Cancer Res Treat.  2020 Jan;52(1):320-333. 10.4143/crt.2019.124.

Prognostic Model for Survival and Recurrence in Patients with Early-Stage Cervical Cancer: A Korean Gynecologic Oncology Group Study (KGOG 1028)

• Paik ES
• Lim MC
• Kim MH
• Kim YH
• Song ES
• Seong SJ
• Suh DH
• Lee JM
• Lee C
• Choi CH

• KMID: 2501224
• DOI: http://doi.org/10.4143/crt.2019.124

Abstract

Purpose
We aimed to develop and validate individual prognostic models in a large cohort of cervical cancer patients that were primarily treated with radical hysterectomy.
Materials and Methods
We analyzed 1,441 patients with early-stage cervical cancer treated between 2000 and 2008 from the Korean Gynecologic Oncology Group multi-institutional cohort: a train cohort (n=788) and a test cohort (n=653). Models predicting the risk for overall survival (OS), disease- free survival (DFS), lymphatic recurrence and hematogenous recurrence were developed using Cox analysis and stepwise backward selection and best-model options. The prognostic performance of each model was assessed in an independent patient cohort. Model-classified risk groups were compared to groups based on traditional risk factors.
Results
Independent risk factors for OS, DFS, lymphatic recurrence, and hematogenous recurrence were identified for prediction model development. Different combinations of risk factors were shown for each outcome with best predictive value. In train cohort, area under the curve (AUC) at 2 and 5 years were 0.842/0.836 for recurrence, and 0.939/0.882 for OS. When applied to a test cohort, the model also showed accurate prediction result (AUC at 2 and 5 years were 0.799/0.723 for recurrence, and 0.844/0.806 for OS, respectively). The Kaplan-Meier plot by proposed model-classified risk groups showed more distinctive survival differences between each risk group.
Conclusion
We developed prognostic models for OS, DFS, lymphatic and hematogenous recurrence in patients with early-stage cervical cancer. Combining weighted clinicopathologic factors, the proposed model can give more individualized predictions in clinical practice.

Keyword

Disease-free survival; Prognostic factor; Prognoses; Survival analyses; Uterine cervical neoplasms

Figure

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  Fig. 1. Flowchart of included patients. SMC, Samsung Medical Center; ROC, receiver operating characteristic.

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  Fig. 2. Survival comparison of train and test cohort.

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  Fig. 3. Stepwise Cox proportional hazards regression analysis for disease-free survival (A), overall survival (B), lymphatic recurrence (C), and hematogenous recurrence (D) for prognostic model. HR, hazard ratio; CI, confidence interval; LN, lymph node; AD, adenocarcinoma; LVSI, lymphovascular space invasion; DI, depth of invasion; PMI, parametrial invasion; BMI, body mass index; SCC Ag, SCC, squamous cell carcinoma antigen. *p < 0.05, **p < 0.01, ***p < 0.001.

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  Fig. 4. (A) Histogram showing significance of risk factors for disease-free survival (DFS), hematogenous recurrence, lymphatic recurrence, and overall survival (OS). (B) Histogram showing significance of risk factors by histologic type. LN, lymph node; SCC, squamous cell carcinoma; DM, diabetes mellitus; LVSI, lymphovascular space invasion; BMI, body mass index; AD, adenocarcinoma.

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  Fig. 5. Validation of the model predicting disease-free survival (DFS) (A), hematogenous recurrence (B), lymphatic recurrence (C), and overall survival (OS) (D).

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  Fig. 6. Time-dependent receiver operating characteristic curves of the prediction model for disease-free survival (DFS), hematogenous recurrence, lymphatic recurrence, and overall survival (OS) (A, at 2 years; B, at 5 years). Red line indicates train cohort, and blue line indicates test cohort. AUC, area under the curve.

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  Fig. 7. Comparison of traditional risk groups and proposed model-classified risk groups and their prognostic significance. (A) Box plot of risk score according to traditional risk assessment. (B) Kaplan-Meier survival according to traditional risk groups. (C) Kaplan-Meier curve according to proposed model-classified risk groups. OS, overall survival; DFS, disease-free survival.

Reference

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