Radiomics is one such “big data” approach that applies advanced image refining/data characterization algorithms to generate imaging features that can quantitatively classify tumor phenotypes in a non-invasive manner. We hypothesize that certain textural features of oropharyngeal cancer (OPC) primary tumors will have statistically significant correlations to patient outcomes such as local control. Patients from an IRB-approved database dispositioned to (chemo)radiotherapy for locally advanced OPC were included in this retrospective series. Pretreatment contrast CT scans were extracted and radiomics-based analysis of gross tumor volume of the primary disease (GTVp) were performed using imaging biomarker explorer (IBEX) software that runs in Matlab platform. Data set was randomly divided into a training dataset and test and tuning holdback dataset. Machine learning methods were applied to yield a radiomic signature consisting of features with minimal overlap and maximum prognostic significance. The radiomic signature was adapted to discriminate patients, in concordance with other key clinical prognosticators. 465 patients were available for analysis. A signature composed of 2 radiomic features from pre-therapy imaging was derived, based on the Intensity Direct and Neighbor Intensity Difference methods. Analysis of resultant groupings showed robust discrimination of recurrence probability and Kaplan-Meier-estimated local control rate (LCR) differences between “favorable” and “unfavorable” clusters were noted.

Purpose/Objective(s) We sought to identify swallowing muscle dose-response thresholds associated with chronic radiation-associated dysphagia (RAD) after IMRT for oropharyngeal cancer. Materials/Methods T1-4 N0-3 M0 oropharyngeal cancer patients who received definitive IMRT and systemic therapy were examined. Chronic RAD was coded as any of the following ≥ 12 months post-IMRT: videofluoroscopy/endoscopy detected aspiration or stricture, gastrostomy tube and/or aspiration pneumonia. DICOM-RT plan data were autosegmented using a custom region-of-interest (ROI) library and included inferior, middle and superior constrictors (IPC, MPC, and SPC), medial and lateral pterygoids (MPM, LPM), anterior and posterior digastrics (ADM, PDM), intrinsic tongue muscles (ITM), mylo/geniohyoid complex (MHM), genioglossus (GGM), ), masseter (MM), Buccinator (BM), palatoglossus (PGM), and cricopharyngeus (CPM), with ROI dose-volume histograms (DVHs) calculated. Recursive partitioning analysis (RPA) was used to identify dose-volume effects associated with chronic-RAD, for use in a multivariate (MV) model. Results Of 300 patients, 34 (11%) had chronic-RAD. RPA showed DVH-derived MHM V69 (i.e. the volume receiving ≥69Gy), GGM V35, ADM V60, MPC V49, and SPC V70 were associated with chronic-RAD. A model including age in addition to MHM V69 as continuous variables was optimal among tested MV models (AUC 0.835). Conclusion In addition to SPCs, dose to MHM should be monitored and constrained, especially in older patients (>62-years), when feasible.

Purpose/Objective To determine the impact of computerized tomography (CT)-determined pretreatment primary tumor volume (TV) on survival and disease control in T4a larynx squamous cell carcinoma. Materials/Methods We retrospectively reviewed 124 patients with T4a larynx cancer from 2000–2011. TV measurements were collected and correlated with outcomes. Results 5-year overall survival (OS) for patients with TV≥21cm3 treated with larynx preservation (n=26 of 41) was significantly inferior compared with <21cm3 (42% vs 64% respectively, p=0.003). 5-year OS for patients with TV≥21cm3 in the cohort treated with total laryngectomy followed by radiotherapy (n=42 of 83) was not statistically significant when compared with <21cm3 (50% vs 63% respectively, p=0.058). On multivariate analysis, TV ≥21cm3 was a significant independent correlate of worse disease-specific survival (p=0.004), event-free survival (p=0.005), recurrence free survival (p=0.04), non-cancer cause specific survival (p=0.02), and OS (p=0.0002). Conclusion Pretreatment CT-based TV is an independent prognostic factor of outcomes in T4a larynx cancer.

No abstract

we sought to examine how often-published studies accounted for time dependent confounders. Materials/Methods: We performed a PUBMED search using the terms: 'NCDB,' 'National Cancer Data Base,' 'postoperative radiation,' and 'adjuvant radiation therapy,' published between 2015-2018. Inclusion for review involved all manuscripts where PORT (with or without chemotherapy) was delivered to any disease site as a comparative arm within the study. This led to review of 42 publications. We specifically assessed how OS was defined and whether any statistical metrics were used to account for potential immortal time bias in the receipt of PORT via landmark analyses or adjusted hazard ratios. Results: Of the 42 publications reviewed, OS was not defined in 8 (19%) studies, was determined from date of diagnosis in 20 (47.6%), from date of treatment start date in 8(19%), or from diagnosis with a one month landmark time in 6 (14.2%). There was no landmark analysis, sequential landmark definition, or an adjusted cox model with a clear time dependent definition in 31 studies (73.8%) when accounting for time to PORT. Amongst the 11 studies that did a landmark analysis, 9 of them (81.8%) had a landmark time with rationale that was not clearly defined. Among the manuscripts analyzed, PORT was concluded to be beneficial in 38 studies (90.4%). Conclusion: Immortal time bias may obscure the effect size (usually via overestimating HR) of PORT as an adjuvant therapy and affect the validity of NCDB hypothesis generating studies. The NCDB has many strengths with its power to generate valid research questions, but its inherent biases require rigorous statistical methods to help validate conclusions. Studies assessing PORT are encouraged to measure OS from treatment start date and perform sequential landmark analyses to help quantify PORT effect size and mitigate this common confounder.