Preoperative nomogram for the identification of lymph node metastasis in early cervical cancer.
BACKGROUND
The objective of this study is to construct a preoperative nomogram predicting lymph node metastasis (LNM) in early-cervical cancer patients.


METHODS
Between 2009 and 2012, 493 early-cervical cancer patients received hysterectomy and pelvic/para-aortic lymphadenectomy. Patients who were diagnosed during 2009-2010 were assigned to a model-development cohort (n=304) and the others were assigned to a validation cohort (n=189). A multivariate logistic model was created from preoperative clinicopathologic data, from which a nomogram was developed and validated. A predicted probability of LNM<5% was defined as low risk.


RESULTS
Age, tumour size assessed by magnetic resonance imaging, and LNM assessed by positron emission tomography/computed tomography were independent predictors of nodal metastasis. The nomogram incorporating these three predictors demonstrated good discrimination and calibration (concordance index=0.878; 95% confidence interval (CI), 0.833-0.917). In the validation cohort, the discrimination accuracy was 0.825 (95% CI, 0.736-0.895). In the model-development cohort, 34% of them were classified as low risk and negative predictive value (NPV) was 99.0%. In the validation cohort, 38% were identified as low risk and NPV was 95.8%. Integrating the model-development and validation cohorts, negative likelihood ratio was 0.094 (95% CI, 0.036-0.248).


CONCLUSIONS
A robust nomogram predicting LNM in early cervical cancer was developed. This model may improve clinical trial design and help physicians to decide whether lymphadenectomy should be performed.
Department of Obstetrics and Gynecology, University of Ulsan College of Medicine, Asan Medical Center, 388-1, Pungnap-dong, Songpa-gu, Seoul 138-736, Korea.
D-Y
DY
Kim
Department of Obstetrics and Gynecology, Konkuk University School of Medicine, 1 Hwayang-dong, Gwangjin-gu, Seoul 143-701, Korea.
S-H
SH
Shim
Department of Clinical Epidemiology and Biostatistics, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
S-O
SO
Kim
Department of Obstetrics and Gynecology, University of Ulsan College of Medicine, Asan Medical Center, 388-1, Pungnap-dong, Songpa-gu, Seoul 138-736, Korea.
S-W
SW
Lee
Department of Obstetrics and Gynecology, University of Ulsan College of Medicine, Asan Medical Center, 388-1, Pungnap-dong, Songpa-gu, Seoul 138-736, Korea.
J-Y
JY
Park
Department of Obstetrics and Gynecology, University of Ulsan College of Medicine, Asan Medical Center, 388-1, Pungnap-dong, Songpa-gu, Seoul 138-736, Korea.
D-S
DS
Suh
Department of Obstetrics and Gynecology, University of Ulsan College of Medicine, Asan Medical Center, 388-1, Pungnap-dong, Songpa-gu, Seoul 138-736, Korea.
J-H
JH
Kim
Department of Obstetrics and Gynecology, University of Ulsan College of Medicine, Asan Medical Center, 388-1, Pungnap-dong, Songpa-gu, Seoul 138-736, Korea.
Y-M
YM
Kim
Department of Obstetrics and Gynecology, University of Ulsan College of Medicine, Asan Medical Center, 388-1, Pungnap-dong, Songpa-gu, Seoul 138-736, Korea.
Y-T
YT
Kim
Department of Obstetrics and Gynecology, University of Ulsan College of Medicine, Asan Medical Center, 388-1, Pungnap-dong, Songpa-gu, Seoul 138-736, Korea.
J-H
JH
Nam
D000328:Adult; D000368:Aged; D015331:Cohort Studies; D005260:Female; D006801:Humans; D016015:Logistic Models; D008198:Lymph Nodes / Q000473:pathology* / Q000601:surgery; D008207:Lymphatic Metastasis; D008279:Magnetic Resonance Imaging; D008875:Middle Aged; D064847:Multimodal Imaging; D015999:Multivariate Analysis; D009367:Neoplasm Staging; D049451:Nomograms; D049268:Positron-Emission Tomography; D011237:Predictive Value of Tests; D002583:Uterine Cervical Neoplasms / Q000473:pathology* / Q000601:surgery; D055815:Young Adult