Comprehensive Nutritional Geriatric Assessments in Identifying Malnutrition in Older Cancer Participants

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.

Participants undergo nutritional geriatric assessment over 15 minutes in person or on the phone every 3 months for 12 months.

Other: Comprehensive Geriatric Assessment

Undergo nutritional geriatric assessment

Plazo: At 6 months

The 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.

Plazo: At 1 year

The 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.

Plazo: At 6 months and 1 year

The 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.

Plazo: At 6 months

The 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.

Plazo: At 1 year

The 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.

Malnutrition in Older Cancer Patients