Development and validation of a nomogram to estimate the pretest probability of cancer in Chinese patients with solid solitary pulmonary nodules: A multi-institutional study

Yunlang She, Lilan Zhao, Chenyang Dai, Yijiu Ren, Gening Jiang, Huikang Xie, Huiyuan Zhu, Xiwen Sun, Ping Yang, Yongbing Chen, Shunbin Shi, Weirong Shi, Bing Yu, Dong Xie, Chang Chen

Research output: Contribution to journalArticle

7 Scopus citations


Objectives: To develop and validate a nomogram to estimate the pretest probability of malignancy in Chinese patients with solid solitary pulmonary nodule (SPN). Materials and Methods: A primary cohort of 1798 patients with pathologically confirmed solid SPNs after surgery was retrospectively studied at five institutions from January 2014 to December 2015. A nomogram based on independent prediction factors of malignant solid SPN was developed. Predictive performance also was evaluated using the calibration curve and the area under the receiver operating characteristic curve (AUC). Results: The mean age of the cohort was 58.9±10.7 years. In univariate and multivariate analysis, age; history of cancer; the log base 10 transformations of serum carcinoembryonic antigen value; nodule diameter; the presence of spiculation, pleural indentation, and calcification remained the predictive factors of malignancy. A nomogram was developed, and the AUC value (0.85; 95%CI, 0.83-0.88) was significantly higher than other three models. The calibration cure showed optimal agreement between the malignant probability as predicted by nomogram and the actual probability. Conclusions: We developed and validated a nomogram that can estimate the pretest probability of malignant solid SPNs, which can assist clinical physicians to select and interpret the results of subsequent diagnostic tests.

Original languageEnglish (US)
JournalJournal of Surgical Oncology
StateAccepted/In press - 2017



  • Lung cancer
  • Nomogram
  • Risk prediction
  • Solitary pulmonary nodule

ASJC Scopus subject areas

  • Surgery
  • Oncology

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