Muscle-Specific MRI Grading of Soft Tissue Involvement Provides Additional Prognostic Value Beyond Skull Base Criteria in Nasopharyngeal Carcinoma: A Retrospective Study

Muscle-Specific MRI Grading of Soft Tissue Involvement Provides Additional Prognostic Value Beyond Skull Base Criteria in Nasopharyngeal Carcinoma: A Retrospective Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Muscle-Specific MRI Grading of Soft Tissue Involvement Provides Additional Prognostic Value Beyond Skull Base Criteria in Nasopharyngeal Carcinoma: A Retrospective Study Ping Yang, Sha Liu, Xinghua Chen, Huang Xin, Ying Kong, Ding Liang, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7251035/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Nov, 2025 Read the published version in BMC Cancer → Version 1 posted 11 You are reading this latest preprint version Abstract Background In the 9th edition of the AJCC/UICC staging system for nasopharyngeal carcinoma (NPC), soft tissue extension to, but not beyond, the lateral pterygoid (LP) muscle is classified as stage T2 disease. Invasion beyond the LP into the masticator space or infratemporal fossa is designated as T4, while any skull base bone erosion is assigned to T3. However, this framework may oversimplify the prognostic spectrum of soft tissue involvement (STI). This study was formulated to investigate whether a muscle-specific magnetic resonance imaging (MRI) grading of offers incremental prognostic value over current skull base-based staging criteria. Methods Patients with newly diagnosed NPC treated with definitive intensity-modulated radiotherapy (IMRT) between 2014 and 2019 were retrospectively analyzed. Pretreatment MRIs were used to categorize STI severity as mild (tensor or levator veli palatini), moderate (prevertebral muscles), or severe (medial/lateral pterygoid or infratemporal fossa). Skull base invasion was classified as either limited (LSBI) or extensive (ESBI). Survival endpoints included local failure-free survival (LFFS), distant metastasis-free survival (DMFS), progression-free survival (PFS), and overall survival (OS). Kaplan–Meier analysis and log-rank tests assessed survival, and Cox proportional hazards models identified independent prognostic factors. Results Of 391 patients (median follow-up 88 months; interquartile range, 68–105), 42.9% exhibited mild, 19.4% moderate, and 37.6% severe STI. Five-year survival rates were 84.1% (LFFS), 90.0% (DMFS), 81.3% (PFS), and 80.3% (OS). Survival declined in a stepwise fashion with increasing STI severity (log-rank P ≤ 0.0001 for all endpoints); the 5-year OS was 92.9% for mild, 73.7% for moderate, and 68.0% for severe invasion. On multivariable analysis, moderate and severe STI were associated with a 3- to 4-fold increased risk of adverse outcomes, including disease progression and mortality (severe vs. mild OS: HR 4.55, 95% CI 2.47–8.37, P < 0.001). Induction chemotherapy was independently protective, reducing the hazard of death by approximately 45% (OS: HR 0.56, 95% CI 0.32–0.97, P = 0.04). In contrast, skull base invasion status was not prognostically significant in either univariate or multivariate models. When directly compared, OS for moderate STI and LSBI was similar (81% vs. 78%, P = 0.98), while severe STI showed a non-significant trend toward poorer OS compared with LSBI (68.0% vs. 76.1%, P = 0.24). Conclusions Muscle-specific MRI grading of STI serves as a more robust predictor of treatment outcomes than conventional skull base bone invasion in NPC patients receiving IMRT. This grading system may facilitate refined risk stratification and inform decisions on treatment escalation or de-intensification. Nasopharyngeal carcinoma MRI soft tissue involvement muscle-specific grading skull base invasion prognosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Nasopharyngeal carcinoma (NPC) is a malignancy with a distinct geographic distribution, particularly prevalent in southern China, Southeast Asia, and North Africa, where it remains a leading cancer type and public health concern. In 2020 alone, NPC accounted for approximately 133,000 new cases and over 80,000 deaths worldwide [ 1 , 2 ]. Despite improvements in locoregional control through intensity-modulated radiotherapy (IMRT) and advancements in systemic therapy, recurrence, either locally or at distant sites, continues to affect a significant subset of patients [ 3 , 4 ]. NPC exhibits unique etiological and epidemiological features. Its pathogenesis is multifactorial, involving Epstein-Barr virus (EBV) infection, genetic predisposition, and environmental exposures. These factors contribute to the disease’s high incidence in endemic regions and underscore the need for precise prognostic tools to guide treatment. The American Joint Committee on Cancer/Union for International Cancer Control (AJCC/UICC) tumor-node-metastasis (TNM) staging system is the global standard for clinical decision-making in NPC. In its 9th edition, soft tissue involvement (STI) is categorized broadly: mild invasion includes tumor extension limited to the parapharyngeal space or adjacent muscular structures such as the medial or lateral pterygoid (MP, LP), prevertebral, or parapharyngeal muscles, while extension beyond the outer border of the LP into the masticator space or infratemporal fossa is classified as extensive and staged as T4. Any skull base bone involvement is designated T3, regardless of its anatomical extent or aggressiveness [ 5 ]. Emerging MRI-based evidence challenges this simplified classification. Studies have shown that midline skull base erosion (e.g., of the clivus or pterygoid process) is associated with a better prognosis than lateral invasion involving neural foramina [ 6 , 7 ]. Similarly, limited muscular involvement such as that affecting the tensor or levator veli palatini (TVP or LVP) muscles may be indicative of more favorable outcomes compared to tumor extension into the prevertebral region or deep muscle compartments like the LP or MP [ 8 – 11 ]. However, many prior studies have dichotomized soft tissue spread, treating it as a simple binary variable rather than employing a detailed, muscle-specific grading system. Magnetic resonance imaging (MRI) has become the cornerstone for local staging in NPC due to its superior soft tissue resolution and sensitivity in detecting perineural spread, muscular infiltration, and skull base invasion. MRI facilitates accurate mapping of tumor spread in anatomically complex regions, such as the parapharyngeal and masticator spaces. The complex muscular architecture surrounding the nasopharynx, including the TVP, LVP, prevertebral muscles, and the MP and LP muscles, offers a series of distinct potential pathways for tumor dissemination. Identifying specific patterns of muscle involvement is essential for optimizing treatment strategies and improving prognostication. Accordingly, the present study was developed with the following aims: (1) to assess whether a muscle-specific grading of STI confers independent prognostic value in NPC; (2) to evaluate the prognostic utility of this grading system compared to conventional skull base criteria; and (3) to identify clinical and pathological predictors associated with deeper muscular invasion, with the goal of enabling individualized, risk-adapted therapy. Materials and Methods Participants This retrospective study analyzed 391 consecutive patients newly diagnosed with NPC at the Department of Radiotherapy of the First Affiliated Hospital of Guangxi Medical University, between January 2014 and December 2019. Inclusion criteria were: (1) histologically confirmed, treatment-naïve NPC; (2) availability of comprehensive clinical and laboratory data at diagnosis; (3) high-resolution pre-treatment MRI of the nasopharynx and cervical region; (4) no prior history of antineoplastic therapy; and (5) completion of radical IMRT. Patients were excluded if they: (1) were lost to follow-up during treatment or subsequent monitoring; (2) were diagnosed with synchronous malignancies; (3) developed second primary cancers post-treatment; (4) were pregnant or lactating; or (5) were medically unfit to complete treatment. These criteria were chosen to minimize bias and ensure consistency in outcome assessment. All patients underwent a standardized pretreatment evaluation protocol, including medical history, physical examination, hematologic and biochemical profiling, nasopharyngoscopy, contrast-enhanced MRI of the head and neck, chest radiography, abdominal ultrasound, and skeletal assessment via whole-body bone scintigraphy or 18F-FDG PET/CT, depending on clinical indications. Plasma EBV-DNA levels were quantified via real-time PCR, in accordance with previously validated protocols [ 7 , 12 – 14 ]. This study was conducted in compliance with the Declaration of Helsinki and approved by the Ethics Committee of the First Affiliated Hospital of Guangxi Medical University. Given its retrospective nature, the requirement for informed consent was waived. Patient confidentiality and data anonymity were maintained throughout. To reduce selection bias, all eligible patients within the study period who met inclusion criteria were enrolled without exception. Imaging assessments All patients underwent pre-treatment MRI using a 1.5-T GE Signa scanner. The imaging protocol incorporated both conventional and contrast-enhanced spin-echo sequences, including T2-weighted imaging (T2WI; TR = 3000–4000 ms, TE = 102–110 ms), T1-weighted imaging (T1WI; TR = 2200–2400 ms, TE = 77–109 ms, T1 = 750 ms), and contrast-enhanced T1WI following intravenous administration of 15 mL of gadolinium-diethylenetriaminepentaacetic acid (Gd-DTPA). Scans were performed in axial, sagittal, and coronal planes using a head coil, with a slice thickness of 6 mm and an interslice gap of 1 mm (matrix: 256 × 192), covering the area from the suprasellar cistern to the inferior clavicular margin. This protocol was optimized to detect soft tissue extension and skull base involvement, with particular focus on delineating the boundaries of the parapharyngeal and masticator spaces. Two board-certified radiologists independently reviewed all MRI scans while blinded to patient outcomes. Based on the deepest anatomical site of muscle infiltration, STI was categorized into three muscle-specific grades: mild (TVP or LVP muscles), moderate (prevertebral muscles), and severe (MP or LP muscles and/or infratemporal fossa involvement) (Fig. 1 ).In parallel, skull base invasion was stratified as limited or extensive, following previously established imaging criteria [ 7 , 12 ]. Disagreements between readers were resolved by consensus through joint image review. This grading system was guided by both anatomical insights and prior literature suggesting that the depth of muscle invasion correlates with clinical outcomes. Treatment protocol All patients received definitive IMRT according to a uniform protocol consistent with guidelines from the International Commission on Radiation Units and Measurements (ICRU) Reports 50 and 62 [ 13 , 14 ]. Radiotherapy target volumes included: the primary nasopharyngeal tumor (GTV nx), gross nodal disease (GTV nd), the surrounding high-risk subclinical zone (CTV1), and the elective cervical lymphatic drainage regions (CTV2). Prescribed radiation doses were as follows: GTV nx: 68–76 Gy in 30–33 fractions; GTV nd: 66–70 Gy in 30–33 fractions; CTV1: 60–64 Gy in 30–33 fractions; CTV2: 50–54 Gy in 30–33 fractions. Daily fraction sizes ranged from 2.00 to 2.33 Gy. Full technical details are available in earlier reports [ 15 – 18 ]. Tumors were restaged according to the 9th edition AJCC system [ 5 ]. Most patients received induction chemotherapy (IC) followed by concurrent chemoradiotherapy (CCRT), with or without adjuvant chemotherapy (AC). IC regimens were administered every 21 days and included one of the following: TP: docetaxel 75 mg/m² + cisplatin 75 mg/m², both on day 1; PF: cisplatin 80 mg/m² (day 1) + 5-fluorouracil 800–1000 mg/m² (days 1–5, continuous infusion); TPF: docetaxel 60 mg/m² + cisplatin 60 mg/m² (day 1), with 5-fluorouracil 600 mg/m² (days 1–5, continuous infusion). While undergoing radiotherapy, concurrent cisplatin was given either weekly or triweekly. In patients unable to tolerate or deemed ineligible for cisplatin, alternative platinum agents were used. AC regimens were identical to those used during IC. Clinical Endpoints and followup Primary clinical endpoints included: local failure-free survival (LFFS), measured time from diagnosis to first occurrence of local recurrence/persistence or censoring at last follow-up/death; distant metastasis-free survival (DMFS), measured as the time to first detection of distant metastasis or censoring; progression-free survival (PFS), measured as the time to any progression (local, regional, or distant), death, or censoring; and overall survival (OS), measured as the time to death from any cause or censoring. Patients were monitored post-treatment every three months for the first two years, then every six months up to five years, or until death. Each follow-up included MRI of the nasopharynx and neck, and CT imaging of the chest and abdomen. Where recurrence or metastasis was suspected, diagnostic confirmation was obtained via fine needle aspiration or histopathologic biopsy when necessary. Patients lost to follow-up or alive without recurrence at study end were censored at their most recent assessment. Statistical Analysis Continuous variables were expressed as medians with interquartile ranges (IQR) and compared across muscle invasion categories using one-way ANOVA or the Kruskal–Wallis test, depending on distribution. Categorical data were summarized as frequencies (percentages) and compared using χ² or Fisher’s exact tests. Kaplan–Meier survival curves were constructed for LFFS, DMFS, PFS, and OS, with differences assessed via log-rank testing. Univariable analyses identified candidate prognostic variables, which were subsequently entered into multivariable Cox proportional hazards models to compute adjusted hazard ratios (HRs) and 95% confidence intervals (CIs). Statistical analyses were conducted using SPSS 26.0 (IBM Corp) and R v2025.05.1 + 513(R Foundation for Statistical Computing). A two-sided P < 0.05 was deemed significant. Results Patient characteristics Baseline characteristics are detailed in Table 1 . The cohort included 391 patients, classified by MRI muscle invasion grading into mild (n = 168, 42.9%), moderate (n = 76, 19.4%), and severe (n = 147, 37.6%) groups. The median age was 46 years (IQR: 37–53), and sex distribution was predominantly male (74.4%), with no significant differences in age or sex across the three groups (all P > 0.05). Alcohol consumption varied significantly, with the highest prevalence in the moderate group (47.4%) and the lowest in the mild group (30.4%; P = 0.037). Smoking status did not differ statistically (P = 0.067). Disease severity increased with muscle invasion depth: T4 classification was observed in 54.6% of severe cases, 28.4% of moderate cases, and 11.0% of mild cases (P < 0.001). Similarly, stage IV disease was more prevalent in the severe (61.0%) compared to the moderate (41.8%) and mild (34.4%) groups (P < 0.001). N-category distributions were not significantly different (P = 0.20). EBV-DNA positivity showed a heterogeneous distribution, with 58.5% in mild, 31.0% in moderate, and 71.7% in severe groups (P = 0.007), though interpretation is limited by substantial missing data (64.2%). Extensive skull base invasion (ESBI) was most common in the severe group (62.2%), followed by moderate (48.7%) and mild (40.8%) (P = 0.003). Treatment regimens were well balanced across groups: 85.9% received IC, 92.8% underwent CCRT, and 34.5% received AC, with no significant intergroup differences (all P > 0.10). Table 1 Patient Characteristics Characteristics Overall N = 391 1 Mild N = 168 1 Moderate N = 76 1 Severe N = 147 1 P-value 2 Sex 0.2 Male 291 (74.4%) 119 (70.8%) 62 (81.6%) 110 (74.8%) Female 100 (25.6%) 49 (29.2%) 14 (18.4%) 37 (25.2%) Age 45.14 ± 10.63 44.70 ± 10.79 44.42 ± 10.60 46.02 ± 10.49 0.3 Drinking 0.037 No 250 (63.9%) 117 (69.6%) 40 (52.6%) 93 (63.3%) Yes 141 (36.1%) 51 (30.4%) 36 (47.4%) 54 (36.7%) Smoking 0.067 No 231 (59.1%) 110 (65.5%) 39 (51.3%) 82 (55.8%) Yes 160 (40.9%) 58 (34.5%) 37 (48.7%) 65 (44.2%) Pathology (WHO) 0.5 I-II 31 (7.9%) 16 (9.5%) 4 (5.3%) 11 (7.5%) III 360 (92.1%) 152 (90.5%) 72 (94.7%) 136 (92.5%) EBV-DNA 0.007 Negative 60 (15.3%) 27 (16.1%) 20 (26.3%) 13 (8.8%) Positive 80 (20.5%) 38 (22.6%) 9 (11.8%) 33 (22.4%) Data missing 251 (64.2%) 103 (61.3%) 47 (61.8%) 101 (68.7%) T classification < 0.001 T1 58 (15.6%) 52 (31.9%) 3 (4.5%) 3 (2.1%) T2 70 (18.9%) 38 (23.3%) 14 (20.9%) 18 (12.8%) T3 129 (34.8%) 55 (33.7%) 31 (46.3%) 43 (30.5%) T4 114 (30.7%) 18 (11.0%) 19 (28.4%) 77 (54.6%) N classification 0.2 N0 18 (4.9%) 7 (4.3%) 3 (4.5%) 8 (5.7%) N1 69 (18.6%) 33 (20.2%) 12 (17.9%) 24 (17.0%) N2 221 (59.6%) 86 (52.8%) 44 (65.7%) 91 (64.5%) N3 63 (17.0%) 37 (22.7%) 8 (11.9%) 18 (12.8%) Overall Stage (9th) < 0.001 1–2 34 (9.2%) 22 (13.5%) 6 (9.0%) 6 (4.3%) 3 167 (45.0%) 85 (52.1%) 33 (49.3%) 49 (34.8%) 4 170 (45.8%) 56 (34.4%) 28 (41.8%) 86 (61.0%) Skull-base invasion 0.003 ESBI 122 (51.0%) 29 (40.8%) 19 (38.8%) 74 (62.2%) LSBI 117 (49.0%) 42 (59.2%) 30 (61.2%) 45 (37.8%) Induction chemotherapy 0.10 No 55 (14.1%) 18 (10.7%) 16 (21.1%) 21 (14.3%) Yes 336 (85.9%) 150 (89.3%) 60 (78.9%) 126 (85.7%) Concurrent chemotherapy 0.7 No 28 (7.2%) 14 (8.3%) 4 (5.3%) 10 (6.8%) Yes 363 (92.8%) 154 (91.7%) 72 (94.7%) 137 (93.2%) Adjuvant chemotherapy 0.3 No 256 (65.5%) 106 (63.1%) 47 (61.8%) 103 (70.1%) Yes 135 (34.5%) 62 (36.9%) 29 (38.2%) 44 (29.9%) Notes: Bold indicates a significant difference among groups with p < 0.05 1 n (%); Mean ± SD 2 Pearson's Chi-squared test; Kruskal-Wallisr ank sum test Abbreviations: EBV, Epstein-Barr virus; ESBI, extensive skull-base invasion; LSBI, limited skull-base invasion Survival outcomes by depth of invasion At a median follow-up of 88 months (IQR: 68–105), 73 of the 391 patients (18.7%) experienced treatment failure (11.9% vs 26.3% vs 22.4%, P = 0.009). The details of treatment failure are listed in Table 2 . Rates of locoregional failure varied significantly by muscle invasion grade: 11.3% (19/168) in the mild group, 23.7% (18/76) in the moderate group, and 17.0% (25/147) in the severe group (P = 0.044). Similarly, the incidence of distant metastasis rose with increasing invasion severity: 4.8% in mild, 15.8% in moderate, and 12.9% in severe categories (P = 0.009). When stratified by skull-base invasion, there was no significant difference in overall treatment failure between limited and extensive involvement (16.2% vs. 18.9%, respectively; P = 0.718). The estimated 5-year survival outcomes for the full cohort were as follows: LFFS 84.1%, DMFS 90.0%, PFS 81.3%, and OS 80.3%. When stratifying by muscle-invasion depth, 5-year rates were for LFFS were 88.7% (mild), 76.3% (moderate), and 83.0% (severe) for mild, moderate, and severe cases, respectively (P = 0.0001), with corresponding DMFS rates of 95.2%, 84.2%, and 87.1% (P < 0.0001), PFS rates of 88.1%, 73.7%, and 77.6% (P < 0.0001), and OS rates of 92.9%, 73.7%, and 68.0% (P < 0.0001) (Fig. 2 ). In contrast, patients grouped by skull-base invasion (limited vs. extensive) exhibited no significant differences in survival outcomes for LFFS (88.0% vs. 83.6%; P = 0.23), DMFS (91.5% vs. 89.3%; P = 0.25), PFS (83.8% vs. 81.1%; P = 0.26), or OS (76.1% vs. 82.8%; P = 0.24) (Fig. 3 ). Table 2 Patterns of Treatment Failure for Patients with soft tissue involvement after IMRT Treatment Failure Pattern Mild N = 168 1 Moderate N = 76 1 Severe N = 147 1 P 2 Distant only 1 (0.6%) 2 (2.6%) 8 (5.4%) 0.024 Bone 1 (100.0%) 2 (100.0%) 1 (12.5%) Bone and liver 0 (0.0%) 0 (0.0%) 1 (12.5%) Bone, lung and liver 0 (0.0%) 0 (0.0%) 1 (12.5%) Liver 0 (0.0%) 0 (0.0%) 1 (12.5%) Lung 0 (0.0%) 0 (0.0%) 2 (25.0%) Other 0 (0.0%) 0 (0.0%) 2 (25.0%) Local and distant 6 (3.6%) 9 (11.8%) 11 (7.5%) 0.049 Regional and distant 1 (0.6%) 1 (1.3%) 0 (0.0%) 0.5 Local and regional 1 (0.6%) 1 (1.3%) 2 (1.4%) 0.7 Local only 5 (3.0%) 5 (6.6%) 10 (6.8%) 0.2 Regional only 6 (3.6%) 2 (2.6%) 2 (1.4%) 0.5 Total 20 (11.9%) 20 (26.3%) 33 (22.4%) 0.009 Notes: Bold indicates a significant difference among groups with p < 0.05 1 n (%) 2 Fisher's exact test; Pearson's Chi-squared test Abbreviations: IMRT, intensity-modulated radiotherapy Univariate and multivariate analyses The prognostic relevance of multiple clinical and treatment-related factors, including age, sex, muscle invasion grade, skull-base involvement, TN staging, EBV-DNA status, and receipt of IC, concurrent chemotherapy, and AC, was next assessed for all four survival endpoints. In univariate analysis, both muscle-specific tumor invasion (STI) and receipt of induction chemotherapy were significantly associated with all endpoints. Age showed a marginal association with overall survival (OS; HR 1.02 per year; P = 0.056). Other variables such as sex, alcohol or tobacco use, histological subtype, EBV-DNA status, T and N stage, overall clinical stage, skull-base involvement, and concurrent or adjuvant chemotherapy did not attain significance (all P > 0.20) (Table 3). Multivariate Cox regression confirmed that both STI grade and use of induction chemotherapy retained independent prognostic value. Compared with mild muscle invasion, moderate involvement significantly increased the risk of locoregional failure by more than three-fold, as reflected by LFFS (HR 3.30), DMFS (HR 3.43), PFS (HR 3.39), and OS (HR 3.39) outcomes (all P ≈ 0.001). Severe muscle invasion conferred even higher risks across all endpoints, with hazard ratios between 4.4 and 4.6 (all P < 0.001). Conversely, IC treatment independently reduced the likelihood of treatment failure by approximately 45%, as reflected by OS (HR 0.56), PFS (HR 0.56), DMFS (HR 0.57), and LFFS (HR 0.55) outcomes (all P ≈ 0.04). While increasing age trended toward worse OS (HR 1.02/year; P = 0.074), other covariates, including skull-base status and nodal involvement, were excluded from final models due to lack of significance (Table 4). Table 3 Univariate Analysis of Variables Correlated with Various Clinical Endpoints LFFS DMFS PFS OS Variables HR (95% CI) P value HR (95% CI) P value HR (95% CI) P value HR (95% CI) P value Sex 0.699 (0.39–1.255) 0.231 0.703 (0.392–1.261) 0.237 0.705 (0.393–1.264) 0.240 0.696 (0.388–1.25) 0.225 Age 1.021 (0.999–1.044) 0.067 1.021 (0.999–1.045) 0.064 1.021 (0.999–1.044) 0.067 1.022 (0.999–1.045) 0.056 Drinking 1.089 (0.674–1.759) 0.727 1.048 (0.649–1.692) 0.849 1.06 (0.657–1.712) 0.811 1.072 (0.664–1.732) 0.775 Smoking 1.384 (0.869–2.204) 0.172 1.328 (0.834–2.115) 0.233 1.35 (0.848–2.151) 0.206 1.354 (0.85–2.157) 0.202 Pathology (WHO) 1.549 (0.565–4.247) 0.395 1.499 (0.547–4.112) 0.431 1.528 (0.557–4.189) 0.410 1.5 (0.547–4.113) 0.431 EBV-DNA 1.187 (0.543–2.591) 0.668 1.203 (0.551–2.627) 0.643 1.161 (0.531–2.535) 0.709 1.221 (0.559–2.667) 0.616 T classification 1.267 (0.518–3.099) 0.605 1.261 (0.515–3.085) 0.611 1.291 (0.528–3.158) 0.576 1.21 (0.494–2.96) 0.677 N classification 0.536 (0.161–1.781) 0.309 0.538 (0.162–1.786) 0.311 0.524 (0.158–1.741) 0.291 0.552 (0.166–1.832) 0.332 Overall Stage (9th) 1.107 (0.427–2.866) 0.835 1.133 (0.438–2.935) 0.797 1.12 (0.433–2.901) 0.815 1.109 (0.428–2.871) 0.832 Soft tissue invasion 3.553 (1.697–7.44) 0.001** 3.636 (1.736–7.615) 0.001** 3.618 (1.727–7.576) 0.001** 3.603 (1.72–7.545) 0.001** Skull-base invasion 1.399 (0.781–2.506) 0.259 1.402 (0.783–2.512) 0.256 1.378 (0.769–2.469) 0.281 1.421 (0.793–2.546) 0.237 Induction chemotherapy 0.525 (0.3-0.919) 0.024* 0.507 (0.289–0.889) 0.018* 0.517 (0.296–0.904) 0.021* 0.515 (0.294–0.904) 0.021* Concurrent chemotherapy 1.013 (0.408–2.515) 0.978 1.004 (0.404–2.492) 0.993 1.017 (0.41–2.525) 0.971 0.976 (0.393–2.423) 0.958 Adjuvant chemotherapy 1.326 (0.826–2.129) 0.243 1.339 (0.834–2.149) 0.228 1.318 (0.821–2.115) 0.254 1.327 (0.826–2.13) 0.242 Notes: Bold indicates statistically significant with p < 0.05 Abbreviations: HR, hazard ratio; CI, confidence interval; LFFS, locoregional recurrence-free survival; DMFS, distant metastasis-free survival; PFS, progression-free survival; OS, overall survival. *P < 0.05; **P < 0.01 Table 4 Multivariate Analysis of Variables Correlated with Various Clinical Endpoints LFFS DMFS PFS OS Variables HR (95% CI) P value HR (95% CI) P value HR (95% CI) P value HR (95% CI) P value Soft tissue involvement (moderate vs mild) 3.305 (1.571–6.953) 0.002 3.429 (1.632–7.204) 0.001 3.385 (1.609–7.119) 0.001 3.387 (1.612–7.119) 0.001 Soft tissue involvement (severe vs mild) 4.491 (2.359–8.55) < 0.001 4.409 (2.315-8.4) < 0.001 4.367 (2.293–8.317) < 0.001 4.605 (2.418–8.769) < 0.001 Induction chemotherapy (yes vs no) 0.551 (0.313–0.971) 0.039 0.567 (0.322–0.996) 0.048 0.56 (0.319–0.985) 0.044 0.562 (0.319–0.989) 0.046 Age (per year increase) 1.02 (0.997–1.044) 0.082 1.02 (0.997–1.043) 0.091 1.02 (0.997–1.043) 0.087 1.021 (0.998–1.045) 0.074 Notes: Bold indicates statistically significant with p < 0.05 Abbreviations: HR, hazard ratio; CI, confidence interval; LFFS, locoregional recurrence-free survival; DMFS, distant metastasis-free survival; PFS, progression-free survival; OS, overall survival. Comparative analysis of anatomical classifications To assess the relative prognostic value of bone versus muscle invasion, survival outcomes were compared between patients with LSBI and those with severe muscle infiltration. The LSBI group achieved 5-year PFS and OS rates of 83.8% and 76.1%, respectively, which were not significantly different from the severe muscle-invasion cohort (77.6% and 68.0%; P = 0.14 and 0.24). Moreover, LSBI outcomes closely resembled those of the moderate muscle-invasion group (PFS 84% vs. 86%, P = 0.70; OS 78% vs. 81%, P = 0.98; Fig. 4). Discussion This study highlights the prognostic utility of a muscle-specific MRI-based grading system for stratifying NPC, revealing survival differences not captured by conventional classifications of skull-base invasion. In this cohort, 5-year LFFS, DMFS, PFS, and OS showed a clear stepwise decline with increasing depth of muscular invasion. Severe muscle involvement emerged as an independent predictor of poorer outcomes, associated with nearly a threefold higher risk of mortality (HR ≈ 2.9, 95% CI 1.7–4.8), even after adjusting for TNM stage, EBV-DNA levels, and treatment factors. Conversely, the extent of skull-base invasion did not significantly influence any evaluated survival outcome. MRI is currently the preferred modality for initial staging, treatment planning, and post-therapy surveillance in NPC due to its superior soft-tissue resolution and enhanced sensitivity for detecting skull-base and cranial nerve involvement [19,20]. Its ability to detect subtle signal alterations associated with early STI makes it particularly effective in identifying early tumor spread [21,22]. Among the anatomical structures adjacent to the nasopharynx, STI is the most commonly affected site during NPC progression, benefiting from MRI’s high-resolution imaging capabilities [23,24]. Consistent with previous findings, the survival analyses in the present study revealed a distinct prognostic gradient based on the extent of muscle invasion. Patients with mild muscular involvement exhibited markedly better 5-year rates for LFFS, DMFS, PFS, and OS compared to those with moderate or severe invasion. The moderate invasion group demonstrated intermediate outcomes, indicating that increasing depth of muscle infiltration is inversely correlated with prognosis in T2 NPC [25]. One explanation is that mild invasion is typically associated with smaller tumors that encroach only minimally on peri-nasopharyngeal tissue, leading to lower tumor burden and improved local control. In contrast, extensive muscle involvement often coincides with larger primary lesions capable of penetrating deep fascial planes and exploiting perineural routes through skull-base foramina, thereby increasing the risk of early systemic dissemination and distant metastasis. Unlike the classification used by Zhang et al., which broadly categorized invasion into parapharyngeal or masticator space and linked poor prognosis with lateral extension, most prior studies have not specifically assessed individual muscle involvement [26]. The present findings build upon this foundation by demonstrating a sequential decline in survival outcomes corresponding to invasion of the palatal, prevertebral, and pterygoid muscles, reinforcing the notion that deeper or more lateral STI is associated with adverse prognosis [27,28]. Several MRI-based studies, including those by Li et al. and Cheng et al., have highlighted the prognostic significance of skull-base bone invasion, reporting worse outcomes in cases of extensive involvement [12,29]. However, in the present study cohort, no significant differences in 5-year LFFS, DMFS, PFS, or OS were observed between patients with LSBI versus ESBI (all p > 0.20). Furthermore, skull-base status did not emerge as a prognostic factor in either univariate or multivariable analysis. This divergence from previous reports may be attributed to several factors. First, MRI-detected skull-base invasion often represents non-measurable or semi-quantitative findings, with the classification of limited versus extensive involvement being highly subjective and dependent on radiologists’ interpretation of marrow or cortical signal alterations. Second, modern high-resolution MRI is capable of detecting subtle changes such as edema or cortical thinning, which may lead to overestimation of disease extent and reduce the clinical utility of this subclassification. Finally, the implementation of IMRT, which provides precise and uniform dose coverage across the skull base, likely mitigates the clinical impact of bone involvement, thereby equalizing outcomes regardless of invasion extent. The unfavorable prognosis linked to deep muscle invasion in NPC arises from a complex interplay of biological and anatomical factors. Tumor infiltration into the prevertebral and pterygoid musculature likely reflects a more aggressive tumor phenotype, associated with increased proliferative activity, heightened invasiveness, and greater potential for perineural and hematogenous dissemination. At the molecular level, tumors exhibiting extensive STI frequently show elevated expression of matrix metalloproteinases, markers of epithelial–mesenchymal transition, and pro-angiogenic mediators. These molecular alterations promote degradation of the extracellular matrix, compromise anatomical barriers, and facilitate early spread to lymphatic and distant sites. Moreover, the anatomical proximity of the pterygoid region and infratemporal fossa to critical neurovascular structures increases the likelihood of cranial nerve encroachment and may hinder surgical salvage options in recurrent disease. The anatomical intricacy of these areas also presents challenges to achieving complete resection, potentially explaining the elevated rates of local failure observed in patients with deep muscle involvement. Additionally, the dense vascular and lymphatic architecture of deep muscular compartments offers multiple conduits for systemic dissemination, aligning with the increased incidence of distant metastases seen in this subgroup. Integrating a muscle-specific MRI-based grading system into routine NPC staging could significantly enhance prognostic accuracy compared to the current AJCC/UICC 9th-edition framework, which collectively classifies involvement of the LVP, TVP, prevertebral muscles, MP, and LP muscles as T2 disease. This aggregated classification may obscure clinically relevant heterogeneity. Patients with severe muscle involvement, particularly those with pterygoid muscle infiltration, face nearly a threefold increased risk of recurrence and mortality, underscoring their potential eligibility for more intensive treatment strategies such as IC, dose-escalated IMRT, or clinical trials evaluating novel systemic therapies. Conversely, patients exhibiting only mild muscle invasion may be candidates for de-escalated regimens, such as reduced elective nodal radiation or omission of AC, aiming to limit treatment-related morbidity without compromising oncologic outcomes. Standardizing radiologic assessments to routinely document involvement of the LVP, TVP, prevertebral muscles, MP, LP, and infratemporal fossa would facilitate more consistent interdisciplinary communication. Such standardization could support personalized surveillance protocols such as more frequent MRI for patients at elevated risk and enable the integration of quantitative imaging biomarkers and serial plasma EBV-DNA monitoring into clinical workflows. Multi-center, prospective validation studies and health-economic evaluations are now needed to confirm that this anatomically nuanced approach can improve outcomes while maintaining cost-effectiveness. The prognostic evaluation of NPC cases will likely increasingly rely on a combination of anatomical imaging, molecular profiling, and functional imaging metrics in the future. Plasma EBV-DNA has already been established as a robust surrogate for tumor burden and therapeutic response. When combined with muscle-specific MRI stratification, radiomic signatures, and gene expression profiling, it may enable the development of highly individualized risk models. These tools could guide treatment decisions by balancing therapeutic intensity with long-term toxicity and quality-of-life considerations. Additionally, advances in liquid biopsy, including circulating tumor DNA and microRNA profiling, offer further opportunities to refine risk stratification. Integration of such molecular data with detailed anatomical grading may yield robust composite prognostic tools, supporting more precise patient selection for emerging therapies. To implement muscle-specific MRI grading in routine clinical practice, standardized imaging protocols and targeted radiologist training will be essential. Multidisciplinary tumor boards should incorporate granular muscle invasion details into decision-making, particularly when evaluating candidacy for treatment intensification or de-escalation. Patients identified with extensive muscle involvement may benefit from early referral to clinical trials or advanced radiation modalities, while those with limited involvement might be safely managed with less intensive regimens. Ensuring reproducibility across institutions will require the development of reference atlases, uniform reporting templates, and ongoing educational initiatives. Artificial intelligence and machine learning algorithms hold promise as a means of enhancing the accuracy and consistency of muscle invasion assessment, potentially broadening access to this grading system across centers with varying radiologic expertise. This study's retrospective, single-center design imposes limitations on the generalizability of its findings. The moderate invasion subgroup was relatively small, which may reduce statistical power for some comparisons. Although muscle grading was performed by two blinded radiologists, inter-observer variability remains a concern. Additionally, this analysis did not incorporate functional imaging parameters such as diffusion-weighted MRI or PET-based metrics, nor did it account for dynamic EBV-DNA kinetics, with these being factors that could have added valuable prognostic insights. Prospective, multi-institutional studies employing harmonized imaging protocols are needed to validate and refine these results. The high rate of missing EBV-DNA data (64.2%) further limits the robustness of multivariable modeling. Future investigations should prioritize the acquisition of complete molecular datasets to facilitate comprehensive risk stratification. Furthermore, the absence of data on treatment response and patient-reported outcomes prevents a full understanding of how muscle-specific grading impacts therapeutic efficacy and quality of life. Conclusion These results suggest that the depth of muscular invasion, rather than skull-base involvement, is the predominant anatomical predictor of locoregional control, metastatic spread, and survival in NPC patients treated with IMRT. Incorporating a muscle-specific MRI grading system into standard diagnostic workflows offers added prognostic value beyond conventional skull-base criteria and supports a framework for risk-adapted therapeutic strategies. Abbreviations MRI, magnetic resonance images; STI, soft tissue involvement; LVP, levator veli palatini; LP, lateral pterygoid; EBV, Epstein-Barr virus; ESBI, extensive skull-base invasion; LSBI ,limited skull-base invasion; IMRT, intensity-modulated radiotherapy; LFFS, local failure-free survival; DMFS, distant metastasis-free survival; PFS , progression-free survival ; OS, overall survival rates; STI, soft tissue involvement; HR, hazard ratio; CI, confidence interval. Declarations Acknowledgements Not applicable. Author contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by PY, SL, XC and XH. The first draft of the manuscript was written by PY and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Funding This work was supported by the National Natural Science Foundation of China (Grant Nos. 82260474 and 82303935), the Scientific Research Project of Health and Family Planning Industry in Hainan Province, China (Grant No. 22A200068), and the Hainan Province Science and Technology Special Fund (Grant Nos. ZDYF2022SHFZ132 and ZDYF2024SHFZ045). Data Availability The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare no competing interests. Ethics approval and consent to participate. This study was conducted in accordance with the Helsinki Declaration and approved by the Ethics Committee of the First Affiliated Hospital of Guangxi Medical University. And this was a retrospective study, so the informed consent was waived by the Ethics Committee of the First Affiliated Hospital of Guangxi Medical University. Participant information is confidential. Consent for publication. Not applicable. References Chen YP, Chan ATC, Le QT, Blanchard P, Sun Y, Ma J. Nasopharyngeal carcinoma. Lancet. 2019;394:64–80. https://doi.org/10.1016/S0140-6736(19)30956-0 . Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71:209–49. https://doi.org/10.3322/caac.21660 . Amin MB, Greene FL, Edge SB, Compton CC, Gershenwald JE, Brookland RK, et al. The eighth edition AJCC cancer staging manual: Continuing to build a bridge from a population-based to a more personalized approach to cancer staging. CA Cancer J Clin. 2017;67:93–9. https://doi.org/10.3322/caac.21388 . Tang LL, Chen YP, Mao YP, Wang ZX, Guo R, Chen L, et al. Validation of the 8th edition of the UICC/AJCC staging system for nasopharyngeal carcinoma from endemic areas in the intensity-modulated radiotherapy era. J Natl Compr Canc Netw. 2017;15:913–9. https://doi.org/10.6004/jnccn.2017.0101 . Pan JJ, Mai HQ, Ng WT, et al. Ninth Version of the AJCC and UICC Nasopharyngeal Cancer TNM Staging Classification. JAMA Oncol. 2024;10:1736. https://doi.org/10.1001/jamaoncol.2024.4354 . Feng Y, Cao C, Hu Q, Chen X. Grading of MRI-detected skull-base invasion in nasopharyngeal carcinoma with skull-base invasion after intensity-modulated radiotherapy. Radiat Oncol. 2019;14:10. https://doi.org/10.1186/s13014-019-1214-3 . Chen L, Liu LZ, Mao YP, Tang LL, Sun Y, Cui CY, et al. Grading of MRI-detected skull-base invasion in nasopharyngeal carcinoma and its prognostic value. Head Neck. 2011;33:1309–14. https://doi.org/10.1002/hed.21606 . Xiao G, Xu G, Gao L. Prognostic influence of parapharyngeal space involvement in nasopharyngeal carcinoma. Zhonghua Zhong Liu Za Zhi. 2001;23:244–6. Xiao Y, Pan J, Chen Y, Chen L, Tang LL, Lu TY, et al. Prognostic value of MRI-derived masticator space involvement in IMRT-treated nasopharyngeal carcinoma patients. Radiat Oncol. 2015;10:204. https://doi.org/10.1186/s13014-015-0513-6 . Xiao Y, Pan J, Chen Y, Chen L, Tang LL, Lu TY, et al. The prognosis of nasopharyngeal carcinoma involving masticatory muscles: A retrospective analysis for revising T subclassifications. Medicine. 2015;94:e420. https://doi.org/10.1097/MD.0000000000000420 . Kang M, Zhou P, Liao X, Xu M, Wang R. Prognostic value of masticatory muscle involvement in nasopharyngeal carcinoma patients treated with intensity-modulated radiation therapy. Oral Oncol. 2017;75:100–5. https://doi.org/10.1016/j.oraloncology.2017.11.002 . Cheng YK, Liu LZ, Jiang N, et al. MRI-detected skull-base invasion: prognostic value and therapeutic implication in intensity-modulated radiotherapy treatment for nasopharyngeal carcinoma. Strahlenther Onkol. 2014;190:905–11. https://doi.org/10.1007/s00066-014-0656-7 . Liang SB, Wang Y, Hu XF, et al. Survival and Toxicities of IMRT Based on the RTOG Protocols in Patients with Nasopharyngeal Carcinoma from the Endemic Regions of China. J Cancer. 2017;8:3718–24. https://doi.org/10.7150/jca.20351 . Lin S, Pan J, Han L, Zhang X, Liao X, Lu JJ. Nasopharyngeal carcinoma treated with reduced-volume intensity-modulated radiation therapy: report on the 3-year outcome of a prospective series. Int J Radiat Oncol Biol Phys. 2009;75:1071–8. https://doi.org/10.1016/j.ijrobp.2008.12.015 . Xue F, Hu C, He X. Long-term Patterns of Regional Failure for Nasopharyngeal Carcinoma following Intensity-Modulated Radiation Therapy. J Cancer. 2017;8:993–9. https://doi.org/10.7150/jca.17858 . Sun X, Su S, Chen C, Han F, Zhao C, Xiao W, et al. Long-term outcomes of intensity-modulated radiotherapy for 868 patients with nasopharyngeal carcinoma: an analysis of survival and treatment toxicities. Radiother Oncol. 2014;110:398–403. https://doi.org/10.1016/j.radonc.2013.10.020 . Au KH, Ngan RKC, Ng AWY, et al. Treatment outcomes of nasopharyngeal carcinoma in modern era after intensity modulated radiotherapy (IMRT) in Hong Kong: A report of 3328 patients (HKNPCSG 1301 study). Oral Oncol. 2018;77:16–21. https://doi.org/10.1016/j.oraloncology.2017.12.004 . Tian YM, Liu MZ, Zeng L, et al. Long-term outcome and pattern of failure for patients with nasopharyngeal carcinoma treated with intensity-modulated radiotherapy. Head Neck. 2019;41:1246–52. https://doi.org/10.1002/hed.25545 . Colevas AD, Yom SS, Pfister DG, Spencer S, Adelstein D, Adkins D, et al. NCCN Guidelines insights: head and neck cancers, Version 1.2018. J Natl Compr Canc Netw. 2018;16:479–90. https://doi.org/10.6004/jnccn.2018.0026 . Gorolay VV, Niles NN, Huo YR, et al. MRI detection of suspected nasopharyngeal carcinoma: a systematic review and meta-analysis. Neuroradiology. 2022;64:1471–81. https://doi.org/10.1007/s00234-022-02941-w . Sun XS, Liu SL, Luo MJ, Li XY, Chen QY, Guo SS, et al. The Association Between the Development of Radiation Therapy, Image Technology, and Chemotherapy, and the Survival of Patients With Nasopharyngeal Carcinoma: A Cohort Study From 1990 to 2012. Int J Radiat Oncol Biol Phys. 2019;105:581–90. https://doi.org/10.1016/j.ijrobp.2019.06.2549 . Liao XB, Mao YP, Liu LZ, Tang LL, Sun Y, Wang Y, et al. How does magnetic resonance imaging influence staging according to AJCC staging system for nasopharyngeal carcinoma compared with computed tomography? Int J Radiat Oncol Biol Phys. 2008;72:1368–77. https://doi.org/10.1016/j.ijrobp.2008.03.017 . Tang LL, Chen YP, Chen CB, et al. The Chinese Society of Clinical Oncology (CSCO) clinical guidelines for the diagnosis and treatment of nasopharyngeal carcinoma. Cancer Commun. 2021;41:1195–227. https://doi.org/10.1002/cac2.12218 . King AD, Lam WW, Leung SF, et al. MRI of local disease in nasopharyngeal carcinoma: tumour extent vs tumour stage. Br J Radiol. 1999;72:734–41. https://doi.org/10.1259/bjr.72.860.10624338 . Dong A, Huang W, Ma H, et al. Grading Soft Tissue Involvement in Nasopharyngeal Carcinoma Using Network and Survival Analyses: A Two-Center Retrospective Study. J Magn Reson Imaging. 2021;53:1752–63. https://doi.org/10.1002/jmri.27515 . Zhang GY, Huang Y, Cai XY, et al. Prognostic value of grading masticator space involvement in nasopharyngeal carcinoma according to MR imaging findings. Radiology. 2014;273:136–43. https://doi.org/10.1148/radiol.14132745 . Nasr Ben Ammar C, Kochbati L, Lejri N, et al. Valeur pronostique de l'extension parapharyngéee dans les carcinomes nasopharyngés [Prognostic value of parapharyngeal extension in nasopharyngeal carcinoma]. Tunis Med. 2009;87:814–7. Sze H, Chan LL, Ng WT, et al. Should all nasopharyngeal carcinoma with masticator space involvement be staged as T4? Oral Oncol. 2014;50:1188–95. https://doi.org/10.1016/j.oraloncology.2014.09.001 . Li S, Luo C, Huang W, et al. Value of skull base invasion subclassification in nasopharyngeal carcinoma: implication for prognostic stratification and use of induction chemotherapy. Eur Radiol. 2022;32:7767–77. https://doi.org/10.1007/s00330-022-08864-7 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 12 Nov, 2025 Read the published version in BMC Cancer → Version 1 posted Editorial decision: Revision requested 12 Sep, 2025 Reviews received at journal 07 Sep, 2025 Reviewers agreed at journal 01 Sep, 2025 Reviews received at journal 27 Aug, 2025 Reviewers agreed at journal 19 Aug, 2025 Reviewers agreed at journal 10 Aug, 2025 Reviewers invited by journal 10 Aug, 2025 Editor assigned by journal 05 Aug, 2025 Editor invited by journal 04 Aug, 2025 Submission checks completed at journal 04 Aug, 2025 First submitted to journal 03 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7251035","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":501424736,"identity":"8f39d7a4-e8e7-4c33-961f-abcd267f928c","order_by":0,"name":"Ping Yang","email":"","orcid":"","institution":"The First Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ping","middleName":"","lastName":"Yang","suffix":""},{"id":501424738,"identity":"33465693-d21f-437a-8c78-3e4d450dca7b","order_by":1,"name":"Sha Liu","email":"","orcid":"","institution":"The First Affiliated Hospital, The First Clinical College of Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Sha","middleName":"","lastName":"Liu","suffix":""},{"id":501424741,"identity":"91ec4752-5680-4b0d-82d5-a3af1042d61f","order_by":2,"name":"Xinghua Chen","email":"","orcid":"","institution":"The First Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xinghua","middleName":"","lastName":"Chen","suffix":""},{"id":501424742,"identity":"b3f3c336-ba60-4af2-9a74-34a8c4cb840e","order_by":3,"name":"Huang Xin","email":"","orcid":"","institution":"The First Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Huang","middleName":"","lastName":"Xin","suffix":""},{"id":501424743,"identity":"31ab3ba8-7971-4d78-b663-417e0da70e0d","order_by":4,"name":"Ying Kong","email":"","orcid":"","institution":"The First Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Kong","suffix":""},{"id":501424744,"identity":"0b29e93c-5c67-4e02-8e09-1253b513a4b2","order_by":5,"name":"Ding Liang","email":"","orcid":"","institution":"The First Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ding","middleName":"","lastName":"Liang","suffix":""},{"id":501424745,"identity":"ab537618-2ba5-4851-9eb3-bd0c4d99a458","order_by":6,"name":"Weimin Chen","email":"","orcid":"","institution":"The First Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Weimin","middleName":"","lastName":"Chen","suffix":""},{"id":501424746,"identity":"48a8c8c0-f690-4f7c-967b-a6b3bf1dcecd","order_by":7,"name":"Tianyu Wu","email":"","orcid":"","institution":"The First Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Tianyu","middleName":"","lastName":"Wu","suffix":""},{"id":501424747,"identity":"47280081-4752-42a3-99e7-df5b44d2cc5d","order_by":8,"name":"Ping Zhou","email":"","orcid":"","institution":"The First Affiliated Hospital, The First Clinical College of Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ping","middleName":"","lastName":"Zhou","suffix":""},{"id":501424748,"identity":"4fcc89b8-6520-4f3d-bb16-e8f56e4c6c75","order_by":9,"name":"Min Kang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYBACCTBpwCAH5TMTr8WYVC0MDIkNRGuRbD97+NWNgjvp8yOy0yQYKqwTG9jPHsCrRZonL806x+BZ7sYzZ7dJMJxJT2zgyUvAq0WOIcfMOMfgcO7G9t5tEoxthxMbJHgM8GvhfwPWkm7YzAvU8o8ILdISOcaPgVoS5NlBtjQQoUVyxhszZqAWww08ZzdbJBxLN27jycGvReJ8jvHnnD+H5eVn5G688aHGWraf/Qx+LUDABo4bgwNAIgHEJaQeCJg/gEj5BiKUjoJRMApGwcgEACudQ13k6WwLAAAAAElFTkSuQmCC","orcid":"","institution":"The First Affiliated Hospital of Guangxi Medical University","correspondingAuthor":true,"prefix":"","firstName":"Min","middleName":"","lastName":"Kang","suffix":""}],"badges":[],"createdAt":"2025-07-30 09:23:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7251035/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7251035/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12885-025-15208-3","type":"published","date":"2025-11-12T15:57:35+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89276452,"identity":"adbf8927-569a-4cd8-90b3-6515a236f269","added_by":"auto","created_at":"2025-08-18 09:32:28","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":549528,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7251035/v1/8532c966d72e43a9047b4dd5.jpg"},{"id":89276453,"identity":"df2a9554-0050-4fa8-ae13-c122b63f2008","added_by":"auto","created_at":"2025-08-18 09:32:28","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":420493,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7251035/v1/199409f849bdd1fb691800ef.jpg"},{"id":89276455,"identity":"12ac530b-69fc-4f79-a8d4-5c6feb9823d8","added_by":"auto","created_at":"2025-08-18 09:32:28","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":426517,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7251035/v1/64b5b3979558b1ec66552209.jpg"},{"id":89276460,"identity":"1385ae61-24eb-4ae2-9127-1ad3b4bd1e0a","added_by":"auto","created_at":"2025-08-18 09:32:28","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":436416,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7251035/v1/d7619d69bf2f3f2e8c60dec1.jpg"},{"id":96105023,"identity":"0ca324c8-94cd-42f1-9012-668efc716397","added_by":"auto","created_at":"2025-11-17 16:07:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3154252,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7251035/v1/4ee3c566-a36c-4c95-8088-9a2ee7b1c2ca.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Muscle-Specific MRI Grading of Soft Tissue Involvement Provides Additional Prognostic Value Beyond Skull Base Criteria in Nasopharyngeal Carcinoma: A Retrospective Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNasopharyngeal carcinoma (NPC) is a malignancy with a distinct geographic distribution, particularly prevalent in southern China, Southeast Asia, and North Africa, where it remains a leading cancer type and public health concern. In 2020 alone, NPC accounted for approximately 133,000 new cases and over 80,000 deaths worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Despite improvements in locoregional control through intensity-modulated radiotherapy (IMRT) and advancements in systemic therapy, recurrence, either locally or at distant sites, continues to affect a significant subset of patients [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. NPC exhibits unique etiological and epidemiological features. Its pathogenesis is multifactorial, involving Epstein-Barr virus (EBV) infection, genetic predisposition, and environmental exposures. These factors contribute to the disease\u0026rsquo;s high incidence in endemic regions and underscore the need for precise prognostic tools to guide treatment.\u003c/p\u003e\u003cp\u003e The American Joint Committee on Cancer/Union for International Cancer Control (AJCC/UICC) tumor-node-metastasis (TNM) staging system is the global standard for clinical decision-making in NPC. In its 9th edition, soft tissue involvement (STI) is categorized broadly: mild invasion includes tumor extension limited to the parapharyngeal space or adjacent muscular structures such as the medial or lateral pterygoid (MP, LP), prevertebral, or parapharyngeal muscles, while extension beyond the outer border of the LP into the masticator space or infratemporal fossa is classified as extensive and staged as T4. Any skull base bone involvement is designated T3, regardless of its anatomical extent or aggressiveness [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Emerging MRI-based evidence challenges this simplified classification. Studies have shown that midline skull base erosion (e.g., of the clivus or pterygoid process) is associated with a better prognosis than lateral invasion involving neural foramina [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Similarly, limited muscular involvement such as that affecting the tensor or levator veli palatini (TVP or LVP) muscles may be indicative of more favorable outcomes compared to tumor extension into the prevertebral region or deep muscle compartments like the LP or MP [\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, many prior studies have dichotomized soft tissue spread, treating it as a simple binary variable rather than employing a detailed, muscle-specific grading system.\u003c/p\u003e\u003cp\u003eMagnetic resonance imaging (MRI) has become the cornerstone for local staging in NPC due to its superior soft tissue resolution and sensitivity in detecting perineural spread, muscular infiltration, and skull base invasion. MRI facilitates accurate mapping of tumor spread in anatomically complex regions, such as the parapharyngeal and masticator spaces. The complex muscular architecture surrounding the nasopharynx, including the TVP, LVP, prevertebral muscles, and the MP and LP muscles, offers a series of distinct potential pathways for tumor dissemination. Identifying specific patterns of muscle involvement is essential for optimizing treatment strategies and improving prognostication.\u003c/p\u003e\u003cp\u003eAccordingly, the present study was developed with the following aims: (1) to assess whether a muscle-specific grading of STI confers independent prognostic value in NPC; (2) to evaluate the prognostic utility of this grading system compared to conventional skull base criteria; and (3) to identify clinical and pathological predictors associated with deeper muscular invasion, with the goal of enabling individualized, risk-adapted therapy.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cb\u003eParticipants\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis retrospective study analyzed 391 consecutive patients newly diagnosed with NPC at the Department of Radiotherapy of the First Affiliated Hospital of Guangxi Medical University, between January 2014 and December 2019. Inclusion criteria were: (1) histologically confirmed, treatment-na\u0026iuml;ve NPC; (2) availability of comprehensive clinical and laboratory data at diagnosis; (3) high-resolution pre-treatment MRI of the nasopharynx and cervical region; (4) no prior history of antineoplastic therapy; and (5) completion of radical IMRT. Patients were excluded if they: (1) were lost to follow-up during treatment or subsequent monitoring; (2) were diagnosed with synchronous malignancies; (3) developed second primary cancers post-treatment; (4) were pregnant or lactating; or (5) were medically unfit to complete treatment. These criteria were chosen to minimize bias and ensure consistency in outcome assessment. All patients underwent a standardized pretreatment evaluation protocol, including medical history, physical examination, hematologic and biochemical profiling, nasopharyngoscopy, contrast-enhanced MRI of the head and neck, chest radiography, abdominal ultrasound, and skeletal assessment via whole-body bone scintigraphy or 18F-FDG PET/CT, depending on clinical indications. Plasma EBV-DNA levels were quantified via real-time PCR, in accordance with previously validated protocols [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This study was conducted in compliance with the Declaration of Helsinki and approved by the Ethics Committee of the First Affiliated Hospital of Guangxi Medical University. Given its retrospective nature, the requirement for informed consent was waived. Patient confidentiality and data anonymity were maintained throughout. To reduce selection bias, all eligible patients within the study period who met inclusion criteria were enrolled without exception.\u003c/p\u003e\u003cp\u003e\u003cb\u003eImaging assessments\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAll patients underwent pre-treatment MRI using a 1.5-T GE Signa scanner. The imaging protocol incorporated both conventional and contrast-enhanced spin-echo sequences, including T2-weighted imaging (T2WI; TR\u0026thinsp;=\u0026thinsp;3000\u0026ndash;4000 ms, TE\u0026thinsp;=\u0026thinsp;102\u0026ndash;110 ms), T1-weighted imaging (T1WI; TR\u0026thinsp;=\u0026thinsp;2200\u0026ndash;2400 ms, TE\u0026thinsp;=\u0026thinsp;77\u0026ndash;109 ms, T1\u0026thinsp;=\u0026thinsp;750 ms), and contrast-enhanced T1WI following intravenous administration of 15 mL of gadolinium-diethylenetriaminepentaacetic acid (Gd-DTPA). Scans were performed in axial, sagittal, and coronal planes using a head coil, with a slice thickness of 6 mm and an interslice gap of 1 mm (matrix: 256 \u0026times; 192), covering the area from the suprasellar cistern to the inferior clavicular margin. This protocol was optimized to detect soft tissue extension and skull base involvement, with particular focus on delineating the boundaries of the parapharyngeal and masticator spaces. Two board-certified radiologists independently reviewed all MRI scans while blinded to patient outcomes. Based on the deepest anatomical site of muscle infiltration, STI was categorized into three muscle-specific grades: mild (TVP or LVP muscles), moderate (prevertebral muscles), and severe (MP or LP muscles and/or infratemporal fossa involvement) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).In parallel, skull base invasion was stratified as limited or extensive, following previously established imaging criteria [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Disagreements between readers were resolved by consensus through joint image review. This grading system was guided by both anatomical insights and prior literature suggesting that the depth of muscle invasion correlates with clinical outcomes.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eTreatment protocol\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAll patients received definitive IMRT according to a uniform protocol consistent with guidelines from the International Commission on Radiation Units and Measurements (ICRU) Reports 50 and 62 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Radiotherapy target volumes included: the primary nasopharyngeal tumor (GTV nx), gross nodal disease (GTV nd), the surrounding high-risk subclinical zone (CTV1), and the elective cervical lymphatic drainage regions (CTV2). Prescribed radiation doses were as follows: GTV nx: 68\u0026ndash;76 Gy in 30\u0026ndash;33 fractions; GTV nd: 66\u0026ndash;70 Gy in 30\u0026ndash;33 fractions; CTV1: 60\u0026ndash;64 Gy in 30\u0026ndash;33 fractions; CTV2: 50\u0026ndash;54 Gy in 30\u0026ndash;33 fractions. Daily fraction sizes ranged from 2.00 to 2.33 Gy. Full technical details are available in earlier reports [\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Tumors were restaged according to the 9th edition AJCC system [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMost patients received induction chemotherapy (IC) followed by concurrent chemoradiotherapy (CCRT), with or without adjuvant chemotherapy (AC). IC regimens were administered every 21 days and included one of the following: TP: docetaxel 75 mg/m\u0026sup2; + cisplatin 75 mg/m\u0026sup2;, both on day 1; PF: cisplatin 80 mg/m\u0026sup2; (day 1)\u0026thinsp;+\u0026thinsp;5-fluorouracil 800\u0026ndash;1000 mg/m\u0026sup2; (days 1\u0026ndash;5, continuous infusion); TPF: docetaxel 60 mg/m\u0026sup2; + cisplatin 60 mg/m\u0026sup2; (day 1), with 5-fluorouracil 600 mg/m\u0026sup2; (days 1\u0026ndash;5, continuous infusion). While undergoing radiotherapy, concurrent cisplatin was given either weekly or triweekly. In patients unable to tolerate or deemed ineligible for cisplatin, alternative platinum agents were used. AC regimens were identical to those used during IC.\u003c/p\u003e\u003cp\u003e\u003cb\u003eClinical Endpoints and followup\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePrimary clinical endpoints included: local failure-free survival (LFFS), measured time from diagnosis to first occurrence of local recurrence/persistence or censoring at last follow-up/death; distant metastasis-free survival (DMFS), measured as the time to first detection of distant metastasis or censoring; progression-free survival (PFS), measured as the time to any progression (local, regional, or distant), death, or censoring; and overall survival (OS), measured as the time to death from any cause or censoring. Patients were monitored post-treatment every three months for the first two years, then every six months up to five years, or until death. Each follow-up included MRI of the nasopharynx and neck, and CT imaging of the chest and abdomen. Where recurrence or metastasis was suspected, diagnostic confirmation was obtained via fine needle aspiration or histopathologic biopsy when necessary. Patients lost to follow-up or alive without recurrence at study end were censored at their most recent assessment.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eContinuous variables were expressed as medians with interquartile ranges (IQR) and compared across muscle invasion categories using one-way ANOVA or the Kruskal\u0026ndash;Wallis test, depending on distribution. Categorical data were summarized as frequencies (percentages) and compared using χ\u0026sup2; or Fisher\u0026rsquo;s exact tests. Kaplan\u0026ndash;Meier survival curves were constructed for LFFS, DMFS, PFS, and OS, with differences assessed via log-rank testing. Univariable analyses identified candidate prognostic variables, which were subsequently entered into multivariable Cox proportional hazards models to compute adjusted hazard ratios (HRs) and 95% confidence intervals (CIs). Statistical analyses were conducted using SPSS 26.0 (IBM Corp) and R v2025.05.1\u0026thinsp;+\u0026thinsp;513(R Foundation for Statistical Computing). A two-sided P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was deemed significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePatient characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBaseline characteristics are detailed in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The cohort included 391 patients, classified by MRI muscle invasion grading into mild (n\u0026thinsp;=\u0026thinsp;168, 42.9%), moderate (n\u0026thinsp;=\u0026thinsp;76, 19.4%), and severe (n\u0026thinsp;=\u0026thinsp;147, 37.6%) groups. The median age was 46 years (IQR: 37\u0026ndash;53), and sex distribution was predominantly male (74.4%), with no significant differences in age or sex across the three groups (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Alcohol consumption varied significantly, with the highest prevalence in the moderate group (47.4%) and the lowest in the mild group (30.4%; P\u0026thinsp;=\u0026thinsp;0.037). Smoking status did not differ statistically (P\u0026thinsp;=\u0026thinsp;0.067). Disease severity increased with muscle invasion depth: T4 classification was observed in 54.6% of severe cases, 28.4% of moderate cases, and 11.0% of mild cases (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, stage IV disease was more prevalent in the severe (61.0%) compared to the moderate (41.8%) and mild (34.4%) groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). N-category distributions were not significantly different (P\u0026thinsp;=\u0026thinsp;0.20). EBV-DNA positivity showed a heterogeneous distribution, with 58.5% in mild, 31.0% in moderate, and 71.7% in severe groups (P\u0026thinsp;=\u0026thinsp;0.007), though interpretation is limited by substantial missing data (64.2%). Extensive skull base invasion (ESBI) was most common in the severe group (62.2%), followed by moderate (48.7%) and mild (40.8%) (P\u0026thinsp;=\u0026thinsp;0.003). Treatment regimens were well balanced across groups: 85.9% received IC, 92.8% underwent CCRT, and 34.5% received AC, with no significant intergroup differences (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.10).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePatient Characteristics\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;391\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;168\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;76\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSevere\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;147\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e291 (74.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e119 (70.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62 (81.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 (74.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100 (25.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (29.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (18.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37 (25.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.14\u0026thinsp;\u0026plusmn;\u0026thinsp;10.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.70\u0026thinsp;\u0026plusmn;\u0026thinsp;10.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.42\u0026thinsp;\u0026plusmn;\u0026thinsp;10.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.02\u0026thinsp;\u0026plusmn;\u0026thinsp;10.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrinking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.037\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e250 (63.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e117 (69.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (52.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93 (63.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e141 (36.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51 (30.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36 (47.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54 (36.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e231 (59.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 (65.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39 (51.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82 (55.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e160 (40.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 (34.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37 (48.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65 (44.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePathology (WHO)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI-II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31 (7.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (9.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (7.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e360 (92.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e152 (90.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72 (94.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e136 (92.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEBV-DNA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60 (15.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (16.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (26.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (8.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 (20.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (22.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (11.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33 (22.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eData missing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e251 (64.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e103 (61.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (61.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e101 (68.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eT classification\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 (15.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52 (31.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70 (18.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (23.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (20.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (12.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e129 (34.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55 (33.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31 (46.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (30.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e114 (30.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (11.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (28.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77 (54.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eN classification\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (4.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (4.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (5.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69 (18.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33 (20.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (17.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (17.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e221 (59.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86 (52.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44 (65.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91 (64.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63 (17.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37 (22.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (11.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (12.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall Stage (9th)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (13.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (9.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (4.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e167 (45.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85 (52.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33 (49.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (34.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e170 (45.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56 (34.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (41.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86 (61.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSkull-base invasion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eESBI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122 (51.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (40.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (38.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74 (62.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLSBI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e117 (49.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42 (59.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (61.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45 (37.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eInduction chemotherapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55 (14.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (10.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (21.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e336 (85.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e150 (89.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60 (78.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e126 (85.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eConcurrent chemotherapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (7.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (6.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e363 (92.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e154 (91.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72 (94.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e137 (93.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjuvant chemotherapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e256 (65.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e106 (63.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (61.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e103 (70.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e135 (34.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62 (36.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (38.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44 (29.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eNotes: Bold indicates a significant difference among groups with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e1\u003c/sup\u003en (%); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003e\u003csup\u003e2\u003c/sup\u003ePearson\u0026apos;s Chi-squared test; Kruskal-Wallisr ank sum test\u003c/p\u003e\n \u003cp\u003eAbbreviations: EBV, Epstein-Barr virus; ESBI, extensive skull-base invasion; LSBI, limited skull-base invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eSurvival outcomes by depth of invasion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt a median follow-up of 88 months (IQR: 68\u0026ndash;105), 73 of the 391 patients (18.7%) experienced\u003c/p\u003e\n\u003cp\u003etreatment failure (11.9% vs 26.3% vs 22.4%, P\u0026thinsp;=\u0026thinsp;0.009). The details of treatment\u003c/p\u003e\n\u003cp\u003efailure are listed in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. Rates of locoregional failure varied significantly by muscle invasion grade: 11.3% (19/168) in the mild group, 23.7% (18/76) in the moderate group, and 17.0% (25/147) in the severe group (P\u0026thinsp;=\u0026thinsp;0.044). Similarly, the incidence of distant metastasis rose with increasing invasion severity: 4.8% in mild, 15.8% in moderate, and 12.9% in severe categories (P\u0026thinsp;=\u0026thinsp;0.009). When stratified by skull-base invasion, there was no significant difference in overall treatment failure between limited and extensive involvement (16.2% vs. 18.9%, respectively; P\u0026thinsp;=\u0026thinsp;0.718). The estimated 5-year survival outcomes for the full cohort were as follows: LFFS 84.1%, DMFS 90.0%, PFS 81.3%, and OS 80.3%. When stratifying by muscle-invasion depth, 5-year rates were for LFFS were 88.7% (mild), 76.3% (moderate), and 83.0% (severe) for mild, moderate, and severe cases, respectively (P\u0026thinsp;=\u0026thinsp;0.0001), with corresponding DMFS rates of 95.2%, 84.2%, and 87.1% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), PFS rates of 88.1%, 73.7%, and 77.6% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and OS rates of 92.9%, 73.7%, and 68.0% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). In contrast, patients grouped by skull-base invasion (limited vs. extensive) exhibited no significant differences in survival outcomes for LFFS (88.0% vs. 83.6%; P\u0026thinsp;=\u0026thinsp;0.23), DMFS (91.5% vs. 89.3%; P\u0026thinsp;=\u0026thinsp;0.25), PFS (83.8% vs. 81.1%; P\u0026thinsp;=\u0026thinsp;0.26), or OS (76.1% vs. 82.8%; P\u0026thinsp;=\u0026thinsp;0.24) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePatterns of Treatment Failure for Patients with soft tissue involvement after IMRT\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTreatment Failure Pattern\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;168\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;76\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSevere\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;147\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistant only\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (5.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.024\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBone and liver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBone, lung and liver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLung\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocal and distant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (11.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (7.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.049\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegional and distant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocal and regional\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (1.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocal only\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (6.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (6.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegional only\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (1.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (11.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (26.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33 (22.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eNotes: Bold indicates a significant difference among groups with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e1\u003c/sup\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003csup\u003e2\u003c/sup\u003eFisher\u0026apos;s exact test; Pearson\u0026apos;s Chi-squared test\u003c/p\u003e\n \u003cp\u003eAbbreviations: IMRT, intensity-modulated radiotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eUnivariate and multivariate analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe prognostic relevance of multiple clinical and treatment-related factors, including age, sex, muscle invasion grade, skull-base involvement, TN staging, EBV-DNA status, and receipt of IC, concurrent chemotherapy, and AC, was next assessed for all four survival endpoints. In univariate analysis, both muscle-specific tumor invasion (STI) and receipt of induction chemotherapy were significantly associated with all endpoints. Age showed a marginal association with overall survival (OS; HR 1.02 per year; P = 0.056). Other variables such as sex, alcohol or tobacco use, histological subtype, EBV-DNA status, T and N stage, overall clinical stage, skull-base involvement, and concurrent or adjuvant chemotherapy did not attain significance (all P \u0026gt; 0.20) (Table 3). Multivariate Cox regression confirmed that both STI grade and use of induction chemotherapy retained independent prognostic value. Compared with mild muscle invasion, moderate involvement significantly increased the risk of locoregional failure by more than three-fold, as reflected by LFFS (HR 3.30), DMFS (HR 3.43), PFS (HR 3.39), and OS (HR 3.39) outcomes (all P \u0026asymp; 0.001). Severe muscle invasion conferred even higher risks across all endpoints, with hazard ratios between 4.4 and 4.6 (all P \u0026lt; 0.001). Conversely, IC treatment independently reduced the likelihood of treatment failure by approximately 45%, as reflected by OS (HR 0.56), PFS (HR 0.56), DMFS (HR 0.57), and LFFS (HR 0.55) outcomes (all P \u0026asymp; 0.04). While increasing age trended toward worse OS (HR 1.02/year; P = 0.074), other covariates, including skull-base status and nodal involvement, were excluded from final models due to lack of significance (Table 4).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eUnivariate Analysis of Variables Correlated with Various Clinical Endpoints\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eLFFS\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eDMFS\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePFS\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eOS\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.699 (0.39\u0026ndash;1.255)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.231\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.703 (0.392\u0026ndash;1.261)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.705 (0.393\u0026ndash;1.264)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.696 (0.388\u0026ndash;1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.225\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.021 (0.999\u0026ndash;1.044)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.021 (0.999\u0026ndash;1.045)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.021 (0.999\u0026ndash;1.044)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.022 (0.999\u0026ndash;1.045)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDrinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.089 (0.674\u0026ndash;1.759)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.048 (0.649\u0026ndash;1.692)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.06 (0.657\u0026ndash;1.712)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.072 (0.664\u0026ndash;1.732)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.775\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.384 (0.869\u0026ndash;2.204)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.328 (0.834\u0026ndash;2.115)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.35 (0.848\u0026ndash;2.151)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.354 (0.85\u0026ndash;2.157)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.202\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePathology (WHO)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.549 (0.565\u0026ndash;4.247)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.499 (0.547\u0026ndash;4.112)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.528 (0.557\u0026ndash;4.189)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.410\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.5 (0.547\u0026ndash;4.113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.431\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEBV-DNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.187 (0.543\u0026ndash;2.591)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.668\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.203 (0.551\u0026ndash;2.627)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.161 (0.531\u0026ndash;2.535)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.709\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.221 (0.559\u0026ndash;2.667)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.616\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT classification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.267 (0.518\u0026ndash;3.099)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.605\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.261 (0.515\u0026ndash;3.085)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.611\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.291 (0.528\u0026ndash;3.158)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.576\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.21 (0.494\u0026ndash;2.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.677\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN classification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.536 (0.161\u0026ndash;1.781)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.538 (0.162\u0026ndash;1.786)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.524 (0.158\u0026ndash;1.741)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.552 (0.166\u0026ndash;1.832)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.332\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOverall Stage (9th)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.107 (0.427\u0026ndash;2.866)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.133 (0.438\u0026ndash;2.935)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.12 (0.433\u0026ndash;2.901)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.815\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.109 (0.428\u0026ndash;2.871)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.832\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSoft tissue invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.553 (1.697\u0026ndash;7.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.636 (1.736\u0026ndash;7.615)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.618 (1.727\u0026ndash;7.576)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.603 (1.72\u0026ndash;7.545)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSkull-base invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.399 (0.781\u0026ndash;2.506)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.402 (0.783\u0026ndash;2.512)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.378 (0.769\u0026ndash;2.469)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.421 (0.793\u0026ndash;2.546)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.237\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInduction chemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.525 (0.3-0.919)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.024*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.507 (0.289\u0026ndash;0.889)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.018*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.517 (0.296\u0026ndash;0.904)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.021*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.515 (0.294\u0026ndash;0.904)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.021*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConcurrent chemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.013 (0.408\u0026ndash;2.515)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.978\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.004 (0.404\u0026ndash;2.492)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.017 (0.41\u0026ndash;2.525)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.971\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.976 (0.393\u0026ndash;2.423)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.958\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdjuvant chemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.326 (0.826\u0026ndash;2.129)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.339 (0.834\u0026ndash;2.149)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.228\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.318 (0.821\u0026ndash;2.115)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.327 (0.826\u0026ndash;2.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.242\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003eNotes: Bold indicates statistically significant with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003eAbbreviations: HR, hazard ratio; CI, confidence interval; LFFS, locoregional recurrence-free survival; DMFS, distant metastasis-free survival; PFS, progression-free survival; OS, overall survival.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **P\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab4\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMultivariate Analysis of Variables Correlated with Various Clinical Endpoints\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eLFFS\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eDMFS\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePFS\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eOS\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSoft tissue involvement (moderate vs mild)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.305 (1.571\u0026ndash;6.953)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.429 (1.632\u0026ndash;7.204)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.385 (1.609\u0026ndash;7.119)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.387 (1.612\u0026ndash;7.119)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSoft tissue involvement (severe vs mild)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.491 (2.359\u0026ndash;8.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.409 (2.315-8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.367 (2.293\u0026ndash;8.317)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.605 (2.418\u0026ndash;8.769)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInduction chemotherapy (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.551 (0.313\u0026ndash;0.971)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.039\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.567 (0.322\u0026ndash;0.996)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.048\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.56 (0.319\u0026ndash;0.985)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.044\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.562 (0.319\u0026ndash;0.989)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.046\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (per year increase)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02 (0.997\u0026ndash;1.044)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02 (0.997\u0026ndash;1.043)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02 (0.997\u0026ndash;1.043)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.021 (0.998\u0026ndash;1.045)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003eNotes: Bold indicates statistically significant with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003eAbbreviations: HR, hazard ratio; CI, confidence interval; LFFS, locoregional recurrence-free survival; DMFS, distant metastasis-free survival; PFS, progression-free survival; OS, overall survival.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eComparative analysis of anatomical classifications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess the relative prognostic value of bone versus muscle invasion, survival outcomes were compared between patients with LSBI and those with severe muscle infiltration. The LSBI group achieved 5-year PFS and OS rates of 83.8% and 76.1%, respectively, which were not significantly different from the severe muscle-invasion cohort (77.6% and 68.0%; P = 0.14 and 0.24). Moreover, LSBI outcomes closely resembled those of the moderate muscle-invasion group (PFS 84% vs. 86%, P = 0.70; OS 78% vs. 81%, P = 0.98; Fig. 4).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study highlights the prognostic utility of a muscle-specific MRI-based grading system for stratifying NPC, revealing survival differences not captured by conventional classifications of skull-base invasion. In this cohort, 5-year LFFS, DMFS, PFS, and OS showed a clear stepwise decline with increasing depth of muscular invasion. Severe muscle involvement emerged as an independent predictor of poorer outcomes, associated with nearly a threefold higher risk of mortality (HR ≈ 2.9, 95% CI 1.7–4.8), even after adjusting for TNM stage, EBV-DNA levels, and treatment factors. Conversely, the extent of skull-base invasion did not significantly influence any evaluated survival outcome.\u003c/p\u003e\n\u003cp\u003eMRI is currently the preferred modality for initial staging, treatment planning, and post-therapy surveillance in NPC due to its superior soft-tissue resolution and enhanced sensitivity for detecting skull-base and cranial nerve involvement [19,20]. Its ability to detect subtle signal alterations associated with early STI makes it particularly effective in identifying early tumor spread [21,22]. Among the anatomical structures adjacent to the nasopharynx, STI is the most commonly affected site during NPC progression, benefiting from MRI’s high-resolution imaging capabilities [23,24]. Consistent with previous findings, the survival analyses in the present study revealed a distinct prognostic gradient based on the extent of muscle invasion. Patients with mild muscular involvement exhibited markedly better 5-year rates for LFFS, DMFS, PFS, and OS compared to those with moderate or severe invasion. The moderate invasion group demonstrated intermediate outcomes, indicating that increasing depth of muscle infiltration is inversely correlated with prognosis in T2 NPC [25]. One explanation is that mild invasion is typically associated with smaller tumors that encroach only minimally on peri-nasopharyngeal tissue, leading to lower tumor burden and improved local control. In contrast, extensive muscle involvement often coincides with larger primary lesions capable of penetrating deep fascial planes and exploiting perineural routes through skull-base foramina, thereby increasing the risk of early systemic dissemination and distant metastasis. Unlike the classification used by Zhang et al., which broadly categorized invasion into parapharyngeal or masticator space and linked poor prognosis with lateral extension, most prior studies have not specifically assessed individual muscle involvement [26]. The present findings build upon this foundation by demonstrating a sequential decline in survival outcomes corresponding to invasion of the palatal, prevertebral, and pterygoid muscles, reinforcing the notion that deeper or more lateral STI is associated with adverse prognosis [27,28]. Several MRI-based studies, including those by Li et al. and Cheng et al., have highlighted the prognostic significance of skull-base bone invasion, reporting worse outcomes in cases of extensive involvement [12,29]. However, in the present study cohort, no significant differences in 5-year LFFS, DMFS, PFS, or OS were observed between patients with LSBI versus ESBI (all p \u0026gt; 0.20). Furthermore, skull-base status did not emerge as a prognostic factor in either univariate or multivariable analysis. This divergence from previous reports may be attributed to several factors. First, MRI-detected skull-base invasion often represents non-measurable or semi-quantitative findings, with the classification of limited versus extensive involvement being highly subjective and dependent on radiologists’ interpretation of marrow or cortical signal alterations. Second, modern high-resolution MRI is capable of detecting subtle changes such as edema or cortical thinning, which may lead to overestimation of disease extent and reduce the clinical utility of this subclassification. Finally, the implementation of IMRT, which provides precise and uniform dose coverage across the skull base, likely mitigates the clinical impact of bone involvement, thereby equalizing outcomes regardless of invasion extent.\u003c/p\u003e\n\u003cp\u003eThe unfavorable prognosis linked to deep muscle invasion in NPC arises from a complex interplay of biological and anatomical factors. Tumor infiltration into the prevertebral and pterygoid musculature likely reflects a more aggressive tumor phenotype, associated with increased proliferative activity, heightened invasiveness, and greater potential for perineural and hematogenous dissemination. At the molecular level, tumors exhibiting extensive STI frequently show elevated expression of matrix metalloproteinases, markers of epithelial–mesenchymal transition, and pro-angiogenic mediators. These molecular alterations promote degradation of the extracellular matrix, compromise anatomical barriers, and facilitate early spread to lymphatic and distant sites. Moreover, the anatomical proximity of the pterygoid region and infratemporal fossa to critical neurovascular structures increases the likelihood of cranial nerve encroachment and may hinder surgical salvage options in recurrent disease. The anatomical intricacy of these areas also presents challenges to achieving complete resection, potentially explaining the elevated rates of local failure observed in patients with deep muscle involvement. Additionally, the dense vascular and lymphatic architecture of deep muscular compartments offers multiple conduits for systemic dissemination, aligning with the increased incidence of distant metastases seen in this subgroup.\u003c/p\u003e\n\u003cp\u003eIntegrating a muscle-specific MRI-based grading system into routine NPC staging could significantly enhance prognostic accuracy compared to the current AJCC/UICC 9th-edition framework, which collectively classifies involvement of the LVP, TVP, prevertebral muscles, MP, and LP muscles as T2 disease. This aggregated classification may obscure clinically relevant heterogeneity. Patients with severe muscle involvement, particularly those with pterygoid muscle infiltration, face nearly a threefold increased risk of recurrence and mortality, underscoring their potential eligibility for more intensive treatment strategies such as IC, dose-escalated IMRT, or clinical trials evaluating novel systemic therapies. Conversely, patients exhibiting only mild muscle invasion may be candidates for de-escalated regimens, such as reduced elective nodal radiation or omission of AC, aiming to limit treatment-related morbidity without compromising oncologic outcomes. Standardizing radiologic assessments to routinely document involvement of the LVP, TVP, prevertebral muscles, MP, LP, and infratemporal fossa would facilitate more consistent interdisciplinary communication. Such standardization could support personalized surveillance protocols such as more frequent MRI for patients at elevated risk and enable the integration of quantitative imaging biomarkers and serial plasma EBV-DNA monitoring into clinical workflows. Multi-center, prospective validation studies and health-economic evaluations are now needed to confirm that this anatomically nuanced approach can improve outcomes while maintaining cost-effectiveness.\u003c/p\u003e\n\u003cp\u003eThe prognostic evaluation of NPC cases will likely increasingly rely on a combination of anatomical imaging, molecular profiling, and functional imaging metrics in the future. Plasma EBV-DNA has already been established as a robust surrogate for tumor burden and therapeutic response. When combined with muscle-specific MRI stratification, radiomic signatures, and gene expression profiling, it may enable the development of highly individualized risk models. These tools could guide treatment decisions by balancing therapeutic intensity with long-term toxicity and quality-of-life considerations. Additionally, advances in liquid biopsy, including circulating tumor DNA and microRNA profiling, offer further opportunities to refine risk stratification. Integration of such molecular data with detailed anatomical grading may yield robust composite prognostic tools, supporting more precise patient selection for emerging therapies.\u003c/p\u003e\n\u003cp\u003eTo implement muscle-specific MRI grading in routine clinical practice, standardized imaging protocols and targeted radiologist training will be essential. Multidisciplinary tumor boards should incorporate granular muscle invasion details into decision-making, particularly when evaluating candidacy for treatment intensification or de-escalation. Patients identified with extensive muscle involvement may benefit from early referral to clinical trials or advanced radiation modalities, while those with limited involvement might be safely managed with less intensive regimens. Ensuring reproducibility across institutions will require the development of reference atlases, uniform reporting templates, and ongoing educational initiatives. Artificial intelligence and machine learning algorithms hold promise as a means of enhancing the accuracy and consistency of muscle invasion assessment, potentially broadening access to this grading system across centers with varying radiologic expertise.\u003c/p\u003e\n\u003cp\u003eThis study's retrospective, single-center design imposes limitations on the generalizability of its findings. The moderate invasion subgroup was relatively small, which may reduce statistical power for some comparisons. Although muscle grading was performed by two blinded radiologists, inter-observer variability remains a concern. Additionally, this analysis did not incorporate functional imaging parameters such as diffusion-weighted MRI or PET-based metrics, nor did it account for dynamic EBV-DNA kinetics, with these being factors that could have added valuable prognostic insights. Prospective, multi-institutional studies employing harmonized imaging protocols are needed to validate and refine these results. The high rate of missing EBV-DNA data (64.2%) further limits the robustness of multivariable modeling. Future investigations should prioritize the acquisition of complete molecular datasets to facilitate comprehensive risk stratification. Furthermore, the absence of data on treatment response and patient-reported outcomes prevents a full understanding of how muscle-specific grading impacts therapeutic efficacy and quality of life.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThese results suggest that the depth of muscular invasion, rather than skull-base involvement, is the predominant anatomical predictor of locoregional control, metastatic spread, and survival in NPC patients treated with IMRT. Incorporating a muscle-specific MRI grading system into standard diagnostic workflows offers added prognostic value beyond conventional skull-base criteria and supports a framework for risk-adapted therapeutic strategies.\u0026nbsp;\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eMRI, magnetic resonance images; STI, soft tissue involvement; LVP, levator veli palatini; LP, lateral pterygoid; EBV, Epstein-Barr virus; ESBI, extensive skull-base invasion; LSBI ,limited skull-base invasion; IMRT, intensity-modulated radiotherapy; LFFS, local failure-free survival; DMFS, distant metastasis-free survival; PFS , progression-free survival ; OS, overall survival rates; STI, soft tissue involvement; HR, hazard ratio; CI, confidence interval.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material\u003c/p\u003e\n\u003cp\u003epreparation, data collection and analysis were performed by PY, SL, XC and XH. The first draft of the manuscript was written by PY and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China\u0026nbsp;(Grant Nos. 82260474 and 82303935), the\u0026nbsp;Scientific\u0026nbsp;Research Project of Health and Family\u0026nbsp;Planning Industry\u0026nbsp;in Hainan Province, China (Grant\u0026nbsp;No. 22A200068), and\u0026nbsp;the Hainan Province Science and Technology\u0026nbsp;Special\u0026nbsp;Fund\u0026nbsp;(Grant\u0026nbsp;Nos.\u0026nbsp;ZDYF2022SHFZ132 and\u0026nbsp;ZDYF2024SHFZ045).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Helsinki Declaration and approved by the Ethics Committee of the First Affiliated Hospital of Guangxi Medical University. And this was a retrospective study, so the informed consent was waived by the Ethics Committee of the First Affiliated Hospital of Guangxi Medical University. Participant information is confidential.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChen YP, Chan ATC, Le QT, Blanchard P, Sun Y, Ma J. Nasopharyngeal carcinoma. Lancet. 2019;394:64\u0026ndash;80. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0140-6736(19)30956-0\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(19)30956-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71:209\u0026ndash;49. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3322/caac.21660\u003c/span\u003e\u003cspan address=\"10.3322/caac.21660\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAmin MB, Greene FL, Edge SB, Compton CC, Gershenwald JE, Brookland RK, et al. The eighth edition AJCC cancer staging manual: Continuing to build a bridge from a population-based to a more personalized approach to cancer staging. CA Cancer J Clin. 2017;67:93\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3322/caac.21388\u003c/span\u003e\u003cspan address=\"10.3322/caac.21388\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTang LL, Chen YP, Mao YP, Wang ZX, Guo R, Chen L, et al. Validation of the 8th edition of the UICC/AJCC staging system for nasopharyngeal carcinoma from endemic areas in the intensity-modulated radiotherapy era. J Natl Compr Canc Netw. 2017;15:913\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.6004/jnccn.2017.0101\u003c/span\u003e\u003cspan address=\"10.6004/jnccn.2017.0101\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePan JJ, Mai HQ, Ng WT, et al. Ninth Version of the AJCC and UICC Nasopharyngeal Cancer TNM Staging Classification. JAMA Oncol. 2024;10:1736. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1001/jamaoncol.2024.4354\u003c/span\u003e\u003cspan address=\"10.1001/jamaoncol.2024.4354\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFeng Y, Cao C, Hu Q, Chen X. Grading of MRI-detected skull-base invasion in nasopharyngeal carcinoma with skull-base invasion after intensity-modulated radiotherapy. Radiat Oncol. 2019;14:10. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s13014-019-1214-3\u003c/span\u003e\u003cspan address=\"10.1186/s13014-019-1214-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen L, Liu LZ, Mao YP, Tang LL, Sun Y, Cui CY, et al. Grading of MRI-detected skull-base invasion in nasopharyngeal carcinoma and its prognostic value. Head Neck. 2011;33:1309\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/hed.21606\u003c/span\u003e\u003cspan address=\"10.1002/hed.21606\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXiao G, Xu G, Gao L. Prognostic influence of parapharyngeal space involvement in nasopharyngeal carcinoma. Zhonghua Zhong Liu Za Zhi. 2001;23:244\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXiao Y, Pan J, Chen Y, Chen L, Tang LL, Lu TY, et al. Prognostic value of MRI-derived masticator space involvement in IMRT-treated nasopharyngeal carcinoma patients. Radiat Oncol. 2015;10:204. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s13014-015-0513-6\u003c/span\u003e\u003cspan address=\"10.1186/s13014-015-0513-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXiao Y, Pan J, Chen Y, Chen L, Tang LL, Lu TY, et al. The prognosis of nasopharyngeal carcinoma involving masticatory muscles: A retrospective analysis for revising T subclassifications. Medicine. 2015;94:e420. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/MD.0000000000000420\u003c/span\u003e\u003cspan address=\"10.1097/MD.0000000000000420\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKang M, Zhou P, Liao X, Xu M, Wang R. Prognostic value of masticatory muscle involvement in nasopharyngeal carcinoma patients treated with intensity-modulated radiation therapy. Oral Oncol. 2017;75:100\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.oraloncology.2017.11.002\u003c/span\u003e\u003cspan address=\"10.1016/j.oraloncology.2017.11.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCheng YK, Liu LZ, Jiang N, et al. MRI-detected skull-base invasion: prognostic value and therapeutic implication in intensity-modulated radiotherapy treatment for nasopharyngeal carcinoma. Strahlenther Onkol. 2014;190:905\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00066-014-0656-7\u003c/span\u003e\u003cspan address=\"10.1007/s00066-014-0656-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiang SB, Wang Y, Hu XF, et al. Survival and Toxicities of IMRT Based on the RTOG Protocols in Patients with Nasopharyngeal Carcinoma from the Endemic Regions of China. J Cancer. 2017;8:3718\u0026ndash;24. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7150/jca.20351\u003c/span\u003e\u003cspan address=\"10.7150/jca.20351\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLin S, Pan J, Han L, Zhang X, Liao X, Lu JJ. Nasopharyngeal carcinoma treated with reduced-volume intensity-modulated radiation therapy: report on the 3-year outcome of a prospective series. Int J Radiat Oncol Biol Phys. 2009;75:1071\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijrobp.2008.12.015\u003c/span\u003e\u003cspan address=\"10.1016/j.ijrobp.2008.12.015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXue F, Hu C, He X. Long-term Patterns of Regional Failure for Nasopharyngeal Carcinoma following Intensity-Modulated Radiation Therapy. J Cancer. 2017;8:993\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7150/jca.17858\u003c/span\u003e\u003cspan address=\"10.7150/jca.17858\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSun X, Su S, Chen C, Han F, Zhao C, Xiao W, et al. Long-term outcomes of intensity-modulated radiotherapy for 868 patients with nasopharyngeal carcinoma: an analysis of survival and treatment toxicities. Radiother Oncol. 2014;110:398\u0026ndash;403. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.radonc.2013.10.020\u003c/span\u003e\u003cspan address=\"10.1016/j.radonc.2013.10.020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAu KH, Ngan RKC, Ng AWY, et al. Treatment outcomes of nasopharyngeal carcinoma in modern era after intensity modulated radiotherapy (IMRT) in Hong Kong: A report of 3328 patients (HKNPCSG 1301 study). Oral Oncol. 2018;77:16\u0026ndash;21. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.oraloncology.2017.12.004\u003c/span\u003e\u003cspan address=\"10.1016/j.oraloncology.2017.12.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTian YM, Liu MZ, Zeng L, et al. Long-term outcome and pattern of failure for patients with nasopharyngeal carcinoma treated with intensity-modulated radiotherapy. Head Neck. 2019;41:1246\u0026ndash;52. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/hed.25545\u003c/span\u003e\u003cspan address=\"10.1002/hed.25545\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eColevas AD, Yom SS, Pfister DG, Spencer S, Adelstein D, Adkins D, et al. NCCN Guidelines insights: head and neck cancers, Version 1.2018. J Natl Compr Canc Netw. 2018;16:479\u0026ndash;90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.6004/jnccn.2018.0026\u003c/span\u003e\u003cspan address=\"10.6004/jnccn.2018.0026\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGorolay VV, Niles NN, Huo YR, et al. MRI detection of suspected nasopharyngeal carcinoma: a systematic review and meta-analysis. Neuroradiology. 2022;64:1471\u0026ndash;81. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00234-022-02941-w\u003c/span\u003e\u003cspan address=\"10.1007/s00234-022-02941-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSun XS, Liu SL, Luo MJ, Li XY, Chen QY, Guo SS, et al. The Association Between the Development of Radiation Therapy, Image Technology, and Chemotherapy, and the Survival of Patients With Nasopharyngeal Carcinoma: A Cohort Study From 1990 to 2012. Int J Radiat Oncol Biol Phys. 2019;105:581\u0026ndash;90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijrobp.2019.06.2549\u003c/span\u003e\u003cspan address=\"10.1016/j.ijrobp.2019.06.2549\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiao XB, Mao YP, Liu LZ, Tang LL, Sun Y, Wang Y, et al. How does magnetic resonance imaging influence staging according to AJCC staging system for nasopharyngeal carcinoma compared with computed tomography? Int J Radiat Oncol Biol Phys. 2008;72:1368\u0026ndash;77. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijrobp.2008.03.017\u003c/span\u003e\u003cspan address=\"10.1016/j.ijrobp.2008.03.017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTang LL, Chen YP, Chen CB, et al. The Chinese Society of Clinical Oncology (CSCO) clinical guidelines for the diagnosis and treatment of nasopharyngeal carcinoma. Cancer Commun. 2021;41:1195\u0026ndash;227. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/cac2.12218\u003c/span\u003e\u003cspan address=\"10.1002/cac2.12218\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKing AD, Lam WW, Leung SF, et al. MRI of local disease in nasopharyngeal carcinoma: tumour extent vs tumour stage. Br J Radiol. 1999;72:734\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1259/bjr.72.860.10624338\u003c/span\u003e\u003cspan address=\"10.1259/bjr.72.860.10624338\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDong A, Huang W, Ma H, et al. Grading Soft Tissue Involvement in Nasopharyngeal Carcinoma Using Network and Survival Analyses: A Two-Center Retrospective Study. J Magn Reson Imaging. 2021;53:1752\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/jmri.27515\u003c/span\u003e\u003cspan address=\"10.1002/jmri.27515\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang GY, Huang Y, Cai XY, et al. Prognostic value of grading masticator space involvement in nasopharyngeal carcinoma according to MR imaging findings. Radiology. 2014;273:136\u0026ndash;43. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1148/radiol.14132745\u003c/span\u003e\u003cspan address=\"10.1148/radiol.14132745\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNasr Ben Ammar C, Kochbati L, Lejri N, et al. Valeur pronostique de l'extension parapharyng\u0026eacute;ee dans les carcinomes nasopharyng\u0026eacute;s [Prognostic value of parapharyngeal extension in nasopharyngeal carcinoma]. Tunis Med. 2009;87:814\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSze H, Chan LL, Ng WT, et al. Should all nasopharyngeal carcinoma with masticator space involvement be staged as T4? Oral Oncol. 2014;50:1188\u0026ndash;95. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.oraloncology.2014.09.001\u003c/span\u003e\u003cspan address=\"10.1016/j.oraloncology.2014.09.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi S, Luo C, Huang W, et al. Value of skull base invasion subclassification in nasopharyngeal carcinoma: implication for prognostic stratification and use of induction chemotherapy. Eur Radiol. 2022;32:7767\u0026ndash;77. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00330-022-08864-7\u003c/span\u003e\u003cspan address=\"10.1007/s00330-022-08864-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Nasopharyngeal carcinoma, MRI, soft tissue involvement, muscle-specific grading, skull base invasion, prognosis","lastPublishedDoi":"10.21203/rs.3.rs-7251035/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7251035/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eIn the 9th edition of the AJCC/UICC staging system for nasopharyngeal carcinoma (NPC), soft tissue extension to, but not beyond, the lateral pterygoid (LP) muscle is classified as stage T2 disease. Invasion beyond the LP into the masticator space or infratemporal fossa is designated as T4, while any skull base bone erosion is assigned to T3. However, this framework may oversimplify the prognostic spectrum of soft tissue involvement (STI). This study was formulated to investigate whether a muscle-specific magnetic resonance imaging (MRI) grading of offers incremental prognostic value over current skull base-based staging criteria.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003ePatients with newly diagnosed NPC treated with definitive intensity-modulated radiotherapy (IMRT) between 2014 and 2019 were retrospectively analyzed. Pretreatment MRIs were used to categorize STI severity as mild (tensor or levator veli palatini), moderate (prevertebral muscles), or severe (medial/lateral pterygoid or infratemporal fossa). Skull base invasion was classified as either limited (LSBI) or extensive (ESBI). Survival endpoints included local failure-free survival (LFFS), distant metastasis-free survival (DMFS), progression-free survival (PFS), and overall survival (OS). Kaplan\u0026ndash;Meier analysis and log-rank tests assessed survival, and Cox proportional hazards models identified independent prognostic factors.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOf 391 patients (median follow-up 88 months; interquartile range, 68\u0026ndash;105), 42.9% exhibited mild, 19.4% moderate, and 37.6% severe STI. Five-year survival rates were 84.1% (LFFS), 90.0% (DMFS), 81.3% (PFS), and 80.3% (OS). Survival declined in a stepwise fashion with increasing STI severity (log-rank P\u0026thinsp;\u0026le;\u0026thinsp;0.0001 for all endpoints); the 5-year OS was 92.9% for mild, 73.7% for moderate, and 68.0% for severe invasion. On multivariable analysis, moderate and severe STI were associated with a 3- to 4-fold increased risk of adverse outcomes, including disease progression and mortality (severe vs. mild OS: HR 4.55, 95% CI 2.47\u0026ndash;8.37, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Induction chemotherapy was independently protective, reducing the hazard of death by approximately 45% (OS: HR 0.56, 95% CI 0.32\u0026ndash;0.97, P\u0026thinsp;=\u0026thinsp;0.04). In contrast, skull base invasion status was not prognostically significant in either univariate or multivariate models. When directly compared, OS for moderate STI and LSBI was similar (81% vs. 78%, P\u0026thinsp;=\u0026thinsp;0.98), while severe STI showed a non-significant trend toward poorer OS compared with LSBI (68.0% vs. 76.1%, P\u0026thinsp;=\u0026thinsp;0.24).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eMuscle-specific MRI grading of STI serves as a more robust predictor of treatment outcomes than conventional skull base bone invasion in NPC patients receiving IMRT. This grading system may facilitate refined risk stratification and inform decisions on treatment escalation or de-intensification.\u003c/p\u003e","manuscriptTitle":"Muscle-Specific MRI Grading of Soft Tissue Involvement Provides Additional Prognostic Value Beyond Skull Base Criteria in Nasopharyngeal Carcinoma: A Retrospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-18 09:32:23","doi":"10.21203/rs.3.rs-7251035/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-12T04:10:11+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-08T02:24:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"325262360615638050349603884151620851621","date":"2025-09-01T12:30:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-27T04:18:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"70186646618020882341357464244671397095","date":"2025-08-19T21:02:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"36194283430270189869152362637819996129","date":"2025-08-10T14:38:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-10T13:41:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-05T08:33:44+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-04T08:02:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-04T06:59:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-08-03T13:56:22+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b17fb644-f410-4209-8b8a-907bd1489385","owner":[],"postedDate":"August 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-17T16:00:58+00:00","versionOfRecord":{"articleIdentity":"rs-7251035","link":"https://doi.org/10.1186/s12885-025-15208-3","journal":{"identity":"bmc-cancer","isVorOnly":false,"title":"BMC Cancer"},"publishedOn":"2025-11-12 15:57:35","publishedOnDateReadable":"November 12th, 2025"},"versionCreatedAt":"2025-08-18 09:32:23","video":"","vorDoi":"10.1186/s12885-025-15208-3","vorDoiUrl":"https://doi.org/10.1186/s12885-025-15208-3","workflowStages":[]},"version":"v1","identity":"rs-7251035","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7251035","identity":"rs-7251035","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}