Evidence Hub

Taste alteration and its relationship with nutritional status among cancer patients receiving chemotherapy, cross-sectional study

F. Al-Amouri, M. Badrasawi

PLoS ONE, 2024

120 participants · 22 citations

Abstract

The aim of this study is to determine the prevalence of taste alterations (TAs) during chemotherapy and their association with nutritional status and malnutrition. In addition to the associated factors with TA, including sociodemographic health-related factors and clinical status, and to investigate coping strategies to manage TA. A multicenter cross-sectional design study was conducted on 120 cancer patients aged at least 18 who had been undergoing at least one round of chemotherapy. TAs were evaluated using the chemotherapy-induced taste alteration scale (CiTAS), the malnutrition universal screening tool (MUST) was used for nutritional screening, the antineoplastic side effects scale (ASES) was used for subjective assessment of chemotherapy side effects, and the Charlson comorbidity index (CCI) was used for comorbidity assessment. SPSS21 software was used to analyze the data, and the independent T-test and one-way ANOVA test were used to determine the association between TAs and a variety of related variables. The prevalence of TAs was 98.3%. Among participants, 48.3% were at low risk of malnutrition, 20% at medium risk, and 31.7% at high risk. Malnutrition risk was associated with taste disorders (p<0.05). Patients’ age, gender, educational level, and physical status were associated with TAs (p<0.05). Type of cancer, chemotherapy regimen, and number of chemotherapy cycles were also associated with TAs (p<0.05). A variety of antineoplastic side effects were associated with…

How strong is the evidence?

Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause. Reported size: 120 participants or records.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free