Addressing challenges in low-income and middle-income countries through novel radiotherapy research opportunities.

Although radiotherapy continues to evolve as a mainstay of the oncological armamentarium, research and innovation in radiotherapy in low-income and middle-income countries (LMICs) faces challenges. This third Series paper examines the current state of LMIC radiotherapy research and provides new data from a 2022 survey undertaken by the International Atomic Energy Agency and new data on funding. In the context of LMIC-related challenges and impediments, we explore several developments and advances-such as deep phenotyping, real-time targeting, and artificial intelligence-to flag specific opportunities with applicability and relevance for resource-constrained settings. Given the pressing nature of cancer in LMICs, we also highlight some best practices and address the broader need to develop the research workforce of the future. This Series paper thereby serves as a resource for radiation professionals.

Individualized risk assessment of distant metastases in oral cavity carcinoma: a validated predictive-score model.

BACKGROUND: We aimed to develop and validate a risk-scoring system for distant metastases (DMs) in oral cavity carcinoma (OCC). METHODS: Patients with OCC who were treated at 4 tertiary cancer institutions with curative surgery with or without postoperative radiation/chemoradiation therapy were randomly assigned to discovery or validation cohorts (3:2 ratio). Cases were staged on the basis of tumor, node, and metastasis staging according to the eighth edition of the American Joint Committee on Cancer/Union for International Cancer Control guidelines. Predictors of DMs on multivariable analysis in the discovery cohort were used to develop a risk-score model and classify patients into risk groups. The utility of the risk classification was evaluated in the validation cohort. RESULTS: Overall, 2749 patients were analyzed. Predictors (risk score coefficient) of DMs in the discovery cohort were the following: pathological stage (p)T3-4 (0.4), pN+ (N1: 0.8; N2: 1.0; N3: 1.5), histologic grade (G) 3 (G3, 0.7), and lymphovascular invasion (0.4). The DM risk groups were defined by the sum of the following risk score coefficients: high (>1.7), intermediate (0.7-1.7), and standard risk (<0.7). The 5-year DM rates (high/intermediate/standard risk groups) were 30%/15%/4% in the discovery cohort (C-index = 0.79) and 35%/16%/5% in the validation cohort, respectively (C-index = 0.77; both P < .001). In the whole cohort, this predictive model showed excellent discriminative ability in predicting DMs without locoregional failure (29%/11%/1%), later (>2 year) DMs (11%/4%/2%), and DMs in patients treated with surgery (20%/12%/5%), postoperative radiation therapy (34%/17%/4%), and postoperative chemoradiation therapy (39%/18%/7%) (all P < .001). The 5-year overall survival rates in the overall cohort were 25%/51%/67% (P < .001). CONCLUSIONS: Patients at higher risk for DMs were identified by use of a predictive-score model for DMs that included pT3-4, pN1/2/3, G3, and lymphovascular invasion. Identified patients may be evaluated for individualized risk-adaptive treatment escalation and/or surveillance strategies.

Association of Household Income at Diagnosis With Financial Toxicity, Health Utility, and Survival in Patients With Head and Neck Cancer.

Importance: While several studies have documented a link between socioeconomic status and survival in head and neck cancer, nearly all have used ecologic, community-based measures. Studies using more granular patient-level data are lacking. Objective: To determine the association of baseline annual household income with financial toxicity, health utility, and survival. Design, Setting, and Participants: This was a prospective cohort of adult patients with head and neck cancer treated at a tertiary cancer center in Toronto, Ontario, between September 17, 2015, and December 19, 2019. Data analysis was performed from April to December 2021. Exposures: Annual household income at time of diagnosis. Main Outcome and Measures: The primary outcome of interest was disease-free survival. Secondary outcomes included subjective financial toxicity, measured using the Financial Index of Toxicity (FIT) tool, and health utility, measured using the Health Utilities Index Mark 3. Cox proportional hazards models were used to estimate the association between household income and survival. Income was regressed onto log-transformed FIT scores using linear models. The association between income and health utility was explored using generalized linear models. Generalized estimating equations were used to account for patient-level clustering. Results: There were 555 patients (mean [SD] age, 62.7 [10.7] years; 109 [20%] women and 446 [80%] men) included in this cohort. Two-year disease-free survival was worse for patients in the bottom income quartile (<$30 000: 67%; 95% CI, 58%-78%) compared with the top quartile (≥$90 000: 88%; 95% CI, 83%-93%). In risk-adjusted models, patients in the bottom income quartile had inferior disease-free survival (adjusted hazard ratio, 2.13; 95% CI, 1.22-3.71) and overall survival (adjusted hazard ratio, 2.01; 95% CI, 0.94-4.29), when compared with patients in the highest quartile. The average FIT score was 22.6 in the lowest income quartile vs 11.7 in the highest quartile. In adjusted analysis, low-income patients had 12-month FIT scores that were, on average, 134% higher (worse) (95% CI, 16%-253%) than high-income patients. Similarly, health utility scores were, on average, 0.104 points lower (95% CI, 0.026-0.182) for low-income patients in adjusted analysis. Conclusions and Relevance: In this cohort study, patients with head and neck cancer with a household income less than CAD$30 000 experienced worse financial toxicity, health status, and disease-free survival. Significant disparities exist for Ontario's patients with head and neck cancer.