<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>13</volume><submitter>Zhang K</submitter><pubmed_abstract>&lt;h4>Background&lt;/h4>Parathyroid carcinoma (PC) is a rare malignancy without a commonly acknowledged prognostic assessment and treatment system. This study captures how independent prognostic factors and tumor size correlate with outcomes in patients with PC.&lt;h4>Methods&lt;/h4>The Surveillance, Epidemiology, and End Results database was used to perform a retrospective analysis on PC patients from 2000 to 2018. Univariate and multivariable survival analyses were performed to evaluate cancer-specific survival (CSS) and overall survival (OS), to identify independent prognostic factors in the PC patient population. A generalized additive model was applied to conduct smooth curve fitting and to examine the association between tumor size and relative risk of death.&lt;h4>Results&lt;/h4>A total of 590 patie</pubmed_abstract><journal>Frontiers in endocrinology</journal><pagination>882579</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9285012</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Non-Linear Correlation Between Tumor Size and Survival Outcomes for Parathyroid Carcinoma: A SEER Population-Based Cohort Study.</pubmed_title><pmcid>PMC9285012</pmcid><pubmed_authors>Li Z</pubmed_authors><pubmed_authors>Zhang K</pubmed_authors><pubmed_authors>Su A</pubmed_authors><pubmed_authors>Zhu J</pubmed_authors><pubmed_authors>Wei T</pubmed_authors><pubmed_authors>Zhao W</pubmed_authors><pubmed_authors>Wang X</pubmed_authors><pubmed_authors>He L</pubmed_authors><pubmed_authors>Chen YW</pubmed_authors></additional><is_claimable>false</is_claimable><name>Non-Linear Correlation Between Tumor Size and Survival Outcomes for Parathyroid Carcinoma: A SEER Population-Based Cohort Study.</name><description>&lt;h4>Background&lt;/h4>Parathyroid carcinoma (PC) is a rare malignancy without a commonly acknowledged prognostic assessment and treatment system. This study captures how independent prognostic factors and tumor size correlate with outcomes in patients with PC.&lt;h4>Methods&lt;/h4>The Surveillance, Epidemiology, and End Results database was used to perform a retrospective analysis on PC patients from 2000 to 2018. Univariate and multivariable survival analyses were performed to evaluate cancer-specific survival (CSS) and overall survival (OS), to identify independent prognostic factors in the PC patient population. A generalized additive model was applied to conduct smooth curve fitting and to examine the association between tumor size and relative risk of death.&lt;h4>Results&lt;/h4>A total of 590 patie</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022</publication><modification>2025-04-04T09:41:42.928Z</modification><creation>2025-04-04T09:41:42.928Z</creation></dates><accession>S-EPMC9285012</accession><cross_references><pubmed>35846299</pubmed><doi>10.3389/fendo.2022.882579</doi></cross_references></HashMap>