Telehealth as a Strategy for Health Equity: A Scoping Review of Telehealth in India During and Following the COVID-19 Pandemic for People with Disabilities.

Introduction: Telehealth in India is growing rapidly and represents a strategy to promote affordable, inclusive, timely and safe access to healthcare. Yet there is a risk that telehealth increases inequity due to the digital divide and existing poor health literacy. Methods: A scoping review was conducted to explore use of telehealth in India during and following the COVID-19 pandemic by people with disabilities to inform strategies to increase equity of telehealth for people with disabilities. Of 1966 studies from the initial search in four databases and three specific telehealth journals, 20 sources met the inclusion criteria, limited to a focus on physical disability in India. Results: Findings showed examples of how people with disabilities can exercise increased control in the timing of appointments, convenience of receiving services from home and not having to travel to clinics or hospitals, and platform preference through tools and applications already familiar to them. Carers and families of people with disabilities were described as highly valued stakeholders with important roles in the uptake and effectiveness of telehealth for people with disabilities. The identified benefits of telehealth resulted in high levels of user satisfaction due to increased control and convenience, however, systemic barriers for accessibility remain. Conclusion: This review suggested that if telehealth is not designed intentionally to change the status quo for people with disabilities and prioritize equity, then the benefits may not be sustainable. Recommendations for telehealth India are provided, based on both findings from the literature and analysis of results.

A scoping assessment of dental services at designated head and neck cancer centres in Ontario, Canada.

BACKGROUND: Dentists serve a crucial role in managing treatment complications for patients with head and neck cancer, including post-radiation caries and oral infection. To date, dental services for head and neck cancer patients in Ontario, Canada have not been well characterized and considerable disparities in allocation, availability, and funding are thought to exist. The current study aims to describe and assess the provision of dental services for head and neck cancer patients in Ontario. METHODS: A mixed methods scoping assessment was conducted. A purposive sample of dentist-in-chiefs at each of Ontario's 9 designated head and neck cancer centres (tertiary centres which meet provincially-set quality and safety standards) was invited to participate. Participants completed a 36-item online survey and 60-minute semi-structured interview which explored perceptions of dental services for head and neck cancer patients at their respective centres, including strengths, gaps, and inequities. If a centre did not have a dentist-in-chief, an alternative stakeholder who was knowledgeable on that centre's dental services participated instead. Thematic analysis of the interview data was completed using a mixed deductive-inductive approach. RESULTS: Survey questionnaires were completed at 7 of 9 designated centres. A publicly funded dental clinic was present at 5 centres, but only 2 centres provided automatic dental assessment for all patients. Survey data from 2 centres were not captured due to these centres' lack of active dental services. Qualitative interviews were conducted at 9 of 9 designated centres and elicited 3 themes: (1) lack of financial resources; (2) heterogeneity in dentistry care provision; and (3) gaps in the continuity of care. Participants noted concerning under-resourcing and limitations/restrictions in funding for dental services across Ontario, resulting in worse health outcomes for vulnerable patients. Extensive advocacy efforts by champions of dental services who have sought to mitigate current disparities in dentistry care were also described. CONCLUSIONS: Inequities exist in the provision of dental services for head and neck cancer patients in Ontario. Data from the current study will broaden the foundation for evidence-based decision-making on the allocation and funding of dental services by government health care agencies.

Prognosing post-treatment outcomes of head and neck cancer using structured data and machine learning: A systematic review.

BACKGROUND: This systematic review aimed to evaluate the performance of machine learning (ML) models in predicting post-treatment survival and disease progression outcomes, including recurrence and metastasis, in head and neck cancer (HNC) using clinicopathological structured data. METHODS: A systematic search was conducted across the Medline, Scopus, Embase, Web of Science, and Google Scholar databases. The methodological characteristics and performance metrics of studies that developed and validated ML models were assessed. The risk of bias was evaluated using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). RESULTS: Out of 5,560 unique records, 34 articles were included. For survival outcome, the ML model outperformed the Cox proportional hazards model in time-to-event analyses for HNC, with a concordance index of 0.70-0.79 vs. 0.66-0.76, and for all sub-sites including oral cavity (0.73-0.89 vs. 0.69-0.77) and larynx (0.71-0.85 vs. 0.57-0.74). In binary classification analysis, the area under the receiver operating characteristics (AUROC) of ML models ranged from 0.75-0.97, with an F1-score of 0.65-0.89 for HNC; AUROC of 0.61-0.91 and F1-score of 0.58-0.86 for the oral cavity; and AUROC of 0.76-0.97 and F1-score of 0.63-0.92 for the larynx. Disease-specific survival outcomes showed higher performance than overall survival outcomes, but the performance of ML models did not differ between three- and five-year follow-up durations. For disease progression outcomes, no time-to-event metrics were reported for ML models. For binary classification of the oral cavity, the only evaluated subsite, the AUROC ranged from 0.67 to 0.97, with F1-scores between 0.53 and 0.89. CONCLUSIONS: ML models have demonstrated considerable potential in predicting post-treatment survival and disease progression, consistently outperforming traditional linear models and their derived nomograms. Future research should incorporate more comprehensive treatment features, emphasize disease progression outcomes, and establish model generalizability through external validations and the use of multicenter datasets.

Prognostic awareness and willingness to explore prognosis in older adults with cancer.

INTRODUCTION: Prognostic awareness varies widely among older adults with cancer. Accurate prognostic awareness helps to ensure delivery of care that is aligned with the patient's goals. Understanding factors associated with poor prognostic awareness in older adults with cancer may help identify which patients may need interventions to improve prognostic awareness. In this study, we assessed factors associated with poor prognostic awareness in older adults with cancer. MATERIALS AND METHODS: We conducted a cross-sectional analysis of older patients with cancer referred to a geriatric oncology clinic at the University of Rochester. We provided paper questionnaires for patients to complete prior to their clinic assessment. Questionnaires asked patients to estimate their overall life expectancy and the life expectancy of a person of the same age with normal health. Prognostic awareness was considered poor if patients estimated living at least as long as a person of the same age with normal health. We assessed independent demographic and clinical variables (age, sex, race, income, religion, living situation, education, marital status, and cancer type and stage), aging-related factors (comorbidities, cognition, depression, social support, nutritional status, and physical function), and willingness to discuss prognosis. Factors significant at p ≤ 0.15 on bivariate analyses were included in the multivariable logistic regression model. RESULTS: We included 257 patients; the mean age was 80 years (standard deviation [SD] 6.8, range 55-97), 37% were female, 71% were White, and 44% were married. Nearly two-thirds of patients (62%) had poor prognostic awareness: 7% estimated they would live longer than and 55% estimated they would live as long as a person of the same age with normal health. Half (49%) were willing to discuss prognosis, 29% were not, and 22% did not answer. On multivariable analysis, factors associated with poor prognostic awareness were older age [one-year increase; adjusted odds ratio (AOR) 1.07, 95% confidence interval (CI) 1.02-1.12], race other than White (AOR 2.35, 95% CI 1.09-5.06), unwillingness to discuss prognosis (AOR 3.33, 95% CI 1.54-7.18), and stage I-III cancer (vs. stage IV, AOR 3.83, 95% CI 1.8-8.17). DISCUSSION: In a cohort of older patients with cancer, approximately two-thirds had poor prognostic awareness. Older age, race other than White, stage I-III cancer, and unwillingness to discuss prognosis were associated with higher odds of poor prognostic awareness. Interventions aiming to improve patients' prognostic awareness may need to gauge patients' willingness to discuss prognosis.

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.

Prevention and Management of Osteoradionecrosis in Patients With Head and Neck Cancer Treated With Radiation Therapy: ISOO-MASCC-ASCO Guideline.

PURPOSE: To provide evidence-based recommendations for prevention and management of osteoradionecrosis (ORN) of the jaw secondary to head and neck radiation therapy in patients with cancer. METHODS: The International Society of Oral Oncology-Multinational Association for Supportive Care in Cancer (ISOO-MASCC) and ASCO convened a multidisciplinary Expert Panel to evaluate the evidence and formulate recommendations. PubMed, EMBASE, and Cochrane Library databases were searched for randomized controlled trials and observational studies, published between January 1, 2009, and December 1, 2023. The guideline also incorporated systematic reviews conducted by ISOO-MASCC, which included studies published from January 1, 1990, through December 31, 2008. RESULTS: A total of 1,539 publications were initially identified. There were 487 duplicate publications, resulting in 1,052 studies screened by abstract, 104 screened by full text, and 80 included for systematic review evaluation. RECOMMENDATIONS: Due to limitations of available evidence, the guideline relied on informal consensus for some recommendations. Recommendations that were deemed evidence-based with strong evidence by the Expert Panel were those pertaining to best practices in prevention of ORN and surgical management. No recommendation was possible for the utilization of leukocyte- and platelet-rich fibrin or photobiomodulation for prevention of ORN. The use of hyperbaric oxygen in prevention and management of ORN remains largely unjustified, with limited evidence to support its practice.Additional information is available at www.asco.org/head-neck-cancer-guidelines.