiujie Cui ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
High Risk ◽  
Cancer Progression ◽  
Risk Score ◽  
Risk Model ◽  
Cox Regression ◽  
Hub Genes ◽  
Cox Regression Analysis ◽  
High Risk Patients ◽  
Risk Patients

BackgroundGastric cancer is a common gastrointestinal malignancy. Since it is often diagnosed in the advanced stage, its mortality rate is high. Traditional therapies (such as continuous chemotherapy) are not satisfactory for advanced gastric cancer, but immunotherapy has shown great therapeutic potential. Gastric cancer has high molecular and phenotypic heterogeneity. New strategies for accurate prognostic evaluation and patient selection for immunotherapy are urgently needed.MethodsWeighted gene coexpression network analysis (WGCNA) was used to identify hub genes related to gastric cancer progression. Based on the hub genes, the samples were divided into two subtypes by consensus clustering analysis. After obtaining the differentially expressed genes between the subtypes, a gastric cancer risk model was constructed through univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis. The differences in prognosis, clinical features, tumor microenvironment (TME) components and immune characteristics were compared between subtypes and risk groups, and the connectivity map (CMap) database was applied to identify potential treatments for high-risk patients.ResultsWGCNA and screening revealed nine hub genes closely related to gastric cancer progression. Unsupervised clustering according to hub gene expression grouped gastric cancer patients into two subtypes related to disease progression, and these patients showed significant differences in prognoses, TME immune and stromal scores, and suppressive immune checkpoint expression. Based on the different expression patterns between the subtypes, we constructed a gastric cancer risk model and divided patients into a high-risk group and a low-risk group based on the risk score. High-risk patients had a poorer prognosis, higher TME immune/stromal scores, higher inhibitory immune checkpoint expression, and more immune characteristics suitable for immunotherapy. Multivariate Cox regression analysis including the age, stage and risk score indicated that the risk score can be used as an independent prognostic factor for gastric cancer. On the basis of the risk score, we constructed a nomogram that relatively accurately predicts gastric cancer patient prognoses and screened potential drugs for high-risk patients.ConclusionsOur results suggest that the 7-gene signature related to tumor progression could predict the clinical prognosis and tumor immune characteristics of gastric cancer.

Value of Gastric Juice Carcinoembryonic Antigen in Identifying High-Risk Patients for Gastric Cancer

Oncology ◽  
1988 ◽  
Vol 45 (1) ◽  
pp. 30-34 ◽  
Author(s):  
Masaharu Tatsuta ◽  
Hiroyasu Iishi ◽  
Hisako Yamamura ◽  
Shigeru Okudo
Keyword(s):  
Gastric Cancer ◽  
High Risk ◽  
Carcinoembryonic Antigen ◽  
Gastric Juice ◽  
High Risk Patients ◽  
Risk Patients

scholarly journals A SEER population analysis of stage IB resected gastric cancer: Who can benefit from adjuvant therapy?

2019 ◽  
Vol 5 (suppl) ◽  
pp. 122-122
Author(s):  
Yue Wang
Keyword(s):  
Gastric Cancer ◽  
High Risk ◽  
Adjuvant Therapy ◽  
Clinical Decision Making ◽  
Family Income ◽  
Population Analysis ◽  
Low Risk ◽  
High Risk Patients ◽  
Stage Ib ◽  
Risk Patients

122 Background: The benefit of adjuvant therapy (AT) remains controversial in stage IB gastric cancer (GC). This study aimed to offer a reference for the rational indications of AT. Methods: We retrospectively included 1935 stage IB GC patients who experienced curative surgery from the SEER database between 2004 and 2015. These patients were allocated into two groups: Group AT and Group surgery alone (Group SA). Risk factors associated with AT were examined using univariate/multivariate analyses. A nomogram to project overall survival (OS) of AT was established and internally validated. Results: Five variables, which were significantly related with OS of AT, were incorporated in the nomogram. These variables were sex, age, examined lymph nodes, tumor site, and family income. The C-index of the model was 0.636 and the calibration curve showed that the anticipated values were in accordance with the actual values. The decision curve demonstrated that the optimal clinical impact was achieved when the threshold possibility was 0-47%. Then the entire cohort was separated into low-risk (≤107 points) as well as high-risk ( > 107 points) groups based on the projected 5-year OS. Group SA revealed a significantly poorer OS than Group AT for high-risk patients (P < 0.001); on the other hand, there was a comparable OS for low-risk patients (P = 0.067). Conclusions: We have developed an effective, intuitional and applied prognostic tool based on nomogram to clinical decision-making. For stage IB GC after surgical resection, AT was only recommended for high-risk patients. However, AT may be dispensable for low-risk patients.

Su1245 - SOS: Save Our Stomachs! Detailed Gastric Mapping Versus Standard Endoscopy as Surveillance for Familial Gastric Cancer in High Risk Patients

2018 ◽  
Vol 154 (6) ◽  
pp. S-516
Author(s):  
Bryan F. Curtin ◽  
Udo Rudloff ◽  
Jonathan M. Hernandez ◽  
Martha Quezado ◽  
Theo Heller ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
High Risk ◽  
Familial Gastric Cancer ◽  
High Risk Patients ◽  
Risk Patients ◽  
Mapping Versus ◽  
Gastric Mapping

scholarly journals Clinical Predictive Factors of Lower Extremity Deep Vein Thrombosis in Relative High-Risk Patients after Neurosurgery: A Retrospective Study

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Juhua Li ◽  
XinZhen Ren ◽  
Xiaole Zhu ◽  
Huayu Chen ◽  
Zhen Lin ◽  
...  
Keyword(s):  
Deep Vein Thrombosis ◽  
High Risk ◽  
Lower Extremity ◽  
Predictive Factors ◽  
High Risk Patients ◽  
Vein Thrombosis ◽  
Risk Patients ◽  
Gcs Score ◽  
Deep Vein ◽  
D Dimer

Introduction. It is acknowledged that patients undergoing neurosurgery with neurological illness are at higher risk of lower extremity deep vein thrombosis (DVT). As an underlying life-threatening complication, the incidence and risk factors for high-risk patients with lower extremity deep vein thrombosis are still controversial in relative high-risk patients after neurosurgery. Materials and Methods. A total of 204 patients who underwent neurosurgery and were considered as a high-risk group of DVT according to times of stay in bed more than 3 days were enrolled in this study. We evaluated the lower extremity DVT by using Color Doppler Ultrasound System (CDUS). Clinical parameters of patients at the time of admission and postoperation were recorded and prepared for further analysis. Early predictive factors for postoperative lower extremity DVT were established. Diagnostic performance of predictive factors was evaluated by using receiver operating characteristic (ROC) curve analysis. Results. The overall incidence rate of DVT in 204 enrolled patients was 30.9%. Multivariate logistic regression indicated that hypertension (OR 3.159, 95% CI 1.465-6.816; P=0.003), higher postoperative D-dimer (OR 1.225, 95% CI 1.016-1.477; P=0.034), female (OR 0.174, 95% CI 0.054-0.568; P=0.004), and lower GCS score (OR 0.809, 95% CI 0.679-0.965; P=0.013) were independently associated with incidence of DVT in patients after neurosurgery. The logistic regression function (LR model) of these four independent risk factors had a better performance on diagnostic value of DVT in patients after neurosurgery. Conclusion. The combined factor was constructed by hypertension, postoperative D-dimer, gender, and GCS score, and it might be a more handy and reliable marker to stratify patients at risk of DVT after neurosurgery.

scholarly journals Exploring the predictive factors for depression among hemodialysis patients: a case-control study

BJPsych Open ◽  
2021 ◽  
Vol 7 (S1) ◽  
pp. S43-S44
Author(s):  
Syed Muhammad Jawad Zaidi ◽  
Mehwish Kaneez ◽  
Hamza Waqar Bhatti ◽  
Shanzeh Khan ◽  
Shafaq Fatima ◽  
...  
Keyword(s):  
Risk Factors ◽  
Depressive Symptoms ◽  
High Risk ◽  
Renal Disease ◽  
Predictive Factors ◽  
Hemodialysis Patients ◽  
High Risk Patients ◽  
Disease Prognosis ◽  
Risk Patients ◽  
Esrd Patients

AimsDepression remains an exceedingly ubiquitous entity that significantly depreciates the quality of life and disease prognosis among end-stage renal disease (ESRD) patients. Even though the deleterious effects of depression on ESRD patients are well-established in the literature, the predictive factors that predispose such patients to depression need to be explored. Our study thus aims to gauge these factors and create a predictive model for optimal psychiatric and medical management of such patients.MethodAll ESRD patients with a disease duration of at least one year underwent a complete psychiatric evaluation based on DSM-V guidelines preceded by a cognitive evaluation by Mini-Mental State Examination (MMSE). A total of 73 patients diagnosed with moderate to severe major depressive disorder were selected as cases. Patients suffering from recurrent psychotic episodes, having a past or family history of psychiatric illness, being already treated for depression, having any substance abuse (current or past), were excluded from the study. Following the similar guidelines, and exclusion criteria, 146 patients (two controls for each case) having no depression were selected as controls. The cases and controls were studied and matched for a myriad of sociodemographic factors. The various risk factors for depression were evaluated using univariate and multivariate binary logistics analysis.ResultThe significant risk factors for depression among hemodialysis patients were age (OR = 1.79, CI = 0.47–3.81), comorbidities (OR = 2.13, CI = 0.51–3.96), duration of renal disease (OR = 2.54, CI 0.63–4.28), duration of hemodialysis (OR = 2.36, CI = 0.89–4.11), unemployment (OR = 2.33, CI = 0.79–3.88), and being unmarried (OR = 1.93, CI = 0.44–3.53). Prospect of survival, financial instability, social stigmatization, and effect of comorbidities on ESRD were major concerns for the cases that attributed to their depressive symptoms.ConclusionThe factors that herald the onset of depression among hemodialysis patients include increasing age, presence of comorbidities, unemployment being unmarried, and increasing duration of hemodialysis. These factors will aid the clinicians to identify high-risk patients that require psychiatric consultation. We recommend prompt psychiatric intervention (pharmacologic or non-pharmacologic) and appropriate patient counseling so that the depressive symptoms can be alleviated and dismal disease prognosis can be prevented among such high-risk patients.

Incidence, Indications, and Predictive Factors for ICU Admission in Elderly, High-Risk Patients Undergoing Laparoscopic Sleeve Gastrectomy

2018 ◽  
Vol 28 (9) ◽  
pp. 2603-2608 ◽  
Author(s):  
Nesreen Khidir ◽  
Moamena EL-Matbouly ◽  
Mohammed Al Kuwari ◽  
Michel Gagner ◽  
Moataz Bashah
Keyword(s):  
Sleeve Gastrectomy ◽  
High Risk ◽  
Laparoscopic Sleeve Gastrectomy ◽  
Predictive Factors ◽  
Icu Admission ◽  
High Risk Patients ◽  
Risk Patients
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