Feasibility and Acceptability Findings of an Energy Balance Data Repository of Children, Adolescents, and Young Adults with Cancer
Abstract
:1. Introduction
2. Experimental Section
2.1. Feasibility and Acceptability Parameters
2.2. Informed Consent
2.3. Inclusion and Exclusion Criteria
2.3.1. Inclusion Criteria
2.3.2. Exclusion Criteria
2.4. Data Collection
2.4.1. Clinical and Demographic Data
2.4.2. Diet and Nutrition Data
2.4.3. Physical Activity Data
2.4.4. Physical Function Data
2.4.5. Off Study Criteria
2.5. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Domains | Assessments | Purpose | |
---|---|---|---|
The body level measures | |||
Body size | Skinfold measurement, circumference (waist, arm, and calf area) | Evaluate muscle mass development | |
Flexibility | Sit and Reach | Evaluate the flexibility of the lower back and hamstring muscles | |
The individual level measures | |||
Motor skills | Tests for <18 years old | Tests for ≥18 years old | Evaluate movement function |
Bruininks-Oseretsky Test of Motor Proficiency (BOT-2) Functional Gait Assessment (FGA) | FGA and Berg Balance Scale | ||
Performance level | Tests for <18 years old | Tests for ≥18 years | Evaluate strength, general mobility and function, and neuromuscular coordination |
Hand grip dynamometry TUG-3m 30 s chair stand BOT-2 Standing Long Jump (SLJ) | Hand grip TUG-3m 30 s chair stand SLJ | ||
Cardiovascular Fitness | 6-min walk test (6-MWT) Borg Scale of Perceived Exertion (part of the 6-MWT) 20-m shuttle run (VO2 max) | Evaluate aerobic fitness and stamina | |
The societal level measures | |||
Self-reported QOL | Tests for <18 years old | Tests for ≥18 years old | Evaluate patient and survivors’ QOL |
PedsQL Cancer Module Wee-Functional Independence Measure (FIM) | PedsQL Cancer Module FIM |
Participant Characteristics | Mean ± SD | |
---|---|---|
Age at enrollment | 18.1 ± 7.5 Range: 4–36 | |
BMI (kg/m2) for those ≥20 years old (n = 30) | 26.6 ± 11.1 | |
n (%) aged <15 years | n (%) aged 15–39 years | |
Children with cancer | 26 (33%) | N/A † |
AYAs with cancer | N/A † | 54 (67%) |
Gender | ||
Male | 17 (65.4%) | 26 (48.1%) |
Female | 9 (34.6%) | 28 (51.9%) |
Race/Ethnicity | ||
Non-Hispanic White | 11 (42.3%) | 22 (40.7%) |
African American | 4 (15.4%) | 3 (5.6%) |
Hispanic | 6 (23.1%) | 23 (42.6%) |
Asian | 2 (7.7%) | 4 (7.4%) |
Other | 2 (7.7%) | 2 (3/7) |
Not reported | 1 (3.8%) | 0 |
BMI percentile ‡ | ||
≥95th percentile | 5 (19.2%) | 12 (22.2%) |
≥85th to <95th percentile | 2 (7.7%) | 2 (3.7%) |
5th to <85th percentile | 17 (65.4%) | 7 (17%) |
<5th percentile | 2 (7.7%) | 1 (1.9%) |
Not applicable | 0 | 32 (59.3%) |
Top 6 cancer diagnoses | ||
Acute lymphoblastic leukemia (ALL) | 9 (34.6%) | 12 (22.2%) |
Acute myeloid leukemia (AML) | 2 (7.7%) | 7 (13%) |
Wilms tumor | 2 (7.7%) | 0 |
Sarcoma | 7 (26.9) | 15 (27.8) |
Osteosarcoma | 5 (19.2%) | 4 (7.4%) |
CNS Tumor | 0 | 4 (7.4%) |
Other | 1 (3.8%) | 12 (22.2%) |
Metastasis status | ||
No | 20 (76.9%) | 38 (70.4%) |
Yes | 5 (19.2%) | 12 (22.2%) |
Not applicable | 1 (3.8%) | 4 (7.4%) |
Relapse status | ||
No | 20 (76.9%) | 37 (68.5%) |
Yes | 5 (19.2%) | 13 (24.1%) |
Not applicable | 1 (3.8%) | 4 (7.4%) |
Lansky–Karnofsky score (n = 29) | ||
60 | 0 | 1 (1.9%) |
70 | 0 | 2 (3.7%) |
80 | 1 (3.8%) | 3 (5.6%) |
90 | 4 (15.4%) | 12 (22.2%) |
100—Fully active | 4 (15.4%) | 2 (3.7%) |
Not reported | 17 (65.4%) | 34 (63%) |
ECOG score (n = 12) | ||
Asymptomatic | 0 | 5 (9.3%) |
Symptomatic, but completely ambulatory | 1 (3.8%) | 6 (11.1%) |
Not reported | 25 (96.2%) | 43 (79.6%) |
Co-enrollment | ||
Therapeutic trials | 0 | 0 |
Non-therapeutic trials | 10 (38.5%) | 22 (40.7%) |
No co-enrollment | 16 (61.5%) | 32 (59.3%) |
Repository Component | Total Number of Participants Consented | Participation Rate: % of Recruited Who Consented | Compliance Rate: Percent of Consented Who Completed Data Collection |
---|---|---|---|
Physical Activity | Patient logs: n = 42 Fitbit: n = 80 | Patient Logs = 52.5% Fitbit = 100% | % of Fitbits connected to Fitabase = 93.8% (75 connected) % of Fitbits collecting data = 83.8% (67 connected and collected data) Patient logs = N/A * |
Nutrition | Food diaries: n = 49 Labs: n = 35 (out of 46 recruited after labs added to the study) ASA24 = 1 consented (out of 15 recruited after ASA24 was added to the study) | Food Diaries = 61.3% Labs = 76.1% | Food Diaries = 49% (23 paper recalls and 1 ASA 24 completed) Labs = 74.3% (26 completed labs) |
Physical Function | Physical Function Tests: n = 9 (out of 15 recruited after physical function added to study) | Physical Function: 60% | Physical function tests = 33% (3 tests completed) |
Repository Component | Data Collection Challenges and Staff Time Descriptions |
---|---|
Recruitment | One and a half full-time equivalence Clinical Research Coordinators (CRCs) were required to review clinic schedules and recruit in clinic and remotely; CRCs spend 60% time on recruitment activities. |
Physical Activity | Missing data in Fitabase/Fitbits not synced to database. CRCs spend 30% time texting, emailing, and following up with participants encouraging them to charge the Fitbit and to sync the data. |
Nutrition | Inability to accurately do a 3-day food record for patient on intravenous nutrition. ASA24 challenges with mobile phone device. Lag time for delivery of paper diet recalls to dietitian for review. Difficulty scheduling patients for lab draws. Missing micronutrient levels for one participant. (Possible reasons include: missed draws, hemolysis, or substance interference.) CRCs spend 20% time on scheduling labs and review labs Research dietitians spend 5% time to review paper-based food diaries and resolve ASA24 issues. |
Physical Function | Inpatient participants difficult to schedule due to acute illness. Contact restrictions due to COVID-19. Team members spend 10% time scheduling and conducting functional assessments. |
Data entry | CRCs spend 30% time doing data entry |
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Swartz, M.C.; Teague, A.K.; Wells, S.J.; Honey, T.; Fu, M.; Mahadeo, K.M.; Kabiri, L.S.; Chandra, J.; Moody, K.; Schadler, K. Feasibility and Acceptability Findings of an Energy Balance Data Repository of Children, Adolescents, and Young Adults with Cancer. J. Clin. Med. 2020, 9, 2879. https://doi.org/10.3390/jcm9092879
Swartz MC, Teague AK, Wells SJ, Honey T, Fu M, Mahadeo KM, Kabiri LS, Chandra J, Moody K, Schadler K. Feasibility and Acceptability Findings of an Energy Balance Data Repository of Children, Adolescents, and Young Adults with Cancer. Journal of Clinical Medicine. 2020; 9(9):2879. https://doi.org/10.3390/jcm9092879
Chicago/Turabian StyleSwartz, Maria C., Alaina K. Teague, Stephanie J. Wells, Theresa Honey, Min Fu, Kris M. Mahadeo, Laura S. Kabiri, Joya Chandra, Karen Moody, and Keri Schadler. 2020. "Feasibility and Acceptability Findings of an Energy Balance Data Repository of Children, Adolescents, and Young Adults with Cancer" Journal of Clinical Medicine 9, no. 9: 2879. https://doi.org/10.3390/jcm9092879