期刊
GYNECOLOGIC ONCOLOGY
卷 159, 期 1, 页码 157-163出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ygyno.2020.07.030
关键词
Cervical cancer; Tumor budding; Intermediate-risk; Prognosis
资金
- Biomedical Research Institute grant, Kyungpook National University Hospital (2020)
Objective. To evaluate the prognostic value and its possible role as an additional intermediate-risk factor of tumor budding (TB) in cervical cancer following radical hysterectomy. Methods. In total, 136 patients with cervical cancer who underwent radical hysterectomy with pelvic and/or paraaortic lymphadenectomy were included. We assessed the status of TB in available hematoxylin and eosinstained specimens. Univariate and multivariate analyses for predicting tumor recurrence and death were performed using TB and other clinicopathologic parameters. To evaluate additional intermediate-risk factors of TB. patients who had at least one high-risk factor were excluded, and a total of 81 patients were included. We added TB to three conventional intermediate-risk models and compared their performance with new and conventional models using the log-rank test and receiver operating characteristic analysis. Results. High TB was defined as >= 5 per high-power field for disease-free survival and >= 8 per high-power field for overall survival. Multivariate analysis revealed that high TB was an independent prognostic factor for predicting overall survival (hazard ratio, 4.96; 95% confidence intervals, 1.06-23.29; p = .0423). The addition of TB to the conventional intermediate-risk models improved the accuracy of recurrence prediction. Among the risk models, the new model using at least two risk factors, including tumor size (>= 4 cm), deep stromal invasion (outer one-third of entire cervical thickness), lymphovascular invasion, and high TB, was the most accurate for predicting tumor recurrence (area under the curve, 0.708, hazard ratio, 4.25; p = .0231). Conclusion. High TB may be a prognostic biomarker of cervical cancer. Moreover, the addition of TB to the conventional intermediate-risk models improves the stratification of tumor recurrence. (C) 2020 Published by Elsevier Inc.
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