A new computational model for human thyroid cancer enhances the preoperative diagnostic efficacy
| Autor: | Hongyu Yu, Quan-cai Cai, Jian-guo Sheng, Tuo Li, Jian-quan Zhang, Xin Zhang, Weiqin Li, Xue-yun Chen, Yongquan Shi, Zhi-min Liu |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Adult
Male medicine.medical_specialty Population Models Biological Risk Assessment Cohort Studies Diagnosis Differential Sex Factors Risk Factors Positive predicative value differential diagnosis thyroid cancer medicine Palpitations Humans Thyroid Neoplasms education Thyroid cancer education.field_of_study business.industry Thyroid Computational Biology Cancer Middle Aged medicine.disease Thyroid Diseases Surgery computational model Logistic Models medicine.anatomical_structure ROC Curve Oncology Multivariate Analysis Preoperative Period Female Radiology Clinical Research Paper Differential diagnosis medicine.symptom business Cohort study |
| Zdroj: | Oncotarget |
| ISSN: | 1949-2553 |
| DOI: | 10.18632/oncotarget.4691 |
| Popis: | Considering the high rate of missed diagnosis and delayed treatments for thyroid cancer, an effective systematic model for the differential diagnosis is highly needed. Thus we analyzed the data on the clinicopathological characteristics, routine laboratory tests and imaging examinations in a cohort of 13,980 patients with thyroid cancer to establish a new diagnostic model for differentiating thyroid cancer in clinical practice. Here, we randomly selected two-thirds of the population to develop the thyroid malignancy risk scoring system (TMRS) for preoperative differentiation between thyroid cancer and benignant thyroid diseases, and then validated its differential diagnostic power in the rest one-third population. The 18 predictors finally enrolled in the TMRS included male gender, clinical manifestations (fever, neck sore, neck lump, palpitations or sweating), laboratory findings (TSH>1.56mIU/L, FT3>5.85pmol/L, TPOAb>14.97IU/ml, TgAb>48.00IU/ml, Tg>34.59μg/L, Ct>64.00ng/L, and CEA>0.41μg/L), and ultrasound features (tumor number≤ 23mm, site, size, echo texture, margins, and shape of neck lymphnodes). The TMRS is validated to be well-calibrated (P = 0.437) and excellently discriminated (AUC = 0.93, 95% CI [0.92, 0.94]), with an accuracy of 83.2%, a sensitivity of 89.3%, a specificity of 81.5%, positive and negative predictive values of 56.8% and 96.6%, positive and negative likelihood ratios of 4.83 and 0.13 in the development cohort, respectively. The TMRS highlights that this differential diagnostic system could help provide accurate preoperative risk stratification for thyroid cancer, and avoid unnecessary over- and under-treatment for such patients. |
| Databáze: | OpenAIRE |
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