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Personalising monitoring for chemotherapy patients through predicting deterioration in renal and hepatic function

Chambers, Pinkie; Watson, Matthew; Bridgewater, John; Forster, Martin D.; Roylance, Rebecca; Burgoyne, Rebecca; Masento, Sebastian; Steventon, Luke; Harmsworth King, James; Duncan, Nick; al Moubayed, Noura

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Authors

Pinkie Chambers

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Matthew Watson matthew.s.watson@durham.ac.uk
Postdoctoral Research Associate

John Bridgewater

Martin D. Forster

Rebecca Roylance

Rebecca Burgoyne

Sebastian Masento

Luke Steventon

James Harmsworth King

Nick Duncan



Abstract

Background
In those receiving chemotherapy, renal and hepatic dysfunction can increase the risk of toxicity and should therefore be monitored. We aimed to develop a machine learning model to identify those patients that need closer monitoring, enabling a safer and more efficient service.

Methods
We used retrospective data from a large academic hospital, for patients treated with chemotherapy for breast cancer, colorectal cancer and diffuse-large B-cell lymphoma, to train and validate a Multi-Layer Perceptrons (MLP) model to predict the outcomes of unacceptable rises in bilirubin or creatinine. To assess the performance of the model, validation was performed using patient data from a separate, independent hospital using the same variables. Using this dataset, we evaluated the sensitivity and specificity of the model.

Results
1214 patients in total were identified. The training set had almost perfect sensitivity and specificity of >0.95; the area under the curve (AUC) was 0.99 (95% CI 0.98–1.00) for creatinine and 0.97 (95% CI: 0.95–0.99) for bilirubin. The validation set had good sensitivity (creatinine: 0.60, 95% CI: 0.55–0.64, bilirubin: 0.54, 95% CI: 0.52–0.56), and specificity (creatinine 0.98, 95% CI: 0.96–0.99, bilirubin 0.90, 95% CI: 0.87–0.94) and area under the curve (creatinine: 0.76, 95% CI: 0.70, 0.82, bilirubin 0.72, 95% CI: 0.68–0.76).

Conclusions
We have demonstrated that a MLP model can be used to reduce the number of blood tests required for some patients at low risk of organ dysfunction, whilst improving safety for others at high risk.

Citation

Chambers, P., Watson, M., Bridgewater, J., Forster, M. D., Roylance, R., Burgoyne, R., …al Moubayed, N. (2023). Personalising monitoring for chemotherapy patients through predicting deterioration in renal and hepatic function. Cancer Medicine, https://doi.org/10.1002/cam4.6418

Journal Article Type Article
Acceptance Date Jul 26, 2023
Online Publication Date Aug 23, 2023
Publication Date 2023
Deposit Date Aug 29, 2023
Publicly Available Date Aug 30, 2023
Journal Cancer Medicine
Electronic ISSN 2045-7634
Publisher Wiley Open Access
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1002/cam4.6418
Public URL https://durham-repository.worktribe.com/output/1726311

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