Utility of a Clinical Decision Support System in Weight Loss Prediction After Head and Neck Cancer Radiotherapy.
Aged
Area Under Curve
Clinical Competence
Combined Modality Therapy
Decision Support Systems, Clinical
Female
Head and Neck Neoplasms
/ complications
Humans
Male
Middle Aged
Neoplasm Staging
Odds Ratio
Physicians
Prognosis
Radiometry
Radiotherapy
/ adverse effects
Radiotherapy Planning, Computer-Assisted
Reproducibility of Results
Tomography, X-Ray Computed
Weight Loss
Journal
JCO clinical cancer informatics
ISSN: 2473-4276
Titre abrégé: JCO Clin Cancer Inform
Pays: United States
ID NLM: 101708809
Informations de publication
Date de publication:
03 2019
03 2019
Historique:
entrez:
13
3
2019
pubmed:
13
3
2019
medline:
17
6
2020
Statut:
ppublish
Résumé
To evaluate the utility of a clinical decision support system (CDSS) using a weight loss prediction model. 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. 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). 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.
Identifiants
pubmed: 30860866
doi: 10.1200/CCI.18.00058
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM