Literature DB >> 28570780

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 She1, Lilan Zhao1, Chenyang Dai1, Yijiu Ren1, Gening Jiang1, Huikang Xie2, Huiyuan Zhu3, Xiwen Sun3, Ping Yang4, Yongbing Chen5, Shunbin Shi6, Weirong Shi7, Bing Yu8, Dong Xie1, Chang Chen1.   

Abstract

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.
© 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  lung cancer; nomogram; risk prediction; solitary pulmonary nodule

Mesh:

Year:  2017        PMID: 28570780     DOI: 10.1002/jso.24704

Source DB:  PubMed          Journal:  J Surg Oncol        ISSN: 0022-4790            Impact factor:   3.454


  16 in total

1.  Developing of risk models for small solid and subsolid pulmonary nodules based on clinical and quantitative radiomics features.

Authors:  Rui Zhang; Huaiqiang Sun; Bojiang Chen; Renjie Xu; Weimin Li
Journal:  J Thorac Dis       Date:  2021-07       Impact factor: 2.895

2.  Development and validation of a predictive model for the diagnosis of solid solitary pulmonary nodules using data mining methods.

Authors:  Yangwei Xiang; Yifeng Sun; Yuan Liu; Baohui Han; Qunhui Chen; Xiaodan Ye; Li Zhu; Wen Gao; Wentao Fang
Journal:  J Thorac Dis       Date:  2019-03       Impact factor: 2.895

3.  Risk of second primary malignancy after non-small cell lung cancer: a competing risk nomogram based on the SEER database.

Authors:  Huaqiang Zhou; Jiayi Shen; Yaxiong Zhang; Yan Huang; Wenfeng Fang; Yunpeng Yang; Shaodong Hong; Jiaqing Liu; Wei Xian; Zhonghan Zhang; Yuxiang Ma; Ting Zhou; Hongyun Zhao; Li Zhang
Journal:  Ann Transl Med       Date:  2019-09

4.  Predicting Lung Cancer Risk of Incidental Solid and Subsolid Pulmonary Nodules in Different Sizes.

Authors:  Rui Zhang; Panwen Tian; Bojiang Chen; Yongzhao Zhou; Weimin Li
Journal:  Cancer Manag Res       Date:  2020-09-04       Impact factor: 3.989

5.  Value of folate receptor-positive circulating tumour cells in the clinical management of indeterminate lung nodules: A non-invasive biomarker for predicting malignancy and tumour invasiveness.

Authors:  Qianjun Zhou; Qing Geng; Lin Wang; Jia Huang; Meilin Liao; Yan Li; Zhengping Ding; Shentu Yang; Hang Zhao; Qiang Shen; Changqing Pan; Jiatao Lou; Shun Lu; Chang Chen; Qingquan Luo
Journal:  EBioMedicine       Date:  2019-03-12       Impact factor: 8.143

6.  Nomogram For The Prediction Of Malignancy In Small (8-20 mm) Indeterminate Solid Solitary Pulmonary Nodules In Chinese Populations.

Authors:  Xiao-Bo Chen; Rui-Ying Yan; Ke Zhao; Da-Fu Zhang; Ya-Jun Li; Lin Wu; Xing-Xiang Dong; Ying Chen; De-Pei Gao; Ying-Ying Ding; Xi-Cai Wang; Zhen-Hui Li
Journal:  Cancer Manag Res       Date:  2019-11-06       Impact factor: 3.989

7.  Comparison of Radiomic Models Based on Low-Dose and Standard-Dose CT for Prediction of Adenocarcinomas and Benign Lesions in Solid Pulmonary Nodules.

Authors:  Jieke Liu; Hao Xu; Haomiao Qing; Yong Li; Xi Yang; Changjiu He; Jing Ren; Peng Zhou
Journal:  Front Oncol       Date:  2021-02-02       Impact factor: 6.244

8.  Convolutional Neural Network-Based Diagnostic Model for a Solid, Indeterminate Solitary Pulmonary Nodule or Mass on Computed Tomography.

Authors:  Ke Sun; Shouyu Chen; Jiabi Zhao; Bin Wang; Yang Yang; Yin Wang; Chunyan Wu; Xiwen Sun
Journal:  Front Oncol       Date:  2021-12-21       Impact factor: 6.244

9.  Clinical-radiological predictive model in differential diagnosis of small (≤ 20 mm) solitary pulmonary nodules.

Authors:  Hai-Cheng Zhao; Qing-Song Xu; Yi-Bing Shi; Xi-Juan Ma
Journal:  BMC Pulm Med       Date:  2021-09-05       Impact factor: 3.317

10.  Development and validation of a prediction model for malignant pulmonary nodules: A cohort study.

Authors:  Zhen Ren; Hongmei Ding; Zhenzhen Cai; Yuan Mu; Lin Wang; Shiyang Pan
Journal:  Medicine (Baltimore)       Date:  2021-12-23       Impact factor: 1.817

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