Abstract
Background:
Older women with breast cancer are more likely than younger women to experience dose-limiting toxicities with chemotherapy. This leads to dose reduction, treatment discontinuation, and inferior treatment outcomes. Older women are also at higher risk of long-term detrimental impacts of treatment on quality of life and physical function.
Aim:
The primary aim of the TeleHealth Resistance exercise Intervention to preserve dose intensity and Vitality in Elder breast cancer patients (THRIVE-65) trial is to assess the effects of an exercise and nutrition intervention on chemotherapy relative dose intensity among women aged ≥65 receiving chemotherapy for early-stage breast cancer.
Methods/Design:
THRIVE-65 is a 2-arm parallel-group randomized controlled trial. The intervention includes two 30–45 min telehealth delivered resistance exercise sessions weekly, 90 min of unsupervised aerobic exercise weekly, and dietitian-guided high protein intake (1.2 g/kg/day)) delivered throughout the course of chemotherapy. The Health Education and Support control group receives a tablet with supportive care materials. Planned and observed chemotherapy dose and treatment schedule are recorded to assess relative dose intensity. Pre- and post- intervention assessments include patient reported outcomes, a geriatric assessment, dietary and physical activity measures, physical function and body composition.
Conclusions:
The THRIVE-65 trial is poised to answer a crucial scientific question: Can exercise and nutrition support improve chemotherapy tolerance among older breast cancer patients? Study results will inform clinical practice related to exercise and nutrition support for this population.
Keywords: Exercise, Nutrition, Breast cancer, Relative dose intensity
1. Introduction
Every year, more than 120,000 women over the age of 65 are diagnosed with breast cancer in the United States [1,2]. Although older patients with breast cancer often have favorable tumor subtypes [3] and present with early stages of disease [4], older women with breast cancer experience worse breast cancer-specific outcomes compared to younger women [5–7]. A recent analysis of data from the Surveillance, Epidemiology and End Results demonstrated increased risk of recurrence and mortality in older women across every stage and subtype of breast cancer [8].
The etiology of the worse prognosis in older women with early-stage breast cancer as compared to younger women is believed to be related to under-treatment and treatment-related toxicity [8–12]. Studies have shown that breast cancer patients who receive a relative dose intensity (RDI), reflecting both chemotherapy dose and dose-intensity, of <85 % have a 1.5 to 3-fold increase in the risk of disease recurrence, breast-cancer specific, and all-cause mortality as compared to women who receive ≥85 % RDI [13–15]. Across chemotherapy regimens, only 50–76 % of breast cancer patients aged 65 years or older receive an RDI >85 [16–18], as compared to 83 % of younger women [19]. Older women are 2.4 times more likely than younger women to experience dose-limiting toxicities with chemotherapy, not only leading to dose reduction, early treatment discontinuation, and inferior treatment outcomes, but also causing long-term detrimental impacts on quality of life, nutritional status, physical function, and mobility [20,21].
Older patients commonly exhibit poor functional status—often reflecting pre-existing comorbidities, protein-calorie malnutrition, and low muscle mass (sarcopenia) [22]. Inadequate nutritional status has been linked to poor chemotherapy tolerance; in particular, inadequate protein intake can contribute to sarcopenia in older cancer patients [23–25]. Studies demonstrate that up to 52 % of older women with breast cancer demonstrate low muscle mass at the time of diagnosis [26], and chemotherapy often exacerbates this condition by inducing further loss of skeletal muscle over the course of treatment [27]. Nutritional status and the effect of chemotherapy on muscle mass may help explain the inter-individual variability in treatment tolerability of older women with breast cancer and presents important targets to reduce treatment toxicity and improve treatment and cancer outcomes.
There is currently no standard approach for improving chemotherapy tolerability and increasing RDI in older patients with breast cancer. Two studies suggested that exercise interventions, particularly those incorporating resistance training during chemotherapy could improve RDI in individuals with breast cancer, but these studies did not focus on older breast cancer patients (mean age of participants was 49 and 50, respectively) and RDI was a secondary endpoint in both trials [28,29]. Exercise interventions lead to improvements in functional status, fall risk, and depression, in older adults without cancer [30–42]. However, in a nationally representative sample of US breast cancer survivors, only 31.7 % of women aged 65 years or older met aerobic physical activity guidelines (moderate to vigorous physical activity ≥150 min per week), and only 15.3 % met muscle-strengthening guidelines (2 sessions per week), underscoring the need for exercise interventions in this population [43,44].
The TeleHealth Resistance exercise Intervention to preserve dose intensity and Vitality in Elder breast cancer patients (THRIVE-65) trial is designed to test the effects of a telehealth delivered resistance training and aerobic exercise intervention, coupled with high protein intake support on RDI, objective physical function outcomes, patient reported outcomes, and body composition. THRIVE-65 is part of a larger NCI funded initiative called Exercise and Nutrition to Improve Cancer Treatment Outcomes (ENICTO), which aims to assess effects of exercise and nutrition on RDI in a variety of tumor types (e.g., breast, ovarian, colon, and gastrointestinal) [45].
2. Methods
2.1. Study overview
A total of 270 participants are being recruited from four sites: University of Pittsburgh’s UPMC Hillman Cancer Center, Dana-Farber Cancer Institute, Case Western Reserve University, and Mount Nittany Medical Center. Randomization in the THRIVE-65 trial occurs as close to the start of chemotherapy as possible (no later than the day of the 2nd infusion) and the intervention continues to the end of chemotherapy. Differences in RDI, chemotoxicities, patient reported outcomes, elements of the geriatric assessment, and muscle mass are compared between groups. (See Fig. 1.)
Fig. 1.

Study schema.
2.2. Study population and recruitment
Eligibility for THRIVE-65 includes women aged 65 and older with a diagnosis of Stage I-III breast cancer who are scheduled to receive at least 10 weeks of neoadjuvant or adjuvant cytotoxic chemotherapy. We limit our sample to women given the low prevalence of disease in males and because one of the mechanisms by which the intervention may be moderated (muscle mass) is known to differ by sex [46]. All participants report no participation in competitive aerobic activities and no history of consistent progressive resistance training within the past 3 months. Instead of an upper age limit, we include functional attributes which exclude women for whom participation would be unsafe. Women on therapeutic diets for comorbid disease are ineligible, except for type 2 diabetes mellitus and cardiovascular disease. Additional eligibility criteria include BMI 18–50 kg/m2, no medical conditions or medications that would prohibit participation in an exercise program or intake of a high protein diet, ability to walk for 6 min (assistive devices allowed), no current use of weight loss medication, no recent history of alcohol or substance use disorder or history of dementia. We specifically seek to include women of all races and ethnicities. Screening for eligible women occurs in the electronic medical record and all potentially eligible women are approached to invite participation. We aim to enroll a cohort that includes 20 % of women from racial and ethnic minority groups in order for the sample to be broadly representative of patients with breast cancer.
2.3. Randomization
To balance groups on factors that may influence the primary outcome, we stratify randomization according to clinical center (4 sites), chemotherapy regimen length (2 levels: ≤12 weeks vs >12 weeks), Cancer and Aging Research Group-Breast Cancer (CARG-BC) toxicity score (≤ 10 vs > 10) [47] and neoadjuvant vs adjuvant treatment period. We randomize study participants in a 1:1 manner to the THRIVE-65 intervention or the Health Education and Support Control group within each of the 32 ( = 4 × 2 × 2 × 2) strata via permuted blocks of random size two and four. The THRIVE-65 biostatistician generated the stratified randomization plan for each of the clinical sites.
2.4. Intervention description
The THRIVE-65 intervention has three components: progressive resistance exercise, aerobic exercise, and support to achieve a high protein diet. Participants receive recommendations from a registered dietitian at the beginning of the intervention period. Qualified trained exercise staff deliver the intervention through a hybrid model, including one initial supervised in-person exercise session (60 min) followed by twice-weekly telehealth exercise sessions (30–45 min) for the duration of their chemotherapy treatment. Frequent visits enable the exercise coach to respond in real time to symptom changes, titrating the exercise dose up or down according to Rated Perceived Exertion ratings for each set of each exercise. The Capability, Opportunity, and Motivation behavioral framework (COM—B) is used to guide coaching [48].
After the in-person exercise session, all diet and exercise sessions are delivered via telehealth through the THRIVE-65 portal, which contains links for video conferencing, a secure messaging channel for participants to communicate with their coaches, a schedule of upcoming sessions, and a graphical depiction of intervention progress. Participants access the portal through a study provided cellular-enabled tablet and tablet stand.
2.5. Intervention components
2.5.1. Progressive resistance exercise
At the first in-person exercise session, the onsite exercise coach teaches five strength training exercises (chest press, single arm rows, squats, lunges, and dead lifts), orients the participant to the tablet and the web portal, and instructs participants how to use the resistance bands (FitSimplify, Pleasanton, CA). If a participant cannot perform one of the five exercises without pain, an alternate exercise is provided that will focus on the same muscle group. The onsite exercise coach provides notes for the telehealth coach regarding biomechanics and adaptations needed. Given the proximity to breast surgery for many participants, all women start the upper body exercises with no greater than 4 pounds of resistance (the yellow band). For all resistance training sessions, the coach starts the session by asking if the woman has had any lymphedema symptoms that have lasted a week or longer. If yes, resistance for the upper body is reduced to body weight until symptoms clear or the woman is cleared by a lymphatic therapist. All participants with diagnosed lymphedema are required to wear a well-fitting compression garment for all resistance exercise activities. Participants work with a THRIVE call center exercise coach twice-weekly through video training sessions. Participants are asked to perform all 5 exercises 2–4 times per session, twice weekly, at progressive resistance levels. The planned resistance exercise dose schedule is provided in Table 2. All exercises can be done with support for balance or limited range of motion (holding onto a chair/wall), and with minimal space requirements. The site-specific coach remains available to participants if needed, but generally, all training is provided through telehealth. Equipment to perform exercises at home is shipped directly to patient homes from the Dana Farber Cancer Institute based THRIVE-65 call center (e.g., activity monitor and resistance bands). Resistance exercise dose progression is titrated to symptom response by asking Rated Perceived Exertion (RPE) for each exercise set, using the 1–10 RPE scale [49]. If RPE is below 8, resistance is increased for the next set. If RPE is 9 or 10 resistance is reduced for the next set.
Table 2.
Planned resistance exercise dose schedule (to be modified according to symptom burden).
| Week | # Resistance training sessions | Exercises per session | Repetitions per set | # of sets/exercise | RPE goal | Resistance and progression |
|---|---|---|---|---|---|---|
|
| ||||||
| 1 | 2 | 5 | 10 | 2 | 4 | Light to teach biomechanical form |
| 2 | 2 | 5 | 10 | 2 | 8 | Progress each week by smallest possible increment according to symptom burden |
| 3 | 2 | 5 | 10 | 2 | 8 | |
| 4 | 2 | 5 | 10 | 2 | 8 | |
| 5 | 2 | 5 | 10 | 3 | 8 | |
| 6 | 2 | 5 | 10 | 3 | 8 | |
| 7 | 2 | 5 | 10 | 3 | 8 | |
| 8 | 2 | 5 | 10 | 3 | 8 | |
| 9 | 2 | 5 | 10 | 4 | 8 | |
| 10 | 2 | 5 | 10 | 4 | 8 | |
| 11 | 2 | 5 | 10 | 4 | 8 | |
| 12 | 2 | 5 | 10 | 4 | 8 | |
2.5.2. Aerobic exercise
Participants are provided with a Fitbit to monitor their aerobic exercise and are taught to log the frequency, intensity, time, and type of aerobic exercise on the THRIVE-65 tablet during the onboarding session. In addition, the exercise coach discusses appropriate modes of aerobic exercise during chemotherapy, emphasizing convenience and safety. The exercise coach guides participants to increase their aerobic exercise to a goal of 3 weekly sessions of 30 min, at moderate intensity. Intensity is gauged using Rated Perceived Exertion, as heart rate response to exercise may be altered by chemotherapy. Participants are guided to exercise at an intensity of 4–6 on an RPE scale of 1–10. Exercise coaches titrate aerobic exercise dose at each supervise session according to patient-reported burden.
2.5.3. High protein intake support
THRIVE-65 intervention group participants receive telehealth-based counseling with a centralized Registered Dietitian Nutritionist (RDN) from the Dana-Farber-based THRIVE-65 site. The initial diet counseling includes (1) a discussion of current dietary protein intake, (2) provision of goal to obtain 1.2 g protein/kg/day – a level of intake currently promoted to advance health, including preservation of muscle mass, in older women (3) counseling on high quality protein sources from food, (4) guidance regarding an overall healthy eating plan, and (5) instruction on how to use a daily protein checklist on their THRIVE-65 tablet, adapted from a validated protein screener [50]. After 1 week, the THRIVE-65 dietitian reviews the average protein intake based on daily checklists. If participants are ingesting less than 1.2 g protein/kg/day through their dietary choices, we initiate supplementation with a powdered protein supplement (multiple options from Vega USA, New York, New York and Naked Nutrition, Miami, FL). Protein is monitored through the patient-reported protein checklists which are reviewed weekly by the exercise coach. If participants are unable to achieve their protein goals, on average, for greater than two weeks, repeat counseling with the registered dietitian is provided. Additionally, site study staff monitor participant renal and hepatic function throughout the intervention period. If the liver function tests and/or glomerular filtration rate increase to >1.5 normal values, patients are advised to decrease protein intake, and the labs are re-evaluated within 4 weeks. Although uncommon, persistent values at this level requires discontinuation of higher protein diet.
Intervention Standardization and Monitoring.
To promote rigor and reproducibility, measures are taken to standardize the intervention, all monitored on bi-weekly intervention team calls that include both PIs, including centralized coordination, monitoring and communication between on-site study coordinators, exercise coaches, and the RDN; monitoring of adverse events and barriers to protein intake arising between intervention sessions.
Fitbit steps are monitored for all participants using a cloud-based data platform (PittBit, University of Pittsburgh). PittBit aggregates and stores daily step count, sleep, and heart rate data. Resistance training is monitored by witnessing the sessions, as most sessions are supervised by an exercise coach. In the event of a makeup session, unsupervised resistance exercise sessions are self-reported. Aerobic exercise is monitored via PittBit and self-report. Monitoring of exercise sessions includes self-report of RPE and the Feeling Scale [51]. Resistance Exercise and Aerobic Exercise Relative Dose Intensity is calculated for each session planned according to a previously published algorithms [52,53]. Protein intake is monitored by a protein intake checklist that is reviewed at all resistance training sessions by the exercise coach and reported to the study dietitian. Comparison of protein prescribed to protein ingested is tracked on a weekly basis for all intervention participants.
Participants have access to a secure messaging system through the THRIVE-65 portal and contact numbers to alert their exercise coach and study personnel of issues that develop. Medical problems will be promptly referred to the participants’ treating oncologist. The time spent on all intervention components is recorded on standardized forms in RedCAP.
2.6. Health education and support control
All study participants are provided with a tablet loaded with supportive care materials. A study staff person introduces the tablet and all interventions on the tablet just after randomization. The resources included on the tablet include recipes and cooking demos (not focused on protein), soothing music, guided meditation, yoga, and light stretching. Women randomized to the Health Education and Support Control Comparison group are also provided with a Fitbit and brief monthly newsletters on topics such as stress, symptom management tips, and healthful recipes. We acknowledge that the attention provided to the Health Education and Support Control group is less than the intervention group and that this presents the potential for attention bias in the THRIVE-65 trial. We designed the trial this way in acknowledgement of available resources and with a desire for the comparison group resources to be more reflective of standard of care activities.
2.7. Consenting, IRB, DSMB, PAB
All participants are required to provide informed consent, either verbal or written, depending on the site. Treating providers provide permission for approach. A single IRB is used for this study and all sites rely on Dana-Farber Cancer Institute’s IRB. Our Data Safety Monitoring Board (DSMB) meets twice yearly to review study progress and provide guidance. Our patient advisory board (PAB) consists of patient advisors from all recruiting sites. The PAB meets 3–4 times annually to ensure that our study design and implementation reflects patients’ needs and concerns.
2.8. Measurements
An overview of all measures is provided in Table 1.
Table 1.
Overview of all measurements in the THRIVE-65 trial.
| Outcomes and measures | Instrument | Baseline | At each cycle | End-of-study |
|---|---|---|---|---|
|
| ||||
| Primary Outcomes | ||||
| Relative Dose Intensity (RDI) | Electronic Health Record | X | ||
| Secondary Outcomes | ||||
| Hematologic chemotoxicities | Electronic Health Record | X | ||
| Chemotoxicities | PRO-CTCAEa | X | ||
| Injury/Illness | Assessment of Adverse Events Questionnaire | X | ||
| Health related quality of life | MOS SF-36b | X | X | |
| Social activity limitation | MOS Social Activity Limitation Scaleb | X | X | |
| Social support | MOS Social Support Survey Subscaleb | X | X | |
| Subjective sleep disturbance | Pittsburgh Sleep Quality Index (PSQI)b | X | X | |
| Anxiety | PROMIS Anxiety Short Form 8a | X | X | |
| Activities of daily living | OARS MFAQ (IADL)b | X | X | |
| Physical health status | OARS Physical Health Sectionb | X | X | |
| Physical activity | Morgenstein Physical Activity Questionnaire (PAQ-M) | X | X | |
| Other Patient Reported Outcomes | ||||
| Socio-demographic data | Demographic survey | X | X | |
| Hunger Vital Sign | Hunger Vital Sign survey | X | X | |
| Symptoms of peripheral neuropathy | FACT/GOG-NTX-4 | X | X | |
| Dietary intake | 24 Hour Dietary Recall | X | X | |
| Depressive symptoms | Geriatric Depression Scale Short Formb | X | X | |
| Presence of lymphedema | Norman Lymphedema Surveyd | X | X | |
| Cognitive impairment | Universal Mini-Cog Scaleb | X | X | |
| Healthcare utilization | Healthcare Utilization survey | X | ||
| Engagement with study tablet | THRIVE-65 Tablet Engagement Questionnaire | X | ||
| Protein intake | Protein checklistc | X | ||
| Physical measurements | ||||
| Anthropometry | Body weight, height, waist circumference | X | X | |
| Grip Strength | Handgrip assessmentb | X | X | |
| Functional exercise capacity | 6-Minute Walk Testb | X | X | |
| Body composition and body size | D3-creatine dilution test | X | X | |
| Physical activity | ActiGraph accelerometry, and activity tracker (Fitbit)e | X | ||
| Karnofsky performance status (KPS) | Assessed by study physicianb | X | X | |
PRO-CTCAE will be administered on Day 1 and Day 8 of the first and final cycles of chemotherapy
Part of the comprehensive geriatric assessment (CGA) (physical function, psychological and psychosocial status)
Intervention participants will complete throughout the study; Health Education and Support participants will complete at start of third cycle of chemotherapy
Administered only to participants who have already completed breast surgery at the time of enrollment
Participants are provided with a Fitbit at randomization and physical activity, as well as, step count, heart rate, and sleep, are collected throughout chemotherapy treatment.
2.8.1. Primary outcome: relative dose intensity
Relative dose intensity (RDI) reflects both chemotherapy dose and the dose-intensity of administration. RDI is calculated according to the formula below, whereby Standard Dose Intensity (SDI) describes the agents, number of cycles, doses, and treatment duration as prescribed by the treating oncologist at the initiation of treatment; and Delivered Dose Intensity (DDI) describes the agents, number of cycles, doses, and treatment duration of the chemotherapy administered to the participant as abstracted from the electronic health record.

RDI is calculated individually for each drug administered as part of a combination chemotherapy regimen, then averaged across the number of agents administered. Notably, the process of calculating RDI in breast cancer is made more complex by the number of regimens which are utilized in the setting of early breast cancer (16 regimens to date in 128 patients randomized).
2.8.2. Secondary outcomes
2.8.2.1. Chemotoxicities; PRO-CTCAE.
Chemotoxicities are assessed by patient report at the start of each chemotherapy cycle and on day 8 of the first and final study cycles using a Patient-Reported Outcomes-Common Terminology Criteria for Adverse Events (PRO-CTCAE) survey [54]. The survey assesses symptoms and adverse events associated with chemotherapy including dry mouth, difficulty swallowing, mouth/throat sores, taste changes, decreased appetite, nausea, vomiting, heartburn, constipation, diarrhea, abdominal pain, shortness of breath, neuropathy, concentration and memory, pain, insomnia, and fatigue.
2.8.2.2. Body composition.
D3-Creatine Dilution Assay.
Participants undergo assessment of muscle mass through D3-Creatine Dilution Assay. The measurement relies on a single spot urine sample taken 72–120 h after D3-Creatine dosing. D3 muscle mass correlates strongly with risk of mobility limitation, injurious falls, and worse physical performance in a cohort 1382 men aged 65 + [55]. Capsules prepared with D3-creatine powder and urine collection kits are shipped to participants from the University of Pittsburgh at baseline and at the end of study. At baseline, participants collect urine specimens in a fasted state on provided collection sticks after an overnight fast between 72 and 120 h after ingestion of a D3-creatine capsule. At the end of study timepoint, participants provide two urine specimens, both after an overnight fast, in a fasted state: one prior to ingestion of the D3-Creatine capsule and one 72–120 h after ingestion of the capsule. D3-creatine dilution assays are performed at the University of California, Berkeley.
2.8.3. Geriatric assessment
The geriatric assessment is a multidimensional, interdisciplinary diagnostic process focusing on determining an older person’s medical, psychosocial, and functional capabilities to develop a coordinated and integrated plan for treatment and long-term follow-up. The assessment is collected at baseline and follow-up. The THRIVE-65 geriatric assessment consists of the following measures: OARS MFAQ (IADL) [56,57], OARS Physical Health Section [56,57], MOS SF-36 Physical Functioning Scale [58–61], MOS Social Activity Limitation Scale [62], MOS Social Support Survey Subscale [62], Universal Mini-Cog Scale [63,64], Geriatric Depression Scale Short Form [65], Karnofsky Performance Status Rated by Healthcare Professional [66], Handgrip assessment, and 6-min walk test [67]. A study staff member screens the patient for depressive symptoms using the Geriatric Depression Scale (GDS) during the in-person visits at baseline and the end of study. In the event of a high score (≥ 5) on the GDS, study staff notifies participants’ oncology provider(s) within 2 days so that they may make referrals, as appropriate. The score of ≤3 on the Universal Mini-Cog Scale is shared to alert staff of the potential need for additional navigation and support to complete study activities. Elements of the Geriatric Assessment enable us to derive a frailty index [68]. In addition, the CARG-BC chemotherapy toxicity calculator [47] will also be used to evaluate frailty.
2.8.4. Patient-reported outcome measurements
Other patient-reported outcomes are measured at baseline and/or end of study timepoints (Table 1). The PROMIS Anxiety Short Form 8a is used to assess anxiety in study participants [69]. The Morgenstein Physical Activity Questionnaire (PAQ-M) is used to capture recreational, occupational, and household activity [70]. The FACT/GOG-NTX-4 survey assesses symptoms of peripheral neuropathy [71]. The Norman Lymphedema Survey is completed by participants who have had a breast cancer surgery prior to study entry at baseline and end of study timepoints [71]. Participants complete a Hunger Vital screening tool [72] and the Pittsburgh Sleep Quality Index (PSQI) [73–75] to assess food security/insecurity and sleep disturbance, respectively. A Healthcare Utilization survey is also administered at the end of study [76]. Participants also complete brief surveys throughout the study to assess chemotoxicities, injury or illness, and engagement with the study tablet.
2.8.5. Additional measures
2.8.5.1. Objective physical measurements (Strength, Endurance/Function).
Physical assessments for strength and endurance are completed at baseline and end of study (Table 1). The 6-Minute Walk Test (6MWT) is used to evaluate aerobic fitness and functional exercise capacity. Isometric grip strength is assessed for each hand using a Takei hand dynamometer (Takei Scientific Instruments, Tokyo, Japan).
2.8.5.2. Accelerometry.
Participants wear an Actigraph accelerometer at the waist for 4–7 consecutive days at baseline and on conclusion of chemotherapy treatment (Actigraph, Walton Beach, FL). Accelerometer data includes estimated average metabolic equivalents expended daily and in hours/week as well as time in sedentary, low, moderate and vigorous activity.
2.8.5.3. Diet.
Participants provide two 24-h dietary recalls at baseline and at end of study. These recalls are conducted through the Behavioral Measurement and Interventions Shared Resource (BMISR) at the University of Arizona (UA) Cancer Center and serve as the primary measure of protein exposure during the study. Participants are also provided with protein checklist, adapted from a validated protein screener [50]. THRIVE-65 Intervention participants complete the protein checklist starting after the initial diet counseling session and continue throughout the study. Health Education and Support Control participants complete a protein checklist during their 3rd cycle on study to assess changes in protein intake. The protein checklist is primarily to support dietary behavior change in the intervention group and secondarily as a measure of protein exposure throughout the study.
2.9. Rigor and reproducibility
To ensure rigor and reproducibility in the THRIVE-65 trial, we undertake annual site visits at each enrolling site to review all patient facing and data management activities. The study team meets weekly to discuss ongoing issues, there is a bi-weekly intervention call to review current participant activities.
2.10. Data management
All data are managed via REDCap at the University of Pittsburgh. Regular meetings are held with the data management team and spot checks for data accuracy are performed. The data management team uses a ‘data double check’ procedure to alert staff with comments in REDCap when there is a value that requires a re-check.
2.10.1. Implementation assessment
The THRIVE-65 team plans two activities designed to speed translation of effective results into practice. First, we will describe the THRIVE-65 intervention’s core functions (i.e., the core purpose of the change process that the intervention seeks to facilitate), as well as the intervention’s forms, (i.e., the specific strategies/activities needed to carry out core functions) [77]. In this efficacy trial, we can develop a better understanding of the interventions’ requirements and demands, as well as the implementation context including patient and health care provider perspectives, to help identify strategies that can be applied to support implementation and adaptation. We will review program documents (proposal, protocol, manual of procedures) to develop a map outlining each intervention’s core functions (required processes) and forms (activities) related to intervention implementation. Identifying the core functions and their forms for each project will help us to acceptable adaptations in future iterations of the interventions for hybrid effectiveness-implementation trials or implementation in practice. The function and form matrix will also inform documentation of (implementation) cost. The identification of function and forms is being done across all projects in the ENICTO consortium [45], to help investigators make cross-project comparisons.
The second implementation planning activity involves gathering input from healthcare system stakeholders to identify barriers and facilitators that would influence implementation of the THRIVE-65 intervention (patients are being interviewed in a separate ENICTO consortium-wide qualitative study). Five to eight stakeholders will be identified from each clinical site, including oncology care teams (including physicians, mid-level practitioners, nurses) and administrators/decision-makers (identified through snowball sampling). The sample size may be adjusted downward if saturation is reached early, or upward if saturation is not achieved with the initial sample size. We will conduct semi-structured interviews using questions based on constructs from the Consolidated Framework for Implementation Research (CFIR) [78,79]. Interviews will be recorded and transcribed prior to analysis, and analyzed using Rapid Qualitative Analysis methods [80]. Each interview will be summarized by two team members, and results will be compiled in a matrix that summarizes data related to constructs and domains across individuals, roles, and sites.
2.11. Statistical considerations
2.11.1. Sample size
The target sample size is 270 randomized women (randomized 1:1 to the THRIVE-65 intervention and Health Education and Support control groups). Assuming a two-sided, 0.05 significance level test and 20 % drop-out rate, the table below provides the study’s power and detectable effect size, based on 65–75 % of control participants reaching an RDI of at least 85 %. (Table 3.)
Table 3.
Power calculations for THRIVE 65.
| 80 % POWER | 85 % POWER | 90 % POWER | |||||||
|---|---|---|---|---|---|---|---|---|---|
|
|
|
|
|
||||||
| GROUP | Proportion reaching 85 % RDI* | Proportion reaching 85 % RDI | Proportion reaching 85 % RDI | ||||||
|
| |||||||||
| Health Education and Support Control | 0.65 | 0.70 | 0.75 | 0.65 | 0.70 | 0.75 | 0.65 | 0.70 | 0.75 |
| Thrive Intervention | 0.82 | 0.86 | 0.89 | 0.83 | 0.87 | 0.90 | 0.84 | 0.88 | 0.91 |
RDI = Relative Dose Intensity.
With respect to the geriatric assessment variables and muscle mass, the sample size of 270 randomized women provides 90 % statistical power for detecting relatively small effect sizes on the order of 0.45 standard deviation units.
2.11.2. Statistical analysis
Aim 1 consists of determining whether the THRIVE-65 intervention, when compared to the Health Education and Support control group, improves the primary outcome variable of received dose intensity (RDI). We will construct a binary variable as to whether a study participant reaches 85 % RDI. We will apply stratified analyses for the primary outcome in order to compare the THRIVE-65 intervention and Health Education and Support control groups while accounting for the 32 strata. It is likely that some of the subgroup and stratified analyses will involve small cell sizes. Although the statistical power in such situations will be low, it will be important to examine the magnitude of the effects and their corresponding confidence intervals to assess those results that are intriguing. We will apply a stratified binary logistic regression analysis via a generalized linear model [81]. We will impose a significance level of 0.05 for the analysis of the primary outcome. As a secondary analysis of RDI, we will invoke VanderWeele’s mediation model to determine the direct effect of the THRIVE-65 intervention and the mediating indirect effects through muscle mass from D3, elements of the geriatric assessment, and responses to the patient reported outcome surveys [82]. A priori secondary analyses will include evaluation of the primary outcome (RDI) as a continuous variable and evaluation of binary and continuous RDI when only including chemotherapy delivered after randomization, as well as subgroup analyses by age groups (splitting by median cohort age), regimen length (<13 weeks versus ≥13 weeks), and by intervention adherence (exercise and protein supplementation). We will report unadjusted and adjusted (false discovery rate) p-values for this set of secondary analyses.
Aim 2 consists of determining whether the THRIVE-65 intervention, when compared to the Health Education and Support control, improves chemotoxicities and patient-reported outcomes, and preserves/improves muscle mass. For the chemotoxicities, each of the items of the PRO-CTCAE survey will be dichotomized such that a score of 3 or higher designates a chemotoxicity (yes/no). Therefore, we will apply a stratified binomial regression (number of chemotoxicities out of total possible) embedded within a generalized linear mixed-effects model to account for the repeated measures from multiple infusions [81].
3. Results and discussion
3.1. Status of recruitment
As of this writing we have consented 159 patients and randomized 128 patients into the trial. Given the pace of recruitment was lower than anticipated during the first year, we have added a recruitment site: Mount Nittany Medical Center.
3.2. Plans for successful completion of the project
Recruitment is often a key challenge for completion of trials. We have added satellite sites existing recruitment sites, as well as Mount Nittany Medical Center, to address this challenge. We anticipate completion of recruitment within the initial five-year funding period.
3.3. Strengths and limitations
The THRIVE-65 study will be the only to date evaluating the impact of a structured exercise and protein supplementation program on RDI in women 65 and older receiving neo/adjuvant chemotherapy, a patient population at risk for poor outcomes due to chemotherapy toxicity and dose disruptions. The remotely supervised nature of the intervention allows for intervention fidelity and a high degree of personalized support. Limitations of the study approach include a relatively modest sample size, precluding adequate power to evaluate disease outcomes such as recurrence and survival. Additionally, the multi-component nature of the intervention will not allow us to determine the individual contributions of exercise and protein supplementation to supporting RDI in this population.
4. Conclusion
The THRIVE-65 trial is poised to establish whether exercise and nutrition support improve chemotherapy tolerance among older breast cancer patients. Study results may alter clinical practice to include exercise and nutrition support to improve clinical outcomes among older breast cancer patients.
Acknowledgements
Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under award numbers P30CA047904 to Schmitz and U01-CA271277 to Schmitz and Ligibel. This trial is registered at ClinicalTrials.gov as NCT05535192. There are no data shared, as this is a protocol paper.
Footnotes
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
CRediT authorship contribution statement
Kathryn H. Schmitz: Writing – review & editing, Writing – original draft, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Nathan A. Berger: Supervision, Project administration, Funding acquisition, Data curation, Conceptualization. Cynthia Owusu: Writing – review & editing, Supervision, Project administration, Investigation, Data curation, Conceptualization. Cynthia A. Thomson: Writing – review & editing, Writing – original draft, Supervision, Project administration, Methodology, Investigation, Data curation, Conceptualization. Vernon M. Chinchilli: Writing – review & editing, Writing – original draft, Supervision, Project administration, Investigation, Formal analysis, Conceptualization. Karen Basen-Engquist: Writing – review & editing, Writing – original draft, Supervision, Project administration, Investigation, Conceptualization. William J. Evans: Writing – review & editing, Writing – original draft, Supervision, Project administration, Methodology, Investigation, Formal analysis, Conceptualization. John J. Pink: Writing – review & editing, Supervision, Project administration, Investigation, Conceptualization. Erica A. Schleicher: Writing – review & editing, Writing – original draft, Supervision, Project administration, Investigation. Chao Cao: Writing – review & editing, Writing – original draft, Supervision, Methodology, Investigation. Shawna E. Doerksen: Writing – review & editing, Writing – original draft, Supervision, Project administration, Investigation, Conceptualization. Jenna D. Binder: Writing – original draft, Supervision, Project administration, Investigation. Michele D. Sobolewski: Writing – original draft, Supervision, Project administration, Investigation. Anna M. Tanasijevic: Writing – original draft, Supervision, Project administration, Investigation. Kaedryn A. Diguglielmo: Writing – original draft, Supervision, Project administration, Investigation. Truong L. Nguyen: Writing – original draft, Supervision, Project administration, Investigation. Carissa A. Mills: Writing – original draft, Supervision, Project administration, Investigation. Wendy Kemp: Writing – original draft, Supervision, Project administration, Investigation. Jay B. Oppenheim: Writing – original draft, Supervision, Project administration, Investigation. Jennifer A. Ligibel: Writing – review & editing, Writing – original draft, Validation, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization.
Data availability
No data was used for the research described in the article.
References
- [1].Surveillance, Epidemiology, and End Results (SEER) Program SEER*State Database: Mortality - All COD, Aggregated with State, Total U.S. (1969–2014), 2016. [Google Scholar]
- [2].Siegel RL, Miller KD, Fuchs HE, Jemal A, Cancer statistics, 2021, CA Cancer J. Clin. 71 (1) (Jan 2021) 7–33, 10.3322/caac.21654. [DOI] [PubMed] [Google Scholar]
- [3].Howlader N, Altekruse SF, Li CI, et al. , US incidence of breast cancer subtypes defined by joint hormone receptor and HER2 status, J. Natl. Cancer Inst. 106 (5) (Apr 28 2014), 10.1093/jnci/dju055. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [4].Schonberg MA, Marcantonio ER, Li D, Silliman RA, Ngo L, McCarthy EP, Breast cancer among the oldest old: tumor characteristics, treatment choices, and survival, J. Clin. Oncol. 28 (12) (Apr 20 2010) 2038–2045, 10.1200/jco.2009.25.9796. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [5].Partridge AH, Hughes ME, Warner ET, et al. , Subtype-dependent relationship between young age at diagnosis and breast Cancer survival, J. Clin. Oncol. 34 (27) (2016) 3308–3314, 10.1200/jco.2015.65.8013. [DOI] [PubMed] [Google Scholar]
- [6].Schonberg MA, Marcantonio ER, Ngo L, Li D, Silliman RA, McCarthy EP, Causes of death and relative survival of older women after a breast cancer diagnosis, J. Clin. Oncol 29 (12) (Apr 20 2011) 1570–1577, 10.1200/jco.2010.33.0472. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [7].Smith BD, Jiang J, McLaughlin SS, et al. , Improvement in breast cancer outcomes over time: are older women missing out? J. Clin. Oncol. 29 (35) (Dec 10 2011) 4647–4653, 10.1200/JCO.2011.35.8408. [DOI] [PubMed] [Google Scholar]
- [8].Freedman RA, Keating NL, Lin NU, et al. , Breast cancer-specific survival by age: worse outcomes for the oldest patients, Cancer 124 (10) (2018/05/15) 2184–2191, 10.1002/cncr.31308. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [9].Freedman RA, He Y, Winer EP, Keating NL, Trends in racial and age disparities in definitive local therapy of early-stage breast cancer, J. Clin. Oncol 27 (5) (Feb 10 2009) 713–719, 10.1200/jco.2008.17.9234. [DOI] [PubMed] [Google Scholar]
- [10].Freedman RA, Hughes ME, Ottesen RA, et al. , Use of adjuvant trastuzumab in women with human epidermal growth factor receptor 2 (HER2)-positive breast cancer by race/ethnicity and education within the National Comprehensive Cancer Network, Cancer 119 (4) (Feb 15 2013) 839–846, 10.1002/cncr.27831. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [11].Freedman RA, Vaz-Luis I, Barry WT, et al. , Patterns of chemotherapy, toxicity, and short-term outcomes for older women receiving adjuvant trastuzumab-based therapy, Breast Cancer Res. Treat. 145 (2) (Jun 2014) 491–501, 10.1007/s10549-014-2968-9. [DOI] [PubMed] [Google Scholar]
- [12].Vaz-Luis I, Keating NL, Lin NU, Lii H, Winer EP, Freedman RA, Duration and toxicity of adjuvant trastuzumab in older patients with early-stage breast cancer: a population-based study, J. Clin. Oncol. 32 (9) (2014) 927–934, 10.1200/JCO.2013.51.1261. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [13].Wood WC, Budman DR, Korzun AH, et al. , Dose and dose intensity of adjuvant chemotherapy for stage II, node-positive breast carcinoma, N. Engl. J. Med. 330 (18) (May 05 1994) 1253–1259, 10.1056/NEJM199405053301801. [DOI] [PubMed] [Google Scholar]
- [14].Zhang L, Yu Q, Wu XC, et al. , Impact of chemotherapy relative dose intensity on cause-specific and overall survival for stage I-III breast cancer: ER+/PR+, HER2− vs. triple-negative, Breast Cancer Res. Treat. 169 (1) (May 2018) 175–187, 10.1007/s10549-017-4646-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [15].Qi W, Wang X, Gan L, Li Y, Li H, Cheng Q, The effect of reduced RDI of chemotherapy on the outcome of breast cancer patients, Sci. Rep. 10(1):13241 (Aug 6 2020), 10.1038/s41598-020-70187-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [16].Shayne M, Culakova E, Poniewierski MS, et al. , Dose intensity and hematologic toxicity in older cancer patients receiving systemic chemotherapy, Cancer 110 (7) (Oct 01 2007) 1611–1620, 10.1002/cncr.22939. [DOI] [PubMed] [Google Scholar]
- [17].Shayne M, Culakova E, Wolff D, et al. , Dose intensity and hematologic toxicity in older breast cancer patients receiving systemic chemotherapy, Cancer 115 (22) (11/15 2009) 5319–5328, 10.1002/cncr.24560. [DOI] [PubMed] [Google Scholar]
- [18].Ladwa R, Kalas T, Pathmanathan S, Woodward N, Wyld D, Sanmugarajah J, Maintaining dose intensity of adjuvant chemotherapy in older patients with breast Cancer, Clin. Breast Cancer 18 (5) (Oct 2018) e1181–e1187, 10.1016/j.clbc.2018.04.016. [DOI] [PubMed] [Google Scholar]
- [19].Sandy J, Della-Fiorentina S, Relative dose intensity in early stage breast cancer chemotherapy: a retrospective analysis of incidence, risk factors and outcomes at a south-West Sydney cancer clinic, Asia Pac. J. Clin. Oncol. 9 (4) (Dec 2013) 365–372, 10.1111/ajco.12093. [DOI] [PubMed] [Google Scholar]
- [20].Crivellari D, Bonetti M, Castiglione-Gertsch M, et al. , Burdens and benefits of adjuvant cyclophosphamide, methotrexate, and fluorouracil and tamoxifen for elderly patients with breast cancer: the international breast Cancer study group trial VII, J. Clin. Oncol. 18 (7) (Apr 2000) 1412–1422, 10.1200/jco.2000.18.7.1412. [DOI] [PubMed] [Google Scholar]
- [21].Muss HB, Berry DA, Cirrincione C, et al. , Toxicity of older and younger patients treated with adjuvant chemotherapy for node-positive breast cancer: the Cancer and leukemia group B experience, J. Clin. Oncol. 25 (24) (Aug 20 2007) 3699–3704, 10.1200/jco.2007.10.9710. [DOI] [PubMed] [Google Scholar]
- [22].Mohile SG, Dale W, Somerfield MR, et al. , Practical assessment and Management of Vulnerabilities in older patients receiving chemotherapy: ASCO guideline for geriatric oncology, J. Clin. Oncol. (May 21 2018), 10.1200/JCO.2018.78.8687.JCO2018788687. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [23].Zanetti M, Gortan Cappellari G, Barazzoni R, Sanson G, The impact of protein supplementation targeted at improving muscle mass on strength in Cancer patients: a scoping review, Nutrients 12 (7) (Jul 16 2020), 10.3390/nu12072099. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [24].Beasley JM, Shikany JM, Thomson CA, The role of dietary protein intake in the prevention of sarcopenia of aging, Nutr. Clin. Pract. 28 (6) (Dec 2013) 684–690, 10.1177/0884533613507607. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [25].Davis MP, Panikkar R, Sarcopenia associated with chemotherapy and targeted agents for cancer therapy, Annals of palliative medicine. 8 (1) (Jan 2019) 86–101, 10.21037/apm.2018.08.02. [DOI] [PubMed] [Google Scholar]
- [26].Caan BJ, Cespedes Feliciano EM, Prado CM, et al. , Association of muscle and adiposity measured by computed tomography with survival in patients with nonmetastatic breast cancer, JAMA Oncol 4 (6) (Jun 1 2018) 798–804, 10.1001/jamaoncol.2018.0137. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [27].Jang MK, Park C, Hong S, Li H, Rhee E, Doorenbos AZ, Skeletal muscle mass change during chemotherapy: a systematic review and meta-analysis, Anticancer Res. 40 (5) (May 1, 2020) 2409–2418, 10.21873/anticanres.14210. [DOI] [PubMed] [Google Scholar]
- [28].van Waart H, Stuiver MM, van Harten WH, et al. , Effect of low-intensity physical activity and moderate-to high-intensity physical exercise during adjuvant chemotherapy on physical fitness, fatigue, and chemotherapy completion rates: results of the paces randomized clinical trial, J. Clin. Oncol. 33 (17) (Jun 10 2015) 1918–1927, 10.1200/JCO.2014.59.1081. [DOI] [PubMed] [Google Scholar]
- [29].Courneya KS, Segal RJ, Mackey JR, et al. , Effects of aerobic and resistance exercise in breast cancer patients receiving adjuvant chemotherapy: a multicenter randomized controlled trial, J. Clin. Oncol. 25 (28) (Oct 1 2007) 4396–4404. [DOI] [PubMed] [Google Scholar]
- [30].Sherrington C, Michaleff ZA, Fairhall N, et al. , Exercise to prevent falls in older adults: an updated systematic review and meta-analysis, Br. J. Sports Med. 51 (24) (Dec 2017) 1750–1758, 10.1136/bjsports-2016-096547. [DOI] [PubMed] [Google Scholar]
- [31].Booth FW, Roberts CK, Laye MJ, Lack of exercise is a major cause of chronic diseases, Compr. Physiol. 2 (2) (Apr 2012) 1143–1211, 10.1002/cphy.c110025. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [32].Landi F, Abbatecola AM, Provinciali M, et al. , Moving against frailty: does physical activity matter? Biogerontology 11 (5) (2010) 537–545, 10.1007/s10522-010-9296-1. [DOI] [PubMed] [Google Scholar]
- [33].Pahor M, Guralnik JM, Ambrosius WT, et al. , Effect of structured physical activity on prevention of major mobility disability in older adults: the LIFE study randomized clinical trial, Jama 311 (23) (2014) 2387, 10.1001/jama.2014.5616. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [34].Thornell LE, Sarcopenic obesity: satellite cells in the aging muscle, Curr. Opin. Clin. Nutr. Metab. Care 14 (1) (Jan 2011) 22–27, 10.1097/MCO.0b013e3283412260. [DOI] [PubMed] [Google Scholar]
- [35].Kang JS, Krauss RS, Muscle stem cells in developmental and regenerative myogenesis, Curr. Opin. Clin. Nutr. Metab. Care 13 (3) (May 2010) 243–248, 10.1097/MCO.0b013e328336ea98. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [36].Calvani R, Joseph AM, Adhihetty PJ, et al. , Mitochondrial pathways in sarcopenia of aging and disuse muscle atrophy, Biol. Chem. 394 (3) (Mar 2013) 393–414, 10.1515/hsz-2012-0247. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [37].Northey JM, Cherbuin N, Pumpa KL, Smee DJ, Rattray B, Exercise interventions for cognitive function in adults older than 50: a systematic review with meta-analysis, Br. J. Sports Med. 52 (3) (Feb 2018) 154–160, 10.1136/bjsports-2016-096587. [DOI] [PubMed] [Google Scholar]
- [38].Rasmussen P, Brassard P, Adser H, et al. , Evidence for a release of brain-derived neurotrophic factor from the brain during exercise, Exp. Physiol. 94 (10) (Oct 2009) 1062–1069, 10.1113/expphysiol.2009.048512. [DOI] [PubMed] [Google Scholar]
- [39].Seo JY, Chao YY, Effects of exercise interventions on depressive symptoms among community-dwelling older adults in the united states: a systematic Review, J. Gerontol. Nurs. 44 (3) (Mar 1 2018) 31–38, 10.3928/00989134-20171024-01. [DOI] [PubMed] [Google Scholar]
- [40].Payne JK, Held J, Thorpe J, Shaw H, Effect of exercise on biomarkers, fatigue, sleep disturbances, and depressive symptoms in older women with breast cancer receiving hormonal therapy, Oncol. Nurs. Forum 35 (4) (Jul 2008) 635–642. [DOI] [PubMed] [Google Scholar]
- [41].Kohut ML, McCann DA, Russell DW, et al. , Aerobic exercise, but not flexibility/resistance exercise, reduces serum IL-18, CRP, and IL-6 independent of beta-blockers, BMI, and psychosocial factors in older adults, Brain Behav. Immun. 20 (3) (2006) 201–209, 10.1016/j.bbi.2005.12.002. [DOI] [PubMed] [Google Scholar]
- [42].Resnick B, Luisi D, Vogel A, Testing the senior exercise self-efficacy project (SESEP) for use with urban dwelling minority older adults, Public Health Nurs. 25 (3) (2008) 221–234, 10.1111/j.1525-1446.2008.00699.x. [DOI] [PubMed] [Google Scholar]
- [43].Thompson CL, Owusu C, Nock NL, Li L, Berger NA, Race, Age, and obesity disparities in adult physical activity levels in breast Cancer patients and controls. Original research. Frontiers, Public Health 2 (150) (2014), 10.3389/fpubh.2014.00150. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [44].Wojcik KM, Wilson OWA, Shiels MS, Sheppard VB, Jayasekera J, Racial, Ethnic, and socioeconomic disparities in meeting physical activity guidelines among female breast Cancer survivors in the United States, Cancer Epidemiol. Biomarkers Prev. 33 (12) (Dec 2 2024) 1610–1622, 10.1158/1055-9965.EPI-24-0650. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [45].Schmitz KH, Brown JC, Irwin ML, et al. , Exercise and nutrition to improve Cancer treatment-related outcomes (ENICTO), JNCI J. Natl. Cancer Inst. (Aug 8 2024), 10.1093/jnci/djae177. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [46].Haizlip KM, Harrison BC, Leinwand LA, Sex-based differences in skeletal muscle kinetics and fiber-type composition, Physiology (Bethesda) 30 (1) (Jan 2015) 30–39, 10.1152/physiol.00024.2014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [47].Magnuson A, Sedrak MS, Gross CP, et al. , Development and validation of a risk tool for predicting severe toxicity in older adults receiving chemotherapy for early-stage breast cancer, J. Clin. Oncol. 39 (6) (Feb 20 2021) 608–618, 10.1200/JCO.20.02063. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [48].Michie S, van Stralen MM, West R, The behaviour change wheel: a new method for characterising and designing behaviour change interventions, Implement. Sci. 6 (1) (2011) 42, 10.1186/1748-5908-6-42. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [49].Williams N, The Borg rating of perceived exertion (RPE) scale, Occup. Med. 67 (5) (2017) 404–405, 10.1093/occmed/kqx063. [DOI] [Google Scholar]
- [50].Morin P, Herrmann F, Ammann P, Uebelhart B, Rizzoli R, A rapid self-administered food frequency questionnaire for the evaluation of dietary protein intake, Clin. Nutr. 24 (5) (Oct 2005) 768–774, 10.1016/j.clnu.2005.03.002. [DOI] [PubMed] [Google Scholar]
- [51].Bok D, Rakovac M, Foster C, An examination and critique of subjective Methods to determine exercise intensity: the talk test, feeling scale, and rating of perceived exertion, Sports Med. 52 (9) (Sep 2022) 2085–2109, 10.1007/s40279-022-01690-3. [DOI] [PubMed] [Google Scholar]
- [52].Fairman CM, Nilsen TS, Newton RU, et al. , Reporting of resistance training dose, adherence, and tolerance in exercise oncology, Med. Sci. Sports Exerc. 52 (2) (Feb 2020) 315–322, 10.1249/MSS.0000000000002127. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [53].Nilsen TS, Scott JM, Michalski M, et al. , Novel Methods for reporting of exercise dose and adherence: an exploratory analysis, Med. Sci. Sports Exerc. 50 (6) (Jun 2018) 1134–1141, 10.1249/MSS.0000000000001545. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [54].Reeve BB, Mitchell SA, Dueck AC, et al. , Recommended patient-reported Core set of symptoms to measure in adult Cancer treatment trials. JNCI, J. Natl. Cancer Inst. 106 (7) (2014), 10.1093/jnci/dju129 dju129–dju129. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [55].Cawthon PM, Orwoll ES, Peters KE, et al. , Strong relation between muscle mass determined by d3-creatine dilution, physical performance, and incidence of falls and mobility limitations in a prospective cohort of older men, J. Gerontol. A Biol. Sci. Med. Sci. 74 (6) (May 16 2019) 844–852, 10.1093/gerona/gly129. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [56].Fillenbaum GG, Smyer MA, The development, validity, and reliability of the OARS multidimensional functional assessment questionnaire. Research support, non-U.S. gov’t research support, U.S. gov’t, non-P.H.S, J. Gerontol. 36 (4) (Jul 1981) 428–434. [DOI] [PubMed] [Google Scholar]
- [57].Fillenbaum GG, Smyer MA, Screening the elderly. A brief instrumental activities of daily living measure, J. Am. Geriatr. Soc. 33 (1985) 698–706. [DOI] [PubMed] [Google Scholar]
- [58].Gandek B, Ware JE, Aaronson NK, et al. , Cross-validation of item selection and scoring for the SF-12 health survey in nine countries: results from the IQOLA project. International quality of life assessment, J. Clin. Epidemiol. 51 (11) (1998) 1171–1178, 10.1016/s0895-4356(98)00109-7. [DOI] [PubMed] [Google Scholar]
- [59].Jenkinson C, Layte R, Jenkinson D, et al. , A shorter form health survey: can the SF-12 replicate results from the SF-36 in longitudinal studies? J. Public Health Med. 19 (2) (Jun 1997) 179–186, 10.1093/oxfordjournals.pubmed.a024606. [DOI] [PubMed] [Google Scholar]
- [60].Ware JE, Kosinski M, Keller SD, A 12-item short-form health survey, Med. Care 34 (3) (1996) 220–233. [DOI] [PubMed] [Google Scholar]
- [61].Care RH. 12-item short form survey (SF-12). Accessed Accessed 29 February 2020, https://www.rand.org/health-care/surveys_tools/mos/12-item-short-form.html.
- [62].Sherbourne CD, Stewart AL, The MOS social support survey, Soc. Sci. Med. 32 (6) (1991) 705–714. [DOI] [PubMed] [Google Scholar]
- [63].Borson S, Scanlan J, Brush M, Vitaliano P, Dokmak A, The mini-cog: a cognitive ‘vital signs’ measure for dementia screening in multi-lingual elderly, Int. J. Geriatr. Psychiatry 15 (11) (Nov 2000) 1021–1027, 10.1002/1099-1166(200011)15:11<1021::aid-gps234>3.0.co;2-6. [DOI] [PubMed] [Google Scholar]
- [64].Folstein MF, Folstein SE, McHugh PR, “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician, J. Psychiatr. Res. 12 (3) (Nov 1975) 189–198, 10.1016/0022-3956(75)90026-6. [DOI] [PubMed] [Google Scholar]
- [65].Sheikh JI, Yesavage JA, Geriatric Depression Scale—Short Form, 1st ed., 1986. [Google Scholar]
- [66].Yates JW, Chalmer B, McKegney FP, Evaluation of patients with advanced cancer using the Karnofsky performance status, Cancer 45 (8) (1980) 2220–2224. [DOI] [PubMed] [Google Scholar]
- [67].Enright PL, The six-minute walk test, Respir. Care 48 (8) (Aug 2003) 783–785. [PubMed] [Google Scholar]
- [68].Nishijima TF, Shimokawa M, Esaki T, Morita M, Toh Y, Muss HB, A 10-item frailty index based on a comprehensive geriatric assessment (FI-CGA-10) in older adults with Cancer: development and construct validation, Oncologist 26 (10) (Oct 2021) e1751–e1760, 10.1002/onco.13894. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [69].Cella D, Riley W, Stone A, et al. , 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. 63 (11) (Nov 2010) 1179–1194, 10.1016/j.jclinepi.2010.04.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [70].Rubenstein JH, Morgenstern H, Kellenberg J, et al. , Validation of a new physical activity questionnaire for a sedentary population, Dig. Dis. Sci. 56 (9) (Sep 2011) 2678–2687, 10.1007/s10620-011-1641-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [71].Postma TJ, Aaronson NK, Heimans JJ, et al. , The development of an EORTC quality of life questionnaire to assess chemotherapy-induced peripheral neuropathy: the QLQ-CIPN20, Eur. J. Cancer 41 (8) (May 2005) 1135–1139, 10.1016/j.ejca.2005.02.012. [DOI] [PubMed] [Google Scholar]
- [72].Gundersen C, Engelhard EE, Crumbaugh AS, Seligman HK, Brief assessment of food insecurity accurately identifies high-risk US adults, Public Health Nutr. 20 (8) (Jun 2017) 1367–1371, 10.1017/s1368980017000180. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [73].Carpenter JS, Andrykowski MA, Psychometric evaluation of the Pittsburgh sleep quality index, J. Psychosom. Res. 45(1 spec no):5–13 (1998). [DOI] [PubMed] [Google Scholar]
- [74].Gentili A, Werner DK, Kuchibhatla M, Edinger JD, Test-retest reliability of the Pittsburgh sleep quality index in nursing home residents, J. Am. Geriatr. Soc. 43 (11) (1995) 1317–1318. [DOI] [PubMed] [Google Scholar]
- [75].Buysse DJ, Reynolds III CF, Monk TH, Berman SR, Kupfer DJ, The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research, Psychiatry Res. 28 (2) (1989) 193–213. [DOI] [PubMed] [Google Scholar]
- [76].van den Brink M, van den Hout WB, Stiggelbout AM, Putter H, van de Velde CJ, Kievit J, Self-reports of health-care utilization: diary or questionnaire? Int. J. Technol. Assess. Health Care Summer 21 (3) (2005) 298–304, 10.1017/s0266462305050397. [DOI] [PubMed] [Google Scholar]
- [77].Perez Jolles M, Lengnick-Hall R, Mittman BS, Core functions and forms of complex health interventions: a patient-centered medical home illustration, J. Gen. Intern. Med. 34 (6) (Jun 2019) 1032–1038, 10.1007/s11606-018-4818-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [78].Kirk MA, Kelley C, Yankey N, Birken SA, Abadie B, Damschroder L, A systematic review of the use of the consolidated framework for implementation research, Implement. Sci. 11 (2015) 1–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [79].Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC, Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science, Implement. Sci. 4 (Aug 07 2009) 50, 10.1186/1748-5908-4-50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [80].Finley EHA, Kowalski C, Midboe A, Nevedal A, Young J, Rapid Qualitative Methods in Implementation Science: Techniquest and Considerations. presented at: 15th Annual Conference on the Science of Dissemination and Implementation in Health, December 13, 2022. Washington, D.C. [Google Scholar]
- [81].McCullagh P, Generalized Linear Models. Routledge, 2019. [Google Scholar]
- [82].VanderWeele TJ, A unification of mediation and interaction: a 4-way decomposition, Epidemiology 25 (5) (2014) 749–761, 10.1097/ede.0000000000000121. [DOI] [PMC free article] [PubMed] [Google Scholar]
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Data Availability Statement
No data was used for the research described in the article.
