Long-term quality of life after definitive treatment of sinonasal and nasopharyngeal malignancies.

OBJECTIVE: To evaluate long-term global and site-specific health-related quality of life (HRQoL) in patients treated for sinonasal and nasopharyngeal malignancies. STUDY DESIGN: Cross-sectional. METHODS: One hundred fourteen patients with sinonasal and nasopharyngeal malignancies received surgery, radiation, systemic chemotherapy, or a combination thereof, with curative intent. Validated global ([EuroQol-5D] Visual Analogue Scale [EQ-5D VAS]) and disease-specific instruments (MD Anderson Symptom Inventory-Head and Neck [MDASI-HN], Anterior Skull Base Questionnaire [ASBQ]) were administered to patients who were both free of disease and had completed treatment at least 12 months previously. Associations between instruments, instrument domains, and specific clinical parameters were analyzed. RESULTS: The median age was 55 years. The mean EQ-5D VAS, MDASI-22 composite score, and ASBQ score were 74 (standard deviation [SD] 21), 48 (SD 36), and 130 (SD 27), respectively. The most frequently reported high-severity items in MDASI-HN were dry mouth and difficulty tasting food. The most frequently reported high-severity items in ASBQ were difficulty with smell and nasal secretions. Advanced Tumor (T) classification was associated with worse overall ASBQ sum score (P = 0.02). ASBQ performance at home and MDASI-HN drowsy symptom items independently predicted worse global HRQoL as measured by the EQ-5D VAS (P < 0.001). CONCLUSION: Global HRQoL for survivors of sinonasal and nasopharyngeal malignancies after multimodality treatment approximates that of the U.S. population for the same age group. ASBQ and MDASI-HN correlate well with global HRQoL outcomes as measured by EQ-5D VAS. MDASI-HN and ASBQ elicited unique symptoms, highlighting the complex symptom burden experienced by these patients. Further studies should identify patients predisposed to reduced long-term QOL. LEVEL OF EVIDENCE: 3 Laryngoscope, 130:86-93, 2020.

Machine Learning Applications in Head and Neck Radiation Oncology: Lessons From Open-Source Radiomics Challenges.

Radiomics leverages existing image datasets to provide non-visible data extraction via image post-processing, with the aim of identifying prognostic, and predictive imaging features at a sub-region of interest level. However, the application of radiomics is hampered by several challenges such as lack of image acquisition/analysis method standardization, impeding generalizability. As of yet, radiomics remains intriguing, but not clinically validated. We aimed to test the feasibility of a non-custom-constructed platform for disseminating existing large, standardized databases across institutions for promoting radiomics studies. Hence, University of Texas MD Anderson Cancer Center organized two public radiomics challenges in head and neck radiation oncology domain. This was done in conjunction with MICCAI 2016 satellite symposium using Kaggle-in-Class, a machine-learning and predictive analytics platform. We drew on clinical data matched to radiomics data derived from diagnostic contrast-enhanced computed tomography (CECT) images in a dataset of 315 patients with oropharyngeal cancer. Contestants were tasked to develop models for (i) classifying patients according to their human papillomavirus status, or (ii) predicting local tumor recurrence, following radiotherapy. Data were split into training, and test sets. Seventeen teams from various professional domains participated in one or both of the challenges. This review paper was based on the contestants' feedback; provided by 8 contestants only (47%). Six contestants (75%) incorporated extracted radiomics features into their predictive model building, either alone (n = 5; 62.5%), as was the case with the winner of the "HPV" challenge, or in conjunction with matched clinical attributes (n = 2; 25%). Only 23% of contestants, notably, including the winner of the "local recurrence" challenge, built their model relying solely on clinical data. In addition to the value of the integration of machine learning into clinical decision-making, our experience sheds light on challenges in sharing and directing existing datasets toward clinical applications of radiomics, including hyper-dimensionality of the clinical/imaging data attributes. Our experience may help guide researchers to create a framework for sharing and reuse of already published data that we believe will ultimately accelerate the pace of clinical applications of radiomics; both in challenge or clinical settings.

Patient reported dry mouth: Instrument comparison and model performance for correlation with quality of life in head and neck cancer survivors.

PURPOSE: To identify a clinically meaningful cut-point for the single item dry mouth question of the MD Anderson Symptom Inventory-Head and Neck module (MDASI-HN). METHODS: Head and neck cancer survivors who had received radiation therapy (RT) completed the MDASI-HN, the University of Michigan Hospital Xerostomia Questionnaire (XQ), and the health visual analog scale (VAS) of the EuroQol Five Dimension Questionnaire (EQ-5D). The Bayesian information criteria (BIC) were used to test the prediction power of each tool for EQ-5D VAS. The modified Breiman recursive partitioning analysis (RPA) was used to identify a cut point of the MDASI-HN dry mouth score (MDASI-HN-DM) with EQ-5D VAS, using a ROC-based approach; regression analysis was used to confirm the threshold effect size. RESULTS: Two-hundred seven respondents formed the cohort. Median follow-up from the end of RT to questionnaire completion was 88 months. The single item MDASI-HN-DM score showed a linear relationship with the XQ composite score (ρ = 0.80, p < 0.001). The MDASI-HN-DM displayed improved model performance for association with EQ-5D VAS as compared to XQ (BIC of 1803.7 vs. 2016.9, respectively). RPA showed that an MDASI-HN-DM score of ≥6 correlated with EQ-5D VAS decline (LogWorth 5.5). CONCLUSION: The single item MDASI-HN-DM correlated with the multi-item XQ and performed favorably in the prediction of QOL. A MDASI-HN-DM cut point of ≥6 correlated with decline in QOL.

Correction to: Long-term patient reported outcomes following radiation therapy for oropharyngeal cancer: cross-sectional assessment of a prospective symptom survey in patients ≥65 years old.

In the original publication [1] the name of author Jeremy M. Aymard was spelled wrong. The original article was updated to rectify this error.

Long-term patient reported outcomes following radiation therapy for oropharyngeal cancer: cross-sectional assessment of a prospective symptom survey in patients ≥65 years old.

BACKGROUND: Given the potential for older patients to experience exaggerated toxicity and symptoms, this study was performed to characterize patient reported outcomes in older patients following definitive radiation therapy (RT) for oropharyngeal cancer (OPC). METHODS: Cancer-free head and neck cancer survivors (>6 months since treatment completion) were eligible for participation in a questionnaire-based study. Participants completed the MD Anderson Symptom Inventory-Head and Neck module (MDASI-HN). Those patients ≥65 years old at treatment for OPC with definitive RT were included. Individual and overall symptom severity and clinical variables were analyzed. RESULTS: Of the 79 participants analyzed, 82% were male, 95% white, 41% T3/4 disease, 39% RT alone, 27% induction chemotherapy, 52% concurrent, and 18% both, and 96% IMRT. Median age at RT was 71 yrs. (range: 65-85); median time from RT to MDASI-HN was 46 mos. (2/3 > 24 mos.). The top 5 MDASI-HN items rated most severe in terms of mean (±SD) ratings (0-10 scale) were dry mouth (3.48 ± 2.95), taste (2.81 ± 3.29), swallowing (2.59 ± 2.96), mucus in mouth/throat (2.04 ± 2.68), and choking (1.30 ± 2.38) reported at moderate-severe levels (≥5) by 35, 29, 29, 18, and 13%, respectively. Thirty-nine % reported none (0) or no more than mild (1-4) symptoms across all 22 MDASI-HN symptoms items, and 38% had at least one item rated as severe (≥7). Hierarchical cluster analysis resulted in 3 patient groups: 1) ~65% with ranging from none to moderate symptom burden, 2) ~35% with moderate-severe ratings for a subset of classically RT-related symptoms (e.g. dry mouth, mucus, swallowing) and 3) 2 pts. with severe ratings of most items. CONCLUSIONS: The overall long-term symptom burden seen in this older OPC cohort treated with modern standard therapy was largely favorable, yet a higher symptom group (~35%) with a distinct pattern of mostly local and classically RT-related symptoms was identified.