Abstract
BackgroundHead and Neck Squamous Cell Carcinoma (HNSCC) has a high incidence in elderly patients. The postoperative complications present great challenges within treatment and they're hard for early warning.MethodsData from 525 patients diagnosed with HNSCC including a training set (n = 513) and an external testing set (n = 12) in our institution between 2006 and 2011 was collected. Variables involved are general demographic characteristics, complications, disease and treatment given. Five data mining algorithms were firstly exploited to construct predictive models in the training set. Subsequently, cross-validation was used to compare the different performance of these models and the best data mining algorithm model was then selected to perform the prediction in an external testing set.ResultsData from 513 patients (age > 60 y) with HNSCC in a training set was included while 44 variables were selected (P < 0.05). Five predictive models were constructed; the model with 44 variables based on the Random Forest algorithm demonstrated the best accuracy (89.084 %) and the best AUC value (0.949). In an external testing set, the accuracy (83.333 %) and the AUC value (0.781) were obtained by using the random forest algorithm model.ConclusionsData mining should be a promising approach used for elderly patients with HNSCC to predict the probability of postoperative complications. Our results highlighted the potential of computational prediction of postoperative complications in elderly patients with HNSCC by using the random forest algorithm model.
Highlights
Head and Neck Squamous Cell Carcinoma (HNSCC) has a high incidence in elderly patients
Patients’ data collection This study had gained ethical approval from the department of Oral and Maxillofacial-Head Neck Oncology at the Affiliated Ninth People’s Hospital School of Medicine, Shanghai Jiao Tong University; The patients’ data were analyzed and collected from the medical records that were documented in the department above; Total 525 patients diagnosed with HNSCC including a training set (n = 513) and an external test set (n = 12) in our institution between 2006 and 2011 was recruited
For the first time, we demonstrated that the potential of computational prediction model of postoperative complications in elderly patients with HNSCC was founded by using data mining approach
Summary
Data from 525 patients diagnosed with HNSCC including a training set (n = 513) and an external testing set (n = 12) in our institution between 2006 and 2011 was collected. Patients’ data collection This study had gained ethical approval from the department of Oral and Maxillofacial-Head Neck Oncology at the Affiliated Ninth People’s Hospital School of Medicine, Shanghai Jiao Tong University; The patients’ data were analyzed and collected from the medical records that were documented in the department above; Total 525 patients diagnosed with HNSCC including a training set (n = 513) and an external test set (n = 12) in our institution between 2006 and 2011 was recruited. Patients who underwent 1) surgery for benign tumors; 2) surgery for minor procedures with local anesthesia, such as biopsies; and 3) surgery with a duration that was shorter than 30 min were excluded from the study.
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