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Global Immune-Nutrition-Inflammation Index as a novel comprehensive biomarker in predicting the radiation-induced trismus rates in locally advanced nasopharyngeal carcinoma patients

dc.contributor.coauthorSomay, Efsun
dc.contributor.coauthorTopkan, Erkan
dc.contributor.coauthorBaşçıl, Sibel
dc.contributor.coauthorÖzturk, Düriye
dc.contributor.coauthorPehlivan, Berrin
dc.contributor.departmentSchool of Medicine
dc.contributor.kuauthorDurankuş, Nilüfer Kılıç
dc.contributor.kuauthorSelek, Uğur
dc.contributor.kuauthorŞenyürek, Şükran
dc.contributor.schoolcollegeinstituteSCHOOL OF MEDICINE
dc.date.accessioned2024-12-29T09:36:38Z
dc.date.issued2024
dc.description.abstractNasopharyngeal carcinoma (NPC) is a prevalent cancer in certain regions, often treated with concurrent chemoradiotherapy (CCRT), which can lead to complications such as radiation-induced trismus (RIT). In this study, we aimed to evaluate whether the novel pretreatment Global Immune-Nutrition-Inflammation Index (GINI) can predict RIT in locally advanced nasopharyngeal carcinoma (LA-NPC) patients undergoing CCRT. Data of LA-NPC patients presenting without RIT were reviewed retrospectively. Any post-CCRT maximum mouth openings (MMO) <= 35 mm were considered RIT. The GINI index was calculated using the formula: GINI = (CRP x Monocytes x Platelets x Neutrophils) - (Albumin x Lymphocytes). We used receiver operating characteristic (ROC) curve analysis to examine the potential correlation between pretreatment GINI measures and post-CCRT RIT status. Logistic regression analysis examined the independence of the association between confounding factors and RIT rates. The study comprised 230 participants, and 52 (22.6%) received an RIT diagnosis. The optimal pre-CCRT GINI cutoff that dichotomizes RIT rates was determined to be 1424 (area under the curve [AUC]: 76%; sensitivity: 75.0%; specificity: 71.7%; J-index: 0.463). RIT incidence was significantly higher in the GINI >= 1424 group than in its GINI < 1424 counterpart (43.3% vs 9.3%; Hazard ratio (HR): 4.76; P < 0.001). Multivariate logistic regression analysis revealed that a pre-CCRT GINI >= 1424 was an independent predictor of increased RIT rates after definitive CCRT in this patient group (P < 0.001). In conclusion, the present results revealed that elevated pre-CCRT GINI measures (>= 1424) can efficiently and independently predict elevated RIT rates in LA-NPC patients after CCRT.
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.indexedbyPubMed
dc.description.issue6
dc.description.openaccessgold
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsorshipFunding: Authors received no specific funding for this work. Data availability: The data supporting this study's findings is available from the corresponding author, Efsun Somay, upon a reasonable special request.
dc.description.volume24
dc.identifier.doi10.17305/bb.2024.10616
dc.identifier.eissn2831-090X
dc.identifier.issn2831-0896
dc.identifier.quartileN/A
dc.identifier.scopus2-s2.0-85206707501
dc.identifier.urihttps://doi.org/10.17305/bb.2024.10616
dc.identifier.urihttps://hdl.handle.net/20.500.14288/22098
dc.identifier.wos1267340000001
dc.keywordsRadiation-induced trismus (RIT)
dc.keywordsGlobal immune-nutrition-inflammation index (GINI)
dc.keywordsConcurrent chemoradiotherapy (CCRT)
dc.keywordsNasopharyngeal carcinoma
dc.language.isoeng
dc.publisherAssociation of Basic Medical Sciences of FBIH
dc.relation.ispartofBiomolecules and Biomedicine
dc.subjectMedicine, research and experimental
dc.titleGlobal Immune-Nutrition-Inflammation Index as a novel comprehensive biomarker in predicting the radiation-induced trismus rates in locally advanced nasopharyngeal carcinoma patients
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.kuauthorDurankuş, Nilüfer Kılıç
local.contributor.kuauthorŞenyürek, Şükran
local.contributor.kuauthorSelek, Uğur
local.publication.orgunit1SCHOOL OF MEDICINE
local.publication.orgunit2School of Medicine
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relation.isOrgUnitOfPublication.latestForDiscoveryd02929e1-2a70-44f0-ae17-7819f587bedd
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