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. 2022 Dec 1:9:996127.
doi: 10.3389/fmed.2022.996127. eCollection 2022.

Recurrence risk stratification based on Epstein-Barr virus DNA to identify enlarged retropharyngeal lymph nodes of nasopharyngeal carcinoma: A model-histopathologic correlation study

Minjie Mao  1   2 , Xueping Wang  1   2 , Sharvesh Raj Seeruttun  2   3 , Peidong Chi  1   2 , Kewei Huang  1   2 , Wen Liu  1   2 , Wencheng Tan  2   4
Affiliations

Recurrence risk stratification based on Epstein-Barr virus DNA to identify enlarged retropharyngeal lymph nodes of nasopharyngeal carcinoma: A model-histopathologic correlation study

Minjie Mao et al. Front Med (Lausanne). .

Abstract

Background: Accurate assessment of the nature of enlarged retropharyngeal lymph nodes (RLN) of nasopharyngeal carcinoma (NPC) patients after radiotherapy is related to selecting appropriate treatments and avoiding unnecessary therapy. This study aimed to develop a non-invasive and effective model for predicting the recurrence of RLN (RRLN) in NPC.

Materials and methods: The data of post-radiotherapy NPC patients (N = 76) with abnormal enlargement of RLN who underwent endonasopharyngeal ultrasound-guided fine-needle aspirations (EPUS-FNA) were examined. They were randomly divided into a discovery (n = 53) and validation (n = 23) cohort. Univariate logistic regression was used to assess the association between variables (magnetic resonance imaging characteristics, EBV DNA) and RRLN. Multiple logistic regression was used to construct a prediction model. The accuracy of the model was assessed by discrimination and calibration, and decision curves were used to assess the clinical reliability of the model for the identification of high risk RLNs for possible recurrence.

Results: Abnormal enhancement, minimum axis diameter (MAD) and EBV-DNA were identified as independent risk factors for RRLN and could stratify NPC patients into three risk groups. The probability of RRLN in the low-, medium-, and high-risk groups were 37.5, 82.4, and 100%, respectively. The AUC of the final predictive model was 0.882 (95% CI: 0.782-0.982) in the discovery cohort and 0.926 (95% CI, 0.827-1.000) in the validation cohort, demonstrating good clinical accuracy for predicting the RRLN of NPC patients. The favorable performance of the model was confirmed by the calibration plot and decision curve analysis.

Conclusion: The nomogram model constructed in the study could be reliable in predicting the risk of RRLN after radiotherapy for NPC patients.

Keywords: EBV; nasopharyngeal carcinoma; prediction model; recurrence; retropharyngeal lymph nodes.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Risk calculator for recurrence of retropharyngeal lymph node (RRLN) in nasopharyngeal carcinoma (NPC) patients with post-radiotherapy. (A) Nomogram predicting the risk of RRLN. Patients can be divided into three groups based on their scores: low-risk group (total points: ≤100), middle-risk group (total points: 100–200) and high-risk group (total points: >200). (B) Bar plot showing RRLN in the three predefined subgroups of predicted outcomes from the discovery cohort, and (C) the validation cohort.
FIGURE 2
FIGURE 2
Comparison of model indices from (A) the discovery cohort and (B) the validation cohort. Calibration curves of the model for recurrence of retropharyngeal lymph node (RRLN) prediction from (C) the discovery cohort and (D) the validation cohort.
FIGURE 3
FIGURE 3
Decision curve analysis demonstrating the clinical utility in predicting recurrence of retropharyngeal lymph node (RRLN) of the model from (A) the discovery cohort and (B) the validation cohort. ROC curves demonstrating the accuracy for predicting RRLN from (C) the discovery cohort and (D) the validation cohort.
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