Clinical utility of pretreatment serum squamous cell carcinoma antigen for prognostication and decision-making in patients with early-stage cervical cancer

Author:

Huang Xiao-Dan1,Huo Lan-Qing1,Luo Ying-Shan2,Chen Kai1,Li Jun-Yun1,Shi Liu1,Huang Lin1,Cao Xin-Ping1,Ou-Yang Yi1,Chen Fo-Ping3

Affiliation:

1. Department of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China

2. Department of Radiation Oncology, Guangzhou Concord Cancer Center, Guangzhou, Guangdong, China

3. Department of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, No. 651 Dongfeng Eastern Road, Guangzhou, Guangdong 510060, China

Abstract

Background: To investigate the prognostic role of pretreatment squamous cell carcinoma antigen (SCCA) in early-stage cervical cancer (CC). Methods: We enrolled 487 cases of pathology-proven early-stage [International Federation of Gynecology and Obstetrics (FIGO) I/II] squamous or adenosquamous CC that were treated from 2012 to 2015. Restricted cubic splines (RCS) with a full Cox regression model were used to evaluate the association between SCCA levels and survival outcomes. Recursive partitioning analysis (RPA) was used to construct a risk stratification model for overall survival (OS). The performance of the RPA-based model was assessed using a receiver operating characteristic (ROC) curve. Results: RCS analysis revealed an association between SCCA and OS and disease-free survival (DFS); SCCA ⩾2.5 ng/mL was robust for risk discrimination in our cohort. SCCA had an interaction effect with FIGO classification: Patients with FIGO I and SCCA ⩾2.5 ng/mL overlapped with those with FIGO II and SCCA < 2.5 ng/mL for OS [hazard ratio, 1.04 (95% confidence interval (CI): 0.49–2.24), p = 0.903] and DFS [1.05 (0.56–1.98), p = 0.876]. RPA modeling incorporating SCCA (<2.5 ng/mL and ⩾2.5 ng/mL) and FIGO classification divided CC into three prognostic groups: RPA I, FIGO stage I, and SCCA < 2.5 ng/mL; RPA II, FIGO stage I, and SCCA ⩾ 2.5 ng/mL, or FIGO stage II and SCCA < 2.5 ng/mL; and RPA III, FIGO stage II, and SCCA ⩾ 2.5 ng/mL; with 5-year OS of 94.0%, 85.1%, and 73.5%, respectively ( p < 0.001). ROC analysis confirmed that the RPA model outperformed the FIGO 2018 stage with significantly improved accuracy for survival prediction [area under the curve: RPA versus FIGO, 0.663 (95% CI: 0.619–0.705] versus 0.621 (0.576–0.664), p = 0.045]. Importantly, the RPA groupings were associated with the efficacy of treatment regimens. Surgery followed by adjuvant treatment had a higher OS ( p < 0.01) and DFS ( p = 0.024) than other treatments for RPA III, whereas outcomes were comparable among treatment regimens for RPA I–II. Conclusion: Herein, the role of SCCA for prognostication was confirmed, and a robust clinicomolecular risk stratification system that outperforms conventional FIGO classification in early-stage squamous and adenosquamous CC was presented. The model correlated with the efficacy of different treatment regimes.

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

SAGE Publications

Subject

Oncology

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