Analysis and validation of probabilistic models for predicting malignancy in solitary pulmonary nodules in a population in Brazil

被引:0
|
作者
de Carvalho Melo, Cromwell Barbosa [1 ]
Juliano Perfeito, Joao Alessi
Daud, Danilo Felix [1 ]
Costa Junior, Altair da Silva [1 ]
Santoro, Ilka Lopes
Villaca Leao, Luiz Eduardo
机构
[1] Univ Fed Sao Paulo, Hosp Sao Paulo, Escola Paulista Med, UNIFESP, Sao Paulo, Brazil
关键词
Solitary Pulmonary Nodule; Risk Factors; Carcinoma; Non-Small-Cell Lung; LUNG-CANCER; MANAGEMENT; CT; GUIDELINES; SCANS;
D O I
暂无
中图分类号
R56 [呼吸系及胸部疾病];
学科分类号
摘要
Objective: To analyze clinical and radiographic findings that influence the pathological diagnosis of solitary pulmonary nodule (SPN) and to compare/validate two probabilistic models for predicting SPN malignancy in patients with SPN in Brazil. Methods: This was a retrospective study involving 110 patients diagnosed with SPN and submitted to resection of SPN at a tertiary hospital between 2000 and 2009. The clinical characteristics studied were gender, age, presence of systemic comorbidities, history of malignancy prior to the diagnosis of SPN, histopathological diagnosis of SPN, smoking status, smoking history, and time since smoking cessation. The radiological characteristics studied, in relation to the SPN, were presence of spiculated margins, maximum transverse diameter, and anatomical location. Two mathematical models, created in 1997 and 2007, respectively, were used in order to determine the probability of SPN malignancy. Results: We found that SPN malignancy was significantly associated with age (p = 0.006; OR = 5.70 for age > 70 years), spiculated margins (p = 0.001), and maximum diameter of SPN (p = 0.001; OR = 2.62 for diameters > 20 mm). The probabilistic model created in 1997 proved to be superior to that created in 2007 area under the ROC curve (AUC), 0.79 +/- 0.44 (95% Cl: 0.70-0.88) vs. 0.69 +/- 0.50 (95% Cl: 0.59-0.79). Conclusions: Advanced age, greater maximum SPN diameter, and spiculated margins were significantly associated with the diagnosis of SPN malignancy. Our analysis shows that, although both mathematical models were effective in determining SPN malignancy in our population, the 1997 model was superior.
引用
收藏
页码:559 / 565
页数:7
相关论文
共 50 条
  • [21] Establishment and validation of a prediction model for the probability of malignancy in solid solitary pulmonary nodules in northwest China
    Duan, Xue-Qin
    Wang, Xiao-Li
    Zhang, Li-Fen
    Liu, Xi-Zhi
    Zhang, Wen-Wen
    Liu, Yi-Hui
    Dong, Chun-Hui
    Zhao, Xin-Han
    Chen, Ling
    JOURNAL OF SURGICAL ONCOLOGY, 2021, 123 (04) : 1134 - 1143
  • [22] Predictors of malignancy in patients with solitary pulmonary nodules undergoing pulmonary resection
    Erdogdu, Eren
    Ozkan, Berker
    Duman, Salih
    Agkoc, Melek
    Erturk, Sukru Mehmet
    Kara, Murat
    Toker, Alper
    CLINICAL RESPIRATORY JOURNAL, 2022, 16 (05): : 361 - 368
  • [23] The probability of malignancy in solitary pulmonary nodules - Application to small radiologically indeterminate nodules
    Swensen, SJ
    Silverstein, MD
    Ilstrup, DM
    Schleck, CD
    Edell, ES
    ARCHIVES OF INTERNAL MEDICINE, 1997, 157 (08) : 849 - 855
  • [24] The study of plain CT combined with contrast-enhanced CT-based models in predicting malignancy of solitary solid pulmonary nodules
    Zhang, Wenjia
    Cui, Xiaonan
    Wang, Jing
    Cui, Sha
    Yang, Jianghua
    Meng, Junjie
    Zhu, Weijie
    Li, Zhiqi
    Niu, Jinliang
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [25] Development and Validation of a Clinical Prediction Model to Estimate the Probability of Malignancy in Solitary Pulmonary Nodules in Chinese People
    Li, Yun
    Chen, Ke-Zhong
    Wang, Jun
    CLINICAL LUNG CANCER, 2011, 12 (05) : 313 - 319
  • [26] Computerized analysis of the likelihood of malignancy in solitary pulmonary nodules with use of artificial neural networks
    Nakamura, K
    Yoshida, H
    Engelmann, R
    MacMahon, H
    Katsuragawa, S
    Ishida, T
    Ashizawa, A
    Doi, K
    RADIOLOGY, 2000, 214 (03) : 823 - 830
  • [27] DETERMINING THE LIKELIHOOD OF MALIGNANCY IN SOLITARY PULMONARY NODULES WITH BAYESIAN-ANALYSIS .1. THEORY
    GURNEY, JW
    RADIOLOGY, 1993, 186 (02) : 405 - 413
  • [28] DETERMINING THE LIKELIHOOD OF MALIGNANCY IN SOLITARY PULMONARY NODULES WITH BAYESIAN-ANALYSIS .2. APPLICATION
    GURNEY, JW
    LYDDON, DM
    MCKAY, JA
    RADIOLOGY, 1993, 186 (02) : 415 - 422
  • [29] ESTIMATING THE PROBABILITY OF MALIGNANCY IN SOLITARY PULMONARY NODULES - A BAYESIAN-APPROACH
    CUMMINGS, SR
    LILLINGTON, GA
    RICHARD, RJ
    AMERICAN REVIEW OF RESPIRATORY DISEASE, 1986, 134 (03): : 449 - 452
  • [30] Clinical Prediction Model To Estimate The Probability Of Malignancy In Solitary Pulmonary Nodules
    Vaszar, L. T.
    Penupolu, S.
    Wesselius, L.
    Gotway, M. B.
    Roarke, M. C.
    Ronan, B. A.
    Blair, J. E.
    AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2014, 189