Prediction model for para-aortic lymph node metastasis in patients with locally advanced cervical cancer

• Published in: Gynecologic oncology Vol. 144; no. 1; pp. 40 - 45
• Main Authors: Shim, Seung-Hyuk, MD, Kim, Dae-Yeon, MD, PhD, Lee, Sun Joo, MD, PhD, Kim, Soo-Nyung, MD, PhD, Kang, Soon-Beom, MD, PhD, Lee, Shin-Wha, MD, PhD, Park, Jeong-Yeol, MD, PhD, Suh, Dae-Shik, MD, PhD, Kim, Jong-Hyeok, MD, PhD, Kim, Yong-Man, MD, PhD, Kim, Young-Tak, MD, PhD, Nam, Joo-Hyun, MD, PhD
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.01.2017
• Subjects: Adult; Aged; Aorta; Carcinoma - diagnostic imaging; Carcinoma - secondary; Cervical cancer; Female; Hematology, Oncology and Palliative Medicine; Humans; Likelihood Functions; Logistic Models; Lymph Node Excision; Lymph Nodes - diagnostic imaging; Lymph Nodes - pathology; Lymphatic Metastasis; Magnetic Resonance Imaging; Middle Aged; Morbidity; Obstetrics and Gynecology; Pelvis; Positron Emission Tomography Computed Tomography; Predictive Value of Tests; Retrospective Studies; Risk Assessment - methods; Tumor Burden; Uterine Cervical Neoplasms - diagnostic imaging; Uterine Cervical Neoplasms - pathology; Lymphatic metastasis; Likelihood functions; Cervical cancer; Lymph node excision; Morbidity
• DOI: 10.1016/j.ygyno.2016.11.011
• ISSN: 0090-8258

Abstract Objective Concurrent chemoradiotherapy is usually administered to patients with locally advanced cervical cancer (LACC). Extended-field chemoradiotherapy is required if para-aortic lymph node (PALN) metastasis is detected. This study aimed to construct a prediction model for PALN metastasis in patients with LACC before definitive treatment. Methods Between 2009 and 2016, all consecutive patients with LACC who underwent para-aortic lymphadenectomy at two tertiary centers were retrospectively analyzed. A multivariate logistic model was constructed, from which a prediction model for PALN metastasis was developed and internally validated. Before analysis, risk grouping was predefined based on the likelihood ratio. Results In total, 245 patients satisfied the eligibility criteria. Thirty-four patients (13.9%) had pathologically proven PALN metastases. Additionally, 16/222 (7.2%) patients with negative PALNs on positron emission tomography/computed tomography (PET/CT) had PALN metastasis. Moreover, 11/105 (10.5%) patients with both negative PALNs and positive pelvic lymph nodes on PET/CT had PALN metastasis. Tumor size on magnetic resonance imaging and PALN status on PET/CT were independent predictors of PALN metastasis. The model incorporating these two predictors displayed good discrimination and calibration (bootstrap-corrected concordance index = 0.886; 95% confidence interval = 0.825–0.947). The model categorized 169 (69%), 52 (22%), and 23 (9%) patients into low-, intermediate-, and high-risk groups, respectively. The predicted probabilities of PALN metastasis for these groups were 2.9, 20.8, and 76.2%, respectively. Conclusion We constructed a robust model predicting PALN metastasis in patients with LACC that may improve clinical trial design and help clinicians determine whether nodal-staging surgery should be performed.