Development and Standardization of an Osteoradionecrosis Classification System in Head and Neck Cancer: Implementation of a Risk-Based Model.

PURPOSE: Osteoradionecrosis of the jaw (ORN) can manifest in varying severity. The aim of this study is to identify ORN risk factors and develop a novel classification to depict the severity of ORN. METHODS: Consecutive patients with head and neck cancer (HNC) treated with curative-intent intensity-modulated radiation therapy (IMRT) (≥45 Gy) from 2011 to 2017 were included. Occurrence of ORN was identified from in-house prospective dental and clinical databases and charts. Multivariable logistic regression model was used to identify risk factors and stratify patients into high-risk and low-risk groups. A novel ORN classification system was developed to depict ORN severity by modifying existing systems and incorporating expert opinion. The performance of the novel system was compared with 15 existing systems for their ability to identify and predict serious ORN event (jaw fracture or requiring jaw resection). RESULTS: ORN was identified in 219 of 2,732 (8%) consecutive patients with HNC. Factors associated with high risk of ORN were oral cavity or oropharyngeal primaries, received IMRT dose ≥60 Gy, current/ex-smokers, and/or stage III to IV periodontal condition. The ORN rate for high-risk versus low-risk patients was 12.7% versus 3.1% (P < .001) with an AUC of 0.71. Existing ORN systems overclassified serious ORN events and failed to recognize maxillary ORN. A novel ORN classification system, ClinRad, was proposed on the basis of vertical extent of bone necrosis and presence/absence of exposed bone/fistula. This system detected serious ORN events in 5.7% of patients and statistically outperformed existing systems. CONCLUSION: We identified risk factors for ORN and proposed a novel ORN classification system on the basis of vertical extent of bone necrosis and presence/absence of exposed bone/fistula. It outperformed existing systems in depicting the seriousness of ORN and may facilitate clinical care and clinical trials.

Causes and impact of delays during the COVID-19 pandemic on head and neck cancer diagnosis.

BACKGROUND: The causes for delays during the COVID19 pandemic and their impact on head and neck cancer (HNC) diagnosis and staging are not well described. METHODS: Two cohorts were defined a priori for review and analysis-a Pre-Pandemic cohort (June 1 to December 31, 2019) and a Pandemic cohort (June 1 to December 31, 2020). Delays were categorized as COVID-19 related or not, and as clinician, patient, or policy related. RESULTS: A total of 638 HNC patients were identified including 327 in the Pre-Pandemic Cohort and 311 in the Pandemic Cohort. Patients in the Pandemic cohort had more N2-N3 category (41% vs. 33%, p = 0.03), T3-T4 category (63% vs. 50%, p = 0.002), and stage III-IV (71% vs. 58%, p < 0.001) disease. Several intervals in the diagnosis to treatment pathway were significantly longer in the pandemic cohort as compared to the Pre-Pandemic cohort. Among the pandemic cohort, 146 (47%) experienced a delay, with 112 related to the COVID-19 pandemic; 80 (71%) were clinician related, 15 (13%) were patient related, and 17 (15%) were policy related. CONCLUSIONS: Patients in the Pandemic cohort had higher stage disease at diagnosis and longer intervals along the diagnostic pathway, with COVID-19 related clinician factors being the most common cause of delay.

Telemedicine-enabled biofeedback electropalatography rehabilitation (TEBER): A pilot study for patients treated with surgery for oral cavity carcinoma.

BACKGROUND: To address the rehabilitative barriers to frequency and precision of care, we conducted a pilot study of a biofeedback electropalatography (EPG) device paired with telemedicine for patients who underwent primary surgery +/- adjuvant radiation for oral cavity carcinoma. We hypothesized that lingual optimization followed by telemedicine-enabled biofeedback electropalatography rehabilitation (TEBER) would further improve speech and swallowing outcomes after "standard-of-care" SOC rehabilitation. METHOD: Pilot prospective 8-week (TEBER) program following 8 weeks of (SOC) rehabilitation. RESULTS: Twenty-seven patients were included and 11 completed the protocol. When examining the benefit of TEBER independent of standard of care, "range-of-liquids" improved by +0.36 [95% CI, 0.02-0.70, p = 0.05] and "range-of-solids" improved by +0.73 [95% CI, 0.12-1.34, p = 0.03]. There was a positive trend toward better oral cavity obliteration; residual volume decreased by -1.2 [95% CI, -2.45 to 0.053, p = 0.06], and "nutritional-mode" increased by +0.55 [95% CI, -0.15 to 1.24, p = 0.08]. CONCLUSION: This pilot suggests that TEBER bolsters oral rehabilitation after 8 weeks of SOC lingual range of motion.

Exploring the Language Used to Describe Older Patients at Multidisciplinary Cancer Conferences.

Older adults with cancer often present with distinct complexities that complicate their care, yet the language used to discuss their management at multidisciplinary cancer conferences (MCCs) remains poorly understood. A mixed methods study was conducted at a tertiary cancer centre in Toronto, Canada, where MCCs spanning five tumour sites were attended over six months. For presentations pertaining to a patient aged 75 or older, a standardized data collection form was used to record their demographic, cancer-related, and non-cancer-related information, as well as the presenter's specialty and training level. Descriptive statistics and thematic analysis were employed to explore MCC depictions of older patients (n = 75). Frailty status was explicitly mentioned in 20.0% of presentations, but discussions more frequently referenced comorbidity burden (50.7%), age (33.3%), and projected treatment tolerance (30.7%) as surrogate measures. None of the presentations included mentions of formal geriatric assessment (GA) or validated frailty tools; instead, presenters tended to feature select GA domains and subjective descriptions of appearance ("looks to be fit") or overall health ("relatively healthy"). In general, MCCs appeared to rely on age-focused language that may perpetuate ageism. Further work is needed to investigate how frailty and geriatric considerations can be objectively incorporated into discussions in geriatric oncology.

RADCURE: An open-source head and neck cancer CT dataset for clinical radiation therapy insights.

PURPOSE: This manuscript presents RADCURE, one of the most extensive head and neck cancer (HNC) imaging datasets accessible to the public. Initially collected for clinical radiation therapy (RT) treatment planning, this dataset has been retrospectively reconstructed for use in imaging research. ACQUISITION AND VALIDATION METHODS: RADCURE encompasses data from 3346 patients, featuring computed tomography (CT) RT simulation images with corresponding target and organ-at-risk contours. These CT scans were collected using systems from three different manufacturers. Standard clinical imaging protocols were followed, and contours were manually generated and reviewed at weekly RT quality assurance rounds. RADCURE imaging and structure set data was extracted from our institution's radiation treatment planning and oncology information systems using a custom-built data mining and processing system. Furthermore, images were linked to our clinical anthology of outcomes data for each patient and includes demographic, clinical and treatment information based on the 7th edition TNM staging system (Tumor-Node-Metastasis Classification System of Malignant Tumors). The median patient age is 63, with the final dataset including 80% males. Half of the cohort is diagnosed with oropharyngeal cancer, while laryngeal, nasopharyngeal, and hypopharyngeal cancers account for 25%, 12%, and 5% of cases, respectively. The median duration of follow-up is five years, with 60% of the cohort surviving until the last follow-up point. DATA FORMAT AND USAGE NOTES: The dataset provides images and contours in DICOM CT and RT-STRUCT formats, respectively. We have standardized the nomenclature for individual contours-such as the gross primary tumor, gross nodal volumes, and 19 organs-at-risk-to enhance the RT-STRUCT files' utility. Accompanying demographic, clinical, and treatment data are supplied in a comma-separated values (CSV) file format. This comprehensive dataset is publicly accessible via The Cancer Imaging Archive. POTENTIAL APPLICATIONS: RADCURE's amalgamation of imaging, clinical, demographic, and treatment data renders it an invaluable resource for a broad spectrum of radiomics image analysis research endeavors. Researchers can utilize this dataset to advance routine clinical procedures using machine learning or artificial intelligence, to identify new non-invasive biomarkers, or to forge prognostic models.

Development and Standardization of a Classification System for Osteoradionecrosis: Implementation of a Risk-Based Model.

Purpose: Osteoradionecrosis of the jaw (ORN) can manifest in varying severity. The aim of this study is to identify ORN risk factors and develop a novel classification to depict the severity of ORN. Methods: Consecutive head-and-neck cancer (HNC) patients treated with curative-intent IMRT (≥ 45Gy) in 2011-2018 were included. Occurrence of ORN was identified from in-house prospective dental and clinical databases and charts. Multivariable logistic regression model was used to identify risk factors and stratify patients into high-risk and low-risk groups. A novel ORN classification system was developed to depict ORN severity by modifying existing systems and incorporating expert opinion. The performance of the novel system was compared to fifteen existing systems for their ability to identify and predict serious ORN event (jaw fracture or requiring jaw resection). Results: ORN was identified in 219 out of 2732 (8%) consecutive HNC patients. Factors associated with high-risk of ORN were: oral-cavity or oropharyngeal primaries, received IMRT dose ≥60Gy, current/ex-smokers, and/or stage III-IV periodontal disease. The ORN rate for high-risk vs low-risk patients was 12.7% vs 3.1% (p<0.001) with an area-under-the-receiver-operating-curve (AUC) of 0.71. Existing ORN systems overclassified serious ORN events and failed to recognize maxillary ORN. A novel ORN classification system, RadORN, was proposed based on vertical extent of bone necrosis and presence/absence of exposed bone/fistula. This system detected serious ORN events in 5.7% of patients and statistically outperformed existing systems. Conclusion: We identified risk factors for ORN, and proposed a novel ORN classification system based on vertical extent of bone necrosis and presence/absence of exposed bone/fistula. It outperformed existing systems in depicting the seriousness of ORN, and may facilitate clinical care and clinical trials.

Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics.

Artificial intelligence (AI) and machine learning (ML) are becoming critical in developing and deploying personalized medicine and targeted clinical trials. Recent advances in ML have enabled the integration of wider ranges of data including both medical records and imaging (radiomics). However, the development of prognostic models is complex as no modeling strategy is universally superior to others and validation of developed models requires large and diverse datasets to demonstrate that prognostic models developed (regardless of method) from one dataset are applicable to other datasets both internally and externally. Using a retrospective dataset of 2,552 patients from a single institution and a strict evaluation framework that included external validation on three external patient cohorts (873 patients), we crowdsourced the development of ML models to predict overall survival in head and neck cancer (HNC) using electronic medical records (EMR) and pretreatment radiological images. To assess the relative contributions of radiomics in predicting HNC prognosis, we compared 12 different models using imaging and/or EMR data. The model with the highest accuracy used multitask learning on clinical data and tumor volume, achieving high prognostic accuracy for 2-year and lifetime survival prediction, outperforming models relying on clinical data only, engineered radiomics, or complex deep neural network architecture. However, when we attempted to extend the best performing models from this large training dataset to other institutions, we observed significant reductions in the performance of the model in those datasets, highlighting the importance of detailed population-based reporting for AI/ML model utility and stronger validation frameworks. We have developed highly prognostic models for overall survival in HNC using EMRs and pretreatment radiological images based on a large, retrospective dataset of 2,552 patients from our institution.Diverse ML approaches were used by independent investigators. The model with the highest accuracy used multitask learning on clinical data and tumor volume.External validation of the top three performing models on three datasets (873 patients) with significant differences in the distributions of clinical and demographic variables demonstrated significant decreases in model performance. Significance: ML combined with simple prognostic factors outperformed multiple advanced CT radiomics and deep learning methods. ML models provided diverse solutions for prognosis of patients with HNC but their prognostic value is affected by differences in patient populations and require extensive validation.

Using Recurrent Neural Networks to Extract High-Quality Information From Lung Cancer Screening Computerized Tomography Reports for Inter-Radiologist Audit and Feedback Quality Improvement.

PURPOSE: Lung cancer screening programs generate a high volume of low-dose computed tomography (LDCT) reports that contain valuable information, typically in a free-text format. High-performance named-entity recognition (NER) models can extract relevant information from these reports automatically for inter-radiologist quality control. METHODS: Using LDCT report data from a longitudinal lung cancer screening program (8,305 reports; 3,124 participants; 2006-2019), we trained a rule-based model and two bidirectional long short-term memory (Bi-LSTM) NER neural network models to detect clinically relevant information from LDCT reports. Model performance was tested using F1 scores and compared with a published open-source radiology NER model (Stanza) in an independent evaluation set of 150 reports. The top performing model was applied to a data set of 6,948 reports for an inter-radiologist quality control assessment. RESULTS: The best performing model, a Bi-LSTM NER recurrent neural network model, had an overall F1 score of 0.950, which outperformed Stanza (F1 score = 0.872) and a rule-based NER model (F1 score = 0.809). Recall (sensitivity) for the best Bi-LSTM model ranged from 0.916 to 0.991 for different entity types; precision (positive predictive value) ranged from 0.892 to 0.997. Test performance remained stable across time periods. There was an average of a 2.86-fold difference in the number of identified entities between the most and the least detailed radiologists. CONCLUSION: We built an open-source Bi-LSTM NER model that outperformed other open-source or rule-based radiology NER models. This model can efficiently extract clinically relevant information from lung cancer screening computerized tomography reports with high accuracy, enabling efficient audit and feedback to improve quality of patient care.

The collateral impact of the COVID-19 pandemic on HPV-positive oropharyngeal cancer diagnosis.

PURPOSE: We aim to assess the potential impact of the COVID-19 pandemic on diagnostic delays in HPV-positive oropharyngeal cancer (OPC), and to describe their underlying reasons. METHODS: All HPV + OPC referred to a tertiary cancer centre and diagnosed between June-December 2019 (Pre-Pandemic cohort) vs June-December 2020 (Pandemic cohort) were reviewed. TNM classification, gross-tumor-volumes (GTV) and intervals between sign/symptom onset and treatment initiation were compared between the cohorts. Reasons for delay (>6 months from onset of signs/symptoms to a positive biopsy of the primary tumor, or a delay specifically mentioned in the patient chart) in establishing the diagnosis were recorded per clinician's documentation, and categorized as COVID-related or non-COVID-related. RESULTS: A total of 157 consecutive HPV + OPC patients were identified (Pre-Pandemic: 92; Pandemic: 65). Compared to the Pre-Pandemic cohort, Pandemic cohort patients had a higher proportion of N2-N3 (32 % vs 15 %, p = 0.019) and stage III (38 % vs 23 %, p = 0.034) disease at presentation. The differences in proportions with > 6 months delay from symptom onset to establishing the diagnosis (29 % vs 20 %, p = 0.16) or to first treatment (49 % vs 38 %, p = 0.22) were not statistically different. 47 % of diagnostic delays in the Pandemic cohort were potentially attributable to COVID-19. CONCLUSION: We observed a collateral impact of the COVID-19 pandemic on HPV + OPC care through more advanced stage at presentation and a non-significant but numerically longer interval to diagnosis. This could adversely impact patient outcomes and future resource allocation. Both COVID-19-related and unrelated factors contribute to diagnostic delays. Tailored interventions to reduce delays are warranted.

Head and neck cancer predictive risk estimator to determine control and therapeutic outcomes of radiotherapy (HNC-PREDICTOR): development, international multi-institutional validation, and web implementation of clinic-ready model-based risk stratification for head and neck cancer.

BACKGROUND: Personalised radiotherapy can improve treatment outcomes of patients with head and neck cancer (HNC), where currently a 'one-dose-fits-all' approach is the standard. The aim was to establish individualised outcome prediction based on multi-institutional international 'big-data' to facilitate risk-based stratification of patients with HNC. METHODS: The data of 4611 HNC radiotherapy patients from three academic cancer centres were split into four cohorts: a training (n = 2241), independent test (n = 786), and external validation cohorts 1 (n = 1087) and 2 (n = 497). Tumour- and patient-related clinical variables were considered in a machine learning pipeline to predict overall survival (primary end-point) and local and regional tumour control (secondary end-points); serially, imaging features were considered for optional model improvement. Finally, patients were stratified into high-, intermediate-, and low-risk groups. RESULTS: Performance score, AJCC8thstage, pack-years, and Age were identified as predictors for overall survival, demonstrating good performance in both the training cohort (c-index = 0.72 [95% CI, 0.66-0.77]) and in all three validation cohorts (c-indices: 0.76 [0.69-0.83], 0.73 [0.68-0.77], and 0.75 [0.68-0.80]). Excellent stratification of patients with HNC into high, intermediate, and low mortality risk was achieved; with 5-year overall survival rates of 17-46% for the high-risk group compared to 92-98% for the low-risk group. The addition of morphological image feature further improved the performance (c-index = 0.73 [0.64-0.81]). These models are integrated in a clinic-ready interactive web interface: https://uic-evl.github.io/hnc-predictor/ CONCLUSIONS: Robust model-based prediction was able to stratify patients with HNC in distinct high, intermediate, and low mortality risk groups. This can effectively be capitalised for personalised radiotherapy, e.g., for tumour radiation dose escalation/de-escalation.

Clinical presentation and outcome of human papillomavirus-positive nasopharyngeal carcinoma in a North American cohort.

BACKGROUND: The objective of this study was to describe the clinical presentation and outcomes of human papillomavirus (HPV)-positive nasopharyngeal cancer (NPC) versus Epstein-Barr virus (EBV)-positive NPC and HPV-positive oropharyngeal cancer (OPC). METHODS: Clinical characteristics and presenting signs/symptoms were compared between patients who had viral-related NPC versus viral-related OPC treated with intensity-modulated radiotherapy from 2005 to 2020 and who were matched 1:1 (by tumor and lymph node categories, smoking, age, sex, histology, and year of diagnosis). Locoregional control (LRC), distant control (DC), and overall survival (OS) were compared using the 2005-2018 cohort to maintain 2 years of minimum follow-up. Multivariable analysis was used to evaluate the cohort effect. RESULTS: Similar to HPV-positive OPC (n = 1531), HPV-positive NPC (n = 29) occurred mostly in White patients compared with EBV-positive NPC (n = 422; 86% vs. 15%; p < .001). Primary tumor volumes were larger in HPV-positive NPC versus EBV-positive NPC (median volume, 51 vs. 23 cm3 ; p = .002), with marginally more Level IB nodal involvement. More patients with HPV-positive NPC complained of local pain (38% vs. 3%; p = .002). The median follow-up for the 2005-2018 cohort was 5.3 years. Patients who had HPV-positive NPC (n = 20) had rates of 3-year LRC (95% vs. 90%; p = .360), DC (75% vs. 87%; p = .188), and OS (84% vs. 89%; p = .311) similar to the rates in those who had EBV-positive NPC (n = 374). Patients who had HPV-positive NPC also had rates of LRC (95% vs. 94%; p = .709) and OS (84% vs. 87%; p = .440) similar to the rates in those who had HPV-positive OPC (n = 1287). The DC rate was lower in patients who had HPV-positive disease (75% vs. 90%; p = .046), but the difference became nonsignificant (p = .220) when the analysis was adjusted for tumor and lymph node categories, smoking, and chemotherapy. CONCLUSIONS: HPV-positive NPC and EBV-positive NPC seem to be mutually exclusive diseases. Patients who have HPV-positive NPC have greater local symptom burden and larger primary tumors but have similar outcomes compared with patients who have EBV-positive NPC or HPV-positive OPC.

Determining the Impact of Thickened Liquids on Swallowing in Patients Undergoing Irradiation for Oropharynx Cancer.

The current standard for the treatment of oropharynx cancers is radiation therapy. However, patients are frequently left with dysphagia characterized by penetration-aspiration (impaired safety) and residue (impaired efficiency). Although thickened liquids are commonly used to manage dysphagia, we lack evidence to guide the modification of liquids for clinical benefit in the head and neck cancer population. The objective of this study was to assess the impact of slightly and mildly thick liquids on penetration-aspiration and residue in 12 patients with oropharyngeal cancer who displayed penetration-aspiration on thin liquid within 3 to 6 months after completion of radiotherapy. Significantly fewer instances of penetration-aspiration were seen with slightly and mildly thick liquids as compared with thin (P < .05). No differences were found across stimuli in the frequency of residue. Patients with oropharyngeal cancers who present with post-radiation therapy dysphagia involving penetration-aspiration on thin liquids may benefit from slightly and mildly thick liquids without risk of worse residue.

A Comparison of Hypofractionated and Twice-Daily Thoracic Irradiation in Limited-Stage Small-Cell Lung Cancer: An Overlap-Weighted Analysis.

Despite evidence for the superiority of twice-daily (BID) radiotherapy schedules, their utilization in practice remains logistically challenging. Hypofractionation (HFRT) is a commonly implemented alternative. We aim to compare the outcomes and toxicities in limited-stage small-cell lung cancer (LS-SCLC) patients treated with hypofractionated versus BID schedules. A bi-institutional retrospective cohort review was conducted of LS-SCLC patients treated with BID (45 Gy/30 fractions) or HFRT (40 Gy/15 fractions) schedules from 2007 to 2019. Overlap weighting using propensity scores was performed to balance observed covariates between the two radiotherapy schedule groups. Effect estimates of radiotherapy schedule on overall survival (OS), locoregional recurrence (LRR) risk, thoracic response, any ≥grade 3 (including lung, and esophageal) toxicity were determined using multivariable regression modelling. A total of 173 patients were included in the overlap-weighted analysis, with 110 patients having received BID treatment, and 63 treated by HFRT. The median follow-up was 20.4 months. Multivariable regression modelling did not reveal any significant differences in OS (hazard ratio [HR] 1.67, p = 0.38), LRR risk (HR 1.48, p = 0.38), thoracic response (odds ratio [OR] 0.23, p = 0.21), any ≥grade 3+ toxicity (OR 1.67, p = 0.33), ≥grade 3 pneumonitis (OR 1.14, p = 0.84), or ≥grade 3 esophagitis (OR 1.41, p = 0.62). HFRT, in comparison to BID radiotherapy schedules, does not appear to result in significantly different survival, locoregional control, or toxicity outcomes.

Limited-stage small cell lung cancer: Outcomes associated with prophylactic cranial irradiation over a 20-year period at the Princess Margaret Cancer Centre.

BACKGROUND & PURPOSE: Prophylactic cranial irradiation (PCI) is recommended for limited-stage small-cell lung cancer (LS-SCLC) patients with good response to concurrent chemoradiation. We report our institution's 20-year experience with this patient population and associated clinical outcomes. MATERIALS & METHODS: A retrospective cohort of consecutive LS-SCLC patients treated with curative intent chemoradiation at our institution (1997-2018) was reviewed. Overall survival (OS) was calculated using the Kaplan-Meier method, and significant covariates determined by the Cox proportional hazards model. Covariates predictive of PCI were determined using Fisher's exact test and the Mann-Whitney test. Brain failure risk (BFR) was calculated using the cumulative incidence method treating death as a competing event. Treatment cohorts (historic vs. contemporary) were stratified by the median year of diagnosis (2005). RESULTS: A total of 369 patients with LS-SCLC were identified, of which 278 patients were notionally PCI eligible. PCI was given to 196 patients (71%). Younger age was associated with PCI utilization (p < 0.001). PCI utilization rates did not change between the historic and contemporary treatment era (p = 0.11), whereas magnetic resonance imaging (MRI) use at baseline and follow-up became more prevalent in the contemporary era (p = <0.001). On multivariable analysis, PCI utilization was associated with improved OS (HR 1.88, 95% CI 1.32-2.69) and decreased BFR (HR 4.66, 95% CI 2.58-8.40). Patients who had MRI follow-up had a higher incidence of BFR (HR 0.35, 95% CI 0.18-0.66) in multivariable analyses. CONCLUSIONS: For LS-SCLC patients at our institution, PCI is more frequently utilized in younger patients, and the utilization rate did not change significantly over the past 20 years. PCI was independently associated with improved OS and lower BFR. Omission of PCI in LS-SCLC patients should not be routinely practiced in the absence of further prospective data.

Prediction of Human Papillomavirus (HPV) Association of Oropharyngeal Cancer (OPC) Using Radiomics: The Impact of the Variation of CT Scanner.

Studies have shown that radiomic features are sensitive to the variability of imaging parameters (e.g., scanner models), and one of the major challenges in these studies lies in improving the robustness of quantitative features against the variations in imaging datasets from multi-center studies. Here, we assess the impact of scanner choice on computed tomography (CT)-derived radiomic features to predict the association of oropharyngeal squamous cell carcinoma with human papillomavirus (HPV). This experiment was performed on CT image datasets acquired from two different scanner manufacturers. We demonstrate strong scanner dependency by developing a machine learning model to classify HPV status from radiological images. These experiments reveal the effect of scanner manufacturer on the robustness of radiomic features, and the extent of this dependency is reflected in the performance of HPV prediction models. The results of this study highlight the importance of implementing an appropriate approach to reducing the impact of imaging parameters on radiomic features and consequently on the machine learning models, without removing features which are deemed non-robust but may contain learning information.

Transitions in oral and gut microbiome of HPV+ oropharyngeal squamous cell carcinoma following definitive chemoradiotherapy (ROMA LA-OPSCC study).

BACKGROUND: Oral and gut microbiomes have emerged as potential biomarkers in cancer. We characterised the oral and gut microbiomes in a prospective observational cohort of HPV+ oropharyngeal squamous cell carcinoma (OPSCC) patients and evaluated the impact of chemoradiotherapy (CRT). METHODS: Saliva, oropharyngeal swabs over the tumour site and stool were collected at baseline and post-CRT. 16S RNA and shotgun metagenomic sequencing were used to generate taxonomic profiles, including relative abundance (RA), bacterial density, α-diversity and ß-diversity. RESULTS: A total of 132 samples from 22 patients were analysed. Baseline saliva and swabs had similar taxonomic composition (R2 = 0.006; p = 0.827). Oropharyngeal swabs and stool taxonomic composition varied significantly by stage, with increased oral RA of Fusobacterium nucleatum observed in stage III disease (p < 0.05). CRT significantly reduced the species richness and increased the RA of gut-associated taxa in oropharyngeal swabs (p < 0.05), while it had no effect in stool samples. These findings remained significant when adjusted by stage, smoking status and antibiotic use. CONCLUSIONS: Baseline oral and gut microbiomes differ by stage in this HPV+ cohort. CRT caused a shift towards a gut-like microbiome composition in oropharyngeal swabs. Stage-specific features and the transitions in oral microbiome might have prognostic and therapeutic implications.

Validating impact of pretreatment tumor growth rate on outcome of early-stage lung cancer treated with stereotactic body radiation therapy.

BACKGROUND: To assess correlation of pretreatment specific growth rate (SGR) value of 0.43 × 10-2 with overall and failure-free survival of patients with early-stage non-small cell lung cancer (NSCLC) treated with stereotactic body radiation therapy (SBRT). METHODS: A retrospective chart review of 160 patients with pathologically confirmed stage I NSCLC treated with SBRT between June 2010 and December 2012 in a large, tertiary cancer institute was undertaken. Both diagnostic and archived planning CT were uploaded to the treatment planning system to determine tumor volume at diagnosis (GTV1) and planning time (GTV2). The time (t) between both CTs was recorded. SGR was calculated using GTV1, GTV2, and t. The median SGR (0.43 × 10-2 ) from our previous data was used to group patients into low and high SGR cohorts. Log-rank test was used to compare overall (OS) and failure-free survivals (FFS) of SGR groups. RESULTS: The median time interval between diagnostic and planning CT scans was 87 days. The median OS was 38 and 66 months for high and low SGR cohorts, respectively (P = 0.03). The median FFS was 27 and 55 months for high and low SGR cohorts, respectively (P = 0.005). High SGR (P < 0.05), male gender (P = <0.01), and GTV2 (P = <0.05) were associated with poorer FFS. CONCLUSIONS: High SGR was associated with poorer outcome in patients with early-stage NSCLC treated with SBRT. SGR can be used in conjunction with other well-known predictive factors to formulate a practical predictive model to identify subgroups of the patient at higher risk of recurrence after SBRT.

Mechanisms of Impaired Swallowing on Thin Liquids Following Radiation Treatment for Oropharyngeal Cancer.

Purpose Dysphagia is one of the most debilitating chronic symptoms experienced by patients who undergo radiation treatment for head and neck cancer. Despite the high prevalence of dysphagia in patients with head and neck cancer, we lack understanding of the specific changes in swallowing physiology that arise in the short-term following radiation therapy and how these changes impact the key functions of swallowing safety and efficiency. This study sought to identify pathophysiological mechanisms underlying impairments in swallowing safety and efficiency on thin liquids following (chemo)radiation for oropharyngeal cancer. Method Videofluoroscopic swallowing studies were completed in 12 male patients within 6 months following completion of (chemo)radiation and in 12 healthy male controls. To compare swallowing function and physiology between groups, we analyzed three discrete sips of 20% w/v thin liquid barium per participant. The videofluoroscopic swallowing study recordings were rated for swallowing safety, efficiency, timing parameters, and pixel-based measures of structural area or movement. Results The oropharyngeal cancer cohort displayed significantly higher frequencies of penetration-aspiration, incomplete laryngeal vestibule closure, prolonged time-to-laryngeal vestibule closure, and poor pharyngeal constriction. Incomplete or delayed laryngeal vestibule closure was associated with airway invasion, while poor pharyngeal constriction was associated with pharyngeal residue. Conclusions This study highlights the primary mechanisms behind impaired safety and efficiency of the swallow in patients following (chemo)radiation for oropharyngeal cancer.

Stereotactic Image Guided Lung Radiation Therapy for Clinical Early Stage Non-Small Cell Lung Cancer: A Long-Term Report From a Multi-Institutional Database of Patients Treated With or Without a Pathologic Diagnosis.

PURPOSE: Early stage lung cancer is treated with stereotactic body radiation therapy (SBRT) in patients who are unable or unwilling to undergo surgical resection. Some patients' comorbidities are so severe that they are unable to even undergo a biopsy. A clinical diagnosis without biopsy before SBRT has been used, but there are limited data on its efficacy. METHODS AND MATERIALS: Data on patients treated with SBRT for non-small cell lung cancer, with and without tissue confirmation, were collected from multiple institutions across Europe, Canada, and the United States. Patients with a minimum of 2 years of comprehensive follow up were selected for analysis. Treatment and patient characteristics were compared. Overall survival (OS), disease-free survival (DFS), cause-specific survival (CSS), and rates of local recurrence (LR), regional recurrence (RR), and distant metastasis (DM) were calculated and analyzed. RESULTS: A total of 701 patients were identified, of which 67% had tissue confirmation of their tumors. The 3- and 5-year outcomes for OS, CSS, and DFS were 83.8%, 93.1%, 69%, and 60.6%, 86.7%, 45.5%, respectively. The rates for LR, RR, and DM at 3 and 5 years were 6.4%, 9.3%, 14.3%, and 10.5%, 14.3%, 19.7%, respectively. There were no statistically significant differences in survival outcomes or recurrences between the biopsy and no-biopsy cohorts. CONCLUSIONS: SBRT for clinically diagnosed lung cancers is efficacious in appropriately selected patients, with similar outcomes as those with a pathologic diagnosis. Thorough clinical and radiographic evaluations in a multidisciplinary setting are critical to the management of these patients.