Pluimakers VG, van Santen SS, Fiocco M, Bakker MCE, van der Lelij AJ, van den Heuvel-Eibrink MM, Neggers SJCMM. Can biomarkers be used to improve diagnosis and prediction of metabolic syndrome in childhood cancer survivors? A systematic review.
Obes Rev 2021;
22:e13312. [PMID:
34258851 PMCID:
PMC8596408 DOI:
10.1111/obr.13312]
[Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 05/11/2021] [Accepted: 06/09/2021] [Indexed: 12/26/2022]
Abstract
Childhood cancer survivors (CCS) are at increased risk to develop metabolic syndrome (MetS), diabetes, and cardiovascular disease. Common criteria underestimate adiposity and possibly underdiagnose MetS, particularly after abdominal radiotherapy. A systematic literature review and meta-analysis on the diagnostic and predictive value of nine newer MetS related biomarkers (adiponectin, leptin, uric acid, hsCRP, TNF-alpha, IL-1, IL-6, apolipoprotein B (apoB), and lipoprotein(a) [lp(a)]) in survivors and adult non-cancer survivors was performed by searching PubMed and Embase. Evidence was summarized with GRADE after risk of bias evaluation (QUADAS-2/QUIPS). Eligible studies on promising biomarkers were pooled. We identified 175 general population and five CCS studies. In the general population, valuable predictive biomarkers are uric acid, adiponectin, hsCRP and apoB (high level of evidence), and leptin (moderate level of evidence). Valuable diagnostic biomarkers are hsCRP, adiponectin, uric acid, and leptin (low, low, moderate, and high level of evidence, respectively). Meta-analysis showed OR for hyperuricemia of 2.94 (age-/sex-adjusted), OR per unit uric acid increase of 1.086 (unadjusted), and AUC for hsCRP of 0.71 (unadjusted). Uric acid, adiponectin, hsCRP, leptin, and apoB can be alternative biomarkers in the screening setting for MetS in survivors, to enhance early identification of those at high risk of subsequent complications.
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