Background/Objectives: Weight management is directly linked to cancer recurrence and survival, but unfortunately, nutritional oncology counseling is not typically covered by insurance, creating a disparity for patients without nutritional education and food access. Novel ways of imparting personalized nutrition advice are needed to address this issue. Large language models (LLMs) offer a promising path toward tailoring dietary advice to individual patients. This study aimed to assess the capacity of LLMs to offer personalized dietary advice to patients with breast cancer. Methods: Thirty-one prompt templates were designed to evaluate dietary recommendations generated by ChatGPT and Gemini with variations within eight categorical variables: cancer stage, comorbidity, location, culture, age, dietary guideline, budget, and store. Seven prompts were selected for four board-certified oncology dietitians to also respond to. Responses were evaluated based on nutritional content and qualitative observations. A quantitative comparison of the calories and macronutrients of the LLM- and dietitian-generated meal plans via the Acceptable Macronutrient Distribution Ranges and United States Department of Agriculture’s estimated calorie needs was performed. Conclusions: The LLMs generated personalized grocery lists and meal plans adapting to location, culture, and budget but not age, disease stage, comorbidities, or dietary guidelines. Gemini provided more comprehensive responses, including visuals and specific prices. While the dietitian-generated diets offered more adherent total daily calorie contents to the United States Department of Agriculture’s estimated calorie needs, ChatGPT and Gemini offered more adherent macronutrient ratios to the Acceptable Macronutrient Distribution Range. Overall, the meal plans were not significantly different between the LLMs and dietitians. LLMs can provide personalized dietary advice to cancer patients who may lack access to this care. Grocery lists and meal plans generated by LLMs are applicable to patients with variable food access, socioeconomic means, and cultural preferences and can be a tool to increase health equity.

The circadian system, a vital temporal regulator influencing physiological processes, has implications for cancer development and treatment response. Our study assessed circadian timing’s impact on whole-brain radiotherapy outcomes in brain metastases for personalized cancer therapy insights. The aim of the study was to evaluate circadian influence on radiation treatment timing and its correlation with clinical outcomes and to identify patient populations benefiting from interventions synchronizing circadian rhythms, considering subgroup differences and potential disparities. An IRB-approved retrospective analysis of 237 patients undergoing whole-brain radiotherapy for brain metastases (2017–2021), receiving over 80% of treatments in the morning or afternoon, was performed. Survival analyses utilized Kaplan–Meier curves. This was a single-institution study involving patients receiving whole-brain radiotherapy. Demographic, disease, and socioeconomic parameters from electronic medical records were collected. Morning treatment (n = 158) showed a trend toward improved overall survival vs. afternoon (n = 79); the median survival was 158 vs. 79 days (p = 0.20, HR = 0.84, CI_95% 0.84–0.91). Subgroup benefits for morning treatment in females (p = 0.04) and trends in controlled primary disease (p = 0.11) and breast cancer metastases (p = 0.08) were observed. Black patients exhibited diminished circadian influence. The present study emphasized chronobiological factors’ relevance in brain metastases radiation therapy. Morning treatment correlated with improved survival, particularly in specific subgroups. Potential circadian influence disparities were identified, laying a foundation for personalized cancer therapy and interventions synchronizing circadian rhythms for enhanced treatment efficacy.

Background: The circadian system, a vital temporal regulator influencing physiological processes, has implications for cancer development and treatment response. Our study assesses circadian timing's impact on whole-brain radiotherapy outcomes in brain metastases for personalized cancer therapy insights. Aim: Evaluate circadian influence on radiation treatment timing and its correlation with clinical outcomes. Identify patient populations benefiting from interventions synchronizing circadian rhythms, considering subgroup differences and potential disparities related to social determinants of health (SDoH). Design: IRB-approved retrospective analysis of 237 patients undergoing whole-brain radiotherapy for brain metastases (2017–2021), receiving over 80% of treatments in the morning or afternoon. Survival analyses utilized Kaplan–Meier curves. Setting/Participants: Single-institution study involving patients receiving whole-brain radiotherapy. Collected demographic, disease, and socioeconomic parameters from electronic medical records. Results: Morning treatment (n=158) showed a trend towards improved overall survival vs. afternoon (n=79), median survival 158 vs. 79 days (p=0.20, HR=0.84, CI95% 0.84–0.91). Subgroup benefits for morning treatment in females (p=0.04) and trends in controlled primary disease (p=0.11) and breast cancer metastases (p=0.08). SDoH-based disparities observed, with Black and lower-income patients exhibiting diminished circadian influence. Conclusions: Emphasizes chronobiological factors' relevance in brain metastases radiation therapy. Morning treatment correlates with improved survival, particularly in specific subgroups. Identifies potential circadian influence disparities based on SDoH, laying a foundation for personalized cancer therapy and interventions synchronizing circadian rhythms for enhanced treatment efficacy.