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. 2026 Feb 10;7(2):102617. doi: 10.1016/j.xcrm.2026.102617

A revised staging system for natural killer/T cell lymphoma incorporating skull base invasion and nasal/non-nasal subtype distinction

Yi Cao 1,2,19, Yuchen Zhang 1,2,19, Liang Wang 3,19, Yongping Song 4,19, Shunan Qi 5,19, Peiqiang Cai 1,6, Rong Tao 7, Zhihua Li 8, Yuerong Shuang 9, Qingsong Yin 10, Zhigang Peng 11, Liye Zhong 12, Xiuhua Sun 13, Hongyu Zhang 14, Ying Zhao 15, Hongmei Jing 16, Bingzong Li 17, Qihua Zou 1, Huiqiang Huang 1,2, Yan Gao 1,2, Yi Xia 1,2, Man Nie 1,2, Xiaojie Fang 1,2, Xinna Gao 1,2, Shenrui Bai 1,2, Jun Cai 1,18,∗, Qingqing Cai 1,2,20,∗∗
PMCID: PMC12923967  PMID: 41672065

Summary

Current staging systems for natural killer/T cell lymphoma (NKTCL) inadequately reflect its predominantly extranodal presentation and lack prognostic accuracy in the asparaginase era. This retrospective multicenter study analyzes 1,872 newly diagnosed NKTCL patients treated with asparaginase-based regimens or radiotherapy alone, from 15 institutions across China. For nasal-type NKTCL, skull base invasion (SBI) is identified as an independent adverse prognostic factor. We reclassify Ann Arbor stage I patients with SBI as stage II and stage II patients with SBI as stage III. For non-nasal-type NKTCL, we retain the Chinese Southwest Oncology Group and Asia Lymphoma Study Group (CA) system due to its superior prognostic discrimination. The revised system demonstrates improved outcome prediction, hazard discrimination, hazard consistency, and sample balance across training, internal, and external validation cohorts. Time-dependent receiver operating characteristic (ROC) analysis confirms superior predictive accuracy over existing systems. This proposal provides a refined prognostic framework to guide clinical decision-making and optimize patient selection for future trials.

Keywords: natural killer/T cell lymphoma, skull base invasion, revised staging system, predictive accuracy, clinical decision

Graphical abstract

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Highlights

  • •

    Skull base invasion (SBI) is an independent prognostic factor in nasal-type NKTCL

  • •

    Ann Arbor stage I/II nasal-type NKTCL is reclassified based on the presence of SBI

  • •

    The CA staging system is applied for non-nasal-type NKTCL

Cao et al. develop a revised staging system for natural killer/T cell lymphoma that incorporates skull base invasion (SBI) and nasal/non-nasal subtypes. This work demonstrates improved prognostic accuracy and a more balanced stage distribution, with implications for clinical risk stratification in the modern treatment era.

Introduction

Natural killer/T cell lymphoma (NKTCL) is a highly aggressive subtype of non-Hodgkin lymphomas (NHLs), with a higher prevalence in Asia and Latin America.1,2,3 It predominantly involves extranodal sites, particularly the upper aerodigestive tract, including the nasal cavity, nasopharynx, and Waldeyer’s ring.4 The high expression of multidrug-resistant P-glycoprotein in natural killer cells confers resistance to anthracyclines, leading to suboptimal responses of NKTCL patients to CHOP (cyclophosphamide, doxorubicin, vincristine, and prednisone) and CHOP-like regimens.5,6 Over the past decade, survival outcomes for patients with NKTCL have markedly improved with the early application of radiotherapy and the introduction of asparaginase-based chemotherapy as a cornerstone of modern therapeutic strategies.7,8,9 Nevertheless, a considerable proportion of patients with NKTCL experience treatment failure due to relapse or treatment-related mortality.

Accurate anatomic staging is fundamental for risk stratification, treatment selection, and outcome prediction in lymphomas. To date, however, no standardized staging system specifically designed for NKTCL has been established. The Ann Arbor system,10 originally designed for anatomic staging of Hodgkin lymphoma, has for decades been applied to NHLs in the absence of a better alternative and remains the most widely used staging framework in NKTCL. However, its prognostic relevance in NKTCL has been shown to be limited.11,12 In particular, it inadequately reflects extranodal disease and omits evaluation of direct extension into contiguous anatomical structures.

Moreover, two additional staging systems have been applied in NKTCL, with relatively infrequent use in clinical practice. The Lugano classification,13 proposed in 2014, introduced positron emission tomography-computed tomography (PET/CT) into the initial staging process and confined the classification of localized extranodal involvement to early-stage disease. However, the designation of limited extranodal involvement is not applied to advanced-stage disease, which, in the context of NKTCL, restricts the classification of cases into stage III. The Chinese Southwest Oncology Group and Asia Lymphoma Study Group (CA) system14 was specifically designed for NKTCL, incorporates presentation patterns (e.g., nasal vs. non-nasal disease and local invasiveness), and yields a more balanced stage distribution than the Ann Arbor system. However, it was developed based on patient cohorts primarily treated with anthracycline-based regimens and its applicability in the asparaginase era remains uncertain.

To address the limitations of current staging systems, various prognostic factors have been identified for NKTCL, such as primary tumor invasion (PTI), non-nasal type disease, and bilateral regional lymph node metastasis.12,15,16 However, few studies have attempted to integrate these variables into a formal staging framework. In the present study, we focused on anatomical parameters, given the growing evidence that both disease extent and involvement of specific anatomical sites are independently associated with prognosis in NKTCL.15,17,18 Using a retrospective cohort of patients with newly diagnosed NKTCL, all with baseline PET/CT data, we incorporated anatomical features into existing staging criteria to develop a revised system aimed at improving prognostic accuracy and guiding individualized treatment in the asparaginase era.

Results

Baseline characteristics

A schematic representation of the study workflow is shown in Figure 1A. Complete baseline and outcome data were available for 2,475 patients, of whom 603 did not meet the eligibility criteria for the final analysis. Consequently, 1,872 cases were included: 1,060 from Sun Yat-sen University Cancer Center (SYSUCC) and Beijing Tongren Hospital (BTH) for model derivation (795 in the training set and 265 in the internal validation set) and 812 from 13 other participating hospitals for external validation.

Figure 1.

Figure 1

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Study profile and identification of skull base invasion

(A) The workflow for developing and validating of a revised staging system for NKTCL.

(B) Forest plots of multivariate Cox regression identifying SBI as an independent prognostic factor in nasal-type NKTCL.

(C and D) Representative axial images of nasal-type NKTCL with (C) and without (D) SBI. Each panel includes a T2-weighted fast spin echo MRI (left) and a fused PET/CT scan (right), with red arrows indicating the presence or absence of SBI.

The pretreatment characteristics of patients are summarized in Table 1. The median age of the entire cohort was 46 years (interquartile range [IQR], 35–57), and 69.4% were male. Most patients (76.2%) had Ann Arbor stage I or II disease, 1,635 (87.3%) had nasal-type NKTCL, and 1,133 (60.5%) presented with PTI. The baseline characteristics at initial diagnosis were generally comparable across the three cohorts. The median follow-up duration was 63.5 months (range: 0.9–119.5 months) for the training and internal validation cohorts and 62.2 months (range: 0.5–120.0 months) for the external validation cohort. The 5-year progression-free survival (PFS) and overall survival (OS) rates for the entire cohort were 53.0% and 62.3%, respectively.

Table 1.

Baseline characteristics of NKTCL patients

Characteristics All patients (n = 1,872) Training cohort (n = 795) Internal validation cohort (n = 265) External validation cohort (n = 812) p
Age 0.193
Median (IQR), y 46 (35–57) 46 (35–56) 44 (35–56) 47 (36–58)
Gender, n (%) 0.873
Male 1,299 (69.4) 556 (69.9) 181 (68.3) 562 (69.2)
Female 573 (30.6) 239 (30.1) 84 (31.7) 250 (30.8)
B symptoms, n (%) 0.047
Yes 791 (42.3) 310 (39.0) 116 (43.8) 365 (45.0)
No 1,081 (57.7) 485 (61.0) 149 (56.2) 447 (55.0)
Elevated LDH, n (%) 0.987
Yes 494 (26.4) 209 (26.3) 71 (26.8) 214 (26.4)
No 1,378 (73.6) 586 (73.7) 194 (73.2) 598 (73.6)
Circulating EBV DNA, n (%) 0.751
Undetectable 739 (39.5) 327 (41.1) 104 (39.2) 308 (37.9)
Detectable 991 (52.9) 413 (51.9) 141 (53.2) 437 (53.8)
Unknown 142 (7.6) 55 (6.9) 20 (7.5) 67 (8.3)
ECOG score, n (%) 0.344
0–1 1,710 (91.3) 726 (91.3) 243 (91.7) 741 (91.3)
≥2 162 (8.7) 69 (8.7) 22 (8.3) 71 (8.7)
Nasal type, n (%) 0.099
Yes 1,635 (87.3) 696 (87.5) 221 (83.4) 718 (88.4)
No 237 (12.7) 99 (12.5) 44 (16.6) 94 (11.6)
Primary tumor invasion, n (%) 0.121
Absent 739 (39.5) 313 (39.4) 119 (44.9) 307 (37.8)
Present 1,133 (60.5) 482 (60.6) 146 (55.1) 505 (62.2)
PINK, n (%) 0.629
High 381 (20.4) 166 (20.9) 58 (21.9) 157 (19.3)
Intermediate 428 (22.9) 171 (21.5) 65 (24.5) 192 (23.6)
Low 1,063 (56.8) 458 (57.6) 142 (53.6) 463 (57.0)
PINK-E, n (%) 0.152
High 309 (16.5) 142 (17.9) 49 (18.5) 118 (14.5)
Intermediate 305 (16.3) 115 (14.5) 46 (17.4) 144 (17.7)
Low 1,258 (67.2) 538 (67.7) 170 (64.2) 550 (67.7)
Ann Arbor system, n (%) 0.300
I 945 (50.5) 415 (52.2) 135 (50.9) 395 (48.6)
II 481 (25.7) 183 (23.0) 66 (24.9) 232 (28.6)
III 67 (3.6) 31 (3.9) 11 (4.2) 25 (3.1)
IV 379 (20.2) 166 (20.9) 53 (20.0) 160 (19.7)
Lugano system, n (%)
I 945 (50.5) 415 (52.2) 135 (50.9) 395 (48.6) 0.159
II 481 (25.7) 183 (23.0) 66 (24.9) 232 (28.6)
IV 446 (23.8) 197 (24.8) 64 (24.2) 185 (22.8)
CA system, n (%) 0.178
I 349 (18.6) 144 (18.1) 48 (18.1) 157 (19.3)
II 596 (31.8) 271 (34.1) 87 (32.8) 238 (29.3)
III 481 (25.7) 183 (23.0) 66 (24.9) 232 (28.6)
IV 446 (23.8) 197 (24.8) 64 (24.2) 185 (22.8)
Treatment, n (%) 0.050
Radiotherapy alone 212 (11.3) 90 (11.3) 32 (12.1) 90 (11.1)
Chemotherapy alone 535 (28.6) 221 (27.8) 76 (28.7) 238 (29.3)
CMT 1,029 (55.0) 428 (53.8) 143 (54.0) 458 (56.4)
Immunochemotherapy 96 (5.1) 56 (7.0) 14 (5.3) 26 (3.2)
Rates of survival outcomes, %
5-year PFS 53.0 53.2 55.6 51.8 0.675
5-year OS 62.3 63.2 63.2 61.1 0.720
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PINK, Prognostic Index for Natural Killer lymphoma; PINK-E, PINK with EBV DNA.

Nasal-type NKTCL

In the training cohort, multivariate analysis identified non-nasal-type NKTCL as an independent adverse prognostic factor for both PFS (hazard ratio [HR]: 1.36, 95% confidence interval [CI]: 1.06–1.75, p = 0.015) and OS (HR: 1.42, 95% CI: 1.08–1.86, p = 0.011) (Figure S1A). Given the marked prognostic heterogeneity between nasal-type and non-nasal-type disease, we first focused on nasal-type NKTCL to explore potential refinements through incorporation of anatomical factors. The Ann Arbor staging system showed limited prognostic discrimination in nasal-type NKTCL. In the training cohort, the 5-year PFS rates were 21.9% and 19.9% for stages III and IV (p = 0.369) and the 5-year OS rates were 66.2%, 46.3%, and 34.0% for stages II, III, and IV (p = 0.080 for II vs. III; p = 0.187 for III vs. IV) (Figure S1B). Similar patterns were observed in the external validation cohort (Figure S1C). These findings indicate the need to refine the staging system for nasal-type NKTCL.

In multivariate Cox regression, skull base invasion (SBI) was independently associated with poor PFS (HR: 2.10, 95% CI: 1.51–2.92, p < 0.001) as well as poor OS (HR: 1.82, 95% CI: 1.23–2.69, p = 0.003) (Figure 1B; Table S1). Inter-rater reliability for SBI assessment yielded κ values of 0.86 (95% CI: 0.59–0.96) at SYSUCC and 0.73 (95% CI: 0.42–0.91) in the external validation cohort (Table S2). Representative magnetic resonance imaging (MRI) and PET/CT images of SBI-positive vs. SBI-negative cases are shown in Figures 1C and 1D. In contrast, remote structure invasion and adjacent soft tissue invasion were not associated with either PFS or OS. The detailed distribution of anatomical involvement is summarized in Table S3.

Further stratification of Ann Arbor stage I patients in the training cohort revealed significant prognostic difference in those with vs. without SBI (n = 39 vs. 354): 33.0% vs. 77.0% 5-year PFS rate and 48.5% vs. 82.4% 5-year OS rate (both p < 0.001) (Figure S2A). Ann Arbor stage I with SBI did not differ from stage II in either PFS or OS (adjusted hazard ratio [AHR]PFS: 1.42, 95% CI: 0.89–2.26, p = 0.141; AHROS: 1.13, 95% CI: 0.62–2.06, p = 0.679); in contrast, stage I patients without SBI demonstrated significantly better outcomes compared to stage II (AHRPFS: 0.41, 95% CI: 0.29–0.58; AHROS: 0.47, 95% CI: 0.31–0.69; both p < 0.001) (Table 2). Consistent results were observed in the internal and external validation cohorts (Figures S2B and S2C; Tables S4 and S5).

Table 2.

Multivariable analysis of Ann Arbor stage incorporating SBI in the training cohort

Risk stratification AHRPFSa (95% CI) p AHROSa (95% CI) p
Stage II as reference reference reference
Stage I without SBI 0.41 (0.29–0.58) <0.001 0.47 (0.31–0.69) <0.001
Stage I with SBI 1.42 (0.89–2.26) 0.141 1.13 (0.62–2.06) 0.679
Risk stratification AHRPFSa (95% CI) p AHROSa (95% CI) p
Stage III as reference reference reference
Stage II without SBI 0.53 (0.29–0.97) 0.041 0.46 (0.23–0.94) 0.034
Stage II with SBI 1.18 (0.60–2.31) 0.626 1.11 (0.52–2.38) 0.782
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a

Age (>60 vs. ≤60 years), ECOG performance status (1 vs. 0 and ≥2 vs. 0), serum LDH level (elevated vs. normal), and EBV DNA (detectable vs. undetectable) were included in the Cox regression model.

Further stratification of Ann Arbor stage II patients in the training cohort also revealed significant prognostic difference in those with vs. without SBI (n = 37 vs. 124): 33.7% vs. 59.2% 5-year PFS rate and 49.6% vs. 72.4% -year OS rate (both p < 0.05) (Figure S3A). Ann Arbor stage II disease with SBI did not differ from stage III disease in either PFS or OS (AHRPFS: 1.18, 95% CI: 0.60–2.31, p = 0.626; AHROS: 1.11, 95% CI: 0.62–2.06, p = 0.679); in contrast, patients with Ann Arbor stage II disease without SBI had significantly better outcomes compared to stage III (AHRPFS: 0.53, 95% CI: 0.29–0.97, p = 0.041; AHROS: 0.46, 95% CI: 0.23–0.94, p = 0.034) (Table 2). These findings were consistent in the internal and external validation cohorts (Tables S4 and S5; Figures S3B and S3C).

Based on these findings, we propose to upgrade Ann Arbor stage I nasal-type NKTCL with SBI to stage II and Ann Arbor stage II nasal-type NKTCL with SBI to stage III. Performance of this revised staging system in the training cohort is shown in Figure 2A. Most notably, statistically significant differences were noted in both PFS and OS between all pairs of adjacent stages. Similar survival patterns were observed in the internal and external validation cohorts of nasal-type NKTCL (Figures 2B and 2C).

Figure 2.

Figure 2

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Prognostic performance of the revised staging system in nasal-type and non-nasal-type NKTCL

(A–C) Kaplan-Meier curves for PFS (top) and OS (bottom) according to the revised staging system for nasal-type NKTCL in the training (A), internal validation (B), and external validation (C) cohorts. p values were calculated using the log rank test.

(D and E) Kaplan-Meier curves for PFS (top) and OS (bottom) according to the revised staging system for non-nasal-type NKTCL in derivation cohort (D) and external validation (E) cohort. p values were calculated using the log rank test.

Non-nasal-type NKTCL

For non-nasal-type NKTCL, the Ann Arbor system failed to achieve adequate prognostic discrimination in the derivation cohort, with considerable overlap in survival curves between adjacent stages (Figure S4A). The Lugano system demonstrated improved stratification but lacked a stage III category (Figure S4B). Notably, in comparison to nasal-type stage I disease as defined by the revised staging system in the training cohort, non-nasal-type Lugano stage I disease had lower 5-year PFS (56.3% vs. 77.0%) as well as lower 5-year OS rate (70.5% vs. 82.4%), raising concerns about the applicability of the Lugano system to non-nasal-type disease.

In the derivation cohort, the CA system demonstrated distinct survival gradients, with 5-year PFS rate of 56.3%, 33.5%, and 16.6% and OS rates of 70.5%, 41.8%, and 24.6% for stages II, III, and IV, respectively (Figure 2D). Statistically significant differences were noted in both PFS and OS between all pairs of adjacent stages. Similar results were observed in the external validation (Figure 2E). Based on these findings, the CA system appears to be most suitable for staging non-nasal-type NKTCL.

Metrics evaluation and clinical relevance of the revised staging system

The detailed stage definitions of the revised staging system are summarized in Table 3. Survival outcomes were clearly separated across stages in the training cohort, with 5-year PFS rates of 77.0%, 52.0%, 29.8%, and 17.9% and 5-year OS rates of 82.4%, 66.6%, 45.5%, and 30.4% from stage I to IV, respectively (Figure 3A). All adjacent stage comparisons showed statistically significant differences (all p < 0.050). Similar findings were observed in the internal and external validations (Figures 3B and 3C).

Table 3.

Classification criteria and differences between the Ann Arbor staging systems and the revised system for NKTCL

Stage Ann Arbor system Revised system
Stage I: Excluded nasal-type cases with SBI and all non-nasal-type cases from Ann arbor stage I.
single extranodal lesion (e.g., nasal cavity or nasopharynx) without nodal involvement (IE) nasal-type NKTCL without SBI and without lymph node involvement
Stage II: Included nasal-type stage I with SBI and non-nasal-type without nodal involvement
single extranodal lesion with regional lymph node involvement on the same side of diaphragm (IIE) (1) nasal-type NKTCL with SBI or with ipsilateral regional lymph node involvement
(2) non-nasal-type NKTCL without lymph node involvement and without disseminated extranodal disease
Stage III: Included nasal-type stage II with SBI and non-nasal-type with regional lymph node involvement
extranodal lesion with lymph node involvement on both sides of diaphragm (IIIE) (1) nasal-type NKTCL with contralateral or bilateral regional lymph node involvement, or with SBI plus ipsilateral lymph node involvement
(2) non-nasal-type NKTCL with regional lymph node involvement
Stage IV: Included non-nasal-type patients with bilateral nodal involvement originally classified as stage III
disseminated extranodal lesions (e.g., bone marrow, liver, multiple extranodal sites), with or without nodal disease (1) nasal-type NKTCL meeting Ann Arbor IV criteria
(2) non-nasal-type NKTCL with disseminated extranodal involvement or localized extranodal disease accompanied by bilateral lymph node involvement.
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Figure 3.

Figure 3

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Prognostic performance of the revised staging system and predictive accuracy in comparison with existing systems

(A–C) Kaplan-Meier curves for PFS (top) and OS (bottom) according to the revised staging system in the training (A), internal validation (B), and external validation (C) cohorts. p values were calculated using the log rank test.

(D and E) Time-dependent receiver operating characteristic curves for 5-year PFS (D) and OS (E), comparing the revised system with Ann Arbor, Lugano, and CA staging systems.

The revised system demonstrated higher area under the curve (AUC) values for both PFS and OS over the Ann Arbor, Lugano, and CA systems across the training, internal validation, and external validation cohorts (Figures S5A–S5C). The time-dependent AUCs from 6 to 60 months of this system consistently outperformed all three existing systems (all p < 0.001). At the 5-year time point, this system demonstrated higher predictive accuracy over all three existing staging systems in the training cohort, as well as in the internal and external validation cohorts (Figures 3D and 3E). Furthermore, the revised staging system demonstrated the highest C-index for both PFS and OS across all cohorts. In the derivation cohort, the C-index for PFS was 0.790 (95% CI, 0.765–0.815), outperforming the Ann Arbor, Lugano, and CA systems (0.785, 0.789, and 0.765, respectively). For OS, the revised system also showed superior discrimination (0.799 vs. 0.775–0.795). Similar patterns were observed in the external validation cohort, with all pairwise comparisons reaching statistical significance (p < 0.05) (Table S6). Metrics analysis using the Groome criteria19 showed higher score in overall performance in outcome prediction, hazard consistency, hazard discrimination, and sample size balance (Figures S5D–S5F).

Therapeutic implications of the revised staging system were explored in the entire study cohort (n = 1,872). In patients with stage I disease under this system, radiotherapy alone achieved comparable outcomes to combined modality therapy (CMT) in those without any risk factors (stage II–IV disease, PTI, age >60, elevated lactate dehydrogenase [LDH], or Eastern Cooperative Oncology Group [ECOG] ≥2)12 (Figure S6A). However, patients with ≥1 risk factor derived significant benefit from CMT over radiotherapy alone (5-year PFS rate: 81.0% vs. 67.4%, p = 0.004; 5-year OS rate: 84.6% vs. 71.7%, p = 0.002) (Figure S6B). Baseline treatment modalities were comparable between patients with and without SBI in Ann Arbor stage I/II nasal-type NKTCL (Table S7). Among those patients with SBI, the absence of disease progression was associated with more intensive systemic treatment (Table S8). Notably, in patients with Ann Arbor stage I and SBI (reclassified as stage II in the revised system), CMT was associated with improved outcomes compared to radiotherapy alone (5-year PFS rate: 43.6% vs. 8.8%, p = 0.019; 5-year OS rate: 61.4% vs. 9.9%, p < 0.001) (Figure S6C). In patients with Ann Arbor stage II and SBI (reclassified as stage III in the revised system), CMT involving six chemotherapy cycles was associated with improved outcomes compared to CMT involving four chemotherapy cycles (5-year PFS rate: 54.1% vs. 24.2%, p = 0.006; 5-year OS rate: 66.1% vs. 42.2%, p = 0.027) (Figure S6D).

Discussion

In this multicenter cohort of NKTCL patients treated in the asparaginase era, we propose a revised staging framework for NKTCL consisting of (1) reclassification of Ann Arbor stage I/II disease based on the presence of SBI and (2) application of the CA system for non-nasal-type NKTCL. This system outperformed the Ann Arbor, Lugano, and CA systems in outcome prediction, hazard consistency, hazard discrimination, and sample size balance. More importantly, classification under this system is consistent with current consensus on the pros and cons of different treatment modalities.

Despite the emergence of various prognostic models in NKTCL,20,21,22 staging remains a fundamental framework for prognostic assessment and treatment decision-making, owing to its reproducibility and direct relevance to practice. Over 70% of newly diagnosed NKTCL patients present with Ann Arbor stage I or II disease, generally associated with favorable outcomes.4 However, a subset of early-stage patients experience disease progression or treatment failure,23,24 reflecting marked heterogeneity in clinical outcomes within this population. In a cohort of 114 patients with nasal-type NKTCL, Ann Arbor stage I did not confer superior survival compared with stage II (5-year OS, 56% vs. 44%, p = 0.422; 5-year disease-free survival [DFS], 59% vs. 45%, p = 0.262).17 Similar findings were reported in a multicenter study, where stage I and II nasal-type cases showed no significant prognostic differences in univariable analysis (p = 0.903 for OS; p = 0.387 for DFS).25 Beyond early-stage disease, an Italian study of 26 evaluable nasal-type cases found no significant differences in DFS or OS between stage I/II and III/IV disease.26 Similar patterns have been observed in non-nasal NKTCL, where OS did not differ between early- and advanced-stage disease.4 Taken together, these observations suggest that the Ann Arbor system does not incorporate the infiltrative growth pattern of NKTCL—particularly direct extension into anatomical sites linked to adverse prognosis—thereby limiting its capacity to stratify risk among patients classified as early stage.

Recent advances in imaging technology have substantially improved the detection of subtle anatomical changes, enabling more precise staging.27 PET/CT is widely recognized as the most sensitive modality for initial staging in lymphomas.28 NKTCL is characteristically fluorodeoxyglucose avid, and prior studies have shown PET/CT to outperform conventional imaging in identifying extranodal involvement.29 Current guidelines for NKTCL30 recommend PET/CT as the preferred imaging modality at diagnosis. To ensure accurate staging and minimize the risk of undetected disease sites, our cohort included only patients with baseline PET/CT data. While PET/CT is optimal for detecting systemic and extranodal spread, MRI offers complementary value in delineating local extension in nasal-type NKTCL. In a study relying mainly on CT, only 21% of NKTCL patients were identified as having local tumor invasion.17 In contrast, an MRI-based study detected invasion in 64.7% of patients15—comparable to the 60.5% observed in our cohort. This marked difference underscores the value of MRI in detecting local extension and supports its utility in our refined classification.

PTI has been frequently reported as an adverse prognostic factor in NKTCL.31 In published cohorts of early-stage nasal-type NKTCL, patients with PTI exhibited significantly inferior survival, with 5-year OS rate ranging from 50.2% to 64.1%, compared to 72.1%–89.0% in those without PTI.15,31 These prior findings highlight the clinical relevance of PTI as an important indicator of locoregional aggressiveness. In our cohort, PTI was present in over 60% of patients. As a broadly defined anatomical feature, its high prevalence may limit its specificity and utility as a staging criterion. Therefore, rather than incorporating PTI as a whole into the staging system, we focused on more specifically defined anatomical sites within PTI that may be more appropriate for stage reclassification.

SBI was independently associated with worse PFS and OS in multivariate analysis, whereas invasion into remote structures or adjacent soft tissues showed no significant prognostic impact. Anatomically, the skull base forms the superior boundary of the nasopharynx and is a common site of direct tumor extension in nasopharyngeal malignancies.32 In nasopharyngeal carcinoma (NPC), SBI is observed in 50%–70% of cases and is widely recognized as a marker of aggressive disease.33,34 In the current study, the pterygoid process and sphenoid base were the most frequently involved skull base sites, closely mirroring the extension patterns seen in NPC.32 Incorporation of SBI as a criterion for stage reclassification among early-stage nasal-type NKTCL was supported by a retrospective study of 86 patients, which demonstrated significantly worse 2-year OS rate in patients with SBI (40.0% vs. 71.6%, p = 0.022).35

Regarding the non-nasal-type NKTCL, previous studies have reported significantly inferior survival compared to the nasal-type disease, even among patients with localized lesions.36,37,38 In line with this, the National Comprehensive Cancer Network guidelines recommend treating non-nasal-type NKTCL using protocols for advanced-stage nasal-type disease.30 In the current study, 5-year PFS and OS rates were comparable between (1) patients without nodal involvement or disseminated extranodal disease vs. nasal-type stage II disease, (2) patients with regional lymph node involvement vs. nasal-type stage III disease, and (3) patients with disseminated or bilaterally node-involved extranodal disease vs. nasal-type stage IV. Based on these findings, classifying non-nasal-type NKTCL into stage II–IV as in the CA system is more appropriate than the Ann Arbor and Lugano systems.

In comparison to the Ann Arbor and Lugano systems, the revised system resulted in more balanced sample distribution across stages. Notably, the proportion of stage III cases increased from 3.6% to 11.1%. Considering the distinct treatment paradigms for early- vs. advanced-stage NKTCL (i.e., radiotherapy-based strategies for early-stage and more intensive systemic therapy for advanced-stage disease)27,39; this change has significant clinical implications. By identifying a subset of patients with adverse features within traditionally defined early-stage groups, the revised staging system may help ensure appropriate treatment intensity. Furthermore, it may aid in optimizing eligibility criteria for future clinical trials by improving risk stratification and facilitating more homogeneous patient selection, particularly in studies investigating treatment escalation or de-escalation strategies.

In conclusion, we proposed a revised staging system that refines the Ann Arbor classification for nasal-type NKTCL by incorporating SBI and adopts the CA system for non-nasal-type disease. In comparison to all three existing staging systems, this system had improved performance in outcome prediction, hazard consistency, hazard discrimination, and sample size balance.

Limitations of the study

The current study has several limitations. First, despite the multicenter design and external validation, the retrospective nature means selection bias and residual confounding remain possible after adjustment. Unmeasured variability in supportive care, adherence, socioeconomic factors, and imaging workflows between centers may have affected outcomes and was not fully modeled. Given the relatively low prevalence of SBI in nasal-type NKTCL in our cohorts, this stage modification is relevant to a subset of patients and warrants validation in larger, prospective studies. Second, imaging-based assessment of SBI was not centrally reviewed, and inter-rater variability in MRI interpretation across centers may have affected staging accuracy. Although our inter-rater evaluation showed good agreement, some variability remained. Larger studies with a broader pool of experienced radiologists could further improve consistency in SBI assessment. Third, the revised system was derived from cohorts with complete PET-CT and MRI data; therefore, its robustness may be reduced when these imaging modalities are unavailable. Future studies should evaluate its applicability under incomplete imaging conditions and explore whether surrogate biomarkers (e.g., Epstein-Barr virus [EBV] DNA) could help improve its clinical practicality. In addition, the relatively narrow range of radiotherapy doses in this cohort limited analysis of the impact of dosage on prognosis in patients with SBI. Finally, all participating centers were in China; accordingly, generalizability to other geographical regions and races/ethnicities is unknown.

Resource availability

Lead contact

Further information and resource requests should be directly to and will be fulfilled by the lead contact, Qingqing Cai (caiqq@sysucc.org.cn).

Materials availability

This study did not generate new unique reagents.

Data and code availability

  • •

    De-identified patient-level clinical and survival data reported in this paper will be shared by the lead contact upon reasonable request.

  • •

    This paper does not report the original code.

  • •

    Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Acknowledgments

This work was supported by grants from National Natural Science Foundation of China (82230001, 82270199, 82400228, and U24A20680), Guangzhou Science and Technology Program (2024B03J1291), National Key Research and Development Program (2022YFC2502602), the Sun Yat-Sen University Clinical Research 5010 Program (2020009), the Clinical Oncology Foundation of Chinese Society of Clinical Oncology (Y-SY2021ZD-0110), and the China National Postdoctoral Program for Innovative Talents (BX20240445). The authors thank Kehong Zhang, MD, PhD, from Ivy Medical Editing (Shanghai, China) for revising the final manuscript.

Author contributions

Q.C. conceived and designed the study. Y.C., Y. Zhang, and J.C. performed data analyses. L.W., Y. Song, S.Q., P.C., and R.T. assisted with data curation. Q.C. supervised the study. All the authors contributed to writing the manuscript.

Declaration of interests

The authors declare no competing interests.

STAR★Methods

Key resources table

REAGENT or RESOURCE SOURCE IDENTIFIER
Software and algorithms
R software (version 4.3.3) The R Project for Statistical Computing https://www.R-project.org/
survival package for R R software https://www.R-project.org/
survminer package for R R software https://www.R-project.org/
ggplot2 package for R R software https://www.R-project.org/
survivalROC package for R R software https://www.R-project.org/
survcomp package for R R software https://www.R-project.org/
forestplot package for R R software https://www.R-project.org/
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Experimental model and study participants

Participants and study design

This retrospective cohort included consecutive adult patients (≥18 years) with newly diagnosed NKTCL who subsequently received either radiotherapy alone or asparaginase-based regimens at 15 centers across China between January 2008 and December 2022. For inclusion in the final analysis, NKTCL diagnosis was based on the World Health Organization (WHO) classification of lymphoid neoplasms. All included patients were required to have baseline positron emission tomography-computed tomography (PET/CT) data, and for patients with nasal-type NKTCL, baseline magnetic resonance imaging (MRI) data was also required. Classification into nasal and non-nasal types was based on involvement of the nasal region. Cases with nasal or paranasal involvement, as determined by physical examination and imaging (MRI, PET/CT or CT), were classified as nasal type, regardless of additional extranodal disease. Lymph node and other extranodal involvement was assessed using imaging studies, histopathological confirmation, or both.

Cases from Sun Yat-sen University Cancer Center (SYSUCC) and Beijing Tongren Hospital (BTH) were used to derive a revised staging system, and randomly allocated at a 3:1 ratio for training versus internal validation. Cases from the remaining 13 centers (the First Affiliated Hospital of Zhengzhou University, Cancer Hospital of Chinese Academy of Medical Sciences, Fudan University Shanghai Cancer Center, Sun Yat-sen Memorial Hospital, Jiangxi Cancer Hospital, Henan Cancer Hospital, the First Affiliated Hospital of Guangxi Medical University, Guangdong General Hospital, the Second Hospital of Dalian Medical University, Peking University Shenzhen Hospital, the First People’s Hospital of Foshan, Peking University Third Hospital, and the Second Affiliated Hospital of Suzhou University) were used for external validation.

This study was conducted in accordance with the principles of the Declaration of Helsinki and was approved by the institutional review boards of all participating centers. The requirement for informed consent was waived as the study involved retrospective analysis of anonymized data.

Method details

Data collection

Clinical and laboratory data at diagnosis—including age, gender, Eastern Cooperative Oncology Group (ECOG) performance status, B symptoms, plasma EBV DNA, serum LDH, and involvement of the nasal cavity/nasopharynx, regional or distant lymph nodes, or other extranodal sites—were extracted from medical records by trained coordinators or physicians. Case report forms (CRFs) were completed accordingly. Progression-free survival (PFS) and overall survival (OS) events were recorded from institutional data without additional central review.

Upon receipt of CRFs, eligibility was verified, and patients were excluded if they were untreated, initially received anthracycline-based chemotherapy (e.g., CHOP), or had histologic subtypes of NHL other than NKTCL. Cases with incomplete follow-up data, i.e., without a recorded last follow-up date, were also excluded. Pathologic diagnoses were confirmed by designated pathologists according to the 2022 WHO classification.40

Radiology evaluation

Head or head and neck MRI was required for patients with nasal-type NKTCL. The MRI protocol consisted of axial unenhanced T1-weighted and T2-weighted fast spin echo sequences, as well as fat-suppressed, contrast-enhanced T1-weighted sequences acquired after intravenous administration of gadopentetate dimeglumine (Gd-DTPA) at a dose of 0.1 mmol/kg.

MRI scans were independently evaluated by two board-certified radiologists with at least 10 years of experience in each participating center. Discrepancies in interpretation were resolved through joint discussion to achieve consensus. Cases for which consensus could not be reached were excluded from the final analysis. PTI was defined as the extension of primary nasal lesions into adjacent anatomical structures, irrespective of disease stage.15 SBI was defined as the presence of low signal intensity replacing normal high-signal bone marrow on T1-weighted images, combined with contrast enhancement following Gd-DTPA administration, consistent with MRI criteria described in previous studies,41,42,43 at any of the following sites: sphenoid base, clivus, petrous apex, foramen lacerum, pterygoid process, pterygoid canal, pterygopalatine fossa, greater wing of the sphenoid, foramen ovale, foramen rotundum, jugular foramen, facial canal, hypoglossal canal, and internal auditory canal.

Treatment

All patients received treatment based on institutional protocols and clinical judgment. Treatment modalities included chemotherapy alone, radiotherapy alone, combined modality therapy (CMT; defined as chemotherapy combined with radiotherapy), and immunochemotherapy. All chemotherapy regimens recorded in this study were asparaginase-based. In the training cohort (n = 795), 53.8% received CMT, 27.8% of patients received chemotherapy alone, 11.3% received radiotherapy alone, and 7.0% received immunochemotherapy. In the internal validation cohort (n = 265), the corresponding proportions were 54.0%, 28.7%, 12.1%, and 5.3%, respectively. In the external validation cohort (n = 812), 56.4% received CMT, 29.3% received chemotherapy alone, 11.1% received radiotherapy alone, and 3.2% received immunochemotherapy.

Development of the revised staging system

All patients were restaged according to the Ann Arbor, Lugano, and CA systems using PET/CT, supplemented by MRI or other conventional assessments (including chest radiography, abdominal ultrasonography, and targeted organ CT/MRI) performed before initiation of therapy.

In the training cohort, all candidate prognostic factors were drawn from variables used in established NKTCL models (e.g., Prognostic Index of Natural Killer Lymphoma incorporating EBV-DNA [PINK-E] and Nomogram-Revised Index [NRI]).20,22 These included: age, ECOG performance status, serum LDH level, non-nasal type disease, EBV DNA, distant lymph node involvement, and primary tumor invasion (PTI; subcategorized as skull base invasion [SBI], remote structure invasion, or adjacent soft tissue invasion). Each factor was individually assessed for its association with PFS and OS using univariable Cox proportional hazards models. Variables showing statistical significance (adjusted p < 0.05 after Benjamini-Hochberg correction) in the univariable analysis were entered into multivariable Cox regression to identify independent prognostic factors. The revised staging system was developed as an anatomical refinement of the Ann Arbor framework, in which stage boundaries were redefined according to the presence or absence of independently significant anatomical risk features identified through multivariable Cox analysis. The revised system was subsequently validated in both internal and external cohorts.

Performance evaluation

The prognostic performance of the revised staging system was assessed in comparison with the Ann Arbor, Lugano, and CA systems. Evaluations were conducted across four predefined domains19:(1) outcome prediction for OS and PFS; (2) hazard discrimination between adjacent stages; (3) hazard consistency within each stage; and (4) sample size balance. Comparisons were performed using a publicly available web-based ranking tool (http://rpa.renlab.org/).44

Model discrimination was evaluated using time-dependent receiver operating characteristic (ROC) curves, with the corresponding area under the curve (AUC) at 5 years and the concordance index (C-index) used to assess discrimination. Longitudinal AUC trajectories were also plotted, and differences across models were assessed using linear mixed-effects models.

Quantification and statistical analysis

PFS was defined as the time from treatment initiation to the date of documented disease progression, relapse, death from any cause, or the last follow-up. Follow-up dates were obtained from case report forms completed by investigators at each participating center, based on patients’ medical records. Patients alive at the last confirmed contact but lost to follow-up were censored at that date. Disease progression or relapse was defined as the appearance of new lesions or the enlargement of existing lesions, as determined by physical examination or imaging assessments at each institution. For patients with multiple recurrences, only the first documented progression or relapse was considered for PFS calculation. OS was defined as the interval from treatment initiation to death from any cause or last follow-up. Survival curves were estimated using the Kaplan–Meier method and compared by the log rank test.

To assess inter-rater reliability for SBI determination, MRI scans from 100 randomly selected cases at SYSUCC and 100 cases from the external validation cohort were independently reviewed. For SYSUCC cases, two radiologists with expertise in head-and-neck imaging independently evaluated the images, whereas for the external cohort, one radiologist from SYSUCC and one from the external center performed independent assessments. Inter-rater concordance was quantified using Cohen’s κ coefficients. Continuous variables were analyzed using the Mann-Whitney U test or Kruskal-Wallis test, as appropriate. Categorical variables were compared using the chi-squared test or Fisher’s exact test, as appropriate. The proportional hazards assumption for all Cox models was evaluated using scaled Schoenfeld residuals computed in the R survival package; p values greater than 0.05 were interpreted as no violation. Potential multiplicative interactions among covariates were examined in the multivariable Cox models by including product terms and assessing Wald p values. All statistical analyses were performed using R software (version 4.3.3). Two-sided P-values <0.05 were considered statistically significant.

Published: February 10, 2026

Footnotes

Supplemental information can be found online at https://doi.org/10.1016/j.xcrm.2026.102617.

Contributor Information

Jun Cai, Email: caijun@sysucc.org.cn.

Qingqing Cai, Email: caiqq@sysucc.org.cn.

Supplemental information

Document S1. Figures S1–S6 and Tables S1–S8
mmc1.pdf (1.1MB, pdf)
Document S2. Article plus supplemental information
mmc2.pdf (4.9MB, pdf)

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Document S1. Figures S1–S6 and Tables S1–S8
mmc1.pdf (1.1MB, pdf)
Document S2. Article plus supplemental information
mmc2.pdf (4.9MB, pdf)

Data Availability Statement

  • •

    De-identified patient-level clinical and survival data reported in this paper will be shared by the lead contact upon reasonable request.

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    This paper does not report the original code.

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    Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Articles from Cell Reports Medicine are provided here courtesy of Elsevier

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