scholarly journals Clinicopathological Significance and Diagnostic Accuracy of HER2 Immunohistochemistry in Colorectal Cancer: A Meta-Analysis

2016 ◽  
Vol 31 (4) ◽  
pp. 389-394 ◽  
Author(s):  
Jung-Soo Pyo ◽  
Guhyun Kang ◽  
Kyeongmee Park
Keyword(s):  
Colorectal Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Diagnostic Accuracy ◽  
Distant Metastasis ◽  
Meta Analysis ◽  
Test Accuracy ◽  
Her2 Expression ◽  
Node Metastasis ◽  
Clinicopathological Significance

Introduction The aim of this study was to elucidate the clinicopathological significance of HER2 expression and the diagnostic accuracy of HER2 immunohistochemistry (IHC) in colorectal cancer (CRC). A total of 2,573 CRC cases from 13 eligible studies were included. Methods We performed a meta-analysis to examine the correlations between HER2 expression and clinicopathological characteristics in CRC. Concordance analysis between HER2 IHC and in situ hybridization (ISH) and diagnostic test accuracy review was conducted. Results The estimated rate of HER2 IHC overexpression was 0.162 (95% confidence interval [CI] 0.106-0.240). HER2 IHC overexpression was significantly correlated with lymph node metastasis and distant metastasis but not tumor depth. HER2 IHC overexpression was not correlated with overall survival. The concordance rates between IHC and ISH were 0.968 (95% CI 0.881-0.992), 0.377 (95% CI 0.225-0.557) and 0.780 (95% CI 0.390-0.952) for HER2 IHC scores of 0/1+, 2+ and 3+, respectively. The diagnostic test accuracy review of HER2 IHC revealed that the pooled sensitivity and specificity were 0.71 (95% CI 0.58-0.82) and 0.96 (95% CI 0.94-0.97), respectively. The diagnostic odds ratio and area under the summary receiver operating characteristic curve were 51.34 (95% CI 3.82-690.54) and 0.9704, respectively. Conclusions HER2 IHC overexpression was significantly correlated with lymph node metastasis and distant metastasis. CRC cases with HER2 IHC scores of 0/1+ exhibited good agreement with the ISH data. However, additional ISH analysis is needed to confirm HER2 status in cases with IHC scores of 2+ or 3+.

Prognostic value and clinicopathological significance of programmed cell death ligand 1 (PD-L1) expression in resected gastric cancer: A meta-analysis.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e15512-e15512
Author(s):  
Shuixiu Yu ◽  
Jing Ning ◽  
Wei Ouyang ◽  
Lingzhi Ding ◽  
Kaisu Lin ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Distant Metastasis ◽  
Prognostic Value ◽  
Meta Analysis ◽  
High Expression ◽  
Node Metastasis ◽  
Clinicopathological Significance ◽  
Resected Gastric Cancer

e15512 Background: Programmed death ligand 1 (PD-L1) expression has become a promising biomarker in predicting the efficacy of immune checkpoint inhibitors in various advanced cancers, including gastric cancer (GC). However, the prognostic value and clinicopathological significance of PD-L1 in GC is still not clearly identified. Hence, we carried out a meta-analysis to investigate the potential role of PD-L1 in GC, expecting to provide new clues for the judgement of prognosis in resected gastric cancer. Methods: A literature search strategy was performed from the PubMed, Web of Science, EMBASE, and the Cochrane Library database as of December 1, 2018. Relevant data was rigorously extracted from the included literatures. Hazard ratios (HRs) and Odds ratios (ORs) along with 95% confidence intervals (95% CIs) were used to evaluate the prognostic value or clinicopathological significance of PD-L1 expression in GC. Results: A total of 21 studies containing 6021 patients fitted into our meta-analysis. The pooled HRs indicated that PD-L1 high-expression accompanied with a worse overall survival (OS) (HR=1.28, 95% CI: 1.01-1.62, P=0.04) in GC, while no correlation with disease-free survival (DFS) (HR=0.88, 95%CI: 0.53-1.45, P=0.61). Subgroup analysis showed that PD-L1 high-expression was negatively associated with distant metastasis groups (OR=0.66, 95%CI:0.48-0.89, P=0.01), but was positively related to elderly(OR=1.19, 95%CI: 1.01-1.40, P=0.04), lymph-node metastasis(OR=1.63, 95%CI: 1.08-2.46, P=0.02), deeper tumor infiltration(OR=1.73, 95%CI: 1.08-2.79, P=0.02), Epstein-Barr virus infection positive (EBV+) (OR=8.01, 95%CI: 3.10-20.72, P<0.0001), and MET positive (MET+) groups (OR=1.78, 95%CI: 1.05-3.00, P=0.03). Conclusions: Our meta-analysis found that the high-expression of PD-L1 accompanied with a poor OS. Moreover, PD-L1 high-expression was related to age, lymph-node metastasis, depth of infiltration, distant metastasis, EBV infection, and MET status.

scholarly journals The role of microvessel density, lymph node metastasis, and tumor size as prognostic factors of distant metastasis in colorectal cancer

2017 ◽  
Vol 13 (6) ◽  
pp. 4327-4333 ◽  
Author(s):  
Tomonari Cho ◽  
Eisuke Shiozawa ◽  
Fumihiko Urushibara ◽  
Nana Arai ◽  
Toshitaka Funaki ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Prognostic Factors ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Distant Metastasis ◽  
Microvessel Density ◽  
Tumor Size ◽  
Node Metastasis

scholarly journals Artificial intelligence for pre-operative lymph node staging in colorectal cancer: a systematic review and meta-analysis

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sergei Bedrikovetski ◽  
Nagendra N. Dudi-Venkata ◽  
Hidde M. Kroon ◽  
Warren Seow ◽  
Ryash Vather ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Colorectal Cancer ◽  
Systematic Review ◽  
Deep Learning ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Meta Analysis ◽  
Cochrane Library ◽  
Learning Models ◽  
Node Metastasis

Abstract Background Artificial intelligence (AI) is increasingly being used in medical imaging analysis. We aimed to evaluate the diagnostic accuracy of AI models used for detection of lymph node metastasis on pre-operative staging imaging for colorectal cancer. Methods A systematic review was conducted according to PRISMA guidelines using a literature search of PubMed (MEDLINE), EMBASE, IEEE Xplore and the Cochrane Library for studies published from January 2010 to October 2020. Studies reporting on the accuracy of radiomics models and/or deep learning for the detection of lymph node metastasis in colorectal cancer by CT/MRI were included. Conference abstracts and studies reporting accuracy of image segmentation rather than nodal classification were excluded. The quality of the studies was assessed using a modified questionnaire of the QUADAS-2 criteria. Characteristics and diagnostic measures from each study were extracted. Pooling of area under the receiver operating characteristic curve (AUROC) was calculated in a meta-analysis. Results Seventeen eligible studies were identified for inclusion in the systematic review, of which 12 used radiomics models and five used deep learning models. High risk of bias was found in two studies and there was significant heterogeneity among radiomics papers (73.0%). In rectal cancer, there was a per-patient AUROC of 0.808 (0.739–0.876) and 0.917 (0.882–0.952) for radiomics and deep learning models, respectively. Both models performed better than the radiologists who had an AUROC of 0.688 (0.603 to 0.772). Similarly in colorectal cancer, radiomics models with a per-patient AUROC of 0.727 (0.633–0.821) outperformed the radiologist who had an AUROC of 0.676 (0.627–0.725). Conclusion AI models have the potential to predict lymph node metastasis more accurately in rectal and colorectal cancer, however, radiomics studies are heterogeneous and deep learning studies are scarce. Trial registration PROSPERO CRD42020218004.

scholarly journals Prognosis assessment of CD44+/CD24- in Breast Cancer Patients: a systematic review and meta-analysis

2021 ◽  
Author(s):  
Jingjing Gu ◽  
Dandan Chen ◽  
Zhiqiang li ◽  
Yongliang Yang ◽  
Zhaoming Ma ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Cancer Patients ◽  
Distant Metastasis ◽  
Tumor Size ◽  
Meta Analysis ◽  
Breast Cancer Patients ◽  
Clinical Prognosis ◽  
Node Metastasis

Abstract Purpose: This meta-analysis investigated the relationships between the CD44+/CD24- phenotype and tumor size, lymph node metastasis, distant metastasis, disease-free survival (DFS), and overall survival (OS) in 8036 postoperative breast cancer patients enrolled in 23 studies.Methods: A literature search of PubMed, Medline, Cochrane, Embase, and PMC was conducted to identify eligible studies. The combined odds ratios (ORs) and 95% confidence intervals (95%CIs) were analyzed to evaluate the relationships between the CD44+/CD24- phenotype and the pathological and biological characteristics of breast cancer patients, and the combined hazard ratios (HRs) and 95% CIs were calculated to evaluate the relationships between CD44+/CD24- and DFS and OS of breast cancer petients using Stata12.0 software.Results: The CD44+/CD24- phenotype were not related to the tumor size (tumor size > 2.0 cm vs ≤ 2.0 cm, combined OR = 0.98, 95%CI: 0.68–1.34, p = 0.792) and didn’t promote lymph node metastasis (lymph node metastasis vs. no lymph node metastasis, combined OR = 0.94, 95% CI: 0.71–1.26, p = 0.692) and distant metastasis (distant metastasis vs no distant metastasis, combined OR = 3.88, 95% CI: 0.93–16.24, p = 0.064). The CD44+/CD24- phenotype was negatively correlated with postoperative DFS (HR = 1.67, 95% CI: 1.35–2.07, p <0.00001) and OS (combined HR = 1.52, 95%CI: 1.21–1.91, p = 0.0004).Conclusion: These results suggested expression of the CD44+/CD24- phenotype can be used as a reliable indicator of clinical prognosis and a potential therapeutic targets in breastcancer patients.

scholarly journals Clinicopathological and Prognostic Significance of LINC00673 in Human Malignancy: A Review and Meta-analysis

2021 ◽  
Author(s):  
Yurong Zhu ◽  
Zhifa Zhang ◽  
Hui Peng ◽  
Weiping Li ◽  
Shaowei Hu ◽  
...  
Keyword(s):  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Distant Metastasis ◽  
Meta Analysis ◽  
Prognostic Significance ◽  
Clinicopathological Parameters ◽  
Tumour Stage ◽  
Malignant Tumours ◽  
Node Metastasis ◽  
T Stage

Background: We conducted this research to investigate the relationship between linc00673 expression and prognosis and clinicopathological parameters in human malignancies. Methods: The PubMed, Embase, WOS and CNKI databases were used to collect eligible research data before January 4, 2021. Meta-analysis was performed using Stata 12.0 software. Pooled ORs (odds ratios) or HRs (hazard ratios) and their 95% CIs were calculated to evaluate the association of linc00673 expression with survival outcomes and clinical parameters. Results: We finally included 17 articles and a total of 1539 cases for the meta-analysis. The results indicated that linc00673 was significantly correlated with T stage (P=0.006), tumour stage (P&lt;0.001), lymph node metastasis (P&lt;0.001), and distant metastasis ( P&lt;0.001). In addition, the results suggested that elevated linc00673 expression predicted a poor overall survival time (P=0.034) and acted as an independent prognostic factor (P&lt;0.001) for OS in patients with malignancy. Although potential evidence of publication bias was found in the studies on OS in relation to tumour stage in the multivariate analysis, the trim-and-fill analysis confirmed that the results remained stable. Conclusion: Overexpression of linc00673 was significantly correlated with shorter OS time in patients with malignant tumours. Moreover, the increased expression level of linc00673 was significantly correlated with T stage, tumour stage, lymph node metastasis, and distant metastasis. The results presented in this article revealed that linc00673 might be involved in the progression and invasion of malignancy and serve as a novel prognostic biomarker and potential therapeutic target for malignancy.

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