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Annals of Surgical Oncology

, Volume 24, Issue 6, pp 1551–1556 | Cite as

Defining a New Tumor Dimension in Staging of Papillary Thyroid Carcinoma

  • Ping Wang
  • Yong Wang
  • Chundi Miao
  • Xing Yu
  • Haichao Yan
  • Qiuping Xie
  • Jaiswal Sanjay
  • Qunzi ZhaoEmail author
Endocrine Tumors

Abstract

Background

Cervical lymph node metastasis is a vital factor associated with local recurrence in papillary thyroid carcinoma (PTC). Tumor size is used in the staging of PTC because it represents the tumor load. This study compared two methods of tumor size assessment to predict tumor behavior in the relationship between size and cervical node involvement for patients with PTC.

Methods

The study enrolled 1084 patients who underwent initial thyroid surgery and had a pathologic diagnosis of PTC between 2012 and 2014 at The Second Affiliated Hospital Zhejiang University School of Medicine. Cervical lymph node metastasis (LNM) risk was analyzed according to the clinicopathologic features. For each patient with multifocal disease, two tumor size estimates were used: (1) the dominant focus size and (2) the aggregate size, calculated as the sum of the maximal diameters of all tumor foci.

Results

Of the 1084 patients, 294 (27.1%) had multifocal cancer lesions, and 49% of these patients had cervical LNM, compared with 38.1% who had unifocal disease (P = 0.001). The use of aggregate dimension significantly increased the tumor size and reclassified significant numbers of multifocal PTCs to a more advanced T stage. This aggregate dimension took account of all tumor foci and predicted LNM risk at a proportion identical with that for size-matched, unifocal tumors.

Conclusion

Multifocality together with aggregate tumor size is a more accurate predictor of node status and, by inference, tumor behavior in the relationship between tumor size and cervical node involvement.

Keywords

Papillary Thyroid Carcinoma Cervical Lymph Node Metastasis Tumor Focus Multifocal Tumor Central Neck Dissection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgment

This study was supported by the Clinical Study Foundation of Zhejiang Province, China (2013ZYC-A20).

Disclosure

The authors have nothing to declare.

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Copyright information

© Society of Surgical Oncology 2017

Authors and Affiliations

  • Ping Wang
    • 1
  • Yong Wang
    • 1
  • Chundi Miao
    • 2
  • Xing Yu
    • 2
  • Haichao Yan
    • 1
  • Qiuping Xie
    • 1
  • Jaiswal Sanjay
    • 2
  • Qunzi Zhao
    • 1
    Email author
  1. 1.Department of SurgeryThe Second Affiliated Hospital of Zhejiang University School of MedicineHangzhouChina
  2. 2.Department of Clinical MedicineZhejiang University School of MedicineHangzhouChina

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