Utility of a clinical decision support system in weight loss prediction after head and neck cancer radiotherapy

Zhi Cheng, Minoru Nakatsugawa, Xian Chong Zhou, Chen Hu, Stephen Greco, Ana Kiess, Brandi Page, Sara Alcorn, John Haller, Kazuki Utsunomiya, Shinya Sugiyama, Wei Fu, John Wong, Junghoon Lee, Todd McNutt, Harry Quon

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Abstract

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 prepost 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.

Original languageEnglish (US)
Pages (from-to)1-11
Number of pages11
JournalJCO Clinical Cancer Informatics
Issue number3
DOIs
StatePublished - Jan 1 2019

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ASJC Scopus subject areas

  • Cancer Research
  • Oncology
  • Health Informatics

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