跳至主要内容
临床试验/NCT04007939
NCT04007939已完成不适用

Personal Lifestyle Engine (PLX) is an Employee Wellness Platform and App Used at the Personal Lifestyle Medicine Center (PLMC). This Study Examines Correlations Between Lifestyle Factors, Genomic Data, Physical Exam Finding and Biomarkers

Metagenics, Inc.1 个研究点 分布在 1 个国家目标入组 400 人开始时间: 2018年1月1日最近更新:
适应症

试验速览

阶段
不适用
状态
已完成
入组人数
400
试验地点
1
主要终点
Homocysteine

研究概览

简要总结

It has been suggested that the best medicine should include four principles (4P) - Medicine should be personalized, predictive, preventative and participatory. Technology has provided the tools to collect data in ways not previously possible. Individuals can now collect information on their genome (including their genetic predisposition to tolerate medications and to respond to healthy lifestyle programs) that will modify their lifestyle and therapeutic choices. Beyond spot checks of vital signs and weight, individuals can now collect information on body composition, continuous monitoring of heart rate, blood pressure, and even blood sugar. Data on food consumption at a caloric, macronutrient and even micronutrient level can be collected. Standard medical histories and detailed physical examination findings and laboratory biomarkers can be correlated with this data.

Collections of individual patient data will need to be managed through computer programs and smart phone applications that provide direct feedback about the influence of lifestyle on health, wellness and biomarkers. To this end, Metagenics is designing and is launching a smart phone application, Personal Lifestyle Engine (PLX), for individual use by patients and their healthcare providers. The statistical analysis of these data is the primary objective of this study.

详细描述

Technology has led to a significant revisioning and modification of the models of medicine in practice today. It has been suggested that the best medicine should include four principles - Medicine should be personalized, predictive, preventative and participatory. This 4P medicine will thus be patient centered with a focus on the person who has the disease and not the disease the person has. It will be predictive as it identifies the preclinical trend/decline towards illness sooner than onset of symptoms that herald the loss of function and health. It will be preventative as the information gathered should offer opportunities to modify these trajectories towards illness and finally it will be participatory as individuals will be intimately involved in the gathering of data to identify trends and in the application of lifestyle measures to improve the quality of their life.

Technology has provided the tools to collect data in ways not previously possible. Individuals can now collect information on their genome (including their genetic predisposition to tolerate medications and to respond to healthy lifestyle programs) that will modify their lifestyle and therapeutic choices. Beyond spot checks of vital signs and weight, individuals can now collect information on body composition, continuous monitoring of heart rate, blood pressure, and even blood sugar. Data on food consumption at a caloric, macronutrient and even micronutrient level can be collected. Standard medical histories and detailed physical examination findings and laboratory biomarkers can be correlated with this data.

As has been noted in the Nathan Price et al. article, "A wellness study of 108 individuals using personal, dense, dynamic data clouds" (PMID: 28714965), a significant challenge to the effective use of these complex sets of individual patient data is how to define the boundaries between disease, average health and optimal wellbeing. To meet this challenge, compiling and analyzing collections of de-identified, detailed patient histories, questionnaires regarding symptoms and general condition, and associated objective findings (genomic data, vital signs, and physical exam and laboratory biomarkers) will theoretically identify these boundaries and will facilitate the deliverance of 4P Medicine. Comprehensive data collections on each subject evaluated in aggregate provides a diversity of uniqueness markers that can be statistically probed to identify patterns that predict wellbeing and perhaps individual response to lifestyle interventions.

An additional challenge for both the patient and their health care provider in 2018 and beyond is how to manage this data in an effective manner. Collections of individual patient data will need to be managed through computer programs and smart phone applications that provide direct feedback about the influence of lifestyle on health, wellness and biomarkers. To this end, Metagenics is designing and is launching a smart phone application, PLX, for individual use by patients and their healthcare providers. After and while a statistical analysis of this data set has been/is being completed, the data set will also be used in an initial beta test of the PLX operating system. The PLX application will not be used to conduct the statistical analysis which is the primary objective of this study."

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Cross Sectional

入排标准

年龄范围
18 Years 至 80 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • Male or Female
  • Ages 18-80, inclusive
  • Willing to give written informed consent to participate in the study

排除标准

  • A serious, unstable illness including cardiac, hepatic, renal, gastrointestinal, respiratory, endocrinologic, neurologic, immunologic, or hematologic disease.
  • Known infection with human immunodeficiency virus (HIV), tuberculosis (TB), or hepatitis B or C.
  • Inability to comply with study and/or follow-up visits.
  • Any concurrent condition (including clinically significant abnormalities in medical history, physical examination or laboratory evaluations) which, in the opinion of the Principle Investigator (PI), would preclude safe participation in this study or interfere with compliance.
  • Any sound medical, psychiatric and/or social reason which, in the opinion of the PI, would preclude safe participation in this study or interfere with compliance.

结局指标

主要结局

Homocysteine

时间窗: Baseline

Homocysteine is measured in serum in micromol/Liter (µmol/L)

Hip Circumference (HC)

时间窗: Baseline

measured in cm

Omega-3 Fatty Acids

时间窗: Baseline

Omega-3 fatty acids: Eicosapentaenoic (EPA), Docosahexaenoic (DHA), and Docosapentaenoic (DPA) levels are measured in % weight.

Beck Depression Inventory (BDI)

时间窗: Baseline

BDI is a 21-question multiple-choice self-report inventory, one of the most widely used psychometric tests for measuring the severity of depression. Rating system: 1-10: These ups and downs are considered normal; 11-16: Mild mood disturbance; 17-20: Borderline clinical depression; 21-30: Severe depression; over 40: Extreme depression

Genomics

时间窗: Baseline

DNA polymorphism measured using 23\&Me

Height

时间窗: Baseline

measured in meter (m)

Weight

时间窗: Baseline

measured in kilogram (kg)

Body Mass index (BMI)

时间窗: Baseline

BMI is measured in (weight in kilogram (kg)/ height in meter (m)\^2) outcome in double digits.

Total Cholesterol

时间窗: Baseline

Fasting total cholesterol level is measured in serum in mg/dL

Waist-to-Hip Ratio (WHR)

时间窗: Baseline

WHR is numerical (0.00) and is and indicator for major health risk.

Glucose

时间窗: Baseline

Fasting glucose levels measured in blood in milligram/deciLiter (mg/dL)

Anti-Nuclear Antibodies (ANA)

时间窗: Baseline

ANA is measured as a titer by serum dilution detects autoimmune disease.

25-hydroxy (OH) Vitamin D3

时间窗: Baseline

25-OH vitamin D3 is measured in blood in nanogram/milliLiter (ng/mL) and detects deficiencies.

Patient-Reported Outcomes Measurement Information System (PROMIS) Sleep Disturbance Test

时间窗: Baseline

PROMIS Sleep Disturbance Test is a self-scored test to identify sleep disturbance. Each item on the measure is rated on a 5-point scale (1=never; 2=rarely; 3=sometimes; 4=often; and 5=always) with a range in score from 8 to 40 with higher scores indicating greater severity of sleep disturbance. The T-scores are interpreted as follows: Less than 55 = None to slight 55.0-59.9 = Mild 60.0-69.9 = Moderate 70 and over = Severe

Patient-Reported Outcomes Measurement Information System (PROMIS) Anxiety Test

时间窗: Baseline

PROMIS Anxiety test is a 7-item questionnaire that assesses the pure domain of anxiety in individuals age 18 and older. Each item on the measure is rated on a 5-point scale (1=never; 2=rarely; 3=sometimes; 4=often; and 5=always) with a range in score from 7 to 35 with higher scores indicating greater severity of anxiety. The T-scores are interpreted as follows: Less than 55 = None to slight 55.0-59.9 = Mild 60.0-69.9 = Moderate 70 and over = Severe

Patient-Reported Outcomes Measurement Information System (PROMIS) Depression Short Form (SF)

时间窗: Baseline

PROMIS Depression SF is an 8-item questionnaire that assesses the pure domain of depression in individuals age 18 and older. Each item on the measure is rated on a 5-point scale (1=never; 2=rarely; 3=sometimes; 4=often; and 5=always) with a range in score from 8 to 40 with higher scores indicating greater severity of depression.The T-scores are interpreted as follows: Less than 55 = None to slight 55.0-59.9 = Mild 60.0-69.9 = Moderate 70 and over = Severe

Waist Circumference (WC)

时间窗: Baseline

measured in centimeters (cm)

High sensitivity C-Reactive Protein (Hs-CRP)

时间窗: Baseline

Hs-CRP is measured in blood in mg/L detects inflammation.

Stool

时间窗: Baseline

Stool analysis measured by a stool analysis kit from American Gut

Beck Anxiety Inventory (BAI)

时间窗: Baseline

BAI is a multiple-choice self-report inventory that is used for measuring the severity of anxiety in children and adults.The BAI contains 21 questions, each answer being scored on a scale value of 0 (not at all) to 3 (severely). Higher total scores indicate more severe anxiety symptoms. The standardized cutoffs\[4\] are: 0-7: minimal anxiety 8-15: mild anxiety 16-25: moderate anxiety 26-63: severe anxiety

次要结局

未报告次要终点

研究者

申办方类型
Industry
责任方
Sponsor

研究点 (1)

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