Development and validation of clinical diagnostic models for the probability of malignancy in solitary pulmonary nodules

Thoracic Cancer
Jingsi DongJie He

Abstract

It is critical to develop a non-invasive and accurate method for differentiating between malignant and benign solitary pulmonary nodules. In large sample studies, the effectiveness of the diagnostic prediction model as a tool of assessment of the probability of malignancy is still unclear. The establishment of a diagnostic model based on large samples is needed. In this study, 3358 patients diagnosed with a solitary pulmonary nodule between January 2005 and March 2013, were enrolled. All patients received surgery for pulmonary nodule resection. Clinical characters, preoperative biomarker results, and computed tomography scan findings were collected. All patients were randomly separated into a training set (n = 1679) and a test set (n = 1679); we used training sets to build a diagnostic model for the malignancy probability of pulmonary nodules, and applied the test set to validate our model, as well as other published diagnostic models. Logistic regression analysis identified 11 clinical characteristics as independent predictors of malignancy in patients with a solitary pulmonary nodule. The goodness-of-fit statistic for the model indicated that the observed proportion of malignancies did not differ from the predicted proportion...Continue Reading

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Citations

Jul 30, 2020·Lung Cancer : Journal of the International Association for the Study of Lung Cancer·Iakovos ToumazisSylvia K Plevritis
Jun 19, 2021·The Clinical Respiratory Journal·Cheng ZhouXing Li

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