<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>2022</volume><submitter>Yang Z</submitter><pubmed_abstract>&lt;h4>Background&lt;/h4>With the development of sequencing technology, an increasing number of biomarkers has been identified in endometrial carcinoma (EC). However, there have been few comprehensive analyses of the &lt;i>KIF4A&lt;/i> gene in patients with EC.&lt;h4>Methods&lt;/h4>Based on raw data in public databases, the &lt;i>KIF4A&lt;/i> gene and protein expression in EC were validated. Logistic regression analysis was conducted to analyze the correlations between clinical characteristics and the &lt;i>KIF4A&lt;/i> expression. Kaplan-Meier analysis was used to explore the difference in survival in clinical subgroups. Meanwhile, we used meta-analysis in multiple datasets to investigate the prognostic value of &lt;i>KIF4A&lt;/i>. In addition, Cox regression analysis was used to confirm the independent prognostic value of </pubmed_abstract><journal>Disease markers</journal><pagination>9621701</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8814714</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Prognostic Value and Immune-Infiltration Pattern of &lt;i>KIF4A&lt;/i> in Patients with Endometrial Carcinoma.</pubmed_title><pmcid>PMC8814714</pmcid><pubmed_authors>Yang Z</pubmed_authors><pubmed_authors>Li Y</pubmed_authors><pubmed_authors>Luo S</pubmed_authors><pubmed_authors>Shen X</pubmed_authors></additional><is_claimable>false</is_claimable><name>Prognostic Value and Immune-Infiltration Pattern of &lt;i>KIF4A&lt;/i> in Patients with Endometrial Carcinoma.</name><description>&lt;h4>Background&lt;/h4>With the development of sequencing technology, an increasing number of biomarkers has been identified in endometrial carcinoma (EC). However, there have been few comprehensive analyses of the &lt;i>KIF4A&lt;/i> gene in patients with EC.&lt;h4>Methods&lt;/h4>Based on raw data in public databases, the &lt;i>KIF4A&lt;/i> gene and protein expression in EC were validated. Logistic regression analysis was conducted to analyze the correlations between clinical characteristics and the &lt;i>KIF4A&lt;/i> expression. Kaplan-Meier analysis was used to explore the difference in survival in clinical subgroups. Meanwhile, we used meta-analysis in multiple datasets to investigate the prognostic value of &lt;i>KIF4A&lt;/i>. In addition, Cox regression analysis was used to confirm the independent prognostic value of </description><dates><release>2022-01-01T00:00:00Z</release><publication>2022</publication><modification>2025-06-01T04:06:39.059Z</modification><creation>2025-06-01T04:06:39.059Z</creation></dates><accession>S-EPMC8814714</accession><cross_references><pubmed>35126794</pubmed><doi>10.1155/2022/9621701</doi></cross_references></HashMap>