Maxillary sinus inflammation assessment using FDG-PET/CT in head and neck cancer patients with photon, proton, and combined radiation therapy.

Identifying Oropharyngeal Head and Neck Cancer Patients Who Will Benefit Most From Proton Therapy: Implementation of a Quantitative Clinical Decision-Support Tool

Measuring Radiation Toxicity Using Circulating Cell-Free DNA in Prostate Cancer Patients

The Importance of Self-Care Rehabilitation in Irradiated Head and Neck Cancer Patients

Due to the radiation-sparing effects on salivary gland acini, changes in the composition of the oral microbiome may be a driver for improved outcomes in patients receiving proton radiation, with potentially worse outcomes in patients exposed to photon radiation therapy. To date, a head-to-head comparison of oral microbiome changes at a metagenomic level with longitudinal sampling has yet to be performed in these patient cohorts. To comparatively analyze oral microbiome shifts during head and neck radiation therapy, a prospective pilot cohort study was performed at the Maryland Proton Treatment Center and the University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center. A longitudinal metagenomic comparative analysis of oral microbiome shifts was performed at three time points (pre-radiation, during radiation, and immediately post-radiation). Head and neck cancer patients receiving proton radiation (n = 4) were compared to photon radiation (n = 4). Additional control groups included healthy age- and sex-matched controls (n = 5), head and neck cancer patients who never received radiation therapy (n = 8), and patients with oral inflammatory disease (n = 3). Photon therapy patients presented with lower microbial alpha diversity at all timepoints, and there was a trend towards reduced species richness as compared with proton therapy. Healthy controls and proton patients exhibited overall higher and similar diversity. A more dysbiotic state was observed in patients receiving photon therapy as compared to proton therapy, in which oral microbial homeostasis was maintained. Mucositis was observed in 3/4 photon patients and was not observed in any proton patients during radiation therapy. The bacterial de novo pyrimidine biosynthesis pathway and the nitrate reduction V pathway were comparatively higher following photon exposure. These functional changes in bacterial metabolism may suggest that photon exposure produces a more permissive environment for the proliferation of pathogenic bacteria. Oral microbiome dysbiosis in patients receiving photon radiation may be associated with increased mucositis occurrence. Proton radiation therapy for head and neck cancer demonstrates a safer side effect profile in terms of oral complications, oral microbiome dysbiosis, and functional metabolic status.

Enteral Feeding Tubes in Patients Undergoing Definitive Chemoradiation Therapy for Head-and-Neck Cancer: A Critical Review

Induced Leukopenia In Head And Neck Cancer Patients Treated With Proton Or Photon Radiotherapy

Introduction: Cancers affecting the parts of head and neck hugely impact the patients. Among Head and Neck Cancer (HNC) patients, the visible signs and symptoms of the disease or the side effects of treatment modalities can cause various degrees of functional impairment such as mastication, swallowing and communication or disfigurement. Aim: To study the relationship between self-image and quality of life among head and neck cancer patients. Materials and Methods: This was a descriptive cross sectional survey conducted among 54 head and neck cancer patients. Data were collected through self- dministered demographic proforma, disease related proforma, self-image scale and Functional Assessment of Head and Neck Cancer (FACT; H&N).Association between self-image and demographic and disease related variables were assessed by computing Chi-square.Kruskal Wallis was computed to find the association between quality of life and demographic and disease related variables.Results: Majority of patients i.e., 36 out of 54 (66.7 %) were above 50 years, 43 (79.6%) were men, 47 (87%) were married, 46 (85.18%) had the disease duration of less than six months, 43 (79.6%) were receiving both radiation therapy and chemotherapy as a mode of treatment, 49 (90.7%) of them did not have any co-morbidity, 16 (29.6%) had a mode of feeding other than oral (ryles tube and PEG feeding) and six (11.1%) had undergone tracheostomy. There was a significant association between self-image and monthly income, treatment modality and radiotherapy dose with p =0.013, 0.006 and 0.046 respectively. Kruskal Wallis test value for mode of feeding (4.881) was also statistically significant (0.027) with quality of life. There is positive correlation (r=0.613, p=0.001) between self-image and quality of life of head and neck cancer patients.Conclusion: HNC patients suffer with the disease 24 hours a day. Self-image and quality of life of these patients is interrelated.As the self-image improves, the quality of life will be better and vice versa.

Introduction: Cancer-related fatigue is physical, emotional, or cognitive exhaustion which can affect treatment adherence and quality of life, and predict survival. Head and neck cancer (HNC) patients experience high levels of fatigue due to the degree of radiotherapy (RT), but that alone does not fully explain it. Recent studies suggest that fatigue may be related to a patient's personalized metabolic and inflammatory response, suggesting a patient's gene expression (GE) may be used to predict and monitor fatigue - a precursor to managing it. In this analysis, we examined whether GE is predictive of pre-RT patient reported fatigue using cross-validated penalized Lasso regression - a machine learning approach. Study population: From Emory University Clinics, 44 HNC patients donated blood samples before undergoing RT. GE was assessed using an Affymetrix Clariom S Human microarray which measures gene transcripts for roughly 24,000 genes; each probe was log-transformed, normalized, and standardized. The validated 20-item self-report multidimensional fatigue inventory questionnaire measured each patient's continuous fatigue score. Methods: To predict fatigue, we used leave-one-out cross validation (CV). This means we built a Lasso regression model using GE probes from 43 of 44 subjects and used that model to predict fatigue for the remaining subject; this process was repeated 44 times until all subjects had a predicted fatigue score. We chose penalized Lasso regression because the ‘penalty' performs variable selection and mitigates collinearity between the GE probes; the penalty was chosen by an extra layer of CV not described. We compared the predicted fatigue scores to the corresponding patient reported fatigue scores using R2 (higher values mean stronger correlation and better prediction). Results: To test the approach, we allowed the Lasso regression to build a model based on all subjects and predict fatigue on all subjects. This prediction was expected to be high, and it was (R2=0.98). However, the approach was less successful predicting fatigue during the leave-one-out CV prediction (R2=0.15). The probes most influential predicting fatigue are linked to genes involved in tryptophan metabolism (precursor to the neurotransmitter serotonin), double strand break DNA repair, and transforming growth factor beta receptor signaling (inflammation cytokine). Conclusions: Gene expression may predict fatigue in head and neck cancer patients, but there is room for improvement. The model suggests that a patient's personalized DNA repair process, metabolic and inflammatory response may play key roles in patient fatigue. Integrating more data focused on these biological processes, for instance patient metabolomics, may improve the model performance. Future efforts include collecting a larger sample, trying alternative machine learning methods, and testing the robustness of the model over time. Citation Format: Ronald C. Eldridge, Andrew H. Miller, Deborah W. Bruner, Jonathan J. Beitler, Kristin A. Higgins, Evanthia C. Wommack, Linh Kha Huynh, Nabil F. Saba, Dong M. Shin, Canhua Xiao. Predicting fatigue levels of head and neck cancer patients with gene expression using machine learning [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4257.

Tooth Failure Post-Radiotherapy in Head and Neck Cancer: Primary Report of the Clinical Registry of Dental Outcomes in Head and Neck Cancer Patients (OraRad) Study

Survival After Proton and Photon Radiation Therapy in Patients With Head and Neck Cancers: A Study of the National Cancer Database

Osteopontin Plasma Levels in Head and Neck Cancer Patients During Radiotherapy

e16056 Background: Little is known about the relationship between psychological distress and physical symptoms in head and neck cancer (HNC) patients undergoing radiation therapy (RT), and how these relationships may change over the course of treatment. We conducted exploratory analyses, on a previously published descriptive study examining the occurrence and severity of physical symptoms during RT. The purpose of this secondary analysis was to determine the relationship over time between psychological distress and physical symptoms in HNC patients. Methods: Ninety HNC patients receiving RT completed a Symptom Inventory (SI) weekly for five weeks, beginning with the week prior to the start of treatment. The SI assesses the presence and severity of 12 symptoms, including, pain, fatigue, nausea, disturbed sleep, feeling distressed, shortness of breath, memory, lack of appetite, drowsiness, vomiting, skin problems, and urination difficulty. Change scores in symptom severity between baseline and weeks 2, 3 and 4 were calculated, and Pearson’s correlations were used to determine the associations between psychological distress and physical symptoms. Results: Changes in psychological distress between baseline and week 2 of treatment were significantly correlated with changes in fatigue (r = 0.35, n=52, p = 0.01) and skin problems (r = 0.40, n=36, p = 0.02). Changes in psychological distress between baseline and week 3 of treatment were significantly correlated with changes in fatigue (r = 0.42, n=42, p = 0.006), shortness of breath (r = 0.48, n=42, p = 0.001), memory (r=0.36, n=42, p = 0.02), and lack of appetite (r = 0.53, n=42, p = 0.001). Changes in psychological distress between baseline and week 4 of treatment were correlated with changes in fatigue (r = 0.57, n=40, p=0.001), memory (r=0.48, n=39, p=0.002), and lack of appetite (r=0.49, n=40, p=0.001). Conclusions: Fatigue, memory, shortness of breath, and lack of appetite are significantly related to psychological distress in HNC patients undergoing RT. Additional research is needed to determine how psychological distress affects physical symptoms and if improvements in psychological distress may attenuate physical symptoms in HNC patients receiving RT.

Proton Radiotherapy to Preserve Fertility and Endocrine Function: A Translational Investigation

Suicidality is a pertinent issue among head and neck cancer patients. Our primary aim is to investigate the current suicidality rate among head and neck cancer (HNC) patients and evaluate risk factors associated with suicidality. We thoroughly searched primary original research from January 2024 onwards across several databases, including PubMed, Embase, ScienceDirect, Web of Science, Scopus, and PsycINFO. Using a random-effects model, we calculated the odds ratio (OR) for risk factors and conducted a proportional meta-analysis to estimate prevalence and 95% confidence intervals (CI). Out of 15 included studies, 305,146 head and neck cancer patients were included. The global prevalence of suicidality among head and neck cancer patients was estimated at 6.8% (95% CI 2.0-20.6%). Major depressive disorder (RR = 5.13, 95% CI 3.60-7.30), psychiatric disorders (RR = 3.73, 95% CI 2.65-5.25), alcohol abuse (RR = 2.67, 95% CI 1.71-4.16), substance abuse (RR = 2.47, 95% CI 1.58-3.85), smoking/nicotine dependence (RR = 2.03, 95% CI 1.60-2.58), and functional compromise (RR = 1.74, 95% CI 1.29-2.36) were identified as significant risk factors. Subgroup analysis by geographical location revealed variations in prevalence, with Asia reporting lower rates than Europe and North America. This systematic review reports the current suicidality rate associated with head and neck cancer patients. Major depressive disorder and other psychiatric comorbidities pose substantial risks requiring early intervention in mitigating the burden of suicidality.

Association of Provider Zip Code Sociodemographic Characteristics with Radiation Therapy Modality Use in the Medicare Population