Aim: SMAD4 immunohistochemistry is considered a valuable prognostic marker in colorectal cancer, but individual studies have often been small and the results variable. A meta-analysis could potentially clarify these findings.
Methods: In September 2014, a Pubmed and Google Scholar search was conducted to find publications that reported the prognostic value of SMAD4 expression. A meta-analysis was performed to clarify the association between SMAD4 expression and survival outcomes.
Results: 137 studies were found, of which 13 were considered eligible. The studies consisted of a total of 3800 patients. Three different endpoints were taken into account, namely, overall survival (OS), disease-free survival (DFS), and cancer-specific survival (CSS). In addition, the studies were divided into univariate and multivariate analyses. The pooled hazard ratios were given as follows: univariate CSS = 1.75 [95% confidence interval (CI): 0.93-3.32; z= 1.69; P= .09]; multivariate CSS = 2.17 (95% CI: 1.56-3.01; z= 4.65; P= .000); univariate DFS = 2.11 (95% CI: 1.36-3.28; z= 3.32; P= .001); multivariate DFS = 2.15 (95% CI: 1.56-3.01; z= 4.65; P= .000); univariate OS and DFS = 2.30 (95% CI: 1.41-3.73; z= 3.36; P= .001); univariate OS = 2.28 (95% CI: 1.30-4.00; z= 2.89; P= .004).
Conclusion: The results of the presented meta-analyses indicate that SMAD4 expression status using immunohistochemistry is a prognostic marker for patient survival.
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http://dx.doi.org/10.1016/j.tranon.2014.11.003 | DOI Listing |
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Necmettin Erbakan University, Meram Faculty of Medicine, Department of Medical Oncology, Konya, Turkey.
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Gastric cancer is an aggressive malignancy characterized by significant clinical heterogeneity arising from complex genetic and environmental interactions. This study employed single-cell RNA sequencing, using the 10 × Genomics platform, to analyze 262,532 cells from gastric cancer samples, identifying 32 distinct clusters and 10 major cell types, including immune cells (e.g.
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Université Libre de Bruxelles, Hôpital Universitaire de Bruxelles, Instiut Jules Bordet, Departement of Medical Oncology.
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Recent Findings: Trials like Neo-Combi, Neo-Trio and COMBI-Neo show that pCR is crucial for long-term success in targeted therapy for melanoma, while studies like OpACIN-neo and SWOG S1801 demonstrate that immunotherapy can provide durable benefits even with partial responses. Findings from NADINA and the INMC analysis highlight that immunotherapy achieves higher pathologic response rates and improved survival outcomes, offering broader benefits compared to the pCR-dependent outcomes of targeted therapy.
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Hunan Provincial Key Laboratory of Micro & Nano Materials Interface Science, College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China.
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Background: Osteoporosis is a common age-related disease with disabling consequences, the early diagnosis of which is difficult due to its long and hidden course, which often leads to diagnosis only after a fracture. In this regard, great expectations are placed on advanced developments in machine learning technologies aimed at predicting osteoporosis at an early stage of development, including the use of large data sets containing information on genetic and clinical predictors of the disease. Nevertheless, the inclusion of DNA markers in prediction models is fraught with a number of difficulties due to the complex polygenic and heterogeneous nature of the disease.
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