GLIM diagnosed malnutrition predicts clinical outcomes and quality of life in patients with non-small cell lung cancer

Association between CONUT scores and survival outcomes in patients with non-small cell lung cancer: meta-analysis from 4973 Asian cases

Background

The controlling nutritional status (CONUT) score is associated with cancer prognosis. However, a consensus on its prognostic value in patients with non-small cell lung cancer(NSCLC) is lacking. The present study aims to investigate the relationship between the CONUT score and prognostic and clinicopathological features of NSCLC.

Methods

The PubMed, Embase, Web of Science and Cochrane Library were searched up to July 2024. Two researchers used the Newcastle Ottawa Scale (NOS) score to evaluate the quality of the included studies and extracted data. The primary and secondary outcomes were overall survival (OS) and disease-free survival (DFS), and the hazard ratio (HR) and 95% confidence interval (CI) were pooled for meta-analysis. The pooled odds ratio (OR) and 95% CI were used to estimate the correlation between the CONUT score and clinical characteristics. Subgroup analysis and sensitivity analysis were performed during the pooled analysis.Funnel plots as well as Begg's and Egger's tests were used to assess publication bias.

Results

Fifteen high-quality studies with 4973 patients were included. The results indicated that a high CONUT score was associated with poor OS (HR = 1.84, 95%CI: 1.55-2.18; P < 0.0001) and DFS (HR=2.40, 95%CI: 1.73-3.34; P < 0.0001).In addition, a high CONUT score was significantly related to male, advanced age, high CEA, and later TNM stage.

Conclusion

The results of our meta-analysis suggest that a high CONUT score predicts a poor prognosis of NSCLC patients. In clinical practice, the CONUT score could act as an valuable tool to predict clinical outcomes in patients with NSCLC.

Systematic Review Registration

https://inplasy.com, identifier INPLASY202408280100.

Routine assessment of nutritional, functional and inflammatory criteria in patients with cancer: A systematic review

BACKGROUND

The review discusses the significant impact of cancer on patients, particularly focusing on cachexia - a condition marked by weight and lean tissue loss. This condition critically affects the nutritional status, quality of life, and treatment outcomes of cancer patients.

RESEARCH QUESTION

The review seeks to understand the effectiveness and necessity of routine clinical monitoring of cancer cachexia, and how it can aid in better therapeutic interventions.

METHODS

The systematic review followed a pre-defined protocol based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)statement. A systematic search using specific keywords was conducted in PubMed and EMBASE databases on October 24, 2023, supplemented by citations from the original papers. The selection process involved screening titles and abstracts for relevance.

RESULTS

The review finds varying levels of effectiveness in the different measurement criteria used for monitoring cachexia. It highlights the potential of the Global Leadership Initiative on Malnutrition (GLIM) framework in defining and managing cancer cachexia, though noting some challenges in standardisation and implementation of measurements.

CONCLUSION

The present systematic review highlights the variability and lack of standardization in the application of GLIM criteria for monitoring cachexia in cancer patients. Despite these challenges, it will be important to determine the most efficacious clinically routine nutritional and inflammation assessments in the routine application of GLIM criteria assessment.

Serum metabolomics analysis of malnutrition in patients with gastric cancer: a cross sectional study

BACKGROUND

Although malnutrition is common in cancer patients, its molecular mechanisms has not been fully clarified. This study aims to identify significantly differential metabolites, match the corresponding metabolic pathways, and develop a predictive model of malnutrition in patients with gastric cancer.

METHODS

In this cross-sectional study, we applied non-targeted metabolomics using liquid chromatography-mass spectrometry to explore the serum fingerprinting of malnutrition in patients with gastric cancer. Malnutrition-specific differential metabolites were identified by orthogonal partial least-squares discriminant analysis and t-test and matched with the Human Metabolome Database and the LIPID Metabolites and Pathways Strategy. We matched the corresponding metabolic pathways of malnutrition using pathway analysis at the MetaboAnalyst 5.0. We used random forest analyses to establish the predictive model.

RESULTS

We recruited 220 malnourished and 198 non-malnourished patients with gastric cancer. The intensities of 25 annotated significantly differential metabolites were lower in patients with malnutrition than those without, while two others were higher in patients with malnutrition than those without, including newly identified significantly differential metabolites such as indoleacrylic acid and lysophosphatidylcholine(18:3/0:0). We matched eight metabolic pathways associated with malnutrition, including aminoacyl-tRNA biosynthesis, tryptophan metabolism, and glycerophospholipid metabolism. We established a predictive model with an area under the curve of 0.702 (95% CI: 0.651-0.768) based on four annotated significantly differential metabolites, namely indoleacrylic acid, lysophosphatidylcholine(18:3/0:0), L-tryptophan, and lysophosphatidylcholine(20:3/0:0).

CONCLUSIONS

We identified 27 specific differential metabolites of malnutrition in malnourished compared to non-malnourished patients with gastric cancer. We also matched eight corresponding metabolic pathways and developed a predictive model. These findings provide supportive data to better understand molecular mechanisms of malnutrition in patients with gastric cancer and new strategies for the prediction, diagnosis, prevention, and treatment for those malnourished.

Association between GLIM-diagnosed malnutrition and quality of life in older patients with cancer

BACKGROUND

Older patients with cancer have a higher risk for malnutrition and impaired quality of life (QoL). The present study aimed to investigate the relationship between malnutrition diagnosed according to the Global Leadership Initiative Malnutrition (GLIM) criteria and QoL across various tumor types, and to evaluate the combined prognostic value of malnutrition and QoL in predicting survival among older patients with cancer.

METHODS

This multicenter, observational cohort study included 5310 older patients with cancer and 2184 with malnutrition (moderate stage, n = 1023; severe stage, n = 1161). An empirical cumulative distribution curve was performed to illustrate the correlation between malnutrition and QoL. The primary objective was to investigate the association between malnutrition and QoL using logistic regression analysis. Survival analyses were performed to assess the combined prognostic value of malnutrition and QoL.

RESULTS

The median age of the patients (66.9% male, 33.1% female) was 70 years (interquartile range [IQR] 67-74 years) years. The median QoL score was highest in patients without malnutrition (91.88 [IQR 84.44-97.44]), followed by those with moderate (86.15 [IQR 76.18-93.85) and severe (82.31 [IQR 69.87-91.11]) malnutrition. Logistics regression revealed that the risk for developing impaired QoL increased 1.98 (95% confidence interval [CI] 1.64-2.38; P < 0.001) and 2.33 (95% CI 1.93-2.81; P < 0.001) times in patients with moderate and severe malnutrition, respectively. Kaplan-Meier curves showed that QoL in combination with GLIM criteria demonstrated a significant discriminative performance for survival and served as an independent prognostic factor among older patients with cancer, especially for lung and gastric cancers.

CONCLUSIONS

Malnutrition diagnosed according to the GLIM criteria was a predictor of impaired QoL. Additionally, the combination of QoL and malnutrition demonstrated utility for predicting survival outcomes in older patients with cancer.

Influence of malnutrition according to the glim criteria on the chemotherapy toxicities in patients with advanced lung cancer

BACKGROUND

Cancer-associated malnutrition is highly prevalent in advanced lung cancer, and 50% of global cancer-related deaths are attributed to cancer-associated malnutrition. Platinum-containing chemotherapy is the standard treatment for advanced lung cancer. Unfortunately, it can cause exacerbated toxicities, which can also have a negative impact on patient's prognosis and quality of life. The Global Leadership Initiative on Malnutrition (GLIM) criteria have been proposed as the world's first accepted diagnostic criteria for malnutrition. However, the effectiveness of GLIM criteria in predicting chemotherapy toxicities in patients with advanced lung cancer is unclear. The aim of this study was to apply the GLIM criteria to assess the prevalence of pre-treatment diagnosis of malnutrition in patients with advanced non-small cell lung cancer (NSCLC) and to determine the impact of nutritional status on patient's chemotherapy toxicity.

METHODS

We conducted a study of hospitalized patients with pathologically and clinically diagnosed advanced NSCLC who presented to our hospital from May 2021 to January 2022. Initially, the Nutritional Risk Screening-2002 (NRS-2002) was used for nutritional risk screening, and nutritional status was assessed using the Scored Patient-Generated Subjective Global Assessment (PG-SGA) and GLIM criteria. Chemotherapy toxicity was assessed and graded according to CTCAE5.0, and chemotherapy efficacy was assessed according to RECIST1.1. Kappa test was used to analyze the agreement between PG-SGA and GLIM criteria. Univariate and multivariate logistic regression analyses were used to determine the relationship between malnutrition and chemotherapy toxicity.

RESULTS

A total of 215 patients with advanced NSCLC were evaluated for nutritional status. Most of the patients had normal BMI (61.86%) before the start of treatment, 40% were well-nourished as assessed by the PG-SGA tool, and 51.17% were well-nourished as assessed by GLIM criteria. Consistency analysis showed moderate agreement (Kappa = 0.463, P < 0.001) and their correlation was also moderate (Spearman, rs = 0.475, P < 0.001). The objective response rate (ORR) (P = 0.040) and disease control rate (DCR) (P < 0.001) were significantly lower in malnourished patients diagnosed according to GLIM criteria than in well-nourished patients. Multivariate analysis showed that malnutrition (OR = 1.531,95%CI 0.757-3.009; OR = 6.623,95%CI 1.390-31.567, P = 0.046) diagnosed by GLIM criteria was an independent predictor of chemotherapy toxicity. Conclusions Malnutrition diagnosed by GLIM criteria better predicts toxicity during chemotherapy, determines the degree of clinical benefit of chemotherapy, and may affect patient prognosis.

Nutritional Assessment Tools for Patients with Cancer: A Narrative Review

Cancer patients are at high risk of malnutrition, which can lead to adverse health outcomes such as prolonged hospitalization, increased complications, and increased mortality. Accurate and timely nutritional assessment plays a critical role in effectively managing malnutrition in these patients. However, while many tools exist to assess malnutrition, there is no universally accepted standard. Although different tools have their own strengths and limitations, there is a lack of narrative reviews on nutritional assessment tools for cancer patients. To address this knowledge gap, we conducted a non-systematic literature search using PubMed, Embase, Web of Science, and the Cochrane Library from their inception until May 2023. A total of 90 studies met our selection criteria and were included in our narrative review. We evaluated the applications, strengths, and limitations of 4 commonly used nutritional assessment tools for cancer patients: the Subjective Global Assessment (SGA), Patient-Generated Subjective Global Assessment (PG-SGA), Mini Nutritional Assessment (MNA), and Global Leadership Initiative on Malnutrition (GLIM). Our findings revealed that malnutrition was associated with adverse health outcomes. Each of these 4 tools has its applications, strengths, and limitations. Our findings provide medical staff with a foundation for choosing the optimal tool to rapidly and accurately assess malnutrition in cancer patients. It is essential for medical staff to be familiar with these common tools to ensure effective nutritional management of cancer patients.

Prevalence of malnutrition based on global leadership initiative in malnutrition criteria for completeness of diagnosis and future risk of malnutrition based on current malnutrition diagnosis: systematic review and meta-analysis

Background

The proposal of the global leadership initiative in malnutrition (GLIM) criteria has received great attention from clinicians. The criteria are mainly used in the research environment and have the potential to be widely used in the clinic in the future. However, the prevalence of malnutrition and risk of future malnutrition based on a current diagnosis of malnutrition are worth exploring.

Methods

A systematic search of PubMed, Embase, and the Cochrane Library was performed from the earliest available date to 1 February 2023. According to the diagnostic criteria of the GLIM, we analysed the prevalence of malnutrition by directly adopting the GLIM criteria for diagnosis without a previous nutritional risk screening (one-step approach) and by adopting the GLIM criteria for diagnosis after a nutritional risk screening (two-step approach). The main outcome was the prevalence of malnutrition based on the one-and two-step approaches. Secondary outcomes were the future risk of malnutrition based on the GLIM diagnosis, including mortality within and beyond 1 year. primary outcomes were pooled using random-effects models, and secondary outcomes are presented as hazard ratios (HRs) and 95% confidence intervals (CIs).

Results

A total of 64 articles were included in the study, including a total of 47,654 adult hospitalized patients and 15,089 malnourished patients based on the GLIM criteria. Malnutrition was diagnosed by the one-step approach in 18 studies and by the two-step approach in 46 studies. The prevalence of malnutrition diagnosed by the one-and two-step approaches was 53% (95% CI, 42%-64%) and 39% (95% CI, 0.35%-0.43%), respectively. The prevalence of malnutrition diagnosed by the GLIM criteria after a nutritional risk screening was quite different; the prevalence of malnutrition diagnosed by the Nutritional Risk Screening 2002 (NRS2002) GLIM tool was 35% (95% CI, 29%-40%); however, the prevalence of malnutrition diagnosed by the Mini Nutrition Assessment (MNA) GLIM tool was 48% (95% CI, 35%-62%). Among the disease types, the prevalence of malnutrition in cancer patients was 44% (95% CI, 36%-52%), while that in acute and critically ill patients was 44% (95% CI, 33%-56%). The prevalence in patients in internal medicine wards was 40% (95% CI, 34%-45%), while that in patients in surgical wards was 47% (95% CI, 30%-64%). In addition, the mortality risk within 1 year (HR, 2.62; 95% CI, 1.95-3.52; I² = 77.1%) and beyond 1 year (HR, 2.04; 95% CI, 1.70-2.45; I² = 59.9%) of patients diagnosed with malnutrition by the GLIM criteria was double that of patients with normal nutrition.

Conclusion

The prevalence of malnutrition diagnosed by the GLIM criteria after a nutritional risk screening was significantly lower than the prevalence of malnutrition diagnosed directly by the GLIM criteria. In addition, the mortality risk was significantly greater among malnourished patients assessed by the GLIM criteria.Systematic review registration: identifier CRD42023398454.

Measurement of sarcopenia in lung cancer inpatients and its association with frailty, nutritional risk, and malnutrition

Background

Sarcopenia, frailty, and malnutrition are associated with undesirable clinical outcomes in cancer patients. Sarcopenia-related measurements may be promising fast biomarkers for frailty. Our objectives were to assess the prevalence of nutritional risk, malnutrition, frailty, and sarcopenia in lung cancer inpatients, and describe the relationship of them.

Methods

Stage III and IV lung cancer inpatients were recruited before chemotherapy. The skeletal muscle index (SMI) was assessed by multi-frequency bioelectric impedance analysis (m-BIA). Sarcopenia, frailty, nutritional risk, and malnutrition were diagnosed according to the Asian Working Group for Sarcopenia 2019 (AWGS 2019), Fried Frailty Phenotype (FFP), nutritional risk screening-2002 (NRS-2002), and Global Leadership Initiative on Malnutrition criteria (GLIM), and correlation analysis was performed between them with Pearson's r correlation coefficients. A univariate and multivariate logistic regression analysis was conducted for all patients, gender and age-stratified subgroups to obtain odds ratios (ORs) and 95% confidence intervals (95%CIs).

Results

The cohort included 97 men (77%) and 29 women (23%), with mean age of 64.8 ± 8.7 years. Among the 126 patients, 32 (25.4%) and 41 (32.5%) had sarcopenia and frailty, and the prevalence of nutritional risk and malnutrition was 31.0% (n = 39) and 25.4% (n = 32). Adjusted for age and gender, SMI was correlated with FFP (r = -0.204, p = 0.027), and did not remain significantly when stratified by gender. Stratification according to age revealed in ≥65-years-old population, SMI and FFP were significantly correlated (r = -0.297, p = 0.016), which is not seen in <65-years-old group (r = 0.048, p = 0.748). The multivariate regression analysis showed FFP, BMI, and ECOG were the independent variables associated with sarcopenia (OR 1.536, 95%CI 1.062-2.452, p = 0.042; OR 0.625, 95%CI 0.479-0.815, p = 0.001; OR 7.286, 95%CI 1.779-29.838, p = 0.004).

Conclusion

Comprehensively assessed sarcopenia is independently associated with frailty based on FFP questionnaire, BMI, and ECOG. Therefore, sarcopenia assessment including m-BIA based SMI, and muscle strength and function could be used to indicate frailty to help select the targeting patients for care. Moreover, in addition to muscle mass, muscle quality should not be ignored in clinical practice.