Literature DB >> 25561761

Comparison of three mathematical prediction models in patients with a solitary pulmonary nodule.

Xuan Zhang1, Hong-Hong Yan1, Jun-Tao Lin1, Ze-Hua Wu1, Jia Liu1, Xu-Wei Cao1, Xue-Ning Yang1.   

Abstract

BACKGROUND: Effective methods for managing patients with solitary pulmonary nodules (SPNs) depend critically on the predictive probability of malignancy.
METHODS: Between July 2009 and June 2011, data on gender, age, cancer history, tumor familial history, smoking status, tumor location, nodule size, spiculation, calcification, the tumor border, and the final pathological diagnosis were collected retrospectively from 154 surgical patients with an SPN measuring 3-30 mm. Each final diagnosis was compared with the probability calculated by three predicted models-the Mayo, VA, and Peking University (PU) models. The accuracy of each model was assessed using area under the receiver operating characteristics (ROC) and calibration curves.
RESULTS: The area under the ROC curve of the PU model [0.800; 95% confidence interval (CI): 0.708-0.891] was higher than that of the Mayo model (0.753; 95% CI: 0.650-0.857) or VA model (0.728; 95% CI: 0.623-0.833); however, this finding was not statistically significant. To varying degrees, calibration curves showed that all three models overestimated malignancy.
CONCLUSIONS: The three predicted models have similar accuracy for prediction of SPN malignancy, although the accuracy is not sufficient. For Chinese patients, the PU model may has greater predictive power.

Entities:  

Keywords:  Solitary pulmonary nodule (SPN); benign and malignant; comparison; model

Year:  2014        PMID: 25561761      PMCID: PMC4279199          DOI: 10.3978/j.issn.1000-9604.2014.11.02

Source DB:  PubMed          Journal:  Chin J Cancer Res        ISSN: 1000-9604            Impact factor:   5.087


  7 in total

Review 1.  Clinical practice. The solitary pulmonary nodule.

Authors:  David Ost; Alan M Fein; Steven H Feinsilver
Journal:  N Engl J Med       Date:  2003-06-19       Impact factor: 91.245

2.  Development and validation of a clinical prediction model to estimate the probability of malignancy in solitary pulmonary nodules in Chinese people.

Authors:  Yun Li; Ke-Zhong Chen; Jun Wang
Journal:  Clin Lung Cancer       Date:  2011-09       Impact factor: 4.785

3.  Existing general population models inaccurately predict lung cancer risk in patients referred for surgical evaluation.

Authors:  James M Isbell; Stephen Deppen; Joe B Putnam; Jonathan C Nesbitt; Eric S Lambright; Aaron Dawes; Pierre P Massion; Theodore Speroff; David R Jones; Eric L Grogan
Journal:  Ann Thorac Surg       Date:  2011-01       Impact factor: 4.330

4.  The probability of malignancy in solitary pulmonary nodules. Application to small radiologically indeterminate nodules.

Authors:  S J Swensen; M D Silverstein; D M Ilstrup; C D Schleck; E S Edell
Journal:  Arch Intern Med       Date:  1997-04-28

5.  Cost-effectiveness of alternative management strategies for patients with solitary pulmonary nodules.

Authors:  Michael K Gould; Gillian D Sanders; Paul G Barnett; Chara E Rydzak; Courtney C Maclean; Mark B McClellan; Douglas K Owens
Journal:  Ann Intern Med       Date:  2003-05-06       Impact factor: 25.391

6.  Validation of two models to estimate the probability of malignancy in patients with solitary pulmonary nodules.

Authors:  E M Schultz; G D Sanders; P R Trotter; E F Patz; G A Silvestri; D K Owens; M K Gould
Journal:  Thorax       Date:  2007-10-26       Impact factor: 9.139

7.  The solitary pulmonary nodule.

Authors:  Bethany B Tan; Kevin R Flaherty; Ella A Kazerooni; Mark D Iannettoni
Journal:  Chest       Date:  2003-01       Impact factor: 9.410

  7 in total
  9 in total

1.  Lo, the ever confounding nipple shadow!

Authors:  W H Boo; Y C Chan
Journal:  Malays Fam Physician       Date:  2020-11-10

2.  Comparison of Veterans Affairs, Mayo, Brock classification models and radiologist diagnosis for classifying the malignancy of pulmonary nodules in Chinese clinical population.

Authors:  Xiaonan Cui; Marjolein A Heuvelmans; Daiwei Han; Yingru Zhao; Shuxuan Fan; Sunyi Zheng; Grigory Sidorenkov; Harry J M Groen; Monique D Dorrius; Matthijs Oudkerk; Geertruida H de Bock; Rozemarijn Vliegenthart; Zhaoxiang Ye
Journal:  Transl Lung Cancer Res       Date:  2019-10

3.  Differential diagnosis of solitary pulmonary nodules with dual-source spiral computed tomography.

Authors:  Zhitao Shi; Yanhui Wang; Xueqi He
Journal:  Exp Ther Med       Date:  2016-07-15       Impact factor: 2.447

4.  Potential Application of Radiomics for Differentiating Solitary Pulmonary Nodules.

Authors:  Kaikai Wei; Huifang Su; Guofeng Zhou; Rong Zhang; Peiqiang Cai; Yi Fan; Chuanmiao Xie; Baowei Fei; Zhenfeng Zhang
Journal:  OMICS J Radiol       Date:  2016-03-21

5.  The Value of a Seven-Autoantibody Panel Combined with the Mayo Model in the Differential Diagnosis of Pulmonary Nodules.

Authors:  Zhougui Ling; Jifei Chen; Zhongwei Wen; Xiaomou Wei; Rui Su; Zhenming Tang; Zhuojun Hu
Journal:  Dis Markers       Date:  2021-02-18       Impact factor: 3.434

Review 6.  [Advances and Clinical Application of Malignant Probability Prediction Models for 
Solitary Pulmonary Nodule].

Authors:  Zhaojue Wang; Jing Zhao; Mengzhao Wang
Journal:  Zhongguo Fei Ai Za Zhi       Date:  2021-08-30

7.  Comprehensive Analysis of Clinical Logistic and Machine Learning-Based Models for the Evaluation of Pulmonary Nodules.

Authors:  Kai Zhang; Zihan Wei; Yuntao Nie; Haifeng Shen; Xin Wang; Jun Wang; Fan Yang; Kezhong Chen
Journal:  JTO Clin Res Rep       Date:  2022-02-22

8.  Value of gadoxetic acid-enhanced MRI for microvascular invasion of small hepatocellular carcinoma: a retrospective study.

Authors:  Meng Zhou; Dan Shan; Chunhui Zhang; Jianhua Nie; Guangyu Wang; Yanqiao Zhang; Yang Zhou; Tongsen Zheng
Journal:  BMC Med Imaging       Date:  2021-03-05       Impact factor: 1.930

9.  Solitary pulmonary nodule malignancy predictive models applicable to routine clinical practice: a systematic review.

Authors:  Marina Senent-Valero; Julián Librero; María Pastor-Valero
Journal:  Syst Rev       Date:  2021-12-06
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.