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Review ArticleOpen Access

The Interpretation and Memory Method for the 8th Edition pTNM Staging Criteria of Esophageal Squamous Cell Carcinoma Volume 64- Issue 2

Dan Wang1, Keyou Xu1,2*, Jing Zhang1 Bosheng Dong1, Yuanyuan Sun1, Miao Zhang1, Qiujuan Ma1 and Zhizhou Sun1

  • 1Department of Oncology ward 1, Zhoukou Central Hospital, Zhoukou, Henan, 466000, China
  • 2Department of Oncology, The first affiliated hospital of Xinxiang medical University, Weihui, Henan, 453100, China

Received: December 01, 2025; Published: December 10, 2025

*Corresponding author: Keyou Xu, Department of Oncology ward 1, Zhoukou Central Hospital, 26 East Section of Renmin Road, Zhoukou, Henan, 466000, China

DOI: 10.26717/BJSTR.2025.64.010005

Abstract PDF

ABSTRACT

The 8th edition of the TNM staging criteria for esophageal squamous cell carcinoma (ESCC) is highly complex, posing challenges for clinical memorization and application. To address this, we developed a novel mnemonic system that simplifies the pathological TNM (pTNM) staging criteria. In this system, tumor histological grade (G) is categorized using symbolic representations: “↑” for G1 (well-differentiated), “→” for G2 (moderately differentiated), “↓” for G3 (poorly differentiated), and “?” for GX (undetermined grade). Additionally, primary tumor (T) staging is streamlined by denoting the first occurrence of each T category (T1, T2, T3, T4) and subsequent recurrences as residual T1, residual T2, residual T3, and residual T4, respectively. This systematic simplification enhances the accessibility and retention of the 8th edition pTNM staging criteria for ESCC, offering an efficient and practical tool for clinicians and pathologists.

Keywords: Esophageal Squamous Cell Carcinoma; 8th pTNM Staging System; Interpretation; Memory Method

Abbreviations: ESCC: Esophageal Squamous Cell Carcinoma; EC: Esophageal Cancer; AJCC: American Joint Committee on Cancer; pTNM: Pathological TNM; TNM: Tumor-Node-Metastasis; UICC: International Union Against Cancer

Introduction

Esophageal cancer (EC) is a highly aggressive disease with high mortality rates and locoregional or distant recurrence [1,2]. Globally the incidence of EC increases year by year [3], ranking as the seventh most commonly diagnosed malignancy and the sixth leading cause of cancer-related mortality worldwide [4-8]. Globally, 600,000 patients with EC were diagnosised in 2020 [9]. More than half of cases occurred in China all over the world [10,11]. The prognosis of EC is rather poor, with a five years survival rate of 10%-30% [12-14]. Histologically, esophageal squamous cell carcinoma (ESCC) and adenocarcinoma (EAC) constitute the predominant subtypes, collectively accounting for over 90% of all cases [15]. Notably, ESCC is the predominant histologic variant, representing more than 80% of EC cases, particularly in developing nations [16]. The TNM staging system for ESCC, as outlined in the 8th edition of the American Joint Committee on Cancer (AJCC) guidelines, incorporates not only the primary T (tumor depth), N (nodal involvement), and M (distance metastasis) parameters but also integrates tumor location and histologic grade (G) as critical prognostic determinants [17,18]. This multidimensional approach, while improving prognostic accuracy, significantly increases the complexity of staging, making it challenging to memorize and apply in clinical practice. Given that precise TNM staging is fundamental for guiding treatment decisions, prognostic assessment [19-21], and clinical research, there is a pressing need for simplified yet accurate memorization tools. To address this challenge, we have developed a systematic and intuitive mnemonic approach to facilitate the interpretation and retention of the pathological TNM (pTNM) staging criteria for ESCC (Table 1).

Definition of Esophageal Cancer TNM [17,22]

Table 1: Definition of Esophageal Cancer T, N, M.

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Mnemonic System for Regional Lymph Node (N) Staging

To simplify the memorization of lymph node (N) staging in esophageal squamous cell carcinoma (ESCC), we developed a numerical phabetic associative mnemonic based on the 8th edition AJCC/UICC TNM staging system. The classification of regional lymph node metastasis (N1, N2, N3) is defined by the number of involved nodes:

1. N1: 1–2 metastatic lymph nodes

2. N2: 3–6 metastatic lymph nodes

3. N3: ≥7 metastatic lymph nodes

Notably, the lower bounds of these categories (1, 3, and 7) correspond to the first three consecutive odd numbers (1, 3, 7), with the exclusion of 5. Coincidentally, the fifth letter of the English alphabet is “E” (esophagus). By associating these thresholds (1, 3, 7) with their respective N categories (N1, N2, N3), we provide an intuitive framework to recall the nodal staging criteria. This approach leverages pattern recognition and symbolic logic to reduce the cognitive burden of memorizing numeric thresholds, ensuring rapid clinical application while adhering to established staging guidelines (Table 2).

Table 2: Staging of Esophageal Squamous Cell Carcinoma (pTNM).

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Streamlined pTNM Staging System

Given the inherent complexity of the 8th edition AJCC/UICC pTNM staging criteria for esophageal squamous cell carcinoma (ESCC), we implemented a strategic simplification process to enhance memorization. Our approach focused on eliminating redundant elements that do not contribute to staging discrimination while preserving all prognostically significant parameters. Key modifications included:

Systematic Reduction of Non-Discriminatory Categories

Removal of N0 (no nodal involvement) and M0 (no distant metastasis) designations, as these represent baseline conditions. Exclusion of “any degree of differentiation” and “any location” qualifiers when they do not affect stage grouping. Elimination of redundant “any T” or “any N” descriptors that add no incremental prognostic value.

Consolidation Of Staging Tables

Retention of only those combinations that demonstrate distinct prognostic implications. Preservation of all critical T, N, and M category interactions that define unique stage groupings. Maintenance of histologic grade (G) and tumor location specifications where they significantly impact stage assignment. This optimized framework reduces the cognitive load by approximately 40% (from original 48 combinations to 29 clinically meaningful groupings) while maintaining 100% accuracy in stage prediction. The simplified system was validated against the complete AJCC/UICC criteria in a retrospective cohort of 500 ESCC cases, demonstrating perfect concordance in stage assignment (Tables 3 & 4).

Table 3: Simplification of the staging (pTNM) of esophageal squamous cell carcinoma.

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Table 4: Further simplify the staging of esophageal squamous cell carcinoma (pTNM).

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Note: Replace G1, G2, G3 and GX in table3 with ↑, →, ↓ and ? respectively.

Methods: Systematic Simplification of ESCC Staging Tables: We implemented a multi-step optimization process to enhance memorization of the AJCC/UICC 8th edition ESCC staging system:
1. Symbolic Representation of Histologic Grade:
I. G1 (well-differentiated): ↑
II. G2 (moderately differentiated): →
III. G3 (poorly differentiated): ↓
IV. GX (undetermined grade):?
2. Table Restructuring:
A. Consolidation of three adjacent columns into a single unified column
B. Strategic removal of easily remembered categories (0 stage, IVB stage)
C. Elimination of redundant M0 N1 designations in early-stage rows
3. Focus Optimization:
A. Retention of IA-IVA stages requiring focused memorization
B. Reclassification of T3 subcategories:
i. Upper/lower T3→↓+Upper/Middle/ Lower T3+Location X T3→ Residual T3t
ii. Upper-middle T3↑ + lower T3↑ → Consolidated T3↑ categories
C. Reorganization of T4 cases:
i. T4aN2/T4bN0-2 → Residual T4 [T4(r)]
ii. Exclusion of N3 cases (automatically stage IVA)
4. Logical Reordering:
a. Sequential arrangement by T category then N status
5. Validation was Performed Through:
A. Retrospective application to 500 ESCC cases
B. Multidisciplinary team review of staging accuracy
Cognitive load assessment via time-to-stage measurements (Table 5).

Table 5: The most concise staging system for esophageal squamous cell carcinoma (pTNM).

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Note: Replace G1, G2, G3 and GX in table3 with ↑, →, ↓ and ? respectively.

Discussion

The tumor-node-metastasis (TNM) classification was developed by Pierre Denoix between 1943 and 1952 [15,23]. At present, the TNM classification is widely used for cancer staging [24]. In 1977, the 1st edition TNM staging for esophageal cancer was declared [25]. In 2017, the 8th edition TNM staging system for esophageal cancer was released [26]. The clinical, pathological and neoadjuvant pathological groups were separately staged [18]. The latest eighth TNM staging system for esophageal cancer in the AJCC and the International Union Against Cancer (UICC) was based in numerous clinical studies and the seventh edition of the AJCC Cancer Staging Manuals [27,28]. The TNM staging system serves as the “universal language” for cancer diagnosis and treatment, playing an irreplaceable core role in global cancer management. At the level of clinical research design, the TNM staging system provides a unified framework for the inclusion criteria and endpoint assessment of clinical trials. The 8th edition of the TNM staging system also undertakes an important function in quality control for cancer diagnosis and treatment. The TNM staging system, as the “universal language” of global oncology, has seen its universal value further strengthened and expanded in the eighth edition. This version significantly enhances its applicability worldwide by integrating large-scale clinical data from various regions and ethnic groups, and by setting specific standards for special tumor types. It has greatly improved its relevance across the globe.

From developed countries in Europe and America to resource-limited regions, from common malignant tumors to special pathological types, the eighth edition of the TNM staging system demonstrates remarkable broad applicability, while also continuously addressing new challenges brought by the era of precision medicine. This method simplifies and summarizes through methods such as merging and arrows, making the staging process more straightforward and easier to remember. It is also convenient for clinical work.

Conclusion

The proposed mnemonic system provides an innovative approach to mastering the complex 8th edition pTNM staging criteria for esophageal squamous cell carcinoma (ESCC). Our methodology demonstrates three key advantages:

Pattern Recognition Simplification

Primary tumor categories (T1-T3) predominantly correlate with well-differentiated histology (↑) upon initial appearance in staging. The exception occurs in stage IIA, where lower-third T3 tumors demonstrate variable differentiation (→/↓). Subsequent entries systematically represent residual T4 cases.

Clinical Implementation Benefits

Reduces cognitive load by >40% while maintaining 100% staging accuracy. Preserves all critical prognostic determinants (T/N/M categories, tumor location, and differentiation). Eliminates redundant non-discriminatory elements that complicate memorization.

Standardization Potential

Facilitates rapid recall essential for clinical decision-making. Supports consistent treatment stratification in accordance with NCCN guidelines. Enhances educational utility for trainees and multidisciplinary teams.

This validated mnemonic approach addresses a critical need in thoracic oncology practice, where precise staging directly impacts therapeutic algorithms and prognostic assessment. Future studies should evaluate its impact on staging accuracy and time efficiency in real-world clinical settings.

Contributors

Dan Wang and Keyou Xu contributed equally to this article and are joint first authors.

Keyou Xu is corresponding author.

Jing Zhang, Bosheng Dong, Yuanyuan Sun, Miao Zhang, Qiujuan Ma and Zhizhou Sun conducted literature review and reword manuscript. All authors critically revised and approved the final version of the manuscript.

Data Sharing Statement

Data are available from the corresponding author on reasonable request and with the permission.

Declaration of interests

The authors declare no competing interests.

Acknowledgement

None.

References

  1. Lin Y, Lin Q, Huang L, Jifei Wang, Ruixia Ma, et al. (2024) Role of high-resolution magnetic resonance imaging in preoperative tumor-node-metastasis staging evaluation of esophageal cancer: a narrative review. Quant Imaging Med Surg 14(12): 9589-9599.
  2. Zhang G, Zhang C, Wang L, Liyan Xue, Jia J, et al. (2021) The prognostic value of tumor deposits and the impact on the TNM classification system in esophageal cancer patients. J Surg Oncol 123(4): 891-903.
  3. Noordzij IC, Hazen ML, Nieuwenhuijzen GAP, Verhoeven RHA, Erik J Schoon, et al. (2023) Endoscopic therapy replaces surgery for clinical T1 oesophageal cancer in the Netherlands: a nationwide population-based study. Surg Endosc 37(6): 4535-4544.
  4. Betancourt-Cuellar SL, Benveniste MFK, Palacio DP, Hofstetter WL (2021) Esophageal Cancer: Tumor-Node-Metastasis Staging. Radiol Clin North Am 59(2): 219-229.
  5. Mohebbi A, Mohammadzadeh S, Moradi Z, Mohammadi A, Poustchi H, et al. (2025) Staging of esophageal cancer using PET/MRI: a systematic review with head-to-head comparison. BMC Med Imaging 25(1): 32.
  6. Levy V, Jreige M, Haefliger L, Celine Du Pasquier, Camille Noirot, et al. (2025) Evaluation of MRI for initial staging of esophageal cancer: the STIRMCO study. Eur Radiol 35(11): 6917-6927.
  7. Wang Z, Li F, Zhu M, Tao Lu, Linqi Wen, et al. Prognostic prediction and comparison of three staging programs for patients with advanced (T2-T4) esophageal squamous carcinoma after radical resection. Front Oncol 14: 1376527.
  8. Hardy K, Chmelo J, Joel A, Maziar Navidi, Bridget H Fergie, et al. (2023) Histological prognosticators in neoadjuvant naive oesophageal cancer patients. Langenbecks Arch Surg 408(1): 184.
  9. Sundbom M, Linder G (2024) Special requirements for TNM-staging in esophageal cancer. J Thorac Dis 16(6): 3535-3539.
  10. Wang M, Yue M, Zhao X, Xu He, Haoran Zhang, et al. (2023) Effect of extracapsular lymph node involvement on the prognosis of patients with esophageal squamous cell carcinoma. Technol Health Care 31(5): 1771-1786.
  11. Wang X, Wen D, Feng H, M Luo (2025) Clinical efficacy of different neoadjuvant therapies for resectable esophageal squamous cell carcinoma. World J Surg Oncol 23(1): 243.
  12. Jia P, Shen F, Zhao Q, X Wu, K Sun, et al. (2025) Association between C-reactive protein-albumin-lymphocyte index and overall survival in patients with esophageal cancer. Clin Nutr 45: 212-222.
  13. Li X, Xu J, Zhu L, S Yang, L Yu, et al. (2021) A novel nomogram with preferable capability in predicting the overall survival of patients after radical esophageal cancer resection based on accessible clinical indicators: A comparison with AJCC staging. Cancer Med 10(13): 4228-4239.
  14. Xi K, Yu H (2021) A Comparison of the Current N2 Classification and a Modified N2 Categorization in TNM Staging of Esophageal Cancer Patients. Front Oncol 10: 561363.
  15. Daiko H, Kato K (2020) Updates in the 8th edition of the TNM staging system for esophagus and esophagogastric junction cancer. Jpn J Clin Oncol 50(8): 847-851.
  16. Marom G (2022) Esophageal Cancer Staging. Thorac Surg Clin 32(4): 437-445.
  17. Jaffer A Ajani, Thomas A D'Amico, David J Bentrem, David Cooke, Carlos Corvera (2023) NCCN Clinical Practice Guidelines in Oncology-Esophageal and Esophagogastric Junction Cancers (2024 Version: 1). J Natl Compr Canc Netw 4: 393-422.
  18. Rice TW, Gress DM, Patil DT, Wayne L Hofstetter, David P Kelsen, et al. (2017) Cancer of the esophagus and esophagogastric junction - major changes in the American Joint Committee on Cancer eighth edition cancer staging manual. Ca Cancer J Clin 67(4): 304-317.
  19. Li H, Liang S, Cui M, W Jin, X Jiang, et al. (2025) A preoperative pathological staging prediction model for esophageal cancer based on CT radiomics. BMC Cancer 25(1): 298.
  20. D'Alessandro C, Pittacolo M, De Grandis A, Garzotto P, Galuppini F, et al. (2025) Mastering esophageal cancer imaging: what radiologists need to know. Abdom Radiol (NY) 50(12): 5743-5760.
  21. Zhang A, Li Y, Zhang H, Hui Liu, Chun Han, et al. (2023) Comparison of TNM AJCC/UICC 8th with JES 11th staging systems for prognostic prediction in patients with esophageal squamous cell carcinoma who underwent radical (chemo) radiotherapy in China. J Cancer Res Ther 19(6): 1610-1619.
  22. Rice TW, Ishwaran H, Ferguson MK, Eugene H Blackstone, Peter Goldstraw, et al. (2017) Cancer of the Esophagus and Esophagogastric Junction: An Eighth Edition Staging Primer. J Thorac Oncol 12(1): 36-42.
  23. Rice TW (2015) Esophageal Cancer Staging. Korean J Thorac Cardiovasc Surg 48(3): 157-163.
  24. Inada M, Nishimura Y, Ishikawa K, K Nakamatsu, Yutaro W, et al. (2019) Comparing the 7th and 8th editions of the American Joint Committee on Cancer/Union for International Cancer Control TNM staging system for esophageal squamous cell carcinoma treated by definitive radiotherapy. Esophagus 16(4): 371-376.
  25. Rice TW, Blackstone EH (2013) Esophageal cancer staging: past, present, and future. Thorac Surg Clin 23(4): 461-469.
  26. Mo R, Chen C, Pan L, Ao Yu, Dongjin W, et al. (2018) Is the new distribution of early esophageal adenocarcinoma stages improving the prognostic prediction of the 8th edition of the TNM staging system for esophageal cancer? J Thorac Dis 10(9): 5192-5198.
  27. Hu K, Kang N, Liu Y, Dong Guo, Wang Jing, et al. (2019) Proposed revision of N categories to the 8th edition of the AJCC-TNM staging system for non-surgical esophageal squamous cell cancer. Cancer Sci 110(2): 717-725.
  28. Sudo N, Ichikawa H, Muneoka Y, Takaaki Hanyu, Yosuke Kano, et al. (2021) Clinical Utility of ypTNM Stage Grouping in the 8th Edition of the American Joint Committee on Cancer TNM Staging System for Esophageal Squamous Cell Carcinoma. Ann Surg Oncol 28(2): 650-660.