Digital Phenotyping (Physical Activity, Sleep) in Women Over 70 Years of Age Treated for Breast Cancer With Any Type of Treatment
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 200
- 试验地点
- 7
- 主要终点
- Identify digital profiles (physical activity, sleep) in breast cancer patients over 70 years of age
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Supportive Care
- 盲法
- None
入排标准
- 年龄范围
- 70 Years 至 —（Older Adult）
- 性别
- Female
- 接受健康志愿者
- 否
入选标准
- •Women over 70 years of age,
- •With histologically confirmed invasive breast cancer,
- •Regardless of histological subtype (hormone receptor positive (HR+), negative (HR-), with or without HER2 overexpression, or triple negative)
- •Treated with local (surgery, radiotherapy) or systemic (hormone therapy, monotherapy, anti HER2, chemotherapy: patient is eligible for inclusion up to one month after initial diagnosis or recurrence (local or distant) of breast cancer,
- •Willing and available to invest in the project for the duration of the study,
- •Using a personal smartphone or personal tablet compatible with the "Withings Health Mate" app (iOS 10/android 5.0 and later) and with an internet connection,
- •Affiliated with a social security plan,
- •Having dated and signed an informed consent,
- •Able to read, write and understand French.
排除标准
- •Presence of disabling metastases,
- •Moderate to severe cognitive impairment,
- •Persons deprived of liberty or under guardianship,
- •Inability to undergo the medical follow-up of the trial for geographical, social or psychological reasons,
研究组 & 干预措施
Intervention with activity tracker
Women allocated to the intervention arm will used an activity tracker
干预措施: Activity tracker (Device)
结局指标
主要结局
Identify digital profiles (physical activity, sleep) in breast cancer patients over 70 years of age
时间窗: Month 12
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.).
Describe sleep profiles in breast cancer patients over 70 years of age
时间窗: Month 12
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
Describe physical activity profiles in breast cancer patients over 70 years of age
时间窗: Month 12
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
次要结局
- Analyze the effects of digital profiles on quality of life(Month 6, Month 12)
- Analyze the effects of digital profiles on fatigue(Month 6, Month 12)
- Analyze the effects of digital profiles on physical activity(Month 6, Month 12)
- Develop models for predicting fatigue changes during the course of treatment(Month 6, Month 12)
- Develop models for predicting quality of life changes during the course of treatment(Month 6, Month 12)
- Analyze the effects of digital profiles on comorbidities(Month 6, Month 12)
- Analyze the effects of digital profiles on significant life events(Month 6, Month 12)