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External validation of a nomogram that predicts the pathological diagnosis of thyroid nodules in a Chinese population.

Wu R, Zhu L, Li W, Tang Q, Pan F, Wu W, Liu J, Yao C, Wang S - PLoS ONE (2013)

Bottom Line: However, the calibration was significant (p = 0.55) only in the high-risk group.Nixon's nomogram is a valuable predictive model for the Chinese population and has been externally validated.It has good performance for patients with a high risk of malignancy and may be more suitable for use with these patients in China.

View Article: PubMed Central - PubMed

Affiliation: Department of Vascular and Thyroid Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, PR China.

ABSTRACT

Introduction: Nomograms are statistical predictive models that can provide the probability of a clinical event. Nomograms have better performance for the estimation of individual risks because of their increased accuracy and objectivity relative to physicians' personal experiences. Recently, a nomogram for predicting the likelihood that a thyroid nodule is malignant was introduced by Nixon. The aim of this study was to determine whether Nixon's nomogram can be validated in a Chinese population.

Materials and methods: All consecutive patients with thyroid nodules who underwent surgery between January and June 2012 in our hospital were enrolled to validate Nixon's nomogram. Univariate and multivariate analyses were used to identify the risk factors for thyroid carcinoma. Discrimination and calibration were employed to evaluate the performance of Nixon's model in our population.

Results: A total of 348 consecutive patients with 409 thyroid nodules were enrolled. Thyroid ultrasonographic characteristics, including shape, echo texture, calcification, margins, vascularity and number (solitary vs. multiple nodules), were associated with malignance in the multivariate analysis. The discrimination of all nodules group, the group with a low risk of malignancy (predictive proportion <50%) and the group with a high risk of malignancy (predictive proportion ≥50%) using Nixon's nomogram was satisfactory, and the area under the receiver operating characteristic curve of the three groups were 0.87, 0.75 and 0.72, respectively. However, the calibration was significant (p = 0.55) only in the high-risk group.

Conclusion: Nixon's nomogram is a valuable predictive model for the Chinese population and has been externally validated. It has good performance for patients with a high risk of malignancy and may be more suitable for use with these patients in China.

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Related in: MedlinePlus

ROCs and calibrations of the total and 50% cut point subgroups of patients.The AUC of the total nodules was 0.87 (range, 0.83 to 0.90), but the calibration showed significant difference between the observed frequencies and predictive probabilities (p = 2.23*10−4). Based on the calibration plot, we used 50% as the threshold to divide the nodules into low risk and high-risk groups. In the low-risk group, the AUC was 0.75, and the calibration p-value was 1.02*10−4. But in the high-risk group, the AUC and calibration p-value were 0.72 and 0.55 respectively, which showed a good performance of the nomogram.
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pone-0065162-g001: ROCs and calibrations of the total and 50% cut point subgroups of patients.The AUC of the total nodules was 0.87 (range, 0.83 to 0.90), but the calibration showed significant difference between the observed frequencies and predictive probabilities (p = 2.23*10−4). Based on the calibration plot, we used 50% as the threshold to divide the nodules into low risk and high-risk groups. In the low-risk group, the AUC was 0.75, and the calibration p-value was 1.02*10−4. But in the high-risk group, the AUC and calibration p-value were 0.72 and 0.55 respectively, which showed a good performance of the nomogram.

Mentions: The AUC for the total nodules was 0.87 (range, 0.83 to 0.90), but the calibration p-value was 2.23*10−4. This result indicates that this model had good discrimination but cannot be well calibrated, indicating that the predictive probabilities were not concordant with the observed frequencies. Based on the calibration plot, we observed that the high-risk group (≥50%) appeared to have better calibration than the low-risk group (<50%) (Figure 1). Therefore, we used 50% as the threshold to identify the high-risk nodules. The AUC of the low-risk and high-risk groups were 0.75 and 0.72, respectively. The discriminations for the two subgroups were as good as that for the whole group. However, the calibrations of the two subgroups were tremendously different from each other. The calibration p-value of the low-risk and high-risk groups were 1.02*10−4 and 0.55, respectively (Table 3). The model only showed good performance for the high-risk group (≥50%).


External validation of a nomogram that predicts the pathological diagnosis of thyroid nodules in a Chinese population.

Wu R, Zhu L, Li W, Tang Q, Pan F, Wu W, Liu J, Yao C, Wang S - PLoS ONE (2013)

ROCs and calibrations of the total and 50% cut point subgroups of patients.The AUC of the total nodules was 0.87 (range, 0.83 to 0.90), but the calibration showed significant difference between the observed frequencies and predictive probabilities (p = 2.23*10−4). Based on the calibration plot, we used 50% as the threshold to divide the nodules into low risk and high-risk groups. In the low-risk group, the AUC was 0.75, and the calibration p-value was 1.02*10−4. But in the high-risk group, the AUC and calibration p-value were 0.72 and 0.55 respectively, which showed a good performance of the nomogram.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3672210&req=5

pone-0065162-g001: ROCs and calibrations of the total and 50% cut point subgroups of patients.The AUC of the total nodules was 0.87 (range, 0.83 to 0.90), but the calibration showed significant difference between the observed frequencies and predictive probabilities (p = 2.23*10−4). Based on the calibration plot, we used 50% as the threshold to divide the nodules into low risk and high-risk groups. In the low-risk group, the AUC was 0.75, and the calibration p-value was 1.02*10−4. But in the high-risk group, the AUC and calibration p-value were 0.72 and 0.55 respectively, which showed a good performance of the nomogram.
Mentions: The AUC for the total nodules was 0.87 (range, 0.83 to 0.90), but the calibration p-value was 2.23*10−4. This result indicates that this model had good discrimination but cannot be well calibrated, indicating that the predictive probabilities were not concordant with the observed frequencies. Based on the calibration plot, we observed that the high-risk group (≥50%) appeared to have better calibration than the low-risk group (<50%) (Figure 1). Therefore, we used 50% as the threshold to identify the high-risk nodules. The AUC of the low-risk and high-risk groups were 0.75 and 0.72, respectively. The discriminations for the two subgroups were as good as that for the whole group. However, the calibrations of the two subgroups were tremendously different from each other. The calibration p-value of the low-risk and high-risk groups were 1.02*10−4 and 0.55, respectively (Table 3). The model only showed good performance for the high-risk group (≥50%).

Bottom Line: However, the calibration was significant (p = 0.55) only in the high-risk group.Nixon's nomogram is a valuable predictive model for the Chinese population and has been externally validated.It has good performance for patients with a high risk of malignancy and may be more suitable for use with these patients in China.

View Article: PubMed Central - PubMed

Affiliation: Department of Vascular and Thyroid Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, PR China.

ABSTRACT

Introduction: Nomograms are statistical predictive models that can provide the probability of a clinical event. Nomograms have better performance for the estimation of individual risks because of their increased accuracy and objectivity relative to physicians' personal experiences. Recently, a nomogram for predicting the likelihood that a thyroid nodule is malignant was introduced by Nixon. The aim of this study was to determine whether Nixon's nomogram can be validated in a Chinese population.

Materials and methods: All consecutive patients with thyroid nodules who underwent surgery between January and June 2012 in our hospital were enrolled to validate Nixon's nomogram. Univariate and multivariate analyses were used to identify the risk factors for thyroid carcinoma. Discrimination and calibration were employed to evaluate the performance of Nixon's model in our population.

Results: A total of 348 consecutive patients with 409 thyroid nodules were enrolled. Thyroid ultrasonographic characteristics, including shape, echo texture, calcification, margins, vascularity and number (solitary vs. multiple nodules), were associated with malignance in the multivariate analysis. The discrimination of all nodules group, the group with a low risk of malignancy (predictive proportion <50%) and the group with a high risk of malignancy (predictive proportion ≥50%) using Nixon's nomogram was satisfactory, and the area under the receiver operating characteristic curve of the three groups were 0.87, 0.75 and 0.72, respectively. However, the calibration was significant (p = 0.55) only in the high-risk group.

Conclusion: Nixon's nomogram is a valuable predictive model for the Chinese population and has been externally validated. It has good performance for patients with a high risk of malignancy and may be more suitable for use with these patients in China.

Show MeSH
Related in: MedlinePlus