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Predicting Teeth Extraction after Concurrent Chemoradiotherapy in Locally Advanced Nasopharyngeal Cancer Patients Using the Novel GLUCAR Index
- Source :
- Diagnostics, Vol 13, Iss 23, p 3594 (2023)
- Publication Year :
- 2023
- Publisher :
- MDPI AG, 2023.
-
Abstract
- To evaluate the value of the newly created GLUCAR index in predicting tooth extraction rates after concurrent chemoradiotherapy (C-CRT) in locally advanced nasopharyngeal carcinomas (LA-NPCs). Methods: A total of 187 LA-NPC patients who received C-CRT were retrospectively analyzed. The GLUCAR index was defined as ′GLUCAR = (Fasting Glucose × CRP/Albumin Ratio) by utilizing measures of glucose, C-reactive protein (CRP), and albumin obtained on the first day of C-CRT. Results: The optimal GLUCAR cutoff was 31.8 (area under the curve: 78.1%; sensitivity: 70.5%; specificity: 70.7%, Youden: 0.412), dividing the study cohort into two groups: GLUCAR ˂ 1.8 (N = 78) and GLUCAR ≥ 31.8 (N = 109) groups. A comparison between the two groups found that the tooth extraction rate was significantly higher in the group with a GLUCAR ≥ 31.8 (84.4% vs. 47.4% for GLUCAR ˂ 31.8; odds ratio (OR):1.82; p < 0.001). In the univariate analysis, the mean mandibular dose ≥ 38.5 Gy group (76.5% vs. 54.9% for p = 0.008), mandibular V55.2 Gy group ≥ 40.5% (80.3 vs. 63.5 for p = 0.004, OR; 1.30), and being diabetic (71.8% vs. 57.9% for nondiabetics; OR: 1.23; p = 0.007) appeared as the additional factors significantly associated with higher tooth extraction rates. All four characteristics remained independent predictors of higher tooth extraction rates after C-CRT in the multivariate analysis (p < 0.05 for each). Conclusions: The GLUCAR index, first introduced here, may serve as a robust new biomarker for predicting post-C-CRT tooth extraction rates and stratifying patients according to their tooth loss risk after treatment.
Details
- Language :
- English
- ISSN :
- 20754418
- Volume :
- 13
- Issue :
- 23
- Database :
- Directory of Open Access Journals
- Journal :
- Diagnostics
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.3ff735fa72de4d22ae3cd6cfb4e647b4
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/diagnostics13233594