ArticleFrontiers in nutrition2026
Dynamic nutritional trajectories and deterioration risk in esophageal cancer radiotherapy: a prospective study.
Article in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Nutritional deterioration (ND) during radiotherapy (RT) for esophageal cancer is common, yet the optimal timing for proactive supportive care remains unclear. We characterized time-resolved nutritional trajectories, examined baseline factors associated with deterioration, and translated the findings into a patient-facing digital prototype. Methods: In this prospective longitudinal cohort, 123 patients underwent nutritional assessment at five timepoints (admission, RT1, RT14, RT20, and discharge) using the Patient-Generated Subjective Global Assessment (PG-SGA), serum albumin, and total protein. ND was defined as an upward shift in PG-SGA risk category (0-3/4-8/≥9) from admission to discharge. Sleep was assessed by baseline interview, the Pittsburgh Sleep Quality Index (PSQI), and exploratory wearable measures. Logistic regression was used to identify baseline factors associated with ND. Complementary continuous-change analysis and linear mixed-effects modeling were additionally performed to characterize deterioration magnitude and longitudinal trajectories. Exploratory correlations assessed sleep-nutrition associations. Based on the findings, a digital prototype ("Esophageal Care Companion") was developed with risk-aware onboarding and phase-specific monitoring prompts. Results: PG-SGA increased from 4.59 ± 3.66 at admission to 6.95 ± 3.48 at RT20 ( Conclusion: Nutritional risk worsened during esophageal cancer RT, particularly in the mid-to-late treatment phase, supporting RT14-RT20 as a clinically relevant window for intensified assessment and supportive-care escalation. Advanced nodal stage emerged as a robust marker of less favorable nutritional trajectory. Baseline sleep problems may serve as a low-burden observational risk signal but should be interpreted cautiously. The prototype demonstrates the feasibility of translating phase-aware risk monitoring into digital supportive care.
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