- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06953648
Remotely Monitored, Mobile Health-supported, High Intensity Interval Training Before Hematopoietic Stem Cell Transplant (REMM-HIIT)
Remotely Monitored, Mobile Health-supported, High Intensity Interval Training Before Hematopoietic Stem Cell Transplantation (REMM-HIIT-HCT)
The goal of this clinical trial is to learn how a remotely monitored high-intensity interval training (REMM-HIIT) affects the cardiorespiratory fitness and physical function for patients planning to undergo stem cell transplantation. The main questions it aims to answer are:
Is there a change in the participant's cardiorespiratory fitness level? Is there a change in the participant's physical function?
Researchers will compare the REMM-HIIT program to a control group of participants who do not take part in the training program to see if REMM-HIIT helps improve stem cell transplantation outcomes.
Participants will:
- Complete cardiopulmonary exercise testing (CPET) 4 times during the study
- Do basic tests to measure physical function 6 times during the study
- Answer questions about their life and how they are feeling 6 times during the study
- Wear a device to keep track of step counts and heart rate daily
- Keep a log of every time they exercise throughout the study
- Optionally, provide blood and stool samples 6 times during the study
Study Overview
Status
Intervention / Treatment
Detailed Description
Each year in the U.S., approximately 8,000 patients undergo allogeneic hematopoietic stem cell transplantation (HCT) as a potentially curative therapy for leukemias, lymphomas, and other hematologic malignancies. However, treatment-related mortality (TRM) is significant, ranging from 10-30%. Moreover, survivors of HCT often face significant physical, psychological, and social challenges post-treatment, leading to a substantial decrease in quality of life (QOL). Outcomes are closely linked to pre-HCT physical activity and function. For example, patients with worse pre-HCT physical function and capacity have markedly lower one-year survival rates (50% vs. 83%). In contrast, every 50-meter increase in pre-HCT six-minute walk distance (6MWD) correlates with a 9% reduction in relative risk for mortality.
Cardiorespiratory fitness (CRF) is a crucial indicator of physical capacity, reflecting the integrated functioning of the heart, lungs, skeletal muscle, adipose tissue, pancreas, liver and adrenal tissues. While CRF naturally declines with age, this decline is notably accelerated by cancer and its treatments, with cancer patients' average CRF levels comparable to individuals 20-30 years older. Importantly, patients with low pre-HCT CRF (VO2peak <16 mL/kg/min) are at much higher risk of TRM (hazard ratio 6.70), even after accounting for other risk factors. This underscores the critical need for interventions to improve CRF prior to HCT to enhance survival and post-treatment quality of life.
It is well established that patients with better pre-HCT physical function tend to have better post-HCT outcomes. The critical question, however, is whether enhancing fitness pre-HCT can improve post-HCT outcomes. Animal studies provide optimism: exercise training in a murine model pre-HCT associated with improved survival, possibly through immune-mediated pathways. Yet, research exploring the impact of pre-HCT exercise on human post-HCT outcomes remains limited. Small studies have linked pre-HCT improvements in physical function with better survival, and preliminary results from a randomized controlled trial suggest that exercise during HCT may reduce mortality. However, a recent large (n=711) randomized Blood and Marrow Transplant Clinical Trials Network study of self-directed exercise and stress management during HCT did not show a significant benefit in outcomes. Study investigators suggested several reasons for this lack of effect, including timing of intervention (peri-HCT rather than pre-HCT), low intensity rather than high intensity exercise, and low engagement in the self-directed program.
To address prior study limitations, the investigators developed the REMM-HIIT program, focusing on pre-HCT intervention, high-intensity interval training (HIIT), and a mobile health (mHealth) platform to support participant engagement. This program, supported by the National Institute of Aging and the Duke Claude D. Pepper Older Americans Independence Center, was piloted in a successful phase 1 study of Remotely Monitored, Mobile health-supported, pre-HCT High Intensity Interval Training (REMM-HIIT). In this feasibility study, participants underwent baseline cardiopulmonary exercise testing (CPET) to ensure cardiac safety and to measure maximal cardiorespiratory fitness (VO2peak). The heart rate (HR) at VO2peak was used to personalize the high and low intensity interval goals. Participants were equipped with an iPhone and Garmin Watch for remote monitoring and exercised three times a week at home, with the first session and subsequent sessions as needed monitored remotely by the coach via videoconference. This approach ensured continuous support and maximized participant engagement while allowing the majority of sessions to occur remotely.
This program was purposely designed based on investigators' prior research and other significant studies in the field, aiming to overcome common barriers to physical activity in cancer populations. To facilitate participation, the investigators enable exercise at home utilizing the participant's preferred activity (e.g., walking, cycling, stairs) and at convenient times. The majority engaged in walking-based intervention, which despite their simplicity, provided sufficient intensity for deconditioned HCT participants. Others used cycle ergometers. This program adheres to the principles of exercise training and recommendations from Sasso and colleagues, ensuring individualization, progressive overload, appropriate recovery periods, and reasonable specificity. Exercise sessions started with a 5-minute warmup (e.g., walking or cycling at a HR corresponding to 60% VO2peak). This was followed by ten intervals, each consisting of one-minute of high intensity exercise at a HR corresponding to 95% VO2peak, alternated with one minute of low to moderate intensity interval at a HR corresponding to 60% VO2peak, totaling 20 minutes. The session concluded with a 5-minute cooldown, resulting in a comprehensive 30-minutes exercise session. For participants unable to complete all intervals, the study team began with fewer intervals and gradually increased the number as tolerated. A recovery period of 24-48 hours between HIIT sessions was recommended to prevent overtraining and ensure adequate recovery. Broad specificity was achieved by incorporating high, moderate, and low intensity aerobic exercises continuously. As such, the program is a progressive HIIT-based intervention, with flexibility given to ensure the principles of exercise training are upheld, and participants receive the best possible information and guidance to rapidly increase CRF and health outcomes pre-HCT.
The investigators' prior phase 1 study was successful. Out of 24 participants approached, 14 enrolled (10 males, 4 females), achieving a recruitment rate of 58%. Of the 14 enrolled, 13 (age 59±12, range 34-76 yrs; 10 White, 3 Black) were medically cleared to proceed with HIIT following a CPET. One participant did not proceed to HIIT and was withdrawn due to cardiac concerns detected on baseline CPET. Importantly, there were no adverse events associated with exercise among the remaining participants. Participants were able to engage in HIIT, even with a baseline CRF as low as 10.6 mL/kg/min; for reference, independent living in healthy adults is generally associated with a CRF >18 in men and >15 in women. Some participants who were habitually exercising were able to complete ten intervals immediately and to maintain intensity over time, while other participants who were less fit required more coaching but were able to rapidly improve fitness to reach program goals. Remarkably, even with low baseline CRF and concomitant chemotherapy (some requiring hospitalization), nine of the 13 participants engaged in the exercise program (69%), and average adherence to the prescribed 3 sessions/week in those nine was excellent at 104 +/- 28%. Mean intervention length was 13.8 +/- 7.5 weeks, with participants staying engaged in the exercise program for approximately three months prior to HCT; this compares very favorably to the 50-70% adherence rates commonly reported in other home-based exercise studies. All 7 participants who had repeat CPET showed improvements in CRF, with average change in VO2peak from 14.6 ± 3.1 mL/kg/min at enrollment to 17.9 ± 3.3 by the start of transplant, or 23% increase (p<0.001). For the other 6, 3 were not evaluated due to the onset of the COVID-19 pandemic, which suspended research operations. Because CRF declines at about 10% per decade, this substantial improvement in CRF equates to a fitness level increase that typically would take over 20 years to achieve, aligning participants' fitness more closely with that of healthy adults34. As highlighted by Wood et al.,16 a pre-HCT VO2peak <16 mL/kg/min is associated with higher post-HCT mortality rate (HR 6.70 (1.29-34.75), p=0.02) and longer hospital stay (median number of hospitalized days before Day 100: 33 vs. 21, p=0.004). Thus, increasing CRF pre-HCT has the potential to improve post-HCT outcomes, suggesting this program could substantially impact participant health and recovery.
The investigators believe this program's success is from a combination of participant motivation and mHealth platform and coaching. Because participants know that they were to undergo HCT within a few months, with a 10-30% chance of death related to the treatment itself, they were highly motived to do anything they could to improve their chances of survival. Furthermore, knowing that an oncology-experienced exercise professional is monitoring their exercise sessions, coupled with personalized and frequent feedback (at least once a week), likely helped improve adherence, with resultant improvements in CRF.
Allogeneic HCT has curative potential for hematologic malignancies but is associated with significant morbidity and TRM, especially in patients with low pre-HCT CRF. Improving CRF through a time-efficient, high-intensity interval training (HIIT) approach, facilitated remotely via mHealth, could improve physical function and clinical outcomes for HCT patients. The investigators hypothesize that patients undergoing REMM-HIIT program will experience improved CRF, physical function, and QOL pre-HCT, leading to better post-HCT outcomes, including improved physical function, reduced TRM, and increased overall survival.
Study Type
Enrollment (Estimated)
Phase
- Not Applicable
Contacts and Locations
Study Contact
- Name: Anthony Sung
- Phone Number: 913-588-6030
- Email: asung2@kumc.edu
Study Locations
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Kansas
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Kansas City, Kansas, United States, 66160
- University of Kansas Cancer Center
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Principal Investigator:
- Anthony Sung, MD
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Contact:
- Anthony Sung, MD
- Phone Number: 913-588-6030
- Email: asung2@kumc.edu
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North Carolina
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Durham, North Carolina, United States, 27705
- Duke University
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Contact:
- Amy Pastva, MD
- Phone Number: 919-681-4380
- Email: amy.pastva@duke.edu
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Principal Investigator:
- Amy Pastva, MD
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Texas
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Houston, Texas, United States, 77030
- The University of Texas MD Anderson Cancer Center
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Principal Investigator:
- Ajay Sheshadri, MD
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Contact:
- Ajay Sheshadri, MD
- Phone Number: 713-563-1987
- Email: asheshadri@mdanderson.org
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Plan to undergo allogeneic hematopoietic stem cell transplant in 4-12 weeks after enrollment on this study.
- Age 18-80 years
- Able to read/write English (as many participant-reported outcome measures lack validated translations in other languages)
Exclusion Criteria:
- Unable or unwilling to follow coaching
- Functional impairment resulting in inability to exercise
Any absolute contraindications to exercise:
- recent (<6 months) acute cardiac event;
- unstable angina;
- uncontrolled dysrhythmias causing symptoms;
- symptomatic aortic stenosis;
- uncontrolled symptomatic heart failure;
- acute pulmonary embolus;
- acute myocarditis or pericarditis;
- suspected or known dissecting aneurysm
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Supportive Care
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
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Experimental: HIIT Group
The intervention will consist of three 30-minute training sessions/week, each starting with a five-minute warm-up, followed by 20 minutes of interval training, and ending with a five-minute cool-down.
The interval training will consist of 10 alternating high- and low-intensity intervals, with a 1:1 work-to-rest ratio (one minute of high intensity followed by one minute of low-moderate intensity).
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The intervention will consist of three 30-minute training sessions/week, each starting with a five-minute warm-up, followed by 20 minutes of interval training, and ending with a five-minute cool-down.
The interval training will consist of 10 alternating high- and low-intensity intervals, with a 1:1 work-to-rest ratio (one minute of high intensity followed by one minute of low-moderate intensity).
As participants' fitness improves, the interval intensity will increase accordingly.
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No Intervention: Control Group
Participants will receive a handout and information on exercise.
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Change in Cardiorespiratory Fitness
Time Frame: At Baseline, Day -10, Day 90, and Day 365
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Change in cardiorespiratory fitness as measured by the difference in peak rate of oxygen consumption (VO2peak) in mL/(kg*min) from baseline to the pre-hematopoietic stem cell transplant (HCT) timepoint; a higher number for VO2 peak indicates greater cardiorespiratory fitness.
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At Baseline, Day -10, Day 90, and Day 365
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Change in Physical Function (Six Minute Walk Test Distance)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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The change in physical function as measured by the difference in six minute walk test distance in meters from baseline to the pre-hematopoietic stem cell transplantation (HCT) timepoint; a greater number of meters walked indicates a higher level of physical function.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Effect on Health-related Quality of Life (Physical Activity/Short Physical Performance Battery)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on health-related quality of life (physical activity) as measured by performance on the Short Physical Performance Battery, which results in a score from 0 to 12 points, with a higher number indicating better physical performance.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Health-related Quality of Life (Physical Activity/30-Second Sit-to-Stand Test)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on health-related qulaity of life (physical activity) as measured by the 30-second sit-to-stand test, which measures the number of times an individual can stand up from a chair and sit back down within 30 seconds, with a higher number indicating greater fitness.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Health-related Quality of Life (Physical Activity/Fried Frailty)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on health-related quality of life (physical activity) as measured by the Fried Frailty assessment, which results in a score from 0 to 5, with a higher number indicating greater frailty.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Health-related Quality of Life (Physical Activity/Fall Question)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on health-related quality of life (physical activity) as measured by the Fall Question, a structured questionnaire asking about any history of falls, with a higher number of falls indicating greater fall risk and physical vulnerability.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Health-related Quality of Life (Physical Activity/Physical Function Questionnaire)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on health-related quality of life (physical activity) as measured by the Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function questionnaire, which results in a numerical score between 0 and 100, with a higher number indicating better physical function.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Health-related Quality of Life (Physical Activity/Fatigue Questionnaire)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on health-related quality of life (physical activity) as measured by the Patient-Reported Outcomes Measurement Information System (PROMIS) Fatigue questionnaire, which results in a numerical score between 0 and 100, with a higher number indicating greater symptom burden.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Health-related Quality of Life (Physical Activity/International Physical Activity Questionnaire)
Time Frame: At Baseline
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Effect on health-related quality of life (physical activity) as measured by the International Physical Activity Questionnaire, which provides 2 results: a categorical rating of low, moderate, or high activity level, and a number of Metabolic Equivalent of Task (MET) minutes per week, with a higher number indicating a greater amount of physical activity.
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At Baseline
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Effect on Health-related Quality of Life (Cognitive/Montreal Cognitive Assessment)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on health-related quality of life (cognitive) as measured by the Montreal Cognitive Assessment (MOCA), which results in a numerical score between 0 and 30, with a higher number indicating better cognitive functioning.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Health-related Quality of Life (Mental Health/Lorig Self-Efficacy)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on health-related quality of life (mental health) as measured by the Lorig Self-Efficacy for Managing Chronic Disease Scale, which results in a numerical score between 1 and 10, with a higher number indicating higher self-efficacy.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Health-related Quality of Life (Mental Health/Depression Scale)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on health-related quality of life (mental health) as measured by the Patient-Reported Outcomes Measurement Information System (PROMIS) Depression scale, which results in a numerical value between 8 and 40, with a higher number indicating greater severity of depression.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Health-related Quality of Life (Mental Health/Anxiety scale)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on health-related quality of life (mental health) as measured by the Patient-Reported Outcomes Measurement Information System (PROMIS) Anxiety scale, which results in a numerical value between 7 and 35, with a higher number indicating greater severity of anxiety.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Health-related Quality of Life (Weight)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on health-related quality of life (weight) as measured by the change in patient's body weight in kilograms.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Health-related Quality of Life (Albumin Level)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on health-related quality of life (albumin level) as measured by the change in patient's albumin level in grams per deciliter; low serum albumin levels can predict higher cancer mortality.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Health-related Quality of Life (Nutrition)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on health-related quality of life (nutrition) as measured by the Patient-Generated Subjective Global Assessment (PG-SGA), which gives 2 results: a numerical score between 0 and 16, where a higher score indicates higher nutritional risk, and a categorical score where A = well nourished, B = moderately malnourished, and C = severely malnourished.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Health-related Quality of Life (Social Support/Emotional Support)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on health-related quality of life (social support) as measured by the Patient-Reported Outcomes Measurement Information System (PROMIS) Emotional Support assessment, which results in a numerical score between 8 and 40, with a higher score indicating a greater level of social participation.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Health-related Quality of Life (Social Support/Social Isolation)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on health-related quality of life (social support) as measured by the Patient-Reported Outcomes Measurement Information System (PROMIS) Social Isolation assessment, which results in a numerical score between 6 and 30, with a higher score indicating a greater level of social participation.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Health-related Quality of Life (EuroQoL-5 Dimension-5 Level)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on health-related quality of life as measured by the EuroQoL-5 Dimension-5 Level (EQ-5D-5L), which results in a 5-digit health state, where each digit is between 1 and 5 (e.g.
12345 or 11111).
For each digit, a higher number indicates a greater severity of problems.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Health-related Quality of Life (Return to Work)
Time Frame: At Day 180 and Day 365
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Effect on health-related quality of life as measured by assessing the patient's return to work as an indicator of recovery.
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At Day 180 and Day 365
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Effect on Clinical Outcomes (Overall Survival)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on clinical outcomes as measured by overall survival.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Clinical Outcomes (Treatment-related Mortality)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on clinical outcomes as measured by treatment-related mortality.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Clinical Outcomes (Incidence of Infection)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on clinical outcomes as measured by incidence of infection.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Clinical Outcomes (Incidence of Graft-versus-host disease)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on clinical outcomes as measured by incidence of graft versus host disease.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Clinical Outcomes (Time to Relapse)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on clinical outcomes as measured by time to relapse.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Length of Stay
Time Frame: At day of hospital discharge
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The length of hospital stay measured in days from time of transplant to time of discharge.
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At day of hospital discharge
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Other Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Effect on Muscle Health (Resting Energy Expenditure)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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The effect on muscle health as measured by resting energy expenditure.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Muscle Health (Intramuscular Adipose Tissue)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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The effect on muscle health as measured by amount of intramuscular adipose tissue assessed using biopsied muscle tissue.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Muscle Health (Glycogen Stores)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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The effect on muscle health as measured by amount of glycogen stores in muscle assessed using biopsied muscle tissue.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Muscle Health (Muscle Mitochondrial Metabolism)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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The effect on muscle health as measured by muscle mitochondrial metabolism assessed in biopsied muscle tissue.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Effect on Biomarkers (Analysis of Plasma)
Time Frame: At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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The effect on biomarkers as measured by analysis of plasma.
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At Baseline, Day -10, Day 30, Day 90, Day 180, and Day 365
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Collaborators and Investigators
Investigators
- Principal Investigator: Anthony Sung, MD, The University of Kansas Cancer Center
Publications and helpful links
General Publications
- Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, Seeman T, Tracy R, Kop WJ, Burke G, McBurnie MA; Cardiovascular Health Study Collaborative Research Group. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001 Mar;56(3):M146-56. doi: 10.1093/gerona/56.3.m146.
- Herdman M, Gudex C, Lloyd A, Janssen M, Kind P, Parkin D, Bonsel G, Badia X. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011 Dec;20(10):1727-36. doi: 10.1007/s11136-011-9903-x. Epub 2011 Apr 9.
- van Hout B, Janssen MF, Feng YS, Kohlmann T, Busschbach J, Golicki D, Lloyd A, Scalone L, Kind P, Pickard AS. Interim scoring for the EQ-5D-5L: mapping the EQ-5D-5L to EQ-5D-3L value sets. Value Health. 2012 Jul-Aug;15(5):708-15. doi: 10.1016/j.jval.2012.02.008. Epub 2012 May 24.
- Enright PL. The six-minute walk test. Respir Care. 2003 Aug;48(8):783-5.
- Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, Pratt M, Ekelund U, Yngve A, Sallis JF, Oja P. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003 Aug;35(8):1381-95. doi: 10.1249/01.MSS.0000078924.61453.FB.
- Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, Scherr PA, Wallace RB. A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol. 1994 Mar;49(2):M85-94. doi: 10.1093/geronj/49.2.m85.
- Jung SH, Ahn C. Sample size estimation for GEE method for comparing slopes in repeated measurements data. Stat Med. 2003 Apr 30;22(8):1305-15. doi: 10.1002/sim.1384.
- Shepherd SO, Wilson OJ, Taylor AS, Thogersen-Ntoumani C, Adlan AM, Wagenmakers AJ, Shaw CS. Low-Volume High-Intensity Interval Training in a Gym Setting Improves Cardio-Metabolic and Psychological Health. PLoS One. 2015 Sep 24;10(9):e0139056. doi: 10.1371/journal.pone.0139056. eCollection 2015.
- David LA, Maurice CF, Carmody RN, Gootenberg DB, Button JE, Wolfe BE, Ling AV, Devlin AS, Varma Y, Fischbach MA, Biddinger SB, Dutton RJ, Turnbaugh PJ. Diet rapidly and reproducibly alters the human gut microbiome. Nature. 2014 Jan 23;505(7484):559-63. doi: 10.1038/nature12820. Epub 2013 Dec 11.
- Shensa A, Sidani JE, Escobar-Viera CG, Switzer GE, Primack BA, Choukas-Bradley S. Emotional support from social media and face-to-face relationships: Associations with depression risk among young adults. J Affect Disord. 2020 Jan 1;260:38-44. doi: 10.1016/j.jad.2019.08.092. Epub 2019 Aug 29.
- Cella D, Riley W, Stone A, Rothrock N, Reeve B, Yount S, Amtmann D, Bode R, Buysse D, Choi S, Cook K, Devellis R, DeWalt D, Fries JF, Gershon R, Hahn EA, Lai JS, Pilkonis P, Revicki D, Rose M, Weinfurt K, Hays R; PROMIS Cooperative Group. The Patient-Reported Outcomes Measurement Information System (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005-2008. J Clin Epidemiol. 2010 Nov;63(11):1179-94. doi: 10.1016/j.jclinepi.2010.04.011. Epub 2010 Aug 4.
- El-Jawahri A, LeBlanc T, VanDusen H, Traeger L, Greer JA, Pirl WF, Jackson VA, Telles J, Rhodes A, Spitzer TR, McAfee S, Chen YA, Lee SS, Temel JS. Effect of Inpatient Palliative Care on Quality of Life 2 Weeks After Hematopoietic Stem Cell Transplantation: A Randomized Clinical Trial. JAMA. 2016 Nov 22;316(20):2094-2103. doi: 10.1001/jama.2016.16786.
- Clover K, Lambert SD, Oldmeadow C, Britton B, King MT, Mitchell AJ, Carter G. PROMIS depression measures perform similarly to legacy measures relative to a structured diagnostic interview for depression in cancer patients. Qual Life Res. 2018 May;27(5):1357-1367. doi: 10.1007/s11136-018-1803-x. Epub 2018 Feb 8.
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