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Comprehensive Nutritional Geriatric Assessments in Identifying Malnutrition in Older Cancer Participants

Malnutrition in Older Cancer Patients

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT03035604
Enrollment
180
Registered
2017-01-30
Start date
2017-01-24
Completion date
2027-06-30
Last updated
2026-05-22

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Hematopoietic and Lymphoid Cell Neoplasm, Malignant Solid Neoplasm

Brief summary

This trial studies how well comprehensive nutritional geriatric assessments work in identifying malnutrition in older cancer participants. Comprehensive nutritional geriatric assessments may help doctors learn about ways to check for malnutrition (loss of weight/appetite that may result in health problems) that is due to cancer or cancer treatment.

Detailed description

PRIMARY OBJECTIVES: I. To evaluate whether nutritional status, as determined by each of 4 screening tools (Mini Nutritional Assessment \[MNA\], weight loss, body mass index \[BMI\], and lean muscle mass), correlates with 6-month and 12-month mortality in older cancer patients after geriatric assessment, after adjusting for covariates. II. To evaluate whether nutritional status, as determined by each of by 4 screening tools (MNA, weight loss, BMI, and lean muscle mass) correlates with 6-month and 12-month unplanned hospitalization in older cancer patients who undergo geriatric assessment, after adjusting for covariates. III. To evaluate whether nutritional status, as determined by each of 4 screening tools (MNA, weight loss, BMI, and lean muscle mass) correlates with 6-month and 12-month hospital readmissions in older cancer patients who undergo geriatric assessment, after adjusting for covariates. OUTLINE: Participants undergo nutritional geriatric assessment over 15 minutes in person or on the phone every 3 months for 12 months.

Interventions

OTHERComprehensive Geriatric Assessment

Undergo nutritional geriatric assessment

Sponsors

M.D. Anderson Cancer Center
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
65 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* With hematologic and solid tumor cancers. * Undergo a comprehensive geriatric assessment by a geriatrician.

Exclusion criteria

* Unable or unwilling to sign consent form. * Life expectancy under 6 months.

Design outcomes

Primary

MeasureTime frameDescription
MortalityAt 6 monthsThe association between nutrition status and mortality (6-month and 1-year mortality since geriatric assessment) will be assessed by logistic regression analysis, considering mortality as a response variable. Univariate logistic regression analysis will be used to estimate the crude odds ratio, and multivariable logistic regression will be used to estimate the adjusted odds ratio, after controlling for potential confounder variables, such as age, race, cancer type, cancer stage, co-morbidity, cognitive status), and frailty. ROC curve to predict 6-month and 1-year mortality will be constructed for nutritional status, as determined by each screening tool. The area under the ROC curve, sensitivity, and specificity and 95% confidence intervals will be obtained for each screening tool.

Secondary

MeasureTime frameDescription
MortalityAt 1 yearThe association between nutrition status and mortality (6-month and 1-year mortality since geriatric assessment) will be assessed by logistic regression analysis, considering mortality as a response variable. Univariate logistic regression analysis will be used to estimate the crude odds ratio, and multivariable logistic regression will be used to estimate the adjusted odds ratio, after controlling for potential confounder variables, such as age, race, cancer type, cancer stage, co-morbidity, cognitive status), and frailty. ROC curve to predict 6-month and 1-year mortality will be constructed for nutritional status, as determined by each screening tool. The area under the ROC curve, sensitivity, and specificity and 95% confidence intervals will be obtained for each screening tool.
Unplanned hospitalization rateAt 6 months and 1 yearThe associations between nutrition status and unplanned hospitalization will be assessed by logistic regression analysis. Univariate logistic regression analysis will be used to get the crude odds ratio, and multivariable logistic regression will be used to get the adjusted odds ratio, after controlling for potential confounder variables, such as age, race, cancer type, cancer stage, co-morbidity, cognitive status, and frailty. Patients who died before 6 months or 1 year from geriatric test will be considered as having unplanned 6-month or 1-year hospitalization. ROC curve to predict each of secondary outcomes will be constructed for nutritional status, as determined by each screening tool. The area under the ROC curve, sensitivity, and specificity and 95% confidence intervals will be obtained for each screening tool. Descriptive statistics will be used to summarize data. Two sample t-test or Wilcoxon rank-sum test will be used for the comparison in numeric variables.
Hospital readmission rateAt 6 monthsThe associations between nutrition status and hospital readmissions will be assessed by logistic regression analysis. Univariate logistic regression analysis will be used to get the crude odds ratio, and multivariable logistic regression will be used to get the adjusted odds ratio, after controlling for potential confounder variables, such as age, race, cancer type, cancer stage, co-morbidity, cognitive status, and frailty. Patients who died before 6 months or 1 year from geriatric test will be considered as having unplanned 6-month or 1-year hospitalization. ROC curve to predict each of secondary outcomes will be constructed for nutritional status, as determined by each screening tool. The area under the ROC curve, sensitivity, and specificity and 95% confidence intervals will be obtained for each screening tool. Descriptive statistics will be used to summarize data. Two sample t-test or Wilcoxon rank-sum test will be used for the comparison in numeric variables.
Re-hospitalization rateAt 1 yearThe associations between nutrition status and hospital readmissions will be assessed by logistic regression analysis. Univariate logistic regression analysis will be used to get the crude odds ratio, and multivariable logistic regression will be used to get the adjusted odds ratio, after controlling for potential confounder variables, such as age, race, cancer type, cancer stage, co-morbidity, cognitive status, and frailty. Patients who died before 6 months or 1 year from geriatric test will be considered as having unplanned 6-month or 1-year hospitalization. ROC curve to predict each of secondary outcomes will be constructed for nutritional status, as determined by each screening tool. The area under the ROC curve, sensitivity, and specificity and 95% confidence intervals will be obtained for each screening tool. Descriptive statistics will be used to summarize data. Two sample t-test or Wilcoxon rank-sum test will be used for the comparison in numeric variables.

Countries

United States

Contacts

PRINCIPAL_INVESTIGATORMehnaz Shafi

M.D. Anderson Cancer Center

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: May 23, 2026