Repository of Research and Investigative Information

Repository of Research and Investigative Information

Hormozgan University of Medical Sciences

Improving the accuracy of early diagnosis of thyroid nodule type based on the SCAD method

(2016) Improving the accuracy of early diagnosis of thyroid nodule type based on the SCAD method. Asian Pacific Journal of Cancer Prevention.

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Abstract

Although early diagnosis of thyroid nodule type is very important, the diagnostic accuracy of standard tests is a challenging issue. We here aimed to find an optimal combination of factors to improve diagnostic accuracy for distinguishing malignant from benign thyroid nodules before surgery. In a prospective study from 2008 to 2012, 345 patients referred for thyroidectomy were enrolled. The sample size was split into a training set and testing set as a ratio of 7:3. The former was used for estimation and variable selection and obtaining a linear combination of factors. We utilized smoothly clipped absolute deviation (SCAD) logistic regression to achieve the sparse optimal combination of factors. To evaluate the performance of the estimated model in the testing set, a receiver operating characteristic (ROC) curve was utilized. The mean age of the examined patients (66 male and 279 female) was 40.9 ± 13.4 years (range 15-90 years). Some 54.8 of the patients (24.3 male and 75.7 female) had benign and 45.2 (14 male and 86 female) malignant thyroid nodules. In addition to maximum diameters of nodules and lobes, their volumes were considered as related factors for malignancy prediction (a total of 16 factors). However, the SCAD method estimated the coefficients of 8 factors to be zero and eliminated them from the model. Hence a sparse model which combined the effects of 8 factors to distinguish malignant from benign thyroid nodules was generated. An optimal cut off point of the ROC curve for our estimated model was obtained (p=0.44) and the area under the curve (AUC) was equal to 77 (95 CI: 68-85). Sensitivity, specificity, positive predictive value and negative predictive values for this model were 70, 72, 71 and 76, respectively. An increase of 10 percent and a greater accuracy rate in early diagnosis of thyroid nodule type by statistical methods (SCAD and ANN methods) compared with the results of FNA testing revealed that the statistical modeling methods are helpful in disease diagnosis. In addition, the factor ranking offered by these methods is valuable in the clinical context.

Item Type: Article
Additional Information: cited By 0
Keywords: adolescent; adult; aged; algorithm; area under the curve; cancer staging; differential diagnosis; early diagnosis; female; fine needle aspiration biopsy; follow up; human; male; middle aged; prognosis; prospective study; receiver operating characteristic; statistical model; Thyroid Neoplasms; thyroid nodule; thyroidectomy; very elderly; young adult, Adolescent; Adult; Aged; Aged, 80 and over; Algorithms; Area Under Curve; Biopsy, Fine-Needle; Diagnosis, Differential; Early Diagnosis; Female; Follow-Up Studies; Humans; Logistic Models; Male; Middle Aged; Models, Statistical; Neoplasm Staging; Prognosis; Prospective Studies; ROC Curve; Thyroid Neoplasms; Thyroid Nodule; Thyroidectomy; Young Adult
Subjects: endocrine
Divisions: Research Vice-Chancellor Department > Mother and Child Welfare Research Center
Depositing User: مهندس هدی فهیم پور
URI: http://eprints.hums.ac.ir/id/eprint/4133

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