Application and Modification of Nutritional Assessment Tools in Hematologic Malignancies

Background: Hematologic malignancies pose a critical threat to global health, with their pathological progression intrinsically linked to metabolic dysregulation and nutrient imbalance. Malnutrition accelerates the trajectory of adverse outcomes while substantially diminishing the quality of survival. Although several nutritional assessment tools are currently used in clinical practice, a significant evidence gap persists regarding their validation in populations with hematologic neoplasms. This study systematically evaluates the prognostic performance of existing nutritional assessment instruments in this cohort. Based on these findings, we further explored the feasibility of a preliminary framework that reflects metabolic characteristics specific to this population. Methods: This prospective cohort study analyzed nutritional assessment data from 1067 patients with hematologic malignancies enrolled in the INSCOC registry. Eight assessment systems were examined: Patient-Generated Subjective Global Assessment (PG-SGA), Modified PGSGA (mPG-SGA), PGSGA Short Form (PG-SGA SF), Abbreviated PGSGA (abPG-SGA), Nutritional Risk Screening-2002 (NRS-2002), Global Leadership Initiative on Malnutrition criteria (GLIM), Scored-GLIM, and Karnofsky Performance Status Scale (KPS). Kaplan-Meier survival curves and multivariate Cox regression analyses were conducted to investigate the association between nutritional status and overall survival (OS) and to determine the prognostic weight of individual components within the nutritional assessment tools. Linear regression models were applied to examine the relationships between nutritional assessment tools, length of hospital stay (LOS), and EORTC QLQ-C30 scores. The predictive performance of the tools was evaluated using the area under the receiver operating characteristic curve (AUC) and the concordance index (C-index). Least absolute shrinkage and selection operator (LASSO) regression was applied to optimize the selection of inflammation-related biomarkers. Results: A total of 1067 participants were analyzed (mean [SD] age, 55.54 [17.4] years; 625 were male [58.6%]). Cox proportional hazards regression demonstrated statistically significant associations for all eight nutritional assessment tools (p ≤ 0.05). However, their prognostic discrimination was limited, as indicated by the AUC analysis. Specifically, the area under the curve (AUC) values for each tool were as follows: mPG-SGA, 0.561; NRS-2002, 0.557; PG-SGA, 0.550; KPS, 0.544; PG-SGA SF, 0.542; abPG-SGA, 0.528; Scored-GLIM, 0.489; and GLIM, 0.473. The concordance index validation further corroborated these findings. Prognostically significant components and inflammation-related biomarkers identified by Cox and LASSO regression were combined to explore a composite assessment approach, termed the Hematologic Marker-Patient Generated Subjective Global Assessment (HMPG-SGA), incorporating the albumin-globulin ratio (AGR). The HMPG-SGA was significantly associated with overall survival (p < 0.001), with an AUC of 0.616 and a C-index of 0.605. Conclusions: Multidimensional validation demonstrated limited prognostic discrimination of eight conventional nutritional assessment tools for overall survival in patients with hematologic malignancies. Based on existing assessment tools and integrated hematologic indicators, the HMPG-SGA was preliminarily explored as a prognostic assessment tool in hematologic malignancies.