International Expert-Based Consensus Definition, Staging Criteria, and Minimum Data Elements for Osteoradionecrosis of the Jaw: An Inter-Disciplinary Modified Delphi Study.

Purpose: Osteoradionecrosis of the jaw (ORNJ) is a severe iatrogenic disease characterized by bone death after radiation therapy (RT) to the head and neck. With over 9 published definitions and at least 16 diagnostic/staging systems, the true incidence and severity of ORNJ are obscured by lack of a standard for disease definition and severity assessment, leading to inaccurate estimation of incidence, reporting ambiguity, and likely under-diagnosis worldwide. This study aimed to achieve consensus on an explicit definition and phenotype of ORNJ and related precursor states through data standardization to facilitate effective diagnosis, monitoring, and multidisciplinary management of ORNJ. Methods: The ORAL Consortium comprised 69 international experts, including representatives from medical, surgical, radiation oncology, and oral/dental disciplines. Using a web-based modified Delphi technique, panelists classified descriptive cases using existing staging systems, reviewed systems for feature extraction and specification, and iteratively classified cases based on clinical/imaging feature combinations. Results: The Consortium ORNJ definition was developed in alignment with SNOMED-CT terminology and recent ISOO-MASCC-ASCO guideline recommendations. Case review using existing ORNJ staging systems showed high rates of inability to classify (up to 76%). Ten consensus statements and nine minimum data elements (MDEs) were outlined for prospective collection and classification of precursor/ORNJ stages. Conclusion: This study provides an international, consensus-based definition and MDE foundation for standardized ORNJ reporting in cancer survivors treated with RT. Head and neck surgeons, radiation, surgical, medical oncologists, and dental specialists should adopt MDEs to enable scalable health information exchange and analytics. Work is underway to develop both a human- and machine-readable knowledge representation for ORNJ (i.e., ontology) and multidisciplinary resources for dissemination to improve ORNJ reporting in academic and community practice settings.

Clinical and prognostic differences in oropharyngeal squamous cell carcinoma in USA and Denmark, two HPV high-prevalence areas.

BACKGROUND: Uncertainty persists regarding clinical and treatment variations crucial to consider when comparing high human papillomavirus (HPV)-prevalence oropharyngeal squamous cell carcinoma (OPSCC) cohorts for accurate patient stratification and replicability of clinical trials across different geographical areas. METHODS: OPSCC patients were included from The University of Texas MD Anderson Cancer Center (UTMDACC), USA and from The University Hospital of Copenhagen, Denmark from 2015-2020, (n = 2484). Outcomes were 3-year overall survival (OS) and recurrence-free interval (RFI). Subgroup analyses were made for low-risk OPSCC patients (T1-2N0M0) and high-risk patients (UICC8 III-IV). RESULTS: There were significantly more HPV-positive (88.2 % vs. 63.1 %), males (89.4 % vs. 74.1 %), never-smokers (52.1 % vs. 23.7 %), lower UICC8-stage (I/II: 79.3 % vs. 68 %), and fewer patients treated with radiotherapy (RT) alone (14.8 % vs. 30.3 %) in the UTMDACC cohort. No difference in the adjusted OS was observed (hazard ratio [HR] 1.21, p = 0.23), but a significantly increased RFI HR was observed for the Copenhagen cohort (HR: 1.74, p = 0.003). Subgroup analyses of low- and high-risk patients revealed significant clinical and treatment differences. No difference in prognosis was observed for low-risk patients, but the prognosis for high-risk patients in the Copenhagen cohort was worse (OS HR 2.20, p = 0.004, RFI HR 2.80, p = 0.002). CONCLUSIONS: We identified significant differences in clinical characteristics, treatment modalities, and prognosis between a Northern European and Northern American OPSCC population. These differences are important to consider when comparing outcomes and for patient stratification in clinical trials, as reproducibility might be challenging.

Neoadjuvant Chemotherapy Alone or Combined with EGFR-Directed Targeted Therapy or Anti-PD-1 Immunotherapy for Locally Advanced Lacrimal Sac and Nasolacrimal Duct Carcinomas.

BACKGROUND/AIMS: We describe our findings in patients with locally advanced lacrimal sac and nasolacrimal duct (NLD) carcinoma who received neoadjuvant systemic therapy. METHODS: We identified patients with locally advanced primary lacrimal sac/NLD carcinoma treated with neoadjuvant systemic intravenous therapy at our institution during 2017-2019. RESULTS: The study included seven patients, four men and three women; the mean age was 60.4 years (range: 43-76). All patients had locally advanced disease with significant orbital soft tissue invasion with or without skull base invasion making eye-sparing surgery not feasible as an initial step. Three patients had poorly differentiated squamous cell carcinoma; two, invasive carcinoma with basaloid and squamous features; one, high-grade carcinoma with features suggestive of sebaceous differentiation; and one, undifferentiated carcinoma. The neoadjuvant regimens were cisplatin and docetaxel (n = 1); carboplatin and docetaxel (n = 1); paclitaxel and cetuximab (n = 1); carboplatin, paclitaxel, and cetuximab (EGFR inhibitor) (n = 2); cisplatin, docetaxel, and pembrolizumab (anti-PD-1 immunotherapy) (n = 1); and carboplatin, paclitaxel, and pembrolizumab (n = 1). All patients had radiologic disease regression, and one patient had radiologic near-complete response. After neoadjuvant therapy, all patients underwent wide local excision and adjuvant concurrent chemoradiation. Two patients had a complete pathologic response. At a median follow-up period of 13 months after chemoradiation (range, 8-54 months), all patients were alive without evidence of disease. One patient had nodal metastasis treated with lymph node dissection and adjuvant chemoradiation. CONCLUSIONS: Neoadjuvant systemic therapy can shrink tumors in patients with locally advanced primary lacrimal sac/NLD carcinoma with orbital or skull base invasion.

MR-guided stereotactic radiation therapy for head and neck cancers.

Purpose: MR-guided radiotherapy (MRgRT) has the advantage of utilizing high soft tissue contrast imaging to track daily changes in target and critical organs throughout the entire radiation treatment course. Head and neck (HN) stereotactic body radiation therapy (SBRT) has been increasingly used to treat localized lesions within a shorter timeframe. The purpose of this study is to examine the dosimetric difference between the step-and-shot intensity modulated radiation therapy (IMRT) plans on Elekta Unity and our clinical volumetric modulated arc therapy (VMAT) plans on Varian TrueBeam for HN SBRT. Method: Fourteen patients treated on TrueBeam sTx with VMAT treatment plans were re-planned in the Monaco treatment planning system for Elekta Unity MR-Linac (MRL). The plan qualities, including target coverage, conformity, homogeneity, nearby critical organ doses, gradient index and low dose bath volume, were compared between VMAT and Monaco IMRT plans. Additionally, we evaluated the Unity adaptive plans of adapt-to-position (ATP) and adapt-to-shape (ATS) workflows using simulated setup errors for five patients and assessed the outcomes of our treated patients. Results: Monaco IMRT plans achieved comparable results to VMAT plans in terms of target coverage, uniformity and homogeneity, with slightly higher target maximum and mean doses. The critical organ doses in Monaco IMRT plans all met clinical goals; however, the mean doses and low dose bath volumes were higher than in VMAT plans. The adaptive plans demonstrated that the ATP workflow may result in degraded target coverage and OAR doses for HN SBRT, while the ATS workflow can maintain the plan quality. Conclusion: The use of Monaco treatment planning and online adaptation can achieve dosimetric results comparable to VMAT plans, with the additional benefits of real-time tracking of target volume and nearby critical structures. This offers the potential to treat aggressive and variable tumors in HN SBRT and improve local control and treatment toxicity.

Optimizing Outpatient Radiation Oncology Consult Workflow by Using Time-Driven Activity-Based Costing: Efficiency and Financial Impacts.

PURPOSE: Clinical efficiency is a key component of value-based health care. Our objective here was to identify workflow inefficiencies by using time-driven activity-based costing (TDABC) and evaluate the implementation of a new clinical workflow in high-volume outpatient radiation oncology clinics. METHODS: Our quality improvement study was conducted with the Departments of GI, Genitourinary (GU), and Thoracic Radiation Oncology at a large academic cancer center and four community network sites. TDABC was used to create process maps and optimize workflow for outpatient consults. Patient encounter metrics were captured with a real-time status function in the electronic medical record. Time metrics were compared using Mann-Whitney U tests. RESULTS: Individual patient encounter data for 1,328 consults before the intervention and 1,234 afterward across all sections were included. The median overall cycle time was reduced by 21% in GI (19 minutes), 18% in GU (16 minutes), and 12% at the community sites (9 minutes). The median financial savings per consult were $52 in US dollars (USD) for the GI, $33 USD for GU, $30 USD for thoracic, and $42 USD for the community sites. Patient satisfaction surveys (from 127 of 228 patients) showed that 99% of patients reported that their providers spent adequate time with them and 91% reported being seen by a care provider in a timely manner. CONCLUSION: TDABC can effectively identify opportunities to improve clinical efficiency. Implementing workflow changes on the basis of our findings led to substantial reductions in overall encounter cycle times across several departments, as well as high patient satisfaction and significant financial savings.

Clinical acceptability of automatically generated lymph node levels and structures of deglutition and mastication for head and neck radiation therapy.

Background and Purpose: Auto-contouring of complex anatomy in computed tomography (CT) scans is a highly anticipated solution to many problems in radiotherapy. In this study, artificial intelligence (AI)-based auto-contouring models were clinically validated for lymph node levels and structures of swallowing and chewing in the head and neck. Materials and Methods: CT scans of 145 head and neck radiotherapy patients were retrospectively curated. One cohort (n = 47) was used to analyze seven lymph node levels and the other (n = 98) used to analyze 17 swallowing and chewing structures. Separate nnUnet models were trained and validated using the separate cohorts. For the lymph node levels, preference and clinical acceptability of AI vs human contours were scored. For the swallowing and chewing structures, clinical acceptability was scored. Quantitative analyses of the test sets were performed for AI vs human contours for all structures using overlap and distance metrics. Results: Median Dice Similarity Coefficient ranged from 0.77 to 0.89 for lymph node levels and 0.86 to 0.96 for chewing and swallowing structures. The AI contours were superior to or equally preferred to the manual contours at rates ranging from 75% to 91%; there was not a significant difference in clinical acceptability for nodal levels I-V for manual versus AI contours. Across all AI-generated lymph node level contours, 92% were rated as usable with stylistic to no edits. Of the 340 contours in the chewing and swallowing cohort, 4% required minor edits. Conclusions: An accurate approach was developed to auto-contour lymph node levels and chewing and swallowing structures on CT images for patients with intact nodal anatomy. Only a small portion of test set auto-contours required minor edits.

Lacrimal Gland Adenocarcinoma Clinicopathologic Features and Outcomes Compared With Those of Lacrimal Gland Adenoid Cystic Carcinoma.

PURPOSE: Lacrimal gland (LG) adenocarcinomas (ACs) are rare, with limited data. We compared clinicopathologic features and local recurrence, distant metastasis, and survival rates between LG AC and LG adenoid cystic carcinoma (ACC). METHODS: The records of LG AC patients treated from 2008 to 2022 and LG ACC patients treated from 1998 to 2022 at the same center were retrospectively reviewed. RESULTS: The study included 20 patients with AC; 10 de-novo AC, 10 ex-pleomorphic AC; and 51 ACC patients. The median age at diagnosis was 61 years for de-novo AC, 54 years for ex-pleomorphic AC, and 45 years for ACC. All groups had male predominance. The initial T category was T2 in 50% (5/10) of de-novo ACs; 60% (6/10) of ex-pleomorphic ACs; and 59% (30/51) of ACCs. Perineural invasion was present in 33% (5/15) of ACs and 90% (45/50) of ACCs (p < 0.001). Of the 20 AC patients, 14 had eye-sparing surgery; 4 had orbital exenteration; and 2 had unresectable disease. All AC patients received postoperative radiotherapy and 15 (75%) received concurrent chemotherapy. Fourteen AC patients were tested for human growth factor receptor 2 expression, and 10 (71%) were human growth factor receptor 2 positive; 5 received human growth factor receptor 2-targeted therapy. AC and ACC had similar 5-year recurrence rates (20% and 33%, respectively, p = 0.31) and metastasis rates (20% and 34%, respectively, p = 0.30). de-novo AC, ex-pleomorphic AC, and ACC had similar 5-year disease-specific survival rates (80%, 79%, and 81%, respectively, p > 0.99). CONCLUSIONS: LG AC and ACC have similar baseline clinicopathologic features, except that perineural invasion is more common in ACC, and similar recurrence, metastasis, and survival rates. Human growth factor receptor 2-targeted therapy may be appropriate in some patients with LG AC.

Revisiting Feeding Tube Utilization in Oropharynx Cancer: 6-Year Prospective Registry Analysis.

OBJECTIVE: Patients treated for oropharyngeal cancer (OPC) have historically demonstrated high feeding tube rates for decreased oral intake and malnutrition. We re-examined feeding tube practices in these patients. STUDY DESIGN: Retrospective analysis of prospective cohort from 2015 to 2021. SETTING: Single-institution NCI-Designated Comprehensive Cancer Center. METHODS: With IRB approval, patients with new oropharyngeal squamous cell cancer or (unknown primary with neck metastasis) were enrolled. Baseline swallowing was assessed via videofluoroscopy and Performance Status Scale for Head and Neck Cancer (PSSHN). G-tubes or nasogastric tubes (NGT) were placed for weight loss before, during, or after treatment. Prophylactic NGT were placed during transoral robotic surgery (TORS). Tube duration was censored at last disease-free follow-up. Multivariate regression was performed for G-tube placement (odds ratio [OR] [95% confidence interval [CI]) and removal (Cox hazard ratio, hazard ratio [HR] [95% CI]). RESULTS: Of 924 patients, most had stage I to II (81%), p16+ (89%), node-positive (88%) disease. Median follow-up was 2.6 years (interquartile range 1.5-3.9). Most (91%) received radiation/chemoradiation, and 16% received TORS. G-tube rate was 27% (5% after TORS). G-tube risk was increased with chemoradiation (OR 2.78 [1.87-4.22]) and decreased with TORS (OR 0.31 [0.15-0.57]) and PSSHN-Diet score ≥60 (OR 0.26 [0.15-0.45]). G-tube removal probability over time was lower for T3 to T4 tumors (HR 0.52 [0.38-0.71]) and higher for PSSHN-Diet score ≥60 (HR 1.65 [1.03-2.66]). CONCLUSIONS: In this modern cohort of patients treated for OPC, 27% received G-tubes-50% less than institutional rates 10 years ago. Patients with preserved baseline swallowing and/or those eligible for TORS may have lower G-tube risk and duration.

Comparison of Machine Leaning Models for Prediction of Acute Pain Severity and On-Treatment Opioid Utilization in Oral Cavity and Oropharyngeal Cancer Patients Receiving Radiation Therapy: Exploratory Analysis from a Large-Scale Retrospective Cohort.

Background: Acute pain is a common and debilitating symptom experienced by oral cavity and oropharyngeal cancer (OC/OPC) patients undergoing radiation therapy (RT). Uncontrolled pain can result in opioid overuse and increased risks of long-term opioid dependence. The specific aim of this exploratory analysis was the prediction of severe acute pain and opioid use in the acute on-treatment setting, to develop risk-stratification models for pragmatic clinical trials. Materials and Methods: A retrospective study was conducted on 900 OC/OPC patients treated with RT during 2017 to 2023. Clinical data including demographics, tumor data, pain scores and medication data were extracted from patient records. On-treatment pain intensity scores were assessed using a numeric rating scale (0-none, 10-worst) and total opioid doses were calculated using morphine equivalent daily dose (MEDD) conversion factors. Analgesics efficacy was assessed based on the combined pain intensity and the total required MEDD. ML models, including Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), and Gradient Boosting Model (GBM) were developed and validated using ten-fold cross-validation. Performance of models were evaluated using discrimination and calibration metrics. Feature importance was investigated using bootstrap and permutation techniques. Results: For predicting acute pain intensity, the GBM demonstrated superior area under the receiver operating curve (AUC) (0.71), recall (0.39), and F1 score (0.48). For predicting the total MEDD, LR outperformed other models in the AUC (0.67). For predicting the analgesics efficacy, SVM achieved the highest specificity (0.97), and best calibration (ECE of 0.06), while RF and GBM achieved the same highest AUC, 0.68. RF model emerged as the best calibrated model with ECE of 0.02 for pain intensity prediction and 0.05 for MEDD prediction. Baseline pain scores and vital signs demonstrated the most contributed features for the different predictive models. Conclusion: These ML models are promising in predicting end-of-treatment acute pain and opioid requirements and analgesics efficacy in OC/OPC patients undergoing RT. Baseline pain score, vital sign changes were identified as crucial predictors. Implementation of these models in clinical practice could facilitate early risk stratification and personalized pain management. Prospective multicentric studies and external validation are essential for further refinement and generalizability.

Orbital and periocular complications in patients with sinonasal tumours with orbital invasion.

AIMS: The purpose of this study was to determine the frequency and associated risk factors of orbital/periocular complications in patients with sinonasal tumour with orbital invasion managed with eye-sparing treatments. METHODS: A retrospective case series of patients with primary sinonasal tumour with orbital invasion from January 2008 to December 2018. Patient factors were compared between the following groups: (1)patients with orbital/periocular complications versus those who did not and (2) patients who needed secondary oculoplastic surgical procedures versus those who did not. RESULTS: Out of 80 patients, 48 had eye-sparing surgery, 8 had orbital exenteration and 24 were managed non-surgically. The most common histology was squamous cell carcinoma (n=28, 35%). Among the eye-sparing treatment group, 51/72 patients experienced one or more orbital/periocular complication(s), with motility deficit (N=26, 36%) being the most frequent. Factors associated with higher risk of complications included tumour involving the orbital floor (p=0.019), clinical disease stage III/IV (p=0.038), maxillectomy (p=0.004), resection of the orbital floor (p=0.027) and cigarette smoking (p=0.041). Tumour involving the orbital floor had an OR of 3.9 (95% CI 1.3 to 11.6, p=0.016) in predicting orbital/periocular complication. In the eye-sparing surgery group, the most frequent secondary oculoplastic procedures was dacryocystorhinostomy (n=6, 13%). The use of a free flap in reconstruction had an OR of 8.2 (95% CI 2.1 to 31.8, p=0.002) in predicting need for secondary oculoplastic surgery. CONCLUSION: Majority of patients with sinonasal tumours and secondary orbital invasion were managed with eye-sparing multidisciplinary treatments. Preservation of the eye can lead to reasonably good functional outcome despite expected orbital and periocular complications.

Patterns of failure for recurrent head and neck squamous cell carcinoma treated with salvage surgery and postoperative IMRT reirradiation.

Purpose/Objectives: The purpose of this study was to evaluate patterns of locoregional recurrence (LRR) after surgical salvage and adjuvant reirradiation with IMRT for recurrent head and neck squamous cell cancer (HNSCC). Materials/Methods: Patterns of LRR for 61 patients treated consecutively between 2003 and 2014 who received post-operative IMRT reirradiation to ≥ 60 Gy for recurrent HNSCC were determined by 2 methods: 1) physician classification via visual comparison of post-radiotherapy imaging to reirradiation plans; and 2) using deformable image registration (DIR). Those without evaluable CT planning image data were excluded. All recurrences were verified by biopsy or radiological progression. Failures were defined as in-field, marginal, or out-of-field. Logistic regression analyses were performed to identify predictors for LRR. Results: A total of 55 patients were eligible for analysis and 23 (42 %) had documented LRR after reirradiation. Location of recurrent disease prior to salvage surgery (lymphatic vs. mucosal) was the most significant predictor of LRR after post-operative reirradiation with salvage rate of 67 % for lymphatic vs. 33 % for mucosal sites (p = 0.037). Physician classification of LRR yielded 14 (61 %) in-field failures, 3 (13 %) marginal failures, and 6 (26 %) out-of-field failures, while DIR yielded 10 (44 %) in-field failures, 4 (17 %) marginal failures, and 9 (39 %) out-of-field failures. Most failures (57 %) occurred within the original site of recurrence or first echelon lymphatic drainage. Of patients who had a free flap placed during salvage surgery, 56 % of failures occurred within 1 cm of the surgical flap. Conclusion: Our study highlights the role of DIR in enhancing the accuracy and consistency of POF analysis. Compared to traditional visual inspection, DIR reduces interobserver variability and provides more nuanced insights into dose-specific and spatial parameters of locoregional recurrences. Additionally, the study identifies the location of the initial recurrence as a key predictor of subsequent locoregional recurrence after salvage surgery and re-IMRT.

Artificial Intelligence and Machine Learning in Cancer Related Pain: A Systematic Review.

Background/objective: Pain is a challenging multifaceted symptom reported by most cancer patients, resulting in a substantial burden on both patients and healthcare systems. This systematic review aims to explore applications of artificial intelligence/machine learning (AI/ML) in predicting pain-related outcomes and supporting decision-making processes in pain management in cancer. Methods: A comprehensive search of Ovid MEDLINE, EMBASE and Web of Science databases was conducted using terms including "Cancer", "Pain", "Pain Management", "Analgesics", "Opioids", "Artificial Intelligence", "Machine Learning", "Deep Learning", and "Neural Networks" published up to September 7, 2023. The screening process was performed using the Covidence screening tool. Only original studies conducted in human cohorts were included. AI/ML models, their validation and performance and adherence to TRIPOD guidelines were summarized from the final included studies. Results: This systematic review included 44 studies from 2006-2023. Most studies were prospective and uni-institutional. There was an increase in the trend of AI/ML studies in cancer pain in the last 4 years. Nineteen studies used AI/ML for classifying cancer patients' pain development after cancer therapy, with median AUC 0.80 (range 0.76-0.94). Eighteen studies focused on cancer pain research with median AUC 0.86 (range 0.50-0.99), and 7 focused on applying AI/ML for cancer pain management decisions with median AUC 0.71 (range 0.47-0.89). Multiple ML models were investigated with. median AUC across all models in all studies (0.77). Random forest models demonstrated the highest performance (median AUC 0.81), lasso models had the highest median sensitivity (1), while Support Vector Machine had the highest median specificity (0.74). Overall adherence of included studies to TRIPOD guidelines was 70.7%. Lack of external validation (14%) and clinical application (23%) of most included studies was detected. Reporting of model calibration was also missing in the majority of studies (5%). Conclusion: Implementation of various novel AI/ML tools promises significant advances in the classification, risk stratification, and management decisions for cancer pain. These advanced tools will integrate big health-related data for personalized pain management in cancer patients. Further research focusing on model calibration and rigorous external clinical validation in real healthcare settings is imperative for ensuring its practical and reliable application in clinical practice.

Systematic Review of Genetic Polymorphisms Associated with Acute Pain Induced by Radiotherapy for Head and Neck Cancers.

Background/objective: Pain is the most common acute symptom following radiation therapy (RT) for head and neck cancer (HNC). The multifactorial origin of RT-induced pain makes it highly challenging to manage. Multiple studies were conducted to identify genetic variants associated with cancer pain, however few of them focused on RT-induced acute pain. In this review, we summarize the potential mechanisms of acute pain after RT in HNC and identify genetic variants associated with RT-induced acute pain and relevant acute toxicities. Methods: A comprehensive search of Ovid Medline, EMBASE and Web of Science databases using terms including "Variants", "Polymorphisms", "Radiotherapy", "Acute pain", "Acute toxicity" published up to February 28, 2022, was performed by two reviewers. Review articles and citations were reviewed manually. The identified SNPs associated with RT-induced acute pain and toxicities were reported, and the molecular functions of the associated genes were described based on genetic annotation using The Human Gene Database; GeneCards. Results: A total of 386 articles were identified electronically and 8 more articles were included after manual search. 21 articles were finally included. 32 variants in 27 genes, of which 25% in inflammatory/immune response, 20% had function in DNA damage response and repair, 20% in cell death or cell cycle, were associated with RT-inflammatory pain and acute oral mucositis or dermatitis. 4 variants in 4 genes were associated with neuropathy and neuropathic pain. 5 variants in 4 genes were associated with RT-induced mixed types of post-RT-throat/neck pain. Conclusion: Different types of pain develop after RT in HNC, including inflammatory pain; neuropathic pain; nociceptive pain; and mixed oral pain. Genetic variants involved in DNA damage response and repair, cell death, inflammation and neuropathic pathways may affect pain presentation post-RT. These variants could be used for personalized pain management in HNC patients receiving RT.

Hypothyroidism following Radiotherapy for Head and Neck Cancer: A Systematic Review of the Literature and Opportunities to Improve the Therapeutic Ratio.

(1) Background: Radiotherapy (RT) is a central component for the treatment of many head and neck cancers. In this systematic review of the literature, we aimed to characterize and quantify the published evidence on RT-related hypothyroidism, including estimated incidence, clinical risk factors, and dosimetric parameters that may be used to guide clinical decision making. Furthermore, we aimed to identify potential areas of improvement in the prevention and clinical management of RT-induced hypothyroidism, including the role of modern advanced therapeutic techniques. (2) Methods: We conducted a systemic review of the literature in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. PubMed and Google Scholar were searched to identify original research articles describing the incidence, mechanism, dosimetry, treatment, or prevention of radiation-related hypothyroidism for adults receiving RT for the treatment of head and neck cancers. The snowball method was used to identify additional articles. For identified articles, we tabulated several datapoints, including publication date, patient sample size, estimated hypothyroidism incidence, cancer site/type, follow-up period, radiation modality and technique, use of multimodality therapy, method of thyroid function evaluation, and proposed dosimetric predictors of hypothyroidism. (3) Results: One hundred and eleven articles met inclusion criteria, reflecting a range of head and neck cancer subtypes. There was a large variation in the estimated incidence of RT-related hypothyroidism, with a median estimate of 36% (range 3% to 79%). Reported incidence increased in later publication dates, which was likely related to improved screening and longer follow up. There were a wide variety of predictive metrics used to identify patients at high risk of hypothyroidism, the most common of which were volumetric and mean dosimetrics related to the thyroid gland (Vxx%, Dmean). More recently, there has been increasing evidence to suggest that the thyroid gland volume itself and the volume of the thyroid gland spared from high-dose radiation (VSxx) may better predict thyroid function after RT. There were no identified studies investigating the role of advanced radiotherapeutic techniques such as MRI-guided RT or particle therapy to decrease RT-related hypothyroidism. Conclusions: Hypothyroidism is a common toxicity resulting from therapeutic radiation for head and neck cancer with recent estimates suggesting 40-50% of patients may experience hypothyroidism after treatment. Dosimetric predictive models are increasingly able to accurately identify patients at risk of hypothyroidism, especially those utilizing thyroid VS metrics. Further investigation regarding the potential for advanced radiotherapeutic therapies to decrease RT-induced thyroid dysfunction is needed.

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-organ spatial stratification of 3-D dose distributions improves risk prediction of long-term self-reported severe symptoms in oropharyngeal cancer patients receiving radiotherapy: development of a pre-treatment decision support tool.

Purpose: Identify Oropharyngeal cancer (OPC) patients at high-risk of developing long-term severe radiation-associated symptoms using dose volume histograms for organs-at-risk, via unsupervised clustering. Material and methods: All patients were treated using radiation therapy for OPC. Dose-volume histograms of organs-at-risk were extracted from patients' treatment plans. Symptom ratings were collected via the MD Anderson Symptom Inventory (MDASI) given weekly during, and 6 months post-treatment. Drymouth, trouble swallowing, mucus, and vocal dysfunction were selected for analysis in this study. Patient stratifications were obtained by applying Bayesian Mixture Models with three components to patient's dose histograms for relevant organs. The clusters with the highest total mean doses were translated into dose thresholds using rule mining. Patient stratifications were compared against Tumor staging information using multivariate likelihood ratio tests. Model performance for prediction of moderate/severe symptoms at 6 months was compared against normal tissue complication probability (NTCP) models using cross-validation. Results: A total of 349 patients were included for long-term symptom prediction. High-risk clusters were significantly correlated with outcomes for severe late drymouth (p <.0001, OR = 2.94), swallow (p = .002, OR = 5.13), mucus (p = .001, OR = 3.18), and voice (p = .009, OR = 8.99). Simplified clusters were also correlated with late severe symptoms for drymouth (p <.001, OR = 2.77), swallow (p = .01, OR = 3.63), mucus (p = .01, OR = 2.37), and voice (p <.001, OR = 19.75). Proposed cluster stratifications show better performance than NTCP models for severe drymouth (AUC.598 vs.559, MCC.143 vs.062), swallow (AUC.631 vs.561, MCC.20 vs -.030), mucus (AUC.596 vs.492, MCC.164 vs -.041), and voice (AUC.681 vs.555, MCC.181 vs -.019). Simplified dose thresholds also show better performance than baseline models for predicting late severe ratings for all symptoms. Conclusion: Our results show that leveraging the 3-D dose histograms from radiation therapy plan improves stratification of patients according to their risk of experiencing long-term severe radiation associated symptoms, beyond existing NTPC models. Our rule-based method can approximate our stratifications with minimal loss of accuracy and can proactively identify risk factors for radiation-associated toxicity.

Identification of Key Elements in Prostate Cancer for Ontology Building via a Multidisciplinary Consensus Agreement.

BACKGROUND: Clinical data collection related to prostate cancer (PCa) care is often unstructured or heterogeneous among providers, resulting in a high risk for ambiguity in its meaning when sharing or analyzing data. Ontologies, which are shareable formal (i.e., computable) representations of knowledge, can address these challenges by enabling machine-readable semantic interoperability. The purpose of this study was to identify PCa-specific key data elements (KDEs) for standardization in clinic and research. METHODS: A modified Delphi method using iterative online surveys was performed to report a consensus agreement on KDEs by a multidisciplinary panel of 39 PCa specialists. Data elements were divided into three themes in PCa and included (1) treatment-related toxicities (TRT), (2) patient-reported outcome measures (PROM), and (3) disease control metrics (DCM). RESULTS: The panel reached consensus on a thirty-item, two-tiered list of KDEs focusing mainly on urinary and rectal symptoms. The Expanded Prostate Cancer Index Composite (EPIC-26) questionnaire was considered most robust for PROM multi-domain monitoring, and granular KDEs were defined for DCM. CONCLUSIONS: This expert consensus on PCa-specific KDEs has served as a foundation for a professional society-endorsed, publicly available operational ontology developed by the American Association of Physicists in Medicine (AAPM) Big Data Sub Committee (BDSC).