title: A predictive nomogram improved diagnostic accuracy and interobserver agreement of perirectal lymph nodes metastases in rectal cancer.
abstract: OBJECTIVE
  To develop a predictive nomogram to improve the diagnostic accuracy and interobserver agreement of pre-therapeutic lymph nodes metastases in patients with rectal cancer.
  
  
  METHODS
  An institutional database of 411 patients with rectal cancer was used to develop a nomogram to predict perirectal lymph nodes metastases. Patients' clinicopathological and MRI-assessed imaging variables were included in the multivariate logistic regression analysis. The model was externally validated and the performance was assessed by area under curve (AUC) of the receiver operator characteristics (ROC) curves. The interobserver agreement was measured between two independent radiologists.
  
  
  RESULTS
  The diagnostic accuracy of the conventional MRI-assessed cN stage was 68%; 14.2% of the patients were over-staged and 17.8% of the patients were under-staged. A total of 35.1% of the patients had disagreed diagnosis for the cN stage between the two radiologists, with a kappa value of 0.295. A nomogram for predicting pathological lymph nodes metastases was successfully developed, with an AUC of 0.78 on the training data and 0.71 on the validation data. The predictors included in the nomogram were MRI cT stage, CRM involvement, preoperative CEA, tumor grade and lymph node size category. This nomogram yielded improved prediction in cN stage than the conventional MRI-based assessment.
  
  
  CONCLUSIONS
  By incorporating clinicopathological and MRI imaging features, we established a nomogram that improved the diagnostic accuracy and remarkably minimized the interobserver disagreement in predicting lymph nodes metastases in rectal cancers.
authors.affiliation: Institute of Health Sciences, Shanghai Jiao Tong University School of Medicine (SJTUSM) and Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai, China.
authors.forename: Yongfeng
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Department of Colorectal Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.|Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
authors.forename: Renjie
authors.initials: R
authors.lastname: Wang
authors.affiliation: Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: Ying
authors.initials: Y
authors.lastname: Ding
authors.affiliation: Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: Shanshan
authors.initials: S
authors.lastname: Tu
authors.affiliation: Department of Statistics, Ohio State University, Columbus, OH, USA.
authors.forename: Yi
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Institute of Health Sciences, Shanghai Jiao Tong University School of Medicine (SJTUSM) and Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai, China.
authors.forename: Youcun
authors.initials: Y
authors.lastname: Qian
authors.affiliation: Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.|Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.
authors.forename: Linghui
authors.initials: L
authors.lastname: Xu
authors.affiliation: Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.|Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.
authors.forename: Tong
authors.initials: T
authors.lastname: Tong
authors.affiliation: Department of Colorectal Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.|Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
authors.forename: Sanjun
authors.initials: S
authors.lastname: Cai
authors.affiliation: Department of Colorectal Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.|Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
authors.forename: Junjie
authors.initials: J
authors.lastname: Peng
mesh_terms: D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008198:Lymph Nodes / Q000473:pathology / Q000601:surgery; D008207:Lymphatic Metastasis; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D060787:Neoplasm Grading; D009367:Neoplasm Staging; D049451:Nomograms; D015588:Observer Variation; D011237:Predictive Value of Tests; D012372:ROC Curve; D012004:Rectal Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000601:surgery; D021701:Sentinel Lymph Node Biopsy
keywords: MRI; lymph node; metastases; nomogram; rectal cancer