A Novel Nomogram for Early Identification and Intervention in Colorectal Cancer Patients at Risk for Malnutrition

Background Malnutrition is under-recognized in cancer patients and can lead to poor treatment outcomes. We aim to develop an outpatient-focused score based on the Malnutrition Screening Tool (MST) to help identify colorectal cancer (CRC) profiles at high risk for malnutrition. Methods 506 CRC patien...

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Bibliographic Details
Published in:The American surgeon 2023-05, Vol.89 (5), p.1485-1496
Main Authors: Tang, Joseph, Wong, Gary, Naffouje, Samer, Felder, Seth, Sanchez, Julian, Dineen, Sean, Powers, Benjamin D., Dessureault, Sophie, Gurd, Erin, Castillo, Diana, Hodul, Pamela
Format: Article
Language:English
Subjects:
Adult
Appetite
Body mass index
Body size
Cancer
Cancer therapies
Chemotherapy
Clinical outcomes
Colorectal cancer
Colorectal carcinoma
Colorectal Neoplasms - complications
Colorectal Neoplasms - diagnosis
Comorbidity
Demographics
Health services
Humans
Laboratories
Lymphocytes
Malnutrition
Malnutrition - diagnosis
Malnutrition - etiology
Metastases
Neutrophils
Nomograms
Nutrition Assessment
Nutritional Status
Oncology
Patients
Peer review
Quality of Life
Radiation
Risk
Risk groups
Signs and symptoms
Socioeconomics
Surgery
Tumors
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Summary:Background Malnutrition is under-recognized in cancer patients and can lead to poor treatment outcomes. We aim to develop an outpatient-focused score based on the Malnutrition Screening Tool (MST) to help identify colorectal cancer (CRC) profiles at high risk for malnutrition. Methods 506 CRC patients during initial outpatient oncology consultation at our tertiary referral outpatient oncology clinic completed the MST. Objective and subjective data were collected through chart review. Data gathered are as follows: demographics, anthropometrics, laboratory values, patient-reported symptoms, MST score, cancer history, performance status, socioeconomic status, and Charlson Comorbidity. Predictors of malnutrition were identified by logistic regression. Receiver operating curve (ROC), area under the curve (AUC), and our model’s predictability were determined. Results Significant predictors of malnutrition are as follows: younger age (20-39 vs >40 years) (P = .007), normal-to-low body mass index at presentation (P = .019), Eastern Cooperative Oncology Group classification 2-3 (P = .012), metastatic disease (P = .046), albumin
ISSN:0003-1348
1555-9823
DOI:10.1177/00031348211058620