Cancer Research and Treatment

Original Articles

Prognostic Model for Survival and Recurrence in Patients with Early-Stage Cervical Cancer: A Korean Gynecologic Oncology Group Study (KGOG 1028): E Sun Paik, Myong Cheol Lim, Moon-Hong Kim, Yun Hwan Kim, Eun Seop Song, Seok Ju Seong, Dong Hoon Suh, Jong-Min Lee, Chulmin Lee, Chel Hun Choi; Cancer Res Treat. 2020;52(1):320-333. Published online August 5, 2019; DOI: https://doi.org/10.4143/crt.2019.124

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.

Citations

Citations to this article as recorded by

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Which factors predict the effectiveness of adjuvant treatment in patients with non-high-risk early-stage cervical cancer? Ancillary analysis of KGOG-1028
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Oncologic outcomes of minimally invasive surgery vs. abdominal hysterectomy in patients with low-risk, early-stage cervical cancer: A retrospective analysis of KGOG 1028 data based on SHAPE trial eligibility criteria
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Profiling of Serum Metabolites Using MALDI-TOF and Triple-TOF Mass Spectrometry to Develop a Screen for Ovarian Cancer: Jun Hwa Lee, Yun Hwan Kim, Kyung-Hee Kim, Jae Youl Cho, Sang Myung Woo, Byong Chul Yoo, Seung Cheol Kim; Cancer Res Treat. 2018;50(3):883-893. Published online September 18, 2017; DOI: https://doi.org/10.4143/crt.2017.275

Abstract PDF Supplementary Material PubReader ePub

Purpose
We sought to develop a matrix assisted laser desorption ionization-time of flight (MALDI-TOF)-based, ovarian cancer (OVC), low-mass-ion discriminant equation (LOME) and to evaluate a possible supportive role for triple-TOF mass analysis in identifying metabolic biomarkers.
Materials and Methods
A total of 114 serum samples from patients with OVC and benign ovarian tumors were subjected to MALDI-TOF analysis and a total of 137 serum samples from healthy female individuals and patients with OVC, colorectal cancer, hepatobiliary cancer, and pancreatic cancer were subjected to triple-TOF analysis. An OVC LOME was constructed by reference to the peak intensity ratios of discriminatory low-mass ion (LMI) pairs. Triple-TOF analysiswas used to select and identify metabolic biomarkers for OVC screening.
Results
Three OVC LOMEs were finally constructed using discriminatory LMI pairs (137.1690 and 84.4119 m/z; 496.5022 and 709.7642 m/z; and 524.5614 and 709.7642 m/z); all afforded accuracies of > 90%. The LMIs at 496.5022 m/z and 524.5614 m/z were those of lysophosphatidylcholine (LPC) 16:0 and LPC 18:0. Triple-TOF analysis selected seven discriminative LMIs; each LMI had a specificity > 90%. Of the seven LMIs, fourwith a 137.0455 m/z ion atretention times of 2.04-3.14 minuteswere upregulated in sera from OVC patients; the ion was identified as that derived from hypoxanthine.
Conclusion
MALDI-TOF–based OVC LOMEs combined with triple-TOF–based OVC metabolic biomarkers allow reliable OVC screening; the techniques are mutually complementary both quantitatively and qualitatively.

Citations

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