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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
Author(s) -
She Yunlang,
Zhao Lilan,
Dai Chenyang,
Ren Yijiu,
Jiang Gening,
Xie Huikang,
Zhu Huiyuan,
Sun Xiwen,
Yang Ping,
Chen Yongbing,
Shi Shunbin,
Shi Weirong,
Yu Bing,
Xie Dong,
Chen Chang
Publication year - 2017
Publication title -
journal of surgical oncology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.201
H-Index - 111
eISSN - 1096-9098
pISSN - 0022-4790
DOI - 10.1002/jso.24704
Subject(s) - nomogram , medicine , malignancy , univariate , carcinoembryonic antigen , radiology , receiver operating characteristic , solitary pulmonary nodule , univariate analysis , nodule (geology) , lung cancer , pre and post test probability , multivariate analysis , cancer , nuclear medicine , multivariate statistics , statistics , mathematics , paleontology , computed tomography , biology
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.

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