Chen Q, Shen L, Li S. Tumor volume reduction after induction chemotherapy with gemcitabine plus cisplatin in nasopharyngeal carcinoma.
Eur Arch Otorhinolaryngol 2022;
280:2497-2509. [PMID:
36572820 DOI:
10.1007/s00405-022-07809-6]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 12/18/2022] [Indexed: 12/28/2022]
Abstract
OBJECTIVES
To evaluate the tumor volume reduction after induction chemotherapy (IC) with gemcitabine plus cisplatin (GP) and to build prediction models for tumor volume reduction in nasopharyngeal carcinoma (NPC).
METHODS
NPC patients who received GP IC were retrospectively enrolled. The gross tumor volume of the nasopharynx and lymph nodes (GTVnx and GTVnd) were contoured before and after IC. Univariate and multivariate analyses were performed to identify associated factors. Nomogram models were constructed to predict the possibility of tumor volume reduction.
RESULTS
A total of 192 patients were enrolled. The mean relative volume reduction for GTVnx and GTVnd was 29.66% and 31.75%, respectively. The volume reduction of GTVnx and GTVnd had a weak association (r = 0.229, p < 0.001). For GTVnx volume reduction, pre-treatment neutrophil count (p = 0.043), lymphocyte count (p = 0.026), LDH level (p = 0.005), and BMI (p = 0.020) were independently associated factors. For GTVnd volume reduction, pre-treatment EBV-DNA (p = 0.029), GTVnd volume (p < 0.001), eosinophil count (p = 0.043), NLR (p = 0.039), LDH level (p = 0.026), and serum potassium level (p = 0.027) were independently associated factors. For the GTVnx nomogram model, areas under the receiver-operating characteristic curve (AUC) were 0.702 and 0.698 for the training and validation cohorts, respectively. For the GTVnd nomogram model, the AUC was 0.872 and 0.758 for the training and validation cohorts, respectively.
CONCLUSIONS
Tumor volumes reduce significantly after GP induction chemotherapy. Nomogram models for predicting the possibility of tumor volume reduction are built.
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