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Trial registered on ANZCTR


Registration number
ACTRN12616000630415
Ethics application status
Approved
Date submitted
14/04/2016
Date registered
16/05/2016
Date last updated
30/06/2021
Date data sharing statement initially provided
22/01/2020
Type of registration
Prospectively registered

Titles & IDs
Public title
Can a new model of care introduced in General Practice improve detection and management of Familial Hypercholesterolaemia?
Scientific title
Use of a new model of care to improve detection and management of Familial Hypercholesterolaemia in a primary care setting: An intervention study
Secondary ID [1] 289003 0
None
Universal Trial Number (UTN)
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Familial Hypercholesterolaemia 298405 0
Condition category
Condition code
Human Genetics and Inherited Disorders 298507 298507 0 0
Other human genetics and inherited disorders
Cardiovascular 298508 298508 0 0
Diseases of the vasculature and circulation including the lymphatic system

Intervention/exposure
Study type
Interventional
Description of intervention(s) / exposure
Using an electronic data extraction method (TARB-Ex) all active General Practice (GP) patients who have ever had a record of either total cholesterol greater than 7.0mmol/l or Low-Density Lipoprotein (LDL) cholesterol greater than 4.0mmol/l will be selected including those patients on medications to reduce cholesterol (statins). The extraction tool also has the ability to adjust the cholesterol levels of patients on cholesterol lowering medication (statins) using a standardising algorithm. Therefore if the patient has been prescribed medication a pre-medicated LDL or total cholesterol can be estimated. Patients are considered to be on statins if prescription dates are within 1 week to 6 months of the date of cholesterol measurement. Information is also extracted on possible secondary causes of hypercholesterolaemia such as liver or renal disease, diabetes mellitus, steroid use or hypothyroidism. The screening tool detects potential for FH risk by calculating a modified Dutch Lipid Clinic Network Criteria score equal to 5. The GP/PN will then review the records flagged by TARB-Ex as possible FH cases and based on this review they will recall patients, via a telephone call and letter for further consultation. It will be up to the GPs discretion and professional opinion to ascertain what the specific needs are for each patient once the screening process is complete and potential FH patients are identified and recalled. In this process the GP can update family and personal history, exclude possible secondary causes, assess adherence to cholesterol lowering medications (if necessary) and undertake clinical examination. The GP will decide management of patients on a case by case basis. Family cascade screening will also be undertaken during this time. Initially the index case person will be asked if they consent to risk notification of first degree relatives. If this isn't agreed to the refusal will be accepted.
If the patient agrees to the notification a letter and information sheet will be given to the family member/s and/or given to the index case to distribute to relatives.
If no response is received within 2 weeks either another letter will be sent out or the GP or practice nurse will try to contact the family member/s via telephone. If after another 2 weeks (4 weeks total) there has been no response by family members it is assumed consent has not been given for cascade testing.
If within the first 2 weeks contact is made by a family member the practice staff will confirm consent for testing and an initial consultation will be made. The family member will then receive counselling on FH and be treated as per their individual requirements at the discretion of the GP. All patients that present to the GP will be assessed for FH and if appropriate receive definitive diagnosis and specific cholesterol management. The study includes monitoring medical records of these patients for a period of 12 months post-diagnosis.
Intervention code [1] 294486 0
Early detection / Screening
Comparator / control treatment
Pre-intervention data will be used as a comparator over a 12 month period. The time period will depend on when the TARB-Ex tool is used to first screen a general practice's files. The time period will start for that particular practice 12 months from then. We will begin screening approximately in June 2016, and depending on each practice this may take up to 3 months so estimated finish time would be September 2017.
Control group
Historical

Outcomes
Primary outcome [1] 298000 0
Number of clinically diagnosed index cases of FH identified through use of screening tool (TARB-Ex), subsequent GP review of medical records, and recall of patients for confirmed diagnosis using the Dutch Lipid Clinic Network Criteria.
Timepoint [1] 298000 0
12 months post screening of patient records with TARB-Ex screening tool in general practice.
Primary outcome [2] 298001 0
Number of patients with FH that have reduced LDL-c. This data will be extracted from medical records of patients who are initially diagnosed with FH from the screening protocol and agree to be part of the study. Six and 12 month reviews will be requested to monitor blood cholesterol levels.
Timepoint [2] 298001 0
Six and 12 months after clinical diagnosis of FH
Secondary outcome [1] 322874 0
Number of family cases detected and diagnosed with FH (including children). This will be assessed using records from the general practice.
Timepoint [1] 322874 0
12 months after the initial index person's confirmed diagnosis of FH.
Secondary outcome [2] 322876 0
Review of Method of Care Approach: Patient, GP, PN, practice staff and Specialist staff perceptions of the success and/or barriers and suggested improvements to using the approach in addressing FH will be examined. This will be achieved using a qualitative methodology which includes a triangulation of data collection methods including both semi structured interviews (face to face and telephone) and focus groups (post study community feedback sessions). The exact method will be guided by availability and preferences of the participants. For example, the preference potentially from a time perspective may be for GPs to complete a telephone interview. Conversely, in order to achieve a balance of individual perspectives, focus groups will be conducted amongst patient groups across practices.
Timepoint [2] 322876 0
12-18 months after the initial index patients diagnosis of FH (to allow for the patients to have had their 6 and 12 month reviews)

Eligibility
Key inclusion criteria
All patients from five participating GP clinics in Perth Western Australia, four in New South Wales, three in Queensland, two in Tasmania and one in Victoria, currently seeing registered GP in the last two years on at least one occasion will have records screened. All active patients who have ever had a record of either total cholesterol >7.0mmol/l or LDL-c >4.0mmol/l, including those patients on medications to reduce cholesterol (statins) will then be contacted by the GP for further examination and potential treatment.
Minimum age
18 Years
Maximum age
No limit
Sex
Both males and females
Can healthy volunteers participate?
No
Key exclusion criteria
No diagnosis of Familial Hypercholesterolaemia.

Study design
Purpose of the study
Treatment
Allocation to intervention
Non-randomised trial
Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
Methods used to generate the sequence in which subjects will be randomised (sequence generation)
Masking / blinding
Open (masking not used)
Who is / are masked / blinded?



Intervention assignment
Single group
Other design features
Phase
Not Applicable
Type of endpoint/s
Statistical methods / analysis
Based on clinical audit data from 3 WA practices, the expected reduction in LDL-c for FH patients receiving intensive statin treatment over 12 months is 2.83 mmol/L (personal communication Co-Investigator Vickery) vs. 0.35 mmol/L in the control arm based on data from our previous study based on usual care. This is an expected mean difference of 2.48 mmol/L. If we assume a more conservative mean difference of 2.0 mmol/L, we will need 41 patients with clinically diagnosed FH to adequately power our study at a 0.80 level with a Type I error probability of 0.05 (two-tailed).
Data from our pilot study suggests the prevalence of FH in general practice is 1:412. Therefore to detect 41 cases of clinically diagnosed FH, we will need to screen 16,892 patients who have visited the GP practice in the last 2 years.
To adjust for variation across practices (ie clustering effect) we will apply a design effect of 1.6 (ICC = 0.153, n = 5 practice clusters), resulting in a total sample size of 27,027.
Pilot data shows that we are likely to have on average 4-8,000 patients who have been seen in the last 2 years on the database per practice. Hence, recruiting from 5 practices will ensure that the study is adequately powered to achieve the primary outcome.
Each index case will generate 1.9 relatives.
Therefore of the 27,027 patients screened we will expect 66 index cases. These will generate 125 more related cases. Hence, FH cases could be between 66 and 125.

A pragmatic, cluster intervention study design with pre-post intervention comparisons. All statistical analyses will be conducted using Stata 13. Descriptive statistics will be used to outline the number of patients at each point of the study (screened, at risk, followed up, and clinically diagnosed with FH). At 12 months, the number of new index cases and number of new family cases detected will be reported. The prevalence of FH will be calculated as the total number of index cases as a proportion of all active patients. The detection rate of FH will be calculated as the number of new clinically identified index cases at 12 months as a proportion of the number of at-risk patients identified through TARB-Ex and referred to the practice at baseline. Change in LDL-c will be examined using multilevel mixed-effects modelling. LDL-c level at 12 months will be the dependent variable. We include two random effects; GP (to account for cluster effects) and Time (to account for repeated observations on the same individual). Analysis will also be adjusted for sex and age.

Recruitment
Recruitment status
Completed
Date of first participant enrolment
Anticipated
30/06/2016
Actual
31/08/2016
Date of last participant enrolment
Anticipated
29/03/2020
Actual
14/11/2019
Date of last data collection
Anticipated
30/04/2020
Actual
13/10/2020
Sample size
Target
125
Accrual to date
Final
133
Recruitment in Australia
Recruitment state(s)
NSW,QLD,TAS,WA,VIC
Recruitment postcode(s) [1] 13074 0
6959 - Fremantle
Recruitment postcode(s) [2] 18653 0
4740 - Mackay
Recruitment postcode(s) [3] 18654 0
7250 - Launceston
Recruitment postcode(s) [4] 18655 0
2037 - Glebe
Recruitment postcode(s) [5] 29081 0
3331 - Bannockburn
Recruitment postcode(s) [6] 34538 0
6059 - Dianella
Recruitment postcode(s) [7] 34539 0
6052 - Bedford
Recruitment postcode(s) [8] 34540 0
6164 - South Lake
Recruitment postcode(s) [9] 34541 0
6168 - Rockingham
Recruitment postcode(s) [10] 34542 0
2040 - Leichhardt
Recruitment postcode(s) [11] 34543 0
2485 - Tweed Heads
Recruitment postcode(s) [12] 34544 0
2025 - Woollahra
Recruitment postcode(s) [13] 34545 0
7301 - Longford

Funding & Sponsors
Funding source category [1] 293360 0
Commercial sector/Industry
Name [1] 293360 0
Sanofi
Country [1] 293360 0
Australia
Funding source category [2] 298492 0
Commercial sector/Industry
Name [2] 298492 0
Amgen Australia Pty Ltd
Country [2] 298492 0
Australia
Funding source category [3] 298493 0
Government body
Name [3] 298493 0
National Health and Medical Research Council
Country [3] 298493 0
Australia
Funding source category [4] 298494 0
Government body
Name [4] 298494 0
Department of Health Western Australia
Country [4] 298494 0
Australia
Funding source category [5] 298495 0
Hospital
Name [5] 298495 0
Royal Perth Hospital Medical Research Foundation
Country [5] 298495 0
Australia
Funding source category [6] 298496 0
Hospital
Name [6] 298496 0
MackayHospital Foundation
Country [6] 298496 0
Australia
Primary sponsor type
University
Name
The University of Notre Dame Australia
Address
School of Medicine, University of Notre Dame Australia
Po Box 1225, Fremantle, WA, 6959
Country
Australia
Secondary sponsor category [1] 297635 0
None
Name [1] 297635 0
Address [1] 297635 0
Country [1] 297635 0

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 294827 0
University of Notre Dame Human Ethics Research Committee
Ethics committee address [1] 294827 0
Ethics committee country [1] 294827 0
Australia
Date submitted for ethics approval [1] 294827 0
12/05/2016
Approval date [1] 294827 0
07/07/2016
Ethics approval number [1] 294827 0
016067F

Summary
Brief summary
Trial website
Trial related presentations / publications
Public notes
Attachments [1] 853 853 0 0
/AnzctrAttachments/370529-Attachment 1_Fig1_Study_Plan_09102015.docx
Attachments [2] 854 854 0 0
/AnzctrAttachments/370529-Attachment 2_Table1_Dutch lipid_09102015.docx
Attachments [3] 855 855 0 0
/AnzctrAttachments/370529-Attachment 3_Fig2_Flow_Plan_management_09102015.docx
Attachments [4] 856 856 0 0
/AnzctrAttachments/370529-Attachment 4_ Fig3_Family contact protocol_09102015.docx

Contacts
Principal investigator
Name 65174 0
Prof Tom Brett
Address 65174 0
School of Medicine, University of Notre Dame Australia
PO Box 1225, Fremantle, WA, 6959
Country 65174 0
Australia
Phone 65174 0
+61 8 9433 0571
Fax 65174 0
Email 65174 0
tom.brett@nd.edu.au
Contact person for public queries
Name 65175 0
Tom Brett
Address 65175 0
University of Notre Dame Australia
19 Moaut St, Fremantle, WA, 6959
Country 65175 0
Australia
Phone 65175 0
+61 8 9433 0571
Fax 65175 0
Email 65175 0
tom.brett@nd.edu.au
Contact person for scientific queries
Name 65176 0
Tom Brett
Address 65176 0
School of Medicine, University of Notre Dame Australia
PO Box 1225, Fremantle, WA, 6959
Country 65176 0
Australia
Phone 65176 0
+61 8 9433 0571
Fax 65176 0
Email 65176 0
tom.brett@nd.edu.au

Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
No/undecided IPD sharing reason/comment
Some clinics have small numbers of participants so deidentified data could be potentially identifiable.


What supporting documents are/will be available?

Doc. No.TypeCitationLinkEmailOther DetailsAttachment
6535Study protocolArnold-Reed DE, Brett T, Troeung L, et al. Detection and management of familial hypercholesterolaemia in primary care in Australia: protocol for a pragmatic cluster intervention study with pre-post intervention comparisons. BMJ Open 2017;7:e017539. doi:10.1136/ bmjopen-2017-017539http://bmjopen.bmj.com/content/bmjopen/7/10/e017539.full.pdf 
6536Statistical analysis planArnold-Reed DE, Brett T, Troeung L, et al. Detection and management of familial hypercholesterolaemia in primary care in Australia: protocol for a pragmatic cluster intervention study with pre-post intervention comparisons. BMJ Open 2017;7:e017539. doi:10.1136/ bmjopen-2017-017539http://bmjopen.bmj.com/content/bmjopen/7/10/e017539.full.pdf 



Results publications and other study-related documents

Documents added manually
No documents have been uploaded by study researchers.

Documents added automatically
No additional documents have been identified.