This phase II/III trial studies the best approach in improving quality of life and survival after a donor stem cell transplant in older, weak, or frail patients with blood diseases. Patients who have undergone a transplant often experience increases in disease and death. One approach, supportive and palliative care (SPC), focuses on relieving symptoms of stress from serious illness and care through physical, cultural, psychological, social, spiritual, and ethical aspects. While a second approach, clinical management of comorbidities (CMC) focuses on managing multiple diseases, other than cancer, such as heart or lung diseases through physical exercise, strength training, stress reduction, medication management, dietary recommendations, and education. Giving SPC, CMC, or a combination of both may work better in improving quality of life and survival after a donor stem cell transplant compared to standard of care in patients with blood diseases.
OUTLINE: Patients are randomized to 1 of 4 arms. ARM I: Patients undergo SPC on days -15 before to +56 after transplant. ARM II: Patients undergo a CMC program on days -15 before to +56 after transplant. ARM III: Patients undergo interventions as outlined in Arm I and Arm II. ARM IV: Patients receive standard of care. In all arms, patients undergo HCT on day 0 and complete questionnaires and surveys at enrollment and 30, 90, 180, and 365 days post HCT. In all arms patients complete a 4-meter walk test, 6-minute walk test, up and go test, measured strength test and cognitive assessment at enrollment, 90, 180, and 365 days post HCT. Patients may also complete surveys on medical and non-medical (transportation, lodging) costs related to transplant after HCT.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
SUPPORTIVE_CARE
Masking
SINGLE
Enrollment
458
focuses on relieving symptoms of stress from serious illness and care through physical, cultural, psychological, social, spiritual, and ethical aspects
physical exercise, strength training, stress reduction, medication management, dietary recommendations, and education
Given standard of care
Undergo HCT
Ancillary studies
Ancillary studies
Complete surveys
Stanford Cancer Institute Palo Alto
Palo Alto, California, United States
University of California San Francisco
San Francisco, California, United States
Wayne State University/Karmanos Cancer Institute
Detroit, Michigan, United States
University of Minnesota/Masonic Cancer Center
Minneapolis, Minnesota, United States
Mayo Clinic
Rochester, Minnesota, United States
Northwell Health Cancer Institute
New Hyde Park, New York, United States
Cleveland Clinic Taussig Cancer Institute, Case Comprehensive Cancer Center
Cleveland, Ohio, United States
Oregon Health and Science University
Portland, Oregon, United States
Vanderbilt University
Nashville, Tennessee, United States
Baylor College of Medicine/Dan L Duncan Comprehensive Cancer Center
Houston, Texas, United States
...and 1 more locations
Improvement in health-related quality of life (HRQOL) (Phase II)
The arm with the largest mean change in Functional Assessment of Cancer Therapy-Bone Marrow Transplant (FACT-BMT) from baseline to day 90. The Wilcoxon rank-sum test will be used to compare change in FACT-BMT between arms, and this will also be the test to be used in computation of the conditional power at the end of phase II.
Time frame: First 90 days after HCT
Survival after hematopoietic cell transplantation (HCT) (Phase III)
Time frame: At 1 year after HCT
Change in HRQOL (Phase III)
Will be measured by the FACT-BMT.
Time frame: Baseline to 90 days post-HCT
Rate of overall survival
Overall survival will be compared between each of the experimental arms and the usual care only (UCO) arm using the log-rank test. Arms that do not survive the screening phase will also be included for comparison.
Time frame: Up to 1 year
Non-relapse mortality
Will be compared between arms using appropriate tests for continuous data (two-sample t-test or Wilcoxon rank-sum test, as appropriate for two-group comparisons; analysis of variance (ANOVA) or Kruskal-Wallis test for comparisons involving more than two groups). Will use generalized estimating equations (GEEs) approach for regression models, which can accommodate the within patient correlation structure and arbitrary patterns of missing data and also allow for the population average interpretation.
Time frame: At 90 days and up to 1 year
Cumulative incidence of relapse
Will be compared between arms using appropriate tests for continuous data (two-sample t-test or Wilcoxon rank-sum test, as appropriate for two-group comparisons; ANOVA or Kruskal-Wallis test for comparisons involving more than two groups). Will use GEEs approach for regression models, which can accommodate the within patient correlation structure and arbitrary patterns of missing data and also allow for the population average interpretation.
Time frame: Up to 1 year
Relapse-free survival
Will be compared between arms using appropriate tests for continuous data (two-sample t-test or Wilcoxon rank-sum test, as appropriate for two-group comparisons; ANOVA or Kruskal-Wallis test for comparisons involving more than two groups). Will use GEEs approach for regression models, which can accommodate the within patient correlation structure and arbitrary patterns of missing data and also allow for the population average interpretation.
Time frame: Up to 1 year
Cumulative incidence of frailty
Will be compared between arms using appropriate tests for continuous data (two-sample t-test or Wilcoxon rank-sum test, as appropriate for two-group comparisons; ANOVA or Kruskal-Wallis test for comparisons involving more than two groups). Will use GEEs approach for regression models, which can accommodate the within patient correlation structure and arbitrary patterns of missing data and also allow for the population average interpretation.
Time frame: Up to 1 year
Cumulative incidence of disability
Will be compared between arms using appropriate tests for continuous data (two-sample t-test or Wilcoxon rank-sum test, as appropriate for two-group comparisons; ANOVA or Kruskal-Wallis test for comparisons involving more than two groups). Will use GEEs approach for regression models, which can accommodate the within patient correlation structure and arbitrary patterns of missing data and also allow for the population average interpretation.
Time frame: Up to 1 year
Frequency of hospitalization
Will be compared between arms using appropriate tests for continuous data (two-sample t-test or Wilcoxon rank-sum test, as appropriate for two-group comparisons; ANOVA or Kruskal-Wallis test for comparisons involving more than two groups). Will use GEEs approach for regression models, which can accommodate the within patient correlation structure and arbitrary patterns of missing data and also allow for the population average interpretation.
Time frame: Up to 90 days after HCT
Duration of each hospitalization
Will be compared between arms using appropriate tests for continuous data (two-sample t-test or Wilcoxon rank-sum test, as appropriate for two-group comparisons; ANOVA or Kruskal-Wallis test for comparisons involving more than two groups). Will use GEEs approach for regression models, which can accommodate the within patient correlation structure and arbitrary patterns of missing data and also allow for the population average interpretation.
Time frame: Up to 90 days after HCT
Number of admissions to intensive care unit
Will be compared between arms using appropriate tests for continuous data (two-sample t-test or Wilcoxon rank-sum test, as appropriate for two-group comparisons; ANOVA or Kruskal-Wallis test for comparisons involving more than two groups). Will use GEEs approach for regression models, which can accommodate the within patient correlation structure and arbitrary patterns of missing data and also allow for the population average interpretation.
Time frame: Up to 90 days after HCT
Duration of admissions to intensive care unit
Will be compared between arms using appropriate tests for continuous data (two-sample t-test or Wilcoxon rank-sum test, as appropriate for two-group comparisons; ANOVA or Kruskal-Wallis test for comparisons involving more than two groups). Will use GEEs approach for regression models, which can accommodate the within patient correlation structure and arbitrary patterns of missing data and also allow for the population average interpretation.
Time frame: Up to 90 days after HCT
Days out of hospital alive
Will be compared between arms using appropriate tests for continuous data (two-sample t-test or Wilcoxon rank-sum test, as appropriate for two-group comparisons; ANOVA or Kruskal-Wallis test for comparisons involving more than two groups). Will use GEEs approach for regression models, which can accommodate the within patient correlation structure and arbitrary patterns of missing data and also allow for the population average interpretation.
Time frame: Up to 90 days after HCT
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