Research on a machine learning method for predicting discharge time of thyroid cancer patients receiving 131I treatment: a retrospective study.

Abstract

Radioactive iodine-131 (¹³¹I) based internal irradiation therapy has become one of the main methods for treating thyroid cancer, but patient usually need to be hospitalized after taking ¹³¹I until the residual activity meets the discharge criteria. However, the complex metabolism of ¹³¹I drug in individualized patient may make it difficult to assess when patients would meet discharge criteria, thereby increasing the hospital stay. In this study, some basic data of 1,044 thyroid cancer patients received ¹³¹I treatment at the First Affiliated Hospital with Nanjing Medical University from January 2022 to January 2024 are collected. Numerical analysis methods are used to analyze the absorption and metabolism of ¹³¹I drug in different patients and support vector machine (SVM) model is used to predict the discharge time of different patients. Results show that the effective half-life of ¹³¹I in both male and female patients are 10.35 h and 9.64 h, whose residual activity less than 400 MBq after 48 h of taking ¹³¹I. While the effective half-life of ¹³¹I in both male and female patients are 14.07 and 13.47 h for that the residual activity are greater than 400 MBq after 48 h of taking ¹³¹I. Furthermore, a discharge time prediction method based on SVM has been developed and the accuracy and precision of this method in predicting whether a patient could be discharged from the hospital after 48 h of taking the ¹³¹I drug are 88.04% and 96.89%. These results show that the discharge time prediction method could be expected to improve the rotation efficiency of nuclear medicine wards and provide timely treatment for more thyroid cancer patients receiving ¹³¹I treatment in the future.