Severe Malnutrition Predicts Worse Survival in Lung Cancer
Key Takeaways
- Among adults with primary lung cancer assessed before oncologic treatment in a multicenter Spanish cohort, severe GLIM-defined malnutrition tracked with worse one-year survival than better nutritional categories.
- One-year mortality increased stepwise from 26.3% in well-nourished patients to 37.1% with moderate malnutrition and 58.6% with severe malnutrition.
- Albumin, inflammatory burden, performance status, muscle-related body-composition measures, ultrasound findings, and mobility all worsened progressively as GLIM malnutrition severity increased.
- Exploratory ROC analyses, mainly comparing well-nourished with severely malnourished patients, favored BIA- and ultrasound-derived variables.
Using Global Leadership Initiative on Malnutrition criteria, 198 patients were classified as well nourished, 89 as moderately malnourished, and 87 as severely malnourished. The source states that baseline assessment was performed between the second and fourth week after diagnosis, although it also describes inclusion of patients before first-line or subsequent treatment lines; vital status was followed for 12 months. Body composition was measured with bioelectrical impedance analysis (BIA), muscle morphology with rectus femoris ultrasound, and function with handgrip strength and the Timed Up and Go (TUG) test; Cox models adjusted for age, sex, body mass index (BMI), and Eastern Cooperative Oncology Group (ECOG) performance status, with BIA- and ultrasound-derived measures evaluated as complementary markers rather than used to define GLIM groups in the prognostic models.
Severe GLIM-defined malnutrition and one-year mortality in lung cancer were associated, with HR 4.31 (95% CI 2.73–6.80) in the unadjusted analysis and HR 3.32 (95% CI 1.96–5.61) after adjustment. Moderate malnutrition was not significantly associated with mortality in either Cox model. Survival separation was most apparent at the severe end of nutritional impairment.
Albumin and prealbumin were lower, C-reactive protein was higher, ECOG performance status was poorer, and multiple body-composition, ultrasound, and mobility measures worsened progressively as malnutrition severity increased. In marker-specific models, lower phase angle (OR 0.54), lower body cell mass index (OR 0.67), and longer TUG time (OR 1.18) were associated with severe malnutrition, while body cell mass, fat-free mass index, rectus femoris cross-sectional area, and rectus femoris circumference showed the same general pattern and handgrip strength was not statistically significant. Exploratory discrimination analyses also favored BIA- and ultrasound-derived variables, with rectus femoris cross-sectional area reaching an AUC of 0.87 in women. Together, the morphofunctional profile mapped onto worsening malnutrition rather than body weight alone.
The authors described the cohort as observational and real world, so the survival findings are adjusted associations rather than causal effects. They also noted that the models did not systematically account for all oncologic prognostic factors, including TNM stage, treatment modality, inflammatory status, molecular tumor profiling, and treatment response, because those data were incomplete or not systematically available. Some nonproportional hazards were present, so the Cox estimates are best read as average associations over the one-year follow-up. The authors likewise characterized the discrimination analyses as exploratory because morphofunctional variables overlap conceptually with reduced muscle mass within GLIM and the ROC cutoffs and random forest rankings were derived and tested in the same cohort without external validation.
The authors concluded that severe GLIM-defined malnutrition in lung cancer tracked with poorer functional status and worse one-year survival, while BIA-derived cellular integrity markers and rectus femoris ultrasound parameters may complement nutritional characterization. They added that the proposed thresholds remain exploratory and require external validation.
Clinician Questions
How was GLIM-defined malnutrition classified and assessed in this lung cancer cohort?
Adults with primary lung cancer were classified as well nourished, moderately malnourished, or severely malnourished using GLIM criteria that required at least one phenotypic and one etiologic criterion, with active lung cancer serving as the etiologic criterion in this cohort. Body composition, rectus femoris ultrasound, handgrip strength, and TUG were evaluated as complementary morphofunctional measures rather than used to define GLIM categories in the prognostic models.
Which lung cancer patients were included in the VALONC nutrition and survival cohort, and how broadly do the findings apply?
Adults aged 18 to 85 years with confirmed primary lung cancer who were referred for nutritional and morphofunctional assessment were enrolled across 10 tertiary hospitals in Spain, without restriction to a single TNM stage, treatment modality, or treatment line; however, patients unable to complete baseline assessment or with estimated life expectancy under 3 months were excluded.
Which morphofunctional measures appeared most useful for identifying severe malnutrition in lung cancer?
Lower phase angle, body cell mass index, body cell mass, fat-free mass index, rectus femoris cross-sectional area, rectus femoris circumference, and longer TUG time were associated with severe malnutrition, whereas handgrip strength was not statistically significant in the marker-specific models. Rectus femoris cross-sectional area showed the strongest reported discrimination, especially in women.
Why did the authors treat the proposed malnutrition cutoffs in lung cancer as exploratory rather than clinically validated?
The authors treated the proposed cutoffs as exploratory because ROC-derived thresholds and random forest rankings were both derived and evaluated within the same cohort, without internal or external validation, and because the morphofunctional variables overlap conceptually with the reduced-muscle-mass domain of GLIM. They also noted that the study was observational and that the Cox estimates should be interpreted as average one-year associations because proportional hazards were not fully satisfied.