ArticlePloS one2016
Identification of Comprehensive Geriatric Assessment Based Risk Factors for Malnutrition in Elderly Asian Cancer Patients.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.
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Who cites it
7 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Risk prediction model for malnutrition in older adults: a systematic review.BMC geriatrics · 2026Pooled it
- The bidirectional association of malnutrition with depression and anxiety in patients with cancer: a systematic review and meta-analysis of evidence.Aging clinical and experimental research · 2025Pooled it
- Global prevalence of malnutrition in older adults: A comprehensive systematic review and meta-analysis.Public health in practice (Oxford, England) · 2025Article
- Relationships of emerging biomarkers of cancer cachexia with quality of life, appetite, and cachexia.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024Article
- Prevalence and the factors associated with malnutrition risk in elderly Chinese inpatients.Aging medicine (Milton (N.S.W)) · 2021Article
- Use of machine learning in geriatric clinical care for chronic diseases: a systematic literature review.JAMIA open · 2020Review
- Impact of Nutritional Status on Caregiver Burden of Elderly Outpatients. A Cross-Sectional Study.Nutrients · 2019Article
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Authors and funding
9 authors.
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No grant is acknowledged in the PubMed record.
Abstract
purposeElderly cancer patients are at increased risk for malnutrition. We aim to identify comprehensive geriatric assessment (CGA) based clinical factors associated with increased nutritional risk and develop a clinical scoring system to identify nutritional risk in elderly cancer patients. PATIENTS AND
methodsCGA data was collected from 249 Asian patients aged 70 years or older. Nutritional risk was assessed based on the Nutrition Screening Initiative (NSI) checklist. Univariate and multivariate logistic regression analyses were applied to assess the association between patient clinical factors together with domains within the CGA and moderate to high nutritional risk. Goodness of fit was assessed using Hosmer-Lemeshow test. Discrimination ability was assessed based on the area under the receiver operating characteristics curve (AUC). Internal validation was performed using simulated datasets via bootstrapping.
resultsAmong the 249 patients, 184 (74%) had moderate to high nutritional risk. Multivariate logistic regression analysis identified stage 3-4 disease (Odds Ratio [OR] 2.54; 95% CI, 1.14-5.69), ECOG performance status of 2-4 (OR 3.04; 95% CI, 1.57-5.88), presence of depression (OR 5.99; 95% CI, 1.99-18.02) and haemoglobin levels <12 g/dL (OR 3.00; 95% CI 1.54-5.84) as significant independent factors associated with moderate to high nutritional risk. The model achieved good calibration (Hosmer-Lemeshow test's p = 0.17) and discrimination (AUC = 0.80). It retained good calibration and discrimination (bias-corrected AUC = 0.79) under internal validation.
conclusionHaving advanced stage of cancer, poor performance status, depression and anaemia were found to be predictors of moderate to high nutritional risk. Early identification of patients with these risk factors will allow for nutritional interventions that may improve treatment tolerance, quality of life and survival outcomes.
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