Utility of a Clinical Decision Support System in Weight Loss Prediction After Head and Neck Cancer Radiotherapy
| Autor: | Xian Chong Zhou, Zhi Cheng, Shinya Sugiyama, John Wong, John Wayne Haller, Utsunomiya Kazuki, Wei Fu, Chen Hu, Sara R. Alcorn, Todd McNutt, Ana P. Kiess, Harry Quon, Junghoon Lee, Brandi R. Page, Stephen Greco, Minoru Nakatsugawa |
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| Rok vydání: | 2019 |
| Předmět: |
Male
Decision support system medicine.medical_specialty medicine.medical_treatment MEDLINE Clinical decision support system 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Weight loss Physicians Weight Loss Odds Ratio Medicine Combined Modality Therapy Humans Radiometry Aged Neoplasm Staging Radiotherapy business.industry Radiotherapy Planning Computer-Assisted Head and neck cancer Reproducibility of Results General Medicine Odds ratio Middle Aged medicine.disease Decision Support Systems Clinical Prognosis Radiation therapy Head and Neck Neoplasms 030220 oncology & carcinogenesis Area Under Curve Female Radiology Clinical Competence medicine.symptom business Tomography X-Ray Computed |
| Zdroj: | JCO clinical cancer informatics. 3 |
| ISSN: | 2473-4276 |
| Popis: | PURPOSE To evaluate the utility of a clinical decision support system (CDSS) using a weight loss prediction model. METHODS A prediction model for significant weight loss (loss of greater than or equal to 7.5% of body mass at 3-month post radiotherapy) was created with clinical, dosimetric, and radiomics predictors from 63 patients in an independent training data set (accuracy, 0.78; area under the curve [AUC], 0.81) using least absolute shrinkage and selection operator logistic regression. Four physicians with varying experience levels were then recruited to evaluate 100 patients in an independent validation data set of head and neck cancer twice (ie, a pre-post design): first without and then with the aid of a CDSS derived from the prediction model. At both evaluations, physicians were asked to predict the development (yes/no) and probability of significant weight loss for each patient on the basis of patient characteristics, including pretreatment dysphagia and weight loss and information from the treatment plan. At the second evaluation, physicians were also provided with the prediction model’s results for weight loss probability. Physicians’ predictions were compared with actual weight loss, and accuracy and AUC were investigated between the two evaluations. RESULTS The mean accuracy of the physicians’ ability to identify patients who will experience significant weight loss (yes/no) increased from 0.58 (range, 0.47 to 0.63) to 0.63 (range, 0.58 to 0.72) with the CDSS ( P = .06). The AUC of weight loss probability predicted by physicians significantly increased from 0.56 (range, 0.46 to 0.64) to 0.69 (range, 0.63 to 0.73) with the aid of the CDSS ( P < .05). Specifically, more improvement was observed among less-experienced physicians ( P < .01). CONCLUSION Our preliminary results demonstrate that physicians’ decisions may be improved by a weight loss CDSS model, especially among less-experienced physicians. Additional study with a larger cohort of patients and more participating physicians is thus warranted for understanding the usefulness of CDSSs. |
| Databáze: | OpenAIRE |
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