Department of Otolaryngology, General University Hospital of Elda, Elda, Alicante, Spain.
Department of Clinical Medicine, Miguel Hernández University, San Juan de Alicante, Alicante, Spain.
Clin Otolaryngol. 2019 Jan;44(1):26-31. doi: 10.1111/coa.13227. Epub 2018 Oct 9.
Though predictive models have been constructed to determine the risk of recurrence in differentiated thyroid carcinoma, various aspects of these models are inadequate. Therefore, we aimed to construct, internally validate and implement on a mobile application a scoring system to determine this risk within 10 years.
A retrospective cohort study in 1984-2016.
A Spanish region.
We enrolled 200 patients with differentiated thyroid carcinoma without distant metastasis at diagnosis.
Time-to-recurrence. A risk table was constructed based on the sum of points to estimate the likelihood of recurrence. The model was internally validated and implemented as a mobile application for Android.
Predictive factors were follicular histology, T, N and multifocality. This risk table had a C-statistic of 0.723. The calibration was satisfactory.
This study provides an instrument able to predict rapidly and very simply which patients with differentiated thyroid carcinoma have a greater risk of recurrence.
尽管已经构建了预测模型来确定分化型甲状腺癌的复发风险，但这些模型的各个方面都存在不足。因此，我们旨在构建、内部验证并在移动应用程序上实施一种评分系统，以在 10 年内确定这种风险。
一项回顾性队列研究，时间为 1984 年至 2016 年。
西班牙一个地区。
我们纳入了 200 例初诊时无远处转移的分化型甲状腺癌患者。
复发时间。根据积分总和构建风险表，以估计复发的可能性。对模型进行了内部验证，并作为 Android 移动应用程序实现。
预测因素为滤泡状组织学、T、N 和多灶性。该风险表的 C 统计量为 0.723。校准结果令人满意。
本研究提供了一种快速且非常简单的工具，能够预测分化型甲状腺癌患者中哪些患者具有更高的复发风险。
