<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03035604</url>
  </required_header>
  <id_info>
    <org_study_id>2016-0705</org_study_id>
    <secondary_id>NCI-2018-01280</secondary_id>
    <secondary_id>2016-0705</secondary_id>
    <nct_id>NCT03035604</nct_id>
  </id_info>
  <brief_title>Comprehensive Nutritional Geriatric Assessments in Identifying Malnutrition in Older Cancer Participants</brief_title>
  <official_title>Malnutrition in Older Cancer Patients</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>M.D. Anderson Cancer Center</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>M.D. Anderson Cancer Center</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      This trial studies how well comprehensive nutritional geriatric assessments work in&#xD;
      identifying malnutrition in older cancer participants. Comprehensive nutritional geriatric&#xD;
      assessments may help doctors learn about ways to check for malnutrition (loss of&#xD;
      weight/appetite that may result in health problems) that is due to cancer or cancer&#xD;
      treatment.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      PRIMARY OBJECTIVES:&#xD;
&#xD;
      I. To evaluate whether nutritional status, as determined by each of 4 screening tools (Mini&#xD;
      Nutritional Assessment [MNA], weight loss, body mass index [BMI], and lean muscle mass),&#xD;
      correlates with 6-month and 12-month mortality in older cancer patients after geriatric&#xD;
      assessment, after adjusting for covariates.&#xD;
&#xD;
      II. To evaluate whether nutritional status, as determined by each of by 4 screening tools&#xD;
      (MNA, weight loss, BMI, and lean muscle mass) correlates with 6-month and 12-month unplanned&#xD;
      hospitalization in older cancer patients who undergo geriatric assessment, after adjusting&#xD;
      for covariates.&#xD;
&#xD;
      III. To evaluate whether nutritional status, as determined by each of 4 screening tools (MNA,&#xD;
      weight loss, BMI, and lean muscle mass) correlates with 6-month and 12-month hospital&#xD;
      readmissions in older cancer patients who undergo geriatric assessment, after adjusting for&#xD;
      covariates.&#xD;
&#xD;
      OUTLINE:&#xD;
&#xD;
      Participants undergo nutritional geriatric assessment over 15 minutes in person or on the&#xD;
      phone every 3 months for 12 months.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Active, not recruiting</overall_status>
  <start_date type="Actual">January 24, 2017</start_date>
  <completion_date type="Anticipated">December 31, 2024</completion_date>
  <primary_completion_date type="Anticipated">December 31, 2024</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Cohort</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Mortality</measure>
    <time_frame>At 6 months</time_frame>
    <description>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.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Mortality</measure>
    <time_frame>At 1 year</time_frame>
    <description>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.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Unplanned hospitalization rate</measure>
    <time_frame>At 6 months and 1 year</time_frame>
    <description>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.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Hospital readmission rate</measure>
    <time_frame>At 6 months</time_frame>
    <description>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.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Re-hospitalization rate</measure>
    <time_frame>At 1 year</time_frame>
    <description>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.</description>
  </secondary_outcome>
  <number_of_groups>1</number_of_groups>
  <enrollment type="Actual">180</enrollment>
  <condition>Hematopoietic and Lymphoid Cell Neoplasm</condition>
  <condition>Malignant Solid Neoplasm</condition>
  <arm_group>
    <arm_group_label>Nutritional geriatric assessment</arm_group_label>
    <description>Participants undergo nutritional geriatric assessment over 15 minutes in person or on the phone every 3 months for 12 months.</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Comprehensive Geriatric Assessment</intervention_name>
    <description>Undergo nutritional geriatric assessment</description>
    <arm_group_label>Nutritional geriatric assessment</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        Participants with hematologic and solid tumor cancers, undergo a comprehensive geriatric&#xD;
        assessment by a geriatrician&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  With hematologic and solid tumor cancers.&#xD;
&#xD;
          -  Undergo a comprehensive geriatric assessment by a geriatrician.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Unable or unwilling to sign consent form.&#xD;
&#xD;
          -  Life expectancy under 6 months.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>65 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Mehnaz Shafi</last_name>
    <role>Principal Investigator</role>
    <affiliation>M.D. Anderson Cancer Center</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>M D Anderson Cancer Center</name>
      <address>
        <city>Houston</city>
        <state>Texas</state>
        <zip>77030</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <link>
    <url>http://www.mdanderson.org</url>
    <description>University of Texas MD Anderson Cancer Center Website</description>
  </link>
  <verification_date>June 2023</verification_date>
  <study_first_submitted>January 24, 2017</study_first_submitted>
  <study_first_submitted_qc>January 26, 2017</study_first_submitted_qc>
  <study_first_posted type="Estimate">January 30, 2017</study_first_posted>
  <last_update_submitted>June 15, 2023</last_update_submitted>
  <last_update_submitted_qc>June 15, 2023</last_update_submitted_qc>
  <last_update_posted type="Actual">June 18, 2023</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Neoplasms</mesh_term>
    <mesh_term>Malnutrition</mesh_term>
  </condition_browse>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03035604
org study id: 2016-0705
secondary id: NCI-2018-01280
secondary id: 2016-0705
nct id: NCT03035604
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
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.
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.
observational model: Cohort
time perspective: Prospective
measure: Mortality
time frame: At 6 months
description: 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.
measure: Mortality
time frame: At 1 year
description: 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.
measure: Unplanned hospitalization rate
time frame: At 6 months and 1 year
description: 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.
measure: Hospital readmission rate
time frame: At 6 months
description: 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.
measure: Re-hospitalization rate
time frame: At 1 year
description: 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.
arm group label: Nutritional geriatric assessment
description: Participants undergo nutritional geriatric assessment over 15 minutes in person or on the phone every 3 months for 12 months.
intervention type: Other
intervention name: Comprehensive Geriatric Assessment
description: Undergo nutritional geriatric assessment
arm group label: Nutritional geriatric assessment
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 65 Years
maximum age: N/A
healthy volunteers: No
last name: Mehnaz Shafi
role: Principal Investigator
affiliation: M.D. Anderson Cancer Center
facility: 
country: United States
url: http://www.mdanderson.org
description: University of Texas MD Anderson Cancer Center Website
responsible party type: Sponsor
mesh term: Neoplasms
mesh term: Malnutrition