scholarly journals The impact of previous cancer on overall survival of bladder cancer patients and the establishment of nomogram for overall survival prediction

Medicine ◽  
2020 ◽  
Vol 99 (38) ◽  
pp. e22191
Author(s):  
Zhengquan Wang ◽  
Yuan Zhou ◽  
Chao Guan ◽  
Yinman Ding ◽  
Sha Tao ◽  
...  
Keyword(s):  
Overall Survival ◽  
Bladder Cancer ◽  
Cancer Patients ◽  
Survival Prediction ◽  
The Impact ◽  
Overall Survival Prediction

scholarly journals RAD51 is a potential marker for prognosis and regulates cell proliferation in pancreatic cancer

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Xiaomeng Zhang ◽  
Ningyi Ma ◽  
Weiqiang Yao ◽  
Shuo Li ◽  
Zhigang Ren
Keyword(s):  
Pancreatic Cancer ◽  
Cell Proliferation ◽  
Overall Survival ◽  
Cancer Cells ◽  
Cancer Patients ◽  
Aerobic Glycolysis ◽  
Cell Counting ◽  
Survival Prediction ◽  
Pancreatic Cancer Cells ◽  
The Impact

Abstract Background The DNA damage and repair pathway is considered a promising target for developing strategies against cancer. RAD51, also known as RECA, is a recombinase that performs the critical step in homologous recombination. RAD51 has recently received considerable attention due to its function in tumor progression and its decisive role in tumor resistance to chemotherapy. However, its role in pancreatic cancer has seldom been investigated. In this report, we provide evidence that RAD51, regulated by KRAS, promotes pancreatic cancer cell proliferation. Furthermore, RAD51 regulated aerobic glycolysis by targeting hypoxia inducible factor 1α (HIF1α). Methods TCGA (The Cancer Genome Atlas) dataset analysis was used to examine the impact of RAD51 expression on overall survival of pancreatic cancer patients. Lentivirus-mediated transduction was used to silence RAD51 and KRAS expression. Quantitative real-time PCR and western blot analysis validated the efficacy of the knockdown effect. Analysis of the glycolysis process in pancreatic cancer cells was also performed. Cell proliferation was determined using a CCK-8 (Cell Counting Kit-8) proliferation assay. Results Pancreatic cancer patients with higher levels of RAD51 exhibited worse survival. In pancreatic cancer cells, RAD51 positively regulated cell proliferation, decreased intracellular reactive oxygen species (ROS) production and increased the HIF1α protein level. KRAS/MEK/ERK activation increased RAD51 expression. In addition, RAD51 was a positive regulator of aerobic glycolysis. Conclusion The present study reveals novel roles for RAD51 in pancreatic cancer that are associated with overall survival prediction, possibly through a mechanism involving regulation of aerobic glycolysis. These findings may provide new predictive and treatment targets for pancreatic cancer.

scholarly journals The Impact of Metformin Use with Survival Outcomes in Urologic Cancers: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xiangyang Yao ◽  
Haoran Liu ◽  
Hua Xu
Keyword(s):  
Prostate Cancer ◽  
Overall Survival ◽  
Bladder Cancer ◽  
Cancer Patients ◽  
Kidney Cancer ◽  
Subgroup Analysis ◽  
Meta Analysis ◽  
Effect Model ◽  
Urologic Cancers ◽  
The Impact

Background. Conflicting results exist between the potential protective effects of metformin and the prognosis of urologic cancers. This meta-analysis summarized the effects of metformin exposure on the recurrence, progression, cancer-specific survival (CSS), and overall survival (OS) of the three main urologic cancers (kidney cancer, bladder cancer, and prostate cancer). Methods. We systematically searched PubMed, Embase, Web of Science, Wanfang, and China National Knowledge Infrastructure databases (January 2010 to December 2019), which identified studies regarding metformin users and nonusers with urologic cancers and extracted patient data. A random effect model or fixed effect model was used to analyze hazard ratios (HRs) and 95% confidence intervals (CIs). Results. Among the 1883 confirmed studies, 27 eligible studies were identified, including 123,212 participants. In prostate cancer, patients using metformin have significant benefits for recurrence ( HR = 0.74 ; 95% CI: 0.61-0.90; P = 0.007 ; I 2 = 56 % ), CSS ( HR = 0.74 ; 95% CI: 0.61-0.91; P = 0.002 ; I 2 = 79 % ), and OS ( HR = 0.76 ; 95% CI: 0.65-0.90; P < 0.001 ; I 2 = 86 % ). Moreover, further subgroup analysis showed that the beneficial effects of metformin may be more significant for patients receiving radical radiotherapy. For kidney cancer, metformin was beneficial for progression ( HR = 0.80 ; 95% CI: 0.65-0.98; P = 0.14 ; I 2 = 46 % ). Analysis revealed that the effect of metformin on the overall survival of kidney cancer patients may be related to nationality (American: HR = 0.76 ; 95% CI: 0.59-0.98; P = 0.88 ; I 2 = 0 % ). For bladder cancer, no obvious benefits of metformin use were identified. However, subgroup analysis indicated that metformin may improve the recurrence of bladder cancer, but this improvement was only found in patients with a median follow-up time of more than 4 years ( HR = 0.43 ; 95% CI: 0.28-0.67; P = 0.61 ; I 2 = 0 % ).

scholarly journals Association of chemotherapy with survival in stage II colon cancer patients who received radical surgery: a retrospective cohort study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhihao Lv ◽  
Yuqi Liang ◽  
Huaxi Liu ◽  
Delong Mo
Keyword(s):  
Colon Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Prediction Models ◽  
Radical Surgery ◽  
Survival Rates ◽  
Stage Ii ◽  
Survival Prediction ◽  
Stage Ii Colon Cancer ◽  
Overall Survival Rates

Abstract Background It remains controversial whether patients with Stage II colon cancer would benefit from chemotherapy after radical surgery. This study aims to assess the real effectiveness of chemotherapy in patients with stage II colon cancer undergoing radical surgery and to construct survival prediction models to predict the survival benefits of chemotherapy. Methods Data for stage II colon cancer patients with radical surgery were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (1:1) was performed according to receive or not receive chemotherapy. Competitive risk regression models were used to assess colon cancer cause-specific death (CSD) and non-colon cancer cause-specific death (NCSD). Survival prediction nomograms were constructed to predict overall survival (OS) and colon cancer cause-specific survival (CSS). The predictive abilities of the constructed models were evaluated by the concordance indexes (C-indexes) and calibration curves. Results A total of 25,110 patients were identified, 21.7% received chemotherapy, and 78.3% were without chemotherapy. A total of 10,916 patients were extracted after propensity score matching. The estimated 3-year overall survival rates of chemotherapy were 0.7% higher than non- chemotherapy. The estimated 5-year and 10-year overall survival rates of non-chemotherapy were 1.3 and 2.1% higher than chemotherapy, respectively. Survival prediction models showed good discrimination (the C-indexes between 0.582 and 0.757) and excellent calibration. Conclusions Chemotherapy improves the short-term (43 months) survival benefit of stage II colon cancer patients who received radical surgery. Survival prediction models can be used to predict OS and CSS of patients receiving chemotherapy as well as OS and CSS of patients not receiving chemotherapy and to make individualized treatment recommendations for stage II colon cancer patients who received radical surgery.

scholarly journals Impact of Palliative Gastrectomy in Patients with Incurable Gastric Cancer

Medicina ◽  
2021 ◽  
Vol 57 (3) ◽  
pp. 198
Author(s):  
Ji Yeon Park ◽  
Byunghyuk Yu ◽  
Ki Bum Park ◽  
Oh Kyoung Kwon ◽  
Seung Soo Lee ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Tumor Resection ◽  
Palliative Resection ◽  
Primary Tumors ◽  
Palliative Intent ◽  
Palliative Gastrectomy ◽  
Gastric Cancer Patients ◽  
The Impact

Background and Objectives: The prognosis of metastatic or unresectable gastric cancer is dismal, and the benefits of the palliative resection of primary tumors with noncurative intent remain controversial. This study aimed to evaluate the impact of palliative gastrectomy (PG) on overall survival in gastric cancer patients. Materials and Methods: One hundred forty-eight gastric cancer patients who underwent PG or a nonresection (NR) procedure between January 2011 and 2017 were retrospectively reviewed to select and analyze clinicopathological factors that affected prognosis. Results: Fifty-five patients underwent primary tumor resection with palliative intent, and 93 underwent NR procedures owing to the presence of metastatic or unresectable disease. The PG group was younger and more female dominant. In the PG group, R1 and R2 resection were performed in two patients (3.6%) and 53 patients (96.4%), respectively. The PG group had a significantly longer median overall survival than the NR group (28.4 vs. 7.7 months, p < 0.001). Multivariate analyses revealed that the overall survival was significantly better after palliative resection (hazard ratio (HR), 0.169; 95% confidence interval (CI), 0.088–0.324; p < 0.001) in patients with American Society of Anesthesiologists Physical Status (ASA) scores ≤1 (HR, 0.506; 95% CI, 0.291–0.878; p = 0.015) and those who received postoperative chemotherapy (HR, 0.487; 95% CI, 0.296–0.799; p = 0.004). Among the patients undergoing palliative resection, the presence of <15 positive lymph nodes was the only significant predictor of better overall survival (HR, 0.329; 95% CI, 0.121–0.895; p = 0.030). Conclusions: PG might lead to the prolonged survival of certain patients with incurable gastric cancer, particularly those with less-extensive lymph-node metastasis.

scholarly journals A Survey and Analysis on Automated Glioma Brain Tumor Segmentation and Overall Patient Survival Prediction

2021 ◽  
Author(s):  
Rupal Agravat ◽  
Mehul Raval
Keyword(s):  
Overall Survival ◽  
Brain Tumor ◽  
Automatic Segmentation ◽  
High Volume ◽  
Physical Symptoms ◽  
Tumor Segmentation ◽  
Survival Prediction ◽  
Neural Network Models ◽  
Brain Tumor Segmentation ◽  
Overall Survival Prediction

<div>Glioma is the most deadly brain tumor with high mortality. Treatment planning by human experts depends on the proper diagnosis of physical symptoms along with Magnetic Resonance(MR) image analysis. Highly variability of a brain tumor in terms of size, shape, location, and a high volume of MR images makes the analysis time-consuming. Automatic segmentation methods achieve a reduction in time with excellent reproducible results.</div><div>The article aims to survey the advancement of automated methods for Glioma brain tumor segmentation. It is also essential to make an objective evaluation of various models based on the benchmark. Therefore, the 2012 - 2019 BraTS challenges database evaluates state-of-the-art methods. The complexity of tasks under the challenge has grown from segmentation (Task1) to overall survival prediction (Task 2) to uncertainty prediction for classification (Task 3). The paper covers the complete gamut of brain tumor segmentation using handcrafted features to deep neural network models for Task 1. The aim is to showcase a complete change of trends in automated brain tumor models. The paper also covers end to end joint models involving brain tumor segmentation and overall survival prediction. All the methods are probed, and parameters that affect performance are tabulated and analyzed.</div>

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