The performance of three nutritional tools varied in colorectal cancer patients: a retrospective analysis

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.

AI-Assisted Body Composition Assessment Using CT Imaging in Colorectal Cancer Patients: Predictive Capacity for Sarcopenia and Malnutrition Diagnosis

(1) Background: The assessment of muscle mass is crucial in the nutritional evaluation of patients with colorectal cancer (CRC), as decreased muscle mass is linked to increased complications and poorer prognosis. This study aims to evaluate the utility of AI-assisted L3 CT for assessing body composition and determining low muscle mass using both the Global Leadership Initiative on Malnutrition (GLIM) criteria for malnutrition and the European Working Group on Sarcopenia in Older People (EWGSOP2) criteria for sarcopenia in CRC patients prior to surgery. Additionally, we aim to establish cutoff points for muscle mass in men and women and propose their application in these diagnostic frameworks. (2) Methods: This retrospective observational study included CRC patients assessed by the Endocrinology and Nutrition services of the Regional University Hospitals of Malaga, Virgen de la Victoria of Malaga, and Vall d'Hebrón of Barcelona from October 2018 to July 2023. A morphofunctional assessment, including anthropometry, bioimpedance analysis (BIA), and handgrip strength, was conducted to apply the GLIM criteria for malnutrition and the EWGSOP2 criteria for sarcopenia. Body composition evaluation was performed through AI-assisted analysis of CT images at the L3 level. ROC analysis was used to determine the predictive capacity of variables derived from the CT analysis regarding the diagnosis of low muscle mass and to describe cutoff points. (3) Results: A total of 586 patients were enrolled, with a mean age of 68.4 ± 10.2 years. Using the GLIM criteria, 245 patients (41.8%) were diagnosed with malnutrition. Applying the EWGSOP2 criteria, 56 patients (9.6%) were diagnosed with sarcopenia. ROC curve analysis for the skeletal muscle index (SMI) showed a strong discriminative capacity of muscle area to detect low fat-free mass index (FFMI) (AUC = 0.82, 95% CI 0.77-0.87, p < 0.001). The identified SMI cutoff for diagnosing low FFMI was 32.75 cm2/m2 (Sn 77%, Sp 64.3%; AUC = 0.79, 95% CI 0.70-0.87, p < 0.001) in women, and 39.9 cm2/m2 (Sn 77%, Sp 72.7%; AUC = 0.85, 95% CI 0.80-0.90, p < 0.001) in men. Additionally, skeletal muscle area (SMA) showed good discriminative capacity for detecting low appendicular skeletal muscle mass (ASMM) (AUC = 0.71, 95% CI 0.65-0.76, p < 0.001). The identified SMA cutoff points for diagnosing low ASMM were 83.2 cm2 (Sn 76.7%, Sp 55.3%; AUC = 0.77, 95% CI 0.69-0.84, p < 0.001) in women and 112.6 cm2 (Sn 82.3%, Sp 58.6%; AUC = 0.79, 95% CI 0.74-0.85, p < 0.001) in men. (4) Conclusions: AI-assisted body composition assessment using CT is a valuable tool in the morphofunctional evaluation of patients with colorectal cancer prior to surgery. CT provides quantitative data on muscle mass for the application of the GLIM criteria for malnutrition and the EWGSOP2 criteria for sarcopenia, with specific cutoff points established for diagnostic use.

The potential of machine learning models to identify malnutrition diagnosed by GLIM combined with NRS-2002 in colorectal cancer patients without weight loss information

BACKGROUND & AIMS

The key step of the Global Leadership Initiative on Malnutrition (GLIM) is nutritional risk screening, while the most appropriate screening tool for colorectal cancer (CRC) patients is yet unknown. The GLIM diagnosis relies on weight loss information, and bias or even failure to recall patients' historical weight can cause misestimates of malnutrition. We aimed to compare the suitability of several screening tools in GLIM diagnosis, and establish machine learning (ML) models to predict malnutrition in CRC patients without weight loss information.

METHODS

This multicenter cohort study enrolled 4487 CRC patients. The capability of GLIM diagnoses combined with four screening tools in predicting survival probability was compared by Kaplan-Meier curves, and the most accurate one was selected as the malnutrition reference standard. Participants were randomly assigned to a training cohort (n = 3365) and a validation cohort (n = 1122). Several ML approaches were adopted to establish models for predicting malnutrition without weight loss data. We estimated feature importance and reserved the top 30% of variables for retraining simplified models. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity were calculated to assess and compare model performance.

RESULTS

NRS-2002 was the most suitable screening tool for GLIM diagnosis in CRC patients, with the highest hazard ratio (1.59; 95% CI, 1.43-1.77). A total of 2076 (46.3%) patients were malnourished diagnosed by GLIM combined with NRS-2002. The simplified random forest (RF) model outperformed other models with an AUC of 0.830 (95% CI, 0.805-0.854), and accuracy, sensitivity and specificity were 0.775, 0.835 and 0.742, respectively. We deployed an online application based on the simplified RF model to accurately estimate malnutrition probability in CRC patients without weight loss information (https://zzuwtt1998.shinyapps.io/dynnomapp/).

CONCLUSIONS

Nutrition Risk Screening 2002 was the optimal initial nutritional risk screening tool in the GLIM process. The RF model outperformed other models, and an online prediction tool was developed to properly identify patients at high risk of malnutrition.

Association between risk of malnutrition defined by patient-generated subjective global assessment and adverse outcomes in patients with cancer: a systematic review and meta-analysis

OBJECTIVE

To assess the association between the risk of malnutrition, as estimated by the Patient-Generated Subjective Global Assessment (PG-SGA) numerical scores, and adverse outcomes in oncology patients.

DESIGN

Systematic review and meta-analysis.

SETTINGS

A comprehensive search was conducted in PubMed, Web of Science, Embase, CKNI, VIP, Sinomed and Wanfang databases. Studies that examined the association between the risk of malnutrition, as estimated by the PG-SGA numerical scores, and overall survival (OS) or postoperative complications in oncology patients were included. Patients were classified as low risk (PG-SGA ≤ 3), medium risk (PG-SGA 4-8) and high risk of malnutrition (PG-SGA > 8).

SUBJECT

Nineteen studies reporting on twenty articles (n 9286 patients).

RESULTS

The prevalence of medium and high risk of malnutrition ranged from 16·0 % to 71·6 %. A meta-analysis showed that cancer patients with medium and high risk of malnutrition had a poorer OS (adjusted hazard ratios (HR) 1·98; 95 % CI 1·77, 2·21) compared with those with a low risk of malnutrition. Stratified analysis revealed that the pooled HR was 1·55 (95 % CI 1·17, 2·06) for medium risk of malnutrition and 2·65 (95 % CI 1·90, 3·70) for high risk of malnutrition. Additionally, the pooled adjusted OR for postoperative complications was 4·65 (95 % CI 1·61, 13·44) for patients at medium and high risk of malnutrition.

CONCLUSIONS

The presence of medium and high risk of malnutrition, as estimated by the PG-SGA numerical scores, is significantly linked to poorer OS and an increased risk of postoperative complications in oncology patients.

Bayesian diagnostic test evaluation and true prevalence estimation of malnutrition in gastric cancer patients

BACKGROUND & AIMS

Malnutrition is prevalent among gastric cancer (GC) patients, necessitating early assessment of nutritional status to guide monitoring and interventions for improved outcomes. We aim to evaluate the accuracy and prognostic capability of three nutritional tools in GC patients, providing insights for clinical implementation.

METHODS

The present study is an analysis of data from 1308 adult GC patients recruited in a multicenter from July 2013 to July 2018. Nutritional status was assessed using Nutritional Risk Screening 2002 (NRS-2002), Patient-Generated Subjective Global Assessment (PG-SGA) and Global Leadership Initiative on Malnutrition (GLIM) criteria. Bayesian latent class model (LCM) estimated the malnutrition prevalence of GC patients, sensitivity and specificity of nutritional tools. Cox regression model analyzed the relationship between nutritional status and overall survival (OS) in GC patients.

RESULTS

Among 1308 GC patients, NRS-2002, PG-SGA, and GLIM identified 50.46%, 76.76%, and 68.81% as positive, respectively. Bayesian LCM analysis revealed that PG-SGA had the highest sensitivity (0.96) for malnutrition assessment, followed by GLIM criteria (0.78) and NRS-2002 (0.65). Malnutrition or being at risk of malnutrition were identified as independent prognostic factors for OS. Use any of these tools improved survival prediction in TNM staging system.

CONCLUSION

PG-SGA is the most reliable tool for diagnosing malnutrition in GC patients, whereas NRS-2002 is suitable for nutritional screening in busy clinical practice. Given the lower sensitivity of NRS-2002, direct utilization of GLIM for nutritional assessment may be necessary. Each nutritional tool should be associated with a specific course of action, although further research is needed.

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.

Predictive value of frailty assessment tools in patients undergoing surgery for gastrointestinal cancer: An observational cohort study

BACKGROUND

Few studies have simultaneously compared the predictive value of various frailty assessment tools for outcome measures in patients undergoing gastrointestinal cancer surgery. Therefore, it is difficult to determine which assessment tool is most relevant to the prognosis of this population.

AIM

To investigate the predictive value of three frailty assessment tools for patient prognosis in patients undergoing gastrointestinal cancer surgery.

METHODS

This single-centre, observational, prospective cohort study was conducted at the Affiliated Lianyungang Hospital of Xuzhou Medical University from August 2021 to July 2022. A total of 229 patients aged ≥ 18 years who underwent surgery for gastrointestinal cancer were included in this study. We collected baseline data on the participants and administered three scales to assess frailty: The comprehensive geriatric assessment (CGA), Fried phenotype and FRAIL scale. The outcome measures were the postoperative severe complications and increased hospital costs.

RESULTS

The prevalence of frailty when assessed with the CGA was 65.9%, 47.6% when assessed with the Fried phenotype, and 34.9% when assessed with the FRAIL scale. Using the CGA as a reference, kappa coefficients were 0.398 for the Fried phenotype and 0.291 for the FRAIL scale (both P < 0.001). Postoperative severe complications and increased hospital costs were observed in 29 (12.7%) and 57 (24.9%) patients, respectively. Multivariate logistic analysis confirmed that the CGA was independently associated with increased hospital costs (odds ratio = 2.298, 95% confidence interval: 1.044-5.057; P = 0.039). None of the frailty assessment tools were associated with postoperative severe complications.

CONCLUSION

The CGA was an independent predictor of increased hospital costs in patients undergoing surgery for gastrointestinal cancer.

Prevalence of Anxiety and Depression Symptoms and Their Relationship with Nutritional Status and Mortality in Patients with Colorectal Cancer

BACKGROUND

Anxiety and depression are common in patients with cancer. The aim of this study is to determine the prevalence of anxiety and depression symptoms in colorectal cancer (CRC) patients awaiting elective surgery and whether there is an association with their preoperative nutritional status and postoperative mortality.

METHODS

A prospective study was conducted on 215 patients with CRC proposed for surgery. Data about nutritional status were collected using the Global Leadership Initiative on Malnutrition (GLIM) criteria, while anxiety and depression symptoms data were collected using Hospital Anxiety and Depression Scale (HADS).

RESULTS

HADS detected possible anxiety in 41.9% of patients, probable anxiety in 25.6%, possible depression in 21.9%, and probable depression in 7.9%. GLIM criteria found 116 (53.9%) patients with malnutrition. The HADS score for depression subscale was significantly higher in malnourished patients than in well-nourished (5.61 ± 3.65 vs. 3.95 ± 2.68; p = 0.001). After controlling for potential confounders, malnourished patients were 10.19 times more likely to present probable depression (95% CI 1.13-92.24; p = 0.039). Mortality was 1.9%, 4,2%, and 5.6% during admission and after 6 and 12 months, respectively. Compared to patients without depressive symptomatology, in patients with probable depression, mortality risk was 14.67 times greater (95% CI 1.54-140.21; p = 0.02) during admission and 6.62 times greater (95% CI 1.34-32.61; p = 0.02) after 6 months.

CONCLUSIONS

The presence of anxiety and depression symptoms in CRC patients awaiting elective surgery is high. There is an association between depression symptoms, preoperative nutritional status, and postoperative mortality.