GrannyFit is a prospective, national, multicenter, single-arm open-label study. It will include a total of 200 participants over the age of 70 years treated for de novo or recurrent (local or distant) BC. Participants will receive a Withing Steel activity tracker, which they will be asked to wear 24 h per day for 12 months. The principal assessments will be performed at baseline, at 6 months and at 12 months. The investigators will evaluate clinical (e.g. comorbidities), lifestyle, quality of life, fatigue, and physical activity parameters. All questionnaires will be completed on a REDCap form, via a secure internet link.
BACKGROUND: In metropolitan France in 2017, 58,968 new cases of breast cancer (BC) were estimated, of which 25,283 (46.7%) involved women older than 65 years. Older patients with cancer often present complex health needs, in particular because of the burden of comorbidities combined with the effects of aging, the cancer and its treatments. GrannyFit aims to use an activity tracker to identify and describe various digital profiles (physical activity, sleep) in women over 70 years of age treated de novo or recurrent (local or distant) BC. METHODS: GrannyFit is a prospective, national, multicenter, single-arm open-label study. It will include a total of 200 participants over the age of 70 years treated for de novo or recurrent (local or distant) BC. Participants will receive a Withing Steel activity tracker, which they will be asked to wear 24 h per day for 12 months. The principal assessments will be performed at baseline, at 6 months and at 12 months. The investigators will evaluate clinical (e.g. comorbidities), lifestyle, quality of life, fatigue, and physical activity parameters. All questionnaires will be completed on a REDCap form, via a secure internet link. DISCUSSION: GrannyFit will make it possible, through the use of an activity tracker, to visualize changes, over a one-year period, in the lifestyle of older BC patients. This study identify more precisely the unmets needs of this population and optimize their care through specific paths. This trial will also pave the way for interventional studies on physical activity and sleep interventions in this population.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
SUPPORTIVE_CARE
Masking
NONE
Enrollment
200
Participants will receive a Withings Steel activity tracker (Withings, Issy-les-Moulineaux, France), which they will be asked to wear 24 hours per day throughout the whole intervention (12 months). At baseline, the Withings Health Mate mobile phone application will be downloaded onto each participant's smartphone or tablet. The clinical research assistant will instruct the participant in the use of the activity tracker. The participant will then accept and activate the sharing of the data collected with the secure server dedicated to the "GrannyFit" study at the Institut Curie. Participants will be asked to synchronize the activity tracker regularly (ideally daily) via Bluetooth with the Withings Health Mate application, for automatic transfer of the data to the secure "GrannyFit" space.
Centre Léon Bérard
Lyon, France
Institut Curie
Paris, France
Institut GODINOT
Reims, France
Institut Curie
Saint-Cloud, France
Describe physical activity profiles in breast cancer patients over 70 years of age
The activity tracker will register step counts for each day. the investigators will plot the average daily step counts and the 95% confidence interval across the entire study period. Then will will study the change in step count trajectory during the study. Linear mixed model will be used for describing change over time
Time frame: Month 12
Describe sleep profiles in breast cancer patients over 70 years of age
The activity tracker will register sleep duration for each day. The investigators will plot the average sleep duration and the 95% confidence interval across the entire study period. Then will tudy the change in sleep duration trajectory during the study. Linear mixed model will be used for describing change over time
Time frame: Month 12
Identify digital profiles (physical activity, sleep) in breast cancer patients over 70 years of age
To identify digital profiles, the investigators will combine step counts profiles and sleep profiles using mixed models with latent classes. The use of a mixed model will make it possible to analyze repeat data for the population, and to determine an average profile or trajectory for the whole population. The optimal number of classes will be determined a posteriori, based on a set of statistical and clinical criteria. The most widely used statistical criterion is the "Bayesian information criterion" (BIC), which penalizes the model's likelihood according to its complexity. The BIC, which is stricter than many other criteria, has been shown to have a better performance in simulations. The number of trajectories will also be based on clinical interpretation (whether it is worthwhile retaining classes containing very small numbers of subjects, etc.).
Time frame: Month 12
Analyze the effects of digital profiles on quality of life
Quality of life will be assessed with the European Organisation for Research and Treatment of Cancer (EORTC QLQ-C30) Quality of Life Questionnaire (EORTC QLQ-C30) version 3 validated in 2000, a multidimensional questionnaire validated for use with cancer patients. The QLQC30 questionnaire contains 30 items assessing five functional domains (physical, role, emotional, cognitive, and social), one overall quality-of-life domain, three symptom domains (pain, fatigue and nausea), and six individual items (dyspnea, insomnia, anorexia, diarrhea, constipation, and financial impact). Participants will respond on a Likert scale ranging from "not at all" to "very much" and from "very poor" to "excellent" for the overall quality-of-life questions only. Scores will be standardized on a scale of 0 to 100, according to the EORTC scoring manual. Higher scores correspond to better functioning, a better overall quality of life and more symptoms.
Time frame: Month 6, Month 12
Analyze the effects of digital profiles on fatigue
The multidimensional aspects of fatigue will be evaluated with the EORTC QLQ-FA12 version 1 module, which was validated for cancer-related fatigue in 2017. EORTC QLQ-FA12 contains 12 items assessing the physical, cognitive, and emotional domains of cancer-related fatigue. Participants will complete a four-point Likert-scale questionnaire, with responses ranging from "not at all" to "very much". All scores will be transformed to a scale of 0 to 100, with higher scores indicating a greater degree of fatigue. The estimated completion time for this questionnaire is five minutes. Tests will be performed to compare means (Student's t test), or categorical variables (chi2test). The investigators will also perform multinomial logistic regression analyses with univariate and multivariate models, to determine the probability of belonging to a class relative to the corresponding reference class
Time frame: Month 6, Month 12
Analyze the effects of digital profiles on comorbidities
Comorbidities will be assessed at diagnosis using the Charlson Comorbidity Index (CCI). This questionnaire takes into account the presence and severity of multiple medical conditions that may affect cancer treatment. It includes 19 comorbid conditions: myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic lung disease, connective tissue disease, ulcers, mild liver disease, diabetes, hemiplegia, moderate or severe kidney disease, organ-damaging diabetes, tumor of any kind, leukemia, lymphoma, moderate or severe liver disease, metastatic solid tumor, AIDS. Each disease has a different weighting according to the strength of its association with one-year mortality. The total CCI score is calculated by adding the weights associated with each comorbid condition presented by the patient. Higher scores indicate more severe disorders and, therefore, a poorer prognosis.
Time frame: Month 6, Month 12
Analyze the effects of digital profiles on significant life events
Significant life events will concern any event that occurred within a period of 6 months prior to the day of the inclusion visit, follow-up at M6 and M12, related to possible falls (the number will be specified if applicable), unplanned hospitalization for fracture or infection (or other reason), death of a close relative, change of living place or any other event considered significant by the patient. This questionnaire was developed by the project team and has not been validated by scientific publication.
Time frame: Month 6, Month 12
Analyze the effects of digital profiles on physical activity
Physical activity level will be measured by the Godin Leisure-Time Exercise Questionnaire (GSLTPAQ) version 1 validated in women with breast cancer in 2015. The GSLTPAQ is a validated self-administered questionnaire that includes three main questions about the frequency (lasting at least 15 minutes) in a normal week of low-intensity (e.g., easy walking), moderate-intensity (e.g., brisk walking), and high-intensity (e.g., jogging) physical activity. The total score is obtained by multiplying the frequencies of light, moderate, and high intensity physical activities by three, five, and nine metabolic equivalents, respectively, and adding them together. Finally, this score is divided into three categories (≥ 24 units equivalent to light active; between 14 and 23 units equivalent to moderately active; and \<14 units equivalent to insufficiently active). The time to complete the questionnaire is estimated at 3 minutes.
Time frame: Month 6, Month 12
Develop models for predicting fatigue changes during the course of treatment
The prediction of fatigue will be assessed by change from baseline in fatigue scores on FA12 questionnaire and at 6 months and at 12 months..
Time frame: Month 6, Month 12
Develop models for predicting quality of life changes during the course of treatment
The prediction of a deterioration of the quality of life will be assessed by change in the global score in EORTC QLQC30 questionnaire from baseline and at 6 months and at 12 months..
Time frame: Month 6, Month 12
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