Prediction model of acute kidney injury induced by cisplatin in older adults using a machine learning algorithm

• Published in: PloS one Vol. 17; no. 1; p. e0262021
• Main Authors: Okawa, Takaya, Mizuno, Tomohiro, Hanabusa, Shogo, Ikeda, Takeshi, Mizokami, Fumihiro, Koseki, Takenao, Takahashi, Kazuo, Yuzawa, Yukio, Tsuboi, Naotake, Yamada, Shigeki, Kameya, Yoshitaka
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 18.01.2022; Public Library of Science (PLoS)
• Subjects: Accuracy; Acute renal failure; Algorithms; Biology and Life Sciences; Cancer; Chemotherapy; Cisplatin; Complications and side effects; Computer and Information Sciences; Creatinine; Datasets; Decision making; Decision trees; Drug dosages; Ethics; Health aspects; Health risks; Hospitals; Kidney diseases; Kidneys; Learning algorithms; Machine learning; Medical prognosis; Medicine; Medicine and Health Sciences; Nephrology; Neural networks; Older people; Patients; Performance evaluation; Pharmacy; Physical Sciences; Prediction models; Recall; Research and Analysis Methods; Risk factors; Serum albumin; Japan; United States > US
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0262021

Early detection and prediction of cisplatin-induced acute kidney injury (Cis-AKI) are essential for the management of patients on chemotherapy with cisplatin. This study aimed to evaluate the performance of a prediction model for Cis-AKI. Japanese patients, who received cisplatin as the first-line chemotherapy at Fujita Health University Hospital, were enrolled in the study. The main metrics for evaluating the machine learning model were the area under the curve (AUC), accuracy, precision, recall, and F-measure. In addition, the rank of contribution as a predictive factor of Cis-AKI was determined by machine learning. A total of 1,014 and 226 patients were assigned to the development and validation data groups, respectively. The current prediction model showed the highest performance in patients 65 years old and above (AUC: 0.78, accuracy: 0.77, precision: 0.38, recall: 0.70, F-measure: 0.49). The maximum daily cisplatin dose and serum albumin levels contributed the most to the prediction of Cis-AKI. Our prediction model for Cis-AKI performed effectively in older patients.