Literature DB >> 27586199

RE: A Risk Prediction Model of Thyroid Cancer in Euthyroid Asymptomatic Patients: Importance of Model Validation.

Li Xu1.   

Abstract

Entities:  

Keywords:  First-degree family history; Risk factor; Thyroid cancer; Ultrasonography

Mesh:

Substances:

Year:  2016        PMID: 27586199      PMCID: PMC5007413          DOI: 10.3348/kjr.2016.17.5.824

Source DB:  PubMed          Journal:  Korean J Radiol        ISSN: 1229-6929            Impact factor:   3.500


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Dear Sir, With great interest, we read the article "risk of thyroid cancer in euthyroid asymptomatic patients with thyroid nodules, with an emphasis on family history of thyroid cancer" by Hwang et al. (1). The paper concludes that a solitary lesion on ultrasonography (US) features observed on US, and the male gender (p < 0.001) were significant independent risk factors for thyroid malignancy (1). We would like to thank the authors for this highly useful work. The authors developed a multivariate regression prediction model to investigate the independent predictive factors associated with thyroid cancer in euthyroid asymptomatic patients. Model predictors include age, male gender, 1st degree family history, solitary lesion on US, serum TSH level, and TSH grade. Multivariate analysis confirmed that a solitary lesion on US (odds ratio [OR], 1.413; 95% confidence interval [CI], 1.014–1.970; p = 0.041), US features (OR, 39.778; 95% CI, 27.953–56.606; p < 0.001), and male gender (OR, 1.994; 95% CI, 1.360–2.925; p < 0.001) was predictive of euthyroid asymptomatic patients with thyroid nodules. However, model validation is possibly the most important step in the model building sequence. Once the models are validated, it would be easy to apply for preoperative individualized prediction of euthyroid asymptomatic patients having thyroid nodules. It is known that split-sample development and validation sets were generally used (2). Therefore, we suggest that the research might be improved by using split-sample development and validation for assessing euthyroid asymptomatic patients with thyroid nodules, with emphasis being on family history of thyroid cancer. The entire data is randomly partitioned into a training set and a test set. Internal validation was performed by applying the fitted model derived from the training set to the test set (3). Finally, the C-index and calibration curve were derived on the basis of the regression analysis. Future research in large cohorts should focus on external validations.
  3 in total

1.  Probability of cancer in pulmonary nodules detected on first screening CT.

Authors:  Annette McWilliams; Martin C Tammemagi; John R Mayo; Heidi Roberts; Geoffrey Liu; Kam Soghrati; Kazuhiro Yasufuku; Simon Martel; Francis Laberge; Michel Gingras; Sukhinder Atkar-Khattra; Christine D Berg; Ken Evans; Richard Finley; John Yee; John English; Paola Nasute; John Goffin; Serge Puksa; Lori Stewart; Scott Tsai; Michael R Johnston; Daria Manos; Garth Nicholas; Glenwood D Goss; Jean M Seely; Kayvan Amjadi; Alain Tremblay; Paul Burrowes; Paul MacEachern; Rick Bhatia; Ming-Sound Tsao; Stephen Lam
Journal:  N Engl J Med       Date:  2013-09-05       Impact factor: 91.245

2.  A Risk Prediction Model Based on Lymph-Node Metastasis in Poorly Differentiated-Type Intramucosal Gastric Cancer.

Authors:  Jeung Hui Pyo; Hyuk Lee; Byung-Hoon Min; Jun Haeng Lee; Min Gew Choi; Jun Ho Lee; Tae Sung Sohn; Jae Moon Bae; Kyoung-Mee Kim; Hyeon Seon Ahn; Sin-Ho Jung; Sung Kim; Jae J Kim
Journal:  PLoS One       Date:  2016-05-26       Impact factor: 3.240

3.  Risk of Thyroid Cancer in Euthyroid Asymptomatic Patients with Thyroid Nodules with an Emphasis on Family History of Thyroid Cancer.

Authors:  Shin Hye Hwang; Eun-Kyung Kim; Hee Jung Moon; Jung Hyun Yoon; Jin Young Kwak
Journal:  Korean J Radiol       Date:  2016-03-02       Impact factor: 3.500

  3 in total

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