A PROGNOSTIC BIOMARKERS IN ENDOMETRIAL CANCER-A META ANALYSIS

Abstract

Introduction: Endometrial cancer (EC) is the most frequent gynaecological cancer in developed countries, and its prevalence is increasing. While the majority of women with endometrial cancer are identified with highly treatable illness and have acceptable outcomes, a considerable minority have severe clinicopathological features that indicate a bad prognosis. Prognostic biomarkers that
reliably identify people at highest risk of disease recurrence and mortality can guide management methods to ensure that patients receive evidence-based and individualised care. Materials and Methods: All selected articles were reviewed, and data were compiled in a comprehensive database that included: general information (first author's name, country, journal, year of publication); number of patients and analytical technique used; association of the described biomarkers with different prognostic factors (histological type, histological grade, FIGO stage, myometrial invasion, lymph node status, LVSI, cervical invasion, metastasis, TCGA molecular classification, A meta-analysis on OS was performed for the five most studied biomarkers. Only studies providing an estimate of the hazard ratio (HR) and the associated 95% CI for the parameter here considered were included.
Results: Our initial PubMed, Medline, Scopus, Chochrane and DOAJ search yielded 250 hits, which were reduced to 155 following the first screening phase. 39 of them satisfied our criteria and were considered for this review. Biomarker research on prognostic biomarkers in the EC has expanded over time, with Asia (43%) and Europe (41%) being the largest contributors. At the country level, Japan, China, the United States of America, Turkey, and Norway are the leading countries.
Conclusion: According to our meta-analysis, ESR1, TP53, and WFDC2 have the ability to predict overall survival in EC. The limitations of the published research are noted in terms of suitable study design, a lack of high-throughput measurements, and statistical flaws, and novel methodologies and possibilities for the identification and validation of clinically relevant EC prognostic biomarkers are presented