JOURNAL ARTICLE

Clinical Validation of a Predictive Model for the Presence of Cervical Lymph Node Metastasis in Papillary Thyroid Cancer

N U Patel, K E Lind, K McKinney, T J Clark, S S Pokharel, J M Meier, E R Stamm, K Garg, B Haugen
AJNR. American Journal of Neuroradiology 2018, 39 (4): 756-761
29449283

BACKGROUND AND PURPOSE: Ultrasound is a standard technique to detect lymph node metastasis in papillary thyroid cancer. Cystic changes and microcalcifications are the most specific features of metastasis, but with low sensitivity. This prospective study compared the diagnostic accuracy of a predictive model for sonographic evaluation of lymph nodes relative to the radiologist's standard assessment in detecting papillary thyroid cancer metastasis in patients after thyroidectomy.

MATERIALS AND METHODS: Cervical lymph node sonographic images were reported by a radiologist (R method) per standard practice. The same images were independently evaluated by another radiologist using a sonographic predictive model (M method). A test was considered positive for metastasis if the R or M method suggested lymph node biopsy. The result of lymph node biopsy or surgical pathology was used as the reference standard. We estimated relative true-positive fraction and relative false-positive fraction using log-linear models for correlated binary data for the M method compared with the R method.

RESULTS: A total of 237 lymph nodes in 103 patients were evaluated. Our analysis of relative true-positive fraction and relative false-positive fraction included 54 nodes with pathologic results in which at least 1 method (R or M) was positive. The M method had a higher relative true-positive fraction of 1.46 (95% CI, 1.12-1.91; P = .006) and a lower relative false-positive fraction of 0.58 (95% CI, 0.36-0.92; P = .02) compared with the R method.

CONCLUSIONS: The sonographic predictive model outperformed the standard assessment to detect lymph node metastasis in patients with papillary thyroid cancer and may reduce unnecessary biopsies.

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