Value of Binary Logit Regression Model Based on FNA-Tg and Serum Tg for Determining Lymph Node Metastasis or Recurrence of Thyroid Cancer

Lin WEI; Mei ZHU; Hailin ZHANG; Yuran FENG; Xi CHEN; Bailing WU; Yang YANG

doi:10.12259/j.issn.2095-610X.S20230219

Volume 44 Issue 2

Feb. 2023

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Article Navigation > Journal of Kunming Medical University > 2023 > 44(2): 102-107

Lin WEI, Mei ZHU, Hailin ZHANG, Yuran FENG, Xi CHEN, Bailing WU, Yang YANG. Value of Binary Logit Regression Model Based on FNA-Tg and Serum Tg for Determining Lymph Node Metastasis or Recurrence of Thyroid Cancer[J]. Journal of Kunming Medical University, 2023, 44(2): 102-107. doi: 10.12259/j.issn.2095-610X.S20230219

Citation:

Lin WEI, Mei ZHU, Hailin ZHANG, Yuran FENG, Xi CHEN, Bailing WU, Yang YANG. Value of Binary Logit Regression Model Based on FNA-Tg and Serum Tg for Determining Lymph Node Metastasis or Recurrence of Thyroid Cancer[J]. Journal of Kunming Medical University, 2023, 44(2): 102-107. doi: 10.12259/j.issn.2095-610X.S20230219

Citation:

Lin WEI, Mei ZHU, Hailin ZHANG, Yuran FENG, Xi CHEN, Bailing WU, Yang YANG. Value of Binary Logit Regression Model Based on FNA-Tg and Serum Tg for Determining Lymph Node Metastasis or Recurrence of Thyroid Cancer[J]. Journal of Kunming Medical University, 2023, 44(2): 102-107. doi: 10.12259/j.issn.2095-610X.S20230219

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Value of Binary Logit Regression Model Based on FNA-Tg and Serum Tg for Determining Lymph Node Metastasis or Recurrence of Thyroid Cancer

doi: 10.12259/j.issn.2095-610X.S20230219

Dept. of Ultrasound，First Affiliated Hospital of Kunming Medical University， Kunming Yunnan 650031，China

Received Date: 2022-12-07
Available Online: 2023-02-01
Publish Date: 2023-02-25

Abstract

Abstract

Objective To establish a prediction model for lymph node metastasis and recurrence of thyroid cancer by analyzing patients’ lymph node FNA-Tg values, serum Tg values, and their ratios by binary logit regression. Methods 1. 64 patients with preoperative differentiated thyroid cancer with suspected lymph node metastasis were collected. 2. The diagnostic value of FNA-Tg value, serum Tg value, and their ratios for the differentiation of benign and malignant lymph nodes were initially evaluated by the ROC curve. 3. The diagnostic value of the above three indices was further evaluated by binary logit regression analysis and a prediction model was established. Results 1. ROC curve: the AUC value corresponding to lymph node FNA-Tg was 0.998 （95% CI 99.27%-100.34%）, with a cut point value of 0.82; the AUC value corresponding to serum Tg was 0.824 （95% CI 70.64%-94.14%）, with a cut point value of 18.27; the AUC value corresponding to lymph node FNA-Tg/serum Tg The AUC value of FNA-Tg/serum Tg in lymph nodes was 1.000 （95% CI 100.00%-100.00%）, and the cut point value was 0.461. 2. Binary logit regression all-entry method with the simultaneous presence of three independent variables: i） Binary logit regression all-entry method with the simultaneous presence of three independent variables: FNA-Tg value, serum Tg value and their ratios all had P values > 0.05, and the model The simultaneous presence of three independent variables has no diagnostic value for benign and malignant lymph nodes; ii） Binary Logit regression all-entry method lymph node FNA-Tg single variable results: lymph node FNA-Tg could explain 88% of the variation in benign and malignant lymph nodes, P = 0.038 < 0.05, regression coefficient 2.68, OR value 14.587, prediction model formula was: In （p/1-p） = -4.122 + 2.680* lymph node FNA-Tg, likelihood ratio test P = 0.000 < 0.001, AIC value 14.386, BIC value 18.704, overall prediction accuracy of 95.31%; iii） Binary Logit regression all-entry method serum Tg single variable results: serum Tg explained 27.8% of the variation in benign and malignant lymph nodes , P = 0.000 < 0.001, regression coefficient 0.164, OR 1.179, prediction model formula: In （p/1-p） = -2.466 + 0.164*serum Tg, likelihood ratio test P = 0.000 < 0.001, AIC value 67.33, BIC value 71.648, overall prediction accuracy 75%. Conclusions 1. Preoperative FNA-Tg, serum Tg and their ratios have good diagnostic value in determining the benignity and malignancy of thyroid nodules. 2. The binary logit regression model （stepwise method） formula based on serum Tg can better predict the benignity and malignancy of thyroid nodules.
- Ultrasound,
- Fine needle aspiration,
- Thyroglobulin,
- Regression model

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References(18)

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