Predictive Factors for Prophylactic Percutaneous Endoscopic Gastrostomy (PEG) Tube Placement and Use in Head and Neck Patients Following Intensity-Modulated Radiation Therapy (IMRT) Treatment: Concordance, Discrepancies, and the Role of Gabapentin.

The prophylactic placement of a percutaneous endoscopic gastrostomy (PEG) tube in the head and neck cancer (HNC) patient is controversial. We sought to identify factors associated with prophylactic PEG placement and actual PEG use. Since 2010, data regarding PEG placement and use were prospectively recorded in a departmental database from January 2010 to December 2012. HNC patients treated with intensity-modulated radiation therapy (IMRT) were retrospectively evaluated from 2010 to 2012. Variables potentially associated with patient post-radiation dysphagia from previous literature, and our experience was evaluated. We performed multivariate logistic regression on these variables with PEG placement and PEG use, respectively, to compare the difference of association between the two arms. We identified 192 HNC patients treated with IMRT. Prophylactic PEG placement occurred in 121 (63.0 %) patients, with PEG use in 97 (80.2 %) patients. PEG placement was associated with male gender (p < .01), N stage ≥ N2 (p < .05), pretreatment swallowing difficulties (p < .01), concurrent chemotherapy (p < .01), pretreatment KPS ≥80 (p = .01), and previous surgery (p = .02). Concurrent chemotherapy (p = .03) was positively associated with the use of PEG feeding by the patient, whereas pretreatment KPS ≥80 (p = .03) and prophylactic gabapentin use (p < .01) were negatively associated with PEG use. The analysis suggests there were discrepancies between prophylactic PEG tube placement and actual use. Favorable pretreatment KPS, no pretreatment dysphagia, no concurrent chemotherapy, and the use of gabapentin were significantly associated with reduced PEG use. This analysis may help refine the indications for prophylactic PEG placement.

A data-mining framework for large scale analysis of dose-outcome relationships in a database of irradiated head and neck cancer patients.

PURPOSE: To develop a hypothesis-generating framework for automatic extraction of dose-outcome relationships from an in-house, analytic oncology database. METHODS: Dose-volume histograms (DVH) and clinical outcomes have been routinely stored to the authors' database for 684 head and neck cancer patients treated from 2007 to 2014. Database queries were developed to extract outcomes that had been assessed for at least 100 patients, as well as DVH curves for organs-at-risk (OAR) that were contoured for at least 100 patients. DVH curves for paired OAR (e.g., left and right parotids) were automatically combined and included as additional structures for analysis. For each OAR-outcome combination, only patients with both OAR and outcome records were analyzed. DVH dose points, DVt, at a given normalized volume threshold Vt were stratified into two groups based on severity of toxicity outcomes after treatment completion. The probability of an outcome was modeled at each Vt = [0%, 1%, …, 100%] by logistic regression. Notable OAR-outcome combinations were defined as having statistically significant regression parameters (p < 0.05) and an odds ratio of at least 1.05 (5% increase in odds per Gy). RESULTS: A total of 57 individual and combined structures and 97 outcomes were queried from the database. Of all possible OAR-outcome combinations, 17% resulted in significant logistic regression fits (p < 0.05) having an odds ratio of at least 1.05. Further manual inspection revealed a number of reasonable models based on either reported literature or proximity between neighboring OARs. The data-mining algorithm confirmed the following well-known OAR-dose/outcome relationships: dysphagia/larynx, voice changes/larynx, esophagitis/esophagus, xerostomia/parotid glands, and mucositis/oral mucosa. Several surrogate relationships, defined as OAR not directly attributed to an outcome, were also observed, including esophagitis/larynx, mucositis/mandible, and xerostomia/mandible. CONCLUSIONS: Prospective collection of clinical data has enabled large-scale analysis of dose-outcome relationships. The current data-mining framework revealed both known and novel dosimetric and clinical relationships, underscoring the potential utility of this analytic approach in hypothesis generation. Multivariate models and advanced, 3D dosimetric features may be necessary to further evaluate the complex relationship between neighboring OAR and observed outcomes.