Frontiers in Oncology (Nov 2021)

The Combination of T Stage and the Number of Pathologic Lymph Nodes Provides Better Prognostic Discrimination in Early-Stage Cervical Cancer With Lymph Node Involvement

  • Yongrui Bai,
  • Ling Rong,
  • Bin Hu,
  • Xiumei Ma,
  • Jiahui Wang,
  • Haiyan Chen

DOI
https://doi.org/10.3389/fonc.2021.764065
Journal volume & issue
Vol. 11

Abstract

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ObjectiveStage I and II cervical cancer with pelvic and/or para-aortic lymph node (LN) metastases are upstaged to stage IIIC under the new FIGO 2018 staging system, and radical chemoradiotherapy was recommended. But heterogeneity in outcome existed in this group of patients. We conducted this retrospective analysis to evaluate the heterogeneity of these patients and tried to provide a more detailed classification to reflect the prognosis and guide the treatment. We also evaluated the efficacy and toxicity of surgery followed by sequential chemoradiotherapy in this cohort.MethodsEarly-stage cervical cancer with LN involvement that had radical hysterectomy followed by sequential chemoradiotherapy were retrospectively analyzed. Survival analyses were conducted to identify the prognostic factors.ResultsA total of 242 patients were included in the study; 64 (26.4%) patients had treatment failure, and 51 (21.1%) died. Pathology, T stage, the number of pathologic LN (pLN), and neoadjuvant chemotherapy or not were independent prognostic factors for disease-free survival and overall survival (OS). Patients with T1N < 3 pLN had significantly better survival than T2N < 3 pLN/T1-2 N≥ 3 pLN, with failure rates of 11.6% and 35.8% in each group; and 5 year OS was 92% and 62%, respectively (P = 0.000). About 1.5% of the patients discontinued radiotherapy, and 14.1% had G3-4 hematological toxic effects during radiotherapy; 1.7% developed G2-3 lower limb edema, and 2.9% developed severe urinary toxicity.ConclusionNodal involvement alone is inadequate as the sole pathologic factor to predict survival in early-stage cervical cancer. The combination of tumor and node subcategory provides better prognostic discrimination.

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