<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03234322</url>
  </required_header>
  <id_info>
    <org_study_id>DRT-Study</org_study_id>
    <nct_id>NCT03234322</nct_id>
  </id_info>
  <brief_title>The Impact of a Diabetes Risk Prediction Model in Primary Care.</brief_title>
  <official_title>A Cluster Randomized Trial to Investigate the Impact of a Type 2 Diabetes Risk Prediction Model on Change in Physical Activity Within Routine Health Checks in Primary Care.</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>German Diabetes Center</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Association of Statutory Health Insurance Physicians North Rhine</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>German Institute of Human Nutrition</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>German Diabetes Center</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      Little evidence exists on the impact of diabetes risk scores, e.g. on physicians and&#xD;
      patient's behavior, perceived risk of persons, shared-decision making and particularly on&#xD;
      patient´s health. The aim of this study is to investigate the impact of a non-invasive&#xD;
      diabetes risk prediction model in the primary health care setting as component of routine&#xD;
      health checks on change in physical activity.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Diabetes risk scores are predictive models to estimate the probability for an individual to&#xD;
      develop diabetes within a defined time period. In the last years, many diabetes risk&#xD;
      prediction models were developed worldwide. It has been proposed that using diabetes risk&#xD;
      scores as first step of diabetes screening is more practical than blood glucose tests as the&#xD;
      latter are time consuming and costly. Given the rapid development of diabetes risk scores and&#xD;
      a simultaneous reluctance of primary care physicians (PCPs) to implement diabetes risk scores&#xD;
      in everyday practice, there is an urgent need to expand our knowledge of the impact of&#xD;
      diabetes risk scores in the primary health care setting. Thus, the aim of the study is to&#xD;
      investigate the impact of a non-invasive risk prediction model in the primary health care&#xD;
      setting as component of routine health checks on change in physical activity.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">September 13, 2017</start_date>
  <completion_date type="Actual">February 10, 2021</completion_date>
  <primary_completion_date type="Actual">February 10, 2021</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Parallel Assignment</intervention_model>
    <intervention_model_description>A pragmatic blinded parallel group superiority cluster randomized controlled trial. Clusters are PCPs (general practitioners, medical practitioners and internists working as general practitioners).</intervention_model_description>
    <primary_purpose>Prevention</primary_purpose>
    <masking>Double (Participant, Outcomes Assessor)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Difference of participant's physical activity at twelve months after the routine health check between the groups.</measure>
    <time_frame>at baseline, 6 and 12 months follow-up</time_frame>
    <description>Self-reported outcome, international validated questionnaire Physical Activity Questionnaire Short Last 7 Days Format (IPAQ-SF), which has been shown to be a reliable and valid tool to obtain comparable estimates of physical activity.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Improvement in the counseling process assessed by PCPs.</measure>
    <time_frame>at baseline and up to one year after the PCP entered the study</time_frame>
    <description>Self-reported outcome, analyzed as difference in proportion of counseling regarding preventive strategies on balanced nutrition, body weight reduction, physical activity, and smoking secession between the groups. Questions are derived from a previous study.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Improvement in the counseling process assessed by participants.</measure>
    <time_frame>at 6 months follow-up</time_frame>
    <description>Self-reported outcome, analyzed as difference in proportion of counseling regarding preventive strategies on balanced nutrition, body weight reduction, physical activity, and smoking secession between the groups. Questions are derived from a previous study.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Improvement of shared decision making, assessed by participants.</measure>
    <time_frame>at baseline</time_frame>
    <description>Self-reported outcome, modified questionnaire to assess the difference in proportion of shared decision making for diabetes prevention opportunities between the groups.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Improvement of shared decision making, assessed by PCPs.</measure>
    <time_frame>at baseline</time_frame>
    <description>Self-reported outcome, modified questionnaire to assess the difference in proportion of shared decision making for diabetes prevention opportunities between the groups.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Improved motivation to change lifestyle, assessed by participants.</measure>
    <time_frame>at baseline, 6 and 12 months follow-up</time_frame>
    <description>Self-reported outcome, questions are based on the stage of change model to assess the stage of motivation according to weight reduction, physical activity, healthy diet, smoking cessation and were derived from previous studies. We will assess the difference of motivation change between the groups.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Change in Body-Mass-Index (BMI)</measure>
    <time_frame>at baseline, 6 and 12 months follow-up</time_frame>
    <description>At baseline, weight and height is objectively measured by the PCP, in the follow-up weight will be self-reported. We will analyse group differences in change of BMI at 6 and 12 months follow-up.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Change in participant's quality of life.</measure>
    <time_frame>at baseline, 6 and 12 months follow-up</time_frame>
    <description>Self-reported outcome, question has been derived from previous studies. We will assess the change of quality of life between the groups.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Change in participant's level of depression and anxiety.</measure>
    <time_frame>at baseline, 6 and 12 months follow-up</time_frame>
    <description>Self-reported outcomes, depression and anxiety will be assessed with a validated questionnaire, the Hospital Anxiety and Depression Scale (HADS-D). We will assess the change of depression and anxiety between the groups.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Change of participant's perceived risk of developing diabetes.</measure>
    <time_frame>at baseline, 6 and 12 months follow-up</time_frame>
    <description>Self-reported outcome by participants, questions derived from previous studies. We will assess the change in perceived risk between the groups.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Acceptance of PCPs according to the application of a diabetes risk score for routine use in clinical practice.</measure>
    <time_frame>at baseline, and up to one year after the PCP entered the study</time_frame>
    <description>Self-reported outcome, differences between the groups will be analyzed. Questions are derived from previous studies.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Acceptance of participants according to the application of a diabetes risk score for routine use in clinical practice.</measure>
    <time_frame>at 6 months follow-up</time_frame>
    <description>Self-reported outcome, questions derived from previous studies.</description>
  </secondary_outcome>
  <other_outcome>
    <measure>Change on participant's individual diabetes risk.</measure>
    <time_frame>at baseline, 6 and 12 months follow-up</time_frame>
    <description>Self-reported outcome. Individual diabetes risk will be derived from the diabetes risk score in the intervention group at baseline, which is a validated questionnaire. In the follow-up questionnaires at 6 and 12 months, the questions of the diabetes risk score are included in the questionnaire of both groups.</description>
  </other_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Actual">315</enrollment>
  <condition>Type 2 Diabetes Mellitus</condition>
  <condition>Primary Prevention</condition>
  <arm_group>
    <arm_group_label>Intervention group</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>In the intervention group the routine health check is expanded by usage of a non-invasive diabetes risk score.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Control group</arm_group_label>
    <arm_group_type>No Intervention</arm_group_type>
    <description>In the control group the routine health check is conducted.</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>external validated risk prediction model</intervention_name>
    <description>The risk prediction model will be integrated into a routine health check. The diabetes risk prediction model contains modifiable non-invasive risk factors and consists of eleven questions on age, height, waist circumference, hypertension, physical activity, smoking status, intake of whole-grain bread, intake of red meat, coffee consumption, and family history of diabetes (parents and siblings) to predict the five-year diabetes risk. The filled diabetes risk score will be used in the counseling interview with the PCP at the end of the health check as a practical guide to discuss individual tailored preventive strategies.</description>
    <arm_group_label>Intervention group</arm_group_label>
    <other_name>The German Diabetes Risk Score</other_name>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion criteria for participation of medical practitioners:&#xD;
&#xD;
          -  general practitioners, medical practitioners and internists working as general&#xD;
             practitioners with and without further training in diabetology according to German&#xD;
             Diabetes Association standards&#xD;
&#xD;
          -  provide the routine health check&#xD;
&#xD;
        Exclusion criteria for participation of medical practitioners:&#xD;
&#xD;
          -  treat exclusively patients with private insurance&#xD;
&#xD;
          -  treat exclusively diabetes patients in a specialized medical practice&#xD;
&#xD;
        Inclusion criteria for participation of participants&#xD;
&#xD;
          -  appointment for the routine health check&#xD;
&#xD;
          -  insured in statutory health insurance&#xD;
&#xD;
          -  age &gt; 35 years&#xD;
&#xD;
          -  Body Mass Index (BMI) of ≥ 27 kg/m2&#xD;
&#xD;
        Exclusion criteria for participation of participants&#xD;
&#xD;
          -  type 1 or type 2 diabetes diagnosis or already abnormal blood glucose level (fasting&#xD;
             glucose ≥ 126 mg/dl or 2 hours oral glucose tolerance test (oGTT) ≥ 200mg/dl or&#xD;
             glycated hemoglobin (HbA1c) ≥6,5%) before the routine health check&#xD;
&#xD;
          -  no sufficient German language skills to fill in the questionnaires&#xD;
&#xD;
          -  presence of an incurable disease with a prognosis of less than one year&#xD;
&#xD;
          -  severe mental illness or dementia&#xD;
&#xD;
          -  severe underlying disease, which largely impairs physical activity&#xD;
&#xD;
          -  pregnancy&#xD;
&#xD;
          -  participation in another clinical study 30 days before study inclusion&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>35 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Wolfgang Rathmann, Prof.</last_name>
    <role>Principal Investigator</role>
    <affiliation>German Diabetes Center</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>German Diabetes Center, Institute for Biometrics and Epidemiology</name>
      <address>
        <city>Düsseldorf</city>
        <state>North Rhine-Westphalia</state>
        <zip>40225</zip>
        <country>Germany</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>Germany</country>
  </location_countries>
  <reference>
    <citation>Dhippayom T, Chaiyakunapruk N, Krass I. How diabetes risk assessment tools are implemented in practice: a systematic review. Diabetes Res Clin Pract. 2014 Jun;104(3):329-42. doi: 10.1016/j.diabres.2014.01.008. Epub 2014 Jan 15.</citation>
    <PMID>24485859</PMID>
  </reference>
  <reference>
    <citation>Noble D, Mathur R, Dent T, Meads C, Greenhalgh T. Risk models and scores for type 2 diabetes: systematic review. BMJ. 2011 Nov 28;343:d7163. doi: 10.1136/bmj.d7163.</citation>
    <PMID>22123912</PMID>
  </reference>
  <reference>
    <citation>Godino JG, van Sluijs EM, Marteau TM, Sutton S, Sharp SJ, Griffin SJ. Lifestyle Advice Combined with Personalized Estimates of Genetic or Phenotypic Risk of Type 2 Diabetes, and Objectively Measured Physical Activity: A Randomized Controlled Trial. PLoS Med. 2016 Nov 29;13(11):e1002185. doi: 10.1371/journal.pmed.1002185. eCollection 2016 Nov.</citation>
    <PMID>27898672</PMID>
  </reference>
  <reference>
    <citation>Muller-Riemenschneider F, Holmberg C, Rieckmann N, Kliems H, Rufer V, Muller-Nordhorn J, Willich SN. Barriers to routine risk-score use for healthy primary care patients: survey and qualitative study. Arch Intern Med. 2010 Apr 26;170(8):719-24. doi: 10.1001/archinternmed.2010.66.</citation>
    <PMID>20421559</PMID>
  </reference>
  <verification_date>August 2021</verification_date>
  <study_first_submitted>July 13, 2017</study_first_submitted>
  <study_first_submitted_qc>July 28, 2017</study_first_submitted_qc>
  <study_first_posted type="Actual">July 31, 2017</study_first_posted>
  <last_update_submitted>August 9, 2021</last_update_submitted>
  <last_update_submitted_qc>August 9, 2021</last_update_submitted_qc>
  <last_update_posted type="Actual">August 10, 2021</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>German Diabetes Center</investigator_affiliation>
    <investigator_full_name>Wolfgang Rathmann</investigator_full_name>
    <investigator_title>PD Dr. Wolfgang Rathmann MSPH (USA)</investigator_title>
  </responsible_party>
  <keyword>prevention</keyword>
  <keyword>risk score</keyword>
  <keyword>behaviour</keyword>
  <keyword>physical activity</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Diabetes Mellitus</mesh_term>
    <mesh_term>Diabetes Mellitus, Type 2</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Yes</sharing_ipd>
    <ipd_description>Twelve months after data publication, de-identified data can be provided to other researchers upon request.</ipd_description>
    <ipd_info_type>Study Protocol</ipd_info_type>
    <ipd_time_frame>12 months</ipd_time_frame>
    <ipd_access_criteria>Universities and other non-profit organizations</ipd_access_criteria>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03234322
org study id: DRT-Study
nct id: NCT03234322
lead sponsor: 
collaborator: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
Little evidence exists on the impact of diabetes risk scores, e.g. on physicians and
      patient's behavior, perceived risk of persons, shared-decision making and particularly on
      patient´s health. The aim of this study is to investigate the impact of a non-invasive
      diabetes risk prediction model in the primary health care setting as component of routine
      health checks on change in physical activity.
Diabetes risk scores are predictive models to estimate the probability for an individual to
      develop diabetes within a defined time period. In the last years, many diabetes risk
      prediction models were developed worldwide. It has been proposed that using diabetes risk
      scores as first step of diabetes screening is more practical than blood glucose tests as the
      latter are time consuming and costly. Given the rapid development of diabetes risk scores and
      a simultaneous reluctance of primary care physicians (PCPs) to implement diabetes risk scores
      in everyday practice, there is an urgent need to expand our knowledge of the impact of
      diabetes risk scores in the primary health care setting. Thus, the aim of the study is to
      investigate the impact of a non-invasive risk prediction model in the primary health care
      setting as component of routine health checks on change in physical activity.
allocation: Randomized
intervention model: Parallel Assignment
intervention model description: A pragmatic blinded parallel group superiority cluster randomized controlled trial. Clusters are PCPs (general practitioners, medical practitioners and internists working as general practitioners).
primary purpose: Prevention
masking: Double (Participant, Outcomes Assessor)
measure: Difference of participant's physical activity at twelve months after the routine health check between the groups.
time frame: at baseline, 6 and 12 months follow-up
description: Self-reported outcome, international validated questionnaire Physical Activity Questionnaire Short Last 7 Days Format (IPAQ-SF), which has been shown to be a reliable and valid tool to obtain comparable estimates of physical activity.
measure: Improvement in the counseling process assessed by PCPs.
time frame: at baseline and up to one year after the PCP entered the study
description: Self-reported outcome, analyzed as difference in proportion of counseling regarding preventive strategies on balanced nutrition, body weight reduction, physical activity, and smoking secession between the groups. Questions are derived from a previous study.
measure: Improvement in the counseling process assessed by participants.
time frame: at 6 months follow-up
description: Self-reported outcome, analyzed as difference in proportion of counseling regarding preventive strategies on balanced nutrition, body weight reduction, physical activity, and smoking secession between the groups. Questions are derived from a previous study.
measure: Improvement of shared decision making, assessed by participants.
time frame: at baseline
description: Self-reported outcome, modified questionnaire to assess the difference in proportion of shared decision making for diabetes prevention opportunities between the groups.
measure: Improvement of shared decision making, assessed by PCPs.
time frame: at baseline
description: Self-reported outcome, modified questionnaire to assess the difference in proportion of shared decision making for diabetes prevention opportunities between the groups.
measure: Improved motivation to change lifestyle, assessed by participants.
time frame: at baseline, 6 and 12 months follow-up
description: Self-reported outcome, questions are based on the stage of change model to assess the stage of motivation according to weight reduction, physical activity, healthy diet, smoking cessation and were derived from previous studies. We will assess the difference of motivation change between the groups.
measure: Change in Body-Mass-Index (BMI)
time frame: at baseline, 6 and 12 months follow-up
description: At baseline, weight and height is objectively measured by the PCP, in the follow-up weight will be self-reported. We will analyse group differences in change of BMI at 6 and 12 months follow-up.
measure: Change in participant's quality of life.
time frame: at baseline, 6 and 12 months follow-up
description: Self-reported outcome, question has been derived from previous studies. We will assess the change of quality of life between the groups.
measure: Change in participant's level of depression and anxiety.
time frame: at baseline, 6 and 12 months follow-up
description: Self-reported outcomes, depression and anxiety will be assessed with a validated questionnaire, the Hospital Anxiety and Depression Scale (HADS-D). We will assess the change of depression and anxiety between the groups.
measure: Change of participant's perceived risk of developing diabetes.
time frame: at baseline, 6 and 12 months follow-up
description: Self-reported outcome by participants, questions derived from previous studies. We will assess the change in perceived risk between the groups.
measure: Acceptance of PCPs according to the application of a diabetes risk score for routine use in clinical practice.
time frame: at baseline, and up to one year after the PCP entered the study
description: Self-reported outcome, differences between the groups will be analyzed. Questions are derived from previous studies.
measure: Acceptance of participants according to the application of a diabetes risk score for routine use in clinical practice.
time frame: at 6 months follow-up
description: Self-reported outcome, questions derived from previous studies.
measure: Change on participant's individual diabetes risk.
time frame: at baseline, 6 and 12 months follow-up
description: Self-reported outcome. Individual diabetes risk will be derived from the diabetes risk score in the intervention group at baseline, which is a validated questionnaire. In the follow-up questionnaires at 6 and 12 months, the questions of the diabetes risk score are included in the questionnaire of both groups.
arm group label: Intervention group
arm group type: Experimental
description: In the intervention group the routine health check is expanded by usage of a non-invasive diabetes risk score.
arm group label: Control group
arm group type: No Intervention
description: In the control group the routine health check is conducted.
intervention type: Other
intervention name: external validated risk prediction model
description: The risk prediction model will be integrated into a routine health check. The diabetes risk prediction model contains modifiable non-invasive risk factors and consists of eleven questions on age, height, waist circumference, hypertension, physical activity, smoking status, intake of whole-grain bread, intake of red meat, coffee consumption, and family history of diabetes (parents and siblings) to predict the five-year diabetes risk. The filled diabetes risk score will be used in the counseling interview with the PCP at the end of the health check as a practical guide to discuss individual tailored preventive strategies.
arm group label: Intervention group
other name: The German Diabetes Risk Score
criteria: 
gender: All
minimum age: 35 Years
maximum age: N/A
healthy volunteers: Accepts Healthy Volunteers
last name: Wolfgang Rathmann, Prof.
role: Principal Investigator
affiliation: German Diabetes Center
facility: 
country: Germany
citation: Dhippayom T, Chaiyakunapruk N, Krass I. How diabetes risk assessment tools are implemented in practice: a systematic review. Diabetes Res Clin Pract. 2014 Jun;104(3):329-42. doi: 10.1016/j.diabres.2014.01.008. Epub 2014 Jan 15.
PMID: 24485859
citation: Noble D, Mathur R, Dent T, Meads C, Greenhalgh T. Risk models and scores for type 2 diabetes: systematic review. BMJ. 2011 Nov 28;343:d7163. doi: 10.1136/bmj.d7163.
PMID: 22123912
citation: Godino JG, van Sluijs EM, Marteau TM, Sutton S, Sharp SJ, Griffin SJ. Lifestyle Advice Combined with Personalized Estimates of Genetic or Phenotypic Risk of Type 2 Diabetes, and Objectively Measured Physical Activity: A Randomized Controlled Trial. PLoS Med. 2016 Nov 29;13(11):e1002185. doi: 10.1371/journal.pmed.1002185. eCollection 2016 Nov.
PMID: 27898672
citation: Muller-Riemenschneider F, Holmberg C, Rieckmann N, Kliems H, Rufer V, Muller-Nordhorn J, Willich SN. Barriers to routine risk-score use for healthy primary care patients: survey and qualitative study. Arch Intern Med. 2010 Apr 26;170(8):719-24. doi: 10.1001/archinternmed.2010.66.
PMID: 20421559
responsible party type: Principal Investigator
investigator affiliation: German Diabetes Center
investigator full name: Wolfgang Rathmann
investigator title: PD Dr. Wolfgang Rathmann MSPH (USA)
mesh term: Diabetes Mellitus
mesh term: Diabetes Mellitus, Type 2
sharing ipd: Yes
ipd description: Twelve months after data publication, de-identified data can be provided to other researchers upon request.
ipd info type: Study Protocol
ipd time frame: 12 months
ipd access criteria: Universities and other non-profit organizations