A systematic review and recommendations on the use of plasma EBV DNA for nasopharyngeal carcinoma

Lee, Anne W.M.; Lee, Victor; Ng, Wai‐Tong; Strojan, Primož; Saba, Nabil F.; Rinaldo, Alessandra; Willems, Stefan M.; Rodrigo, Juan P.; Forastiere, Arlene A.; Ferlito, Alfio

doi:10.1016/j.ejca.2021.05.022

Cited by 55 publications

(49 citation statements)

References 102 publications

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“…Only approximately 2% of NPC patients have stage I nasopharyngeal tumors, and most patients (>70%) are in the advanced stages 3 . To detect early‐stage NPC, circulating plasma Epstein–Barr virus (EBV) DNA is a useful biomarker to screen asymptomatic subjects for NPC, 4 and people with positive EBV DNA detection are recommended to undergo further nasopharyngoscopy. NPC often manifests as a protuberant tumor in the nasopharynx.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning for nasopharyngeal Carcinoma Identification Using Both White Light and Narrow‐Band Imaging Endoscopy

Wang

Bian

et al. 2021

The Laryngoscope

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Objectives/Hypothesis To develop a deep‐learning‐based automatic diagnosis system for identifying nasopharyngeal carcinoma (NPC) from noncancer (inflammation and hyperplasia), using both white light imaging (WLI) and narrow‐band imaging (NBI) nasopharyngoscopy images. Study Design Retrospective study. Methods A total of 4,783 nasopharyngoscopy images (2,898 WLI and 1,885 NBI) of 671 patients were collected and a novel deep convolutional neural network (DCNN) framework was developed named Siamese deep convolutional neural network (S‐DCNN), which can simultaneously utilize WLI and NBI images to improve the classification performance. To verify the effectiveness of combining the above‐mentioned two modal images for prediction, we compared the proposed S‐DCNN with two baseline models, namely DCNN‐1 (only considering WLI images) and DCNN‐2 (only considering NBI images). Results In the threefold cross‐validation, an overall accuracy and area under the curve of the three DCNNs achieved 94.9% (95% confidence interval [CI] 93.3%–96.5%) and 0.986 (95% CI 0.982–0.992), 87.0% (95% CI 84.2%–89.7%) and 0.930 (95% CI 0.906–0.961), and 92.8% (95% CI 90.4%–95.3%) and 0.971 (95% CI 0.953–0.992), respectively. The accuracy of S‐DCNN is significantly improved compared with DCNN‐1 (P‐value <.001) and DCNN‐2 (P‐value = .008). Conclusion Using the deep‐learning technology to automatically diagnose NPC under nasopharyngoscopy can provide valuable reference for NPC screening. Superior performance can be obtained by simultaneously utilizing the multimodal features of NBI image and WLI image of the same patient. Level of Evidence 3 Laryngoscope, 132:999–1007, 2022

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Section: Introductionmentioning

confidence: 99%

Deep Learning for nasopharyngeal Carcinoma Identification Using Both White Light and Narrow‐Band Imaging Endoscopy

Wang

Bian

et al. 2021

The Laryngoscope

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“…However, these relevant data are not available for all patients, and plasma EBV DNA assay by RT-PCR (reverse transcription-polymerase chain reaction) is not yet a routine investigation in many centres, especially in low income countries and cities. Additionally, most published studies are based on laboratory-derived test of the individual institute: the lowest detection limit varies widely among different institutions, resulting in variation in false-negative rates and recommended cutoff values ( 30 ). Therefore, considering that the updated stage system should have wide popularization and application prospects, we did not include this factor in the analysis.…”

Section: Discussionmentioning

confidence: 99%

The Integration of the Pre-Treatment Neutrophil-to-Lymphocyte Ratio in the Eighth Edition of the AJCC Staging System for Nasopharynx Cancer

Liang

Zhang

et al. 2021

Front. Oncol.

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ObjectiveThe present study aimed to evaluate the role of integrating the pretreatment neutrophil-to-lymphocyte ratio (NLR) into the eighth edition of the AJCC staging system for nasopharynx cancer in an endemic region.MethodsBetween May 2007 and December 2012, a total of 713 cases with NPC were retrospectively analyzed. The separation ability in terms of overall survival (OS), local failure-free survival (LFFS), distant metastasis-free survival (DMFS), and failure-free survival (FFS) was evaluated. The discriminatory ability was assessed using Harrell’s concordance index (c-index). Recursive partitioning analysis (RPA) was conducted and incorporated with pretreatment NLR.ResultsWhen integrated with NLR, the separate and discriminatory abilities for N classifications were improved in terms of OS and DMFS, but not for T categories. By using Recursive partitioning analysis, five subgroups were generated. Compared with the overall stage, the integration of NLR could not enhance the separate and discriminatory abilities. However, patients in the RPA 4 group gained significant benefits in terms of OS (HR 0.390 (95%CI 0.212-0.716), P = 0.002) and FFS (HR 0.548 (95%CI 0.314-0.958), P = 0.032) from the additional adjuvant chemotherapy after concurrent chemoradiotherapy.ConclusionThe integration of NLR into the 8th edition of the AJCC staging system could enhance the separation and discriminatory abilities for N classifications, but not for T categories. In addition, patients in the RPA 4 group could benefit from the addition of adjuvant chemotherapy to concurrent chemoradiotherapy.

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“…The role for plasma EBV ctDNA load in the detection and screening utility of NPC has been well-characterized in the endemic literature [ 51 , 52 ]. It continues to be a role vigorously investigated ( Table 2 ).…”

Section: Ctdna Utility In Ebv-associated Nasopharyngeal Carcinomamentioning

confidence: 99%

The Promise of Circulating Tumor DNA in Head and Neck Cancer

Aulakh

Silverman

Young

et al. 2022

Cancers

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As the seventh most common cancer globally, head and neck cancers (HNC) exert considerable disease burden, with an estimated 277,597 deaths worldwide in 2020 alone. Traditional risk factors for HNC include tobacco, alcohol, and betel nut; more recently, human papillomavirus has emerged as a distinct driver of disease. Currently, limitations of cancer screening and surveillance methods often lead to identifying HNC in more advanced stages, with associated poor outcomes. Liquid biopsies, in particular circulating tumor DNA (ctDNA), offer the potential for enhancing screening, early diagnosis, and surveillance in HNC patients, with potential improvements in HNC patient outcomes. In this review, we examine current methodologies for detecting ctDNA and highlight current research illustrating viral and non-viral ctDNA biomarker utilities in HNC screening, diagnosis, treatment response, and prognosis. We also summarize current challenges and future directions for ctDNA testing in HNC patients.

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A systematic review and recommendations on the use of plasma EBV DNA for nasopharyngeal carcinoma

Cited by 55 publications

References 102 publications

Deep Learning for nasopharyngeal Carcinoma Identification Using Both White Light and Narrow‐Band Imaging Endoscopy

Deep Learning for nasopharyngeal Carcinoma Identification Using Both White Light and Narrow‐Band Imaging Endoscopy

The Integration of the Pre-Treatment Neutrophil-to-Lymphocyte Ratio in the Eighth Edition of the AJCC Staging System for Nasopharynx Cancer

The Promise of Circulating Tumor DNA in Head and Neck Cancer

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