Types of studies

All randomised controlled trials (RCTs), cluster‐RCTs and non‐randomised study interventions (NRSI). Eligible NRSIs were non‐randomised controlled trials, prospective cohort studies, controlled before‐and‐after studies, and controlled interrupted‐time‐series (ITS) studies as per the Effective Practice and Organisation of Care guidelines (EPOC 2017).

Due to the complex nature of the intervention and setting, we have included NRSIs as we anticipated potential limitations in the availability of RCTs.

Types of participants

Eligible participants of any age from the general population who access primary care or other community healthcare settings. We excluded participants who were selected from specialist settings with expertise in lipid disorders or those with a previous diagnosis of FH or other inherited lipid disorders. If the study contained both eligible and ineligible participants, we would have included the study if the data on eligible participants could be extracted (where at least 70% of the participants were eligible for our review).

Types of interventions

Intervention strategies that aimed to systematically identify people with possible or definite FH, in primary care and other community healthcare settings. Interventions which involved specialists delivering the interventions in these settings (e.g. FH nurse specialists performing case findings) were also appropriate for inclusion.

A systematic intervention strategy for identifying FH is defined as:

• prospective general population screening for FH using diagnostic criteria;

• retrospective electronic and manual health records search for participants who might have FH (i.e. based on elevated cholesterol levels, relevant family history, clinical characteristics, or combination of these factors);

• proactive computer‐generated reminders for participants who might have FH (i.e. based on elevated cholesterol levels, past medical history, relevant family history, clinical characteristics, or combination of these factors);

• population based case‐finding activities (i.e. healthcare practitioner reviewing patient records and contacting individuals; pathology laboratories reporting back high cholesterol levels).

We planned to compare these systematic strategies to identify individuals with possible or definite clinical FH with usual care, where participants continued to receive their standard or current medical care (Reeves 2016). In this situation, usual care for FH identification in primary care and other community healthcare practice could include no activity to identify people with FH, or incidental and non‐systematic strategies during routine consultations. An example of usual care could be noting a raised cholesterol during consultation with individuals presenting with concerns about their personal or family history. However, we excluded studies that used a comparator based on routinely available or historical data due to inherent biases associated with using this non‐directly comparative design.

Where possible, we planned to compare interventions to each other if the usual care healthcare strategies were similar between or within the studies.

Types of outcome measures

Electronic searches

We identified relevant studies from the Cystic Fibrosis and Genetic Disorders Group's Inborn Errors of Metabolism Trials Register using the terms: (Hyperlipoproteinaemia:kw) AND (PCSK* OR proprotein OR evolocumab OR alirocumab OR IgG1 OR IgG2 OR antibod*:ti,ab,kw,mh,emt,misc1).

The Inborn Errors of Metabolism Trials Register is compiled from electronic searches of the Cochrane Central Register of Controlled Trials (CENTRAL) (updated with each new issue of the Cochrane Library), and weekly searches of MEDLINE. Unpublished work is identified by searching the abstract books of the Society for the Study of Inborn Errors of Metabolism conference and the SHS Inborn Error Review Series. For full details of all searching activities for the register, please see the relevant section of the Cochrane Cystic Fibrosis and Genetic Disorders Group's website.

Date of the most recent search of the Cochrane Cystic Fibrosis and Genetic Disorders Group's Inborn Errors of Metabolism Trials Register: 13 September 2021.

In addition to the above, we have conducted a search of the following databases combining free‐text terms and controlled vocabulary where applicable. For details of our search strategies, please see Appendix 2.

• Cochrane Central Register of Controlled Trials (CENTRAL in the Cochrane Library (www.cochranelibrary.com; all years: searched 05 March 2020);

• PubMed (Epub Ahead of print, In process & Other non‐Indexed Citations only) (www.ncbi.nlm.nih.gov/pubmed; 1946 to 05 March 2020);

• MEDLINE (OvidSP, EpubAhead of Print, In‐process & Other Non‐Indexed Citations, Ovid MEDLINE Daily and Ovid MEDLINE) (1946 to 05 March 2020);

• Embase (OvidSP) (1974 to 05 March 2020);

• CINAHL (EBSCOHost) (1937 to 05 March 2020);

• ProQuest Dissertations & Theses Global ProQuest (www.proquest.com/; 1861 to 05 March 2020);

• Web of Science (CPCI‐S) (1898 to 05 March 2020);

• SCOPUS (Elsevier) (1823 to 05 March 2020).

We searched the following trial databases and resources: 

• ISRCTN registry (www.isrctn.com/; all years: searched to 05 March 2020);

• US National Institutes of Health Ongoing Trials Register ClinicalTrials.gov (www.clinicaltrials.gov; all years: searched to 05 March 2020);

• World Health Organization International Clinical Trials Registry Platform (ICTRP) (www.who.int/ictrp.en; all years: searched to 05 March 2020).

Searching other resources

Selection of studies

We selected studies according to chapter 7 of the Cochrane Handbook for Systematic Reviews of Interventions (Lefebvre 2021). We saved the results from the searches in Endnote reference managing software (EndNote X8). Two authors (JT*, MLDS) independently screened the titles and abstracts of the identified studies to check for eligibility. We then retrieved the full texts (where available) of the potentially eligible studies and two authors (JT, MLDS) independently screened these. We resolved any disagreements through discussion, or where necessary, with the assistance of a third author (NQ or JLB).

To guard against potential duplicate publication, we linked multiple reports using the same study participants. We reached agreement in all cases. We recorded details of studies excluded at the full‐text stage together with reasons for exclusion based on the inclusion criteria for the review.

* please refer to 'Acknowledgements'.

Data extraction and management

Two review authors (MLDS, HA‐H) would have independently extracted and recorded data from included studies following guidance in chapter 5 of the Cochrane Handbook for Systematic Reviews of Interventions (Li 2021). We would have used standard data extraction forms, based on the checklist from the Cystic Fibrosis and Genetics Disorders Review Group, which we would have modified to allow relevant data to be captured from all the study designs which were eligible for inclusion in this review.

The data extraction form would have included study characteristics such as study methodology, participant characteristics (including ethnic or cultural characteristics, geographical location), sample size, strategies and characteristics (including process and duration of intervention), primary and secondary outcome measures, FH diagnostic criteria and definitions of other outcomes, and analysis performed in the original trials.

For NRSIs, we would have extracted additional data on confounding factors, the comparability of groups on confounding factors, methods used to control for confounding and on multiple effect estimates (both unadjusted and adjusted estimates) (Reeves 2021). Confounding factors need to be associated with both the intervention and the outcomes, thus such factors would be those assessed at a population‐ or service‐level. Therefore, studies which have adjusted for confounders at participant‐level, e.g. gender, should not have been adjusted for in the analyses. Population‐ or service‐level factors may include, but are not limited to:

• type of health professional(s) delivering the intervention;

• size of the population being assessed;

• workload of the health professional(s)

• introduction of clinical nurse specialists

• introduction of direct pathway to access genetic testing in primary care or other community settings

For future versions of the review, if studies are included, we plan to resolve any discrepancies that arise in data extraction through discussion with a third author (JLB).

Assessment of risk of bias in included studies

If studies are included in future updates of the review, two review authors (NQ and SW) will independently assess the risk of bias; if there is a disagreement, a third author (JLB) will check each assessment and we will discuss the outcome until consensus is achieved.

If we include RCTs in future updates of the review, we will assess the risk of bias using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions according to the following domains: random sequence generation; allocation concealment; blinding of participants and personnel; blinding of outcome assessment; incomplete outcome data; selective outcome reporting; and other sources of bias (Higgins 2017). We will assess each domain as low, unclear or high risk of bias.

If we include NRSIs in future updates of the review, we will assess the risk of bias for each outcome of interest in each study using the ROBINS‐I tool developed by the Cochrane Non‐Randomised Studies Methods Group (Sterne 2016). The tool considers seven domains: two domains of bias pre‐intervention (bias due to confounding at population‐ or service‐level (examples are described in ‘Data extraction and management section’) and bias in selection of participants into the study); one domain of bias at intervention (bias in the measurement of interventions); and four domains of bias post‐intervention (bias due to departures from intended interventions, bias due to missing data, bias in measurement of outcomes and bias in selection of the reported result. We will assess each domain as low, moderate, serious, or critical risk of bias or no information.

For controlled ITS designs, we will use the EPOC Risk of Bias tool which is based on assessing seven standard domains:

• intervention independent of other changes;

• shape of the intervention pre‐specified;

• intervention unlikely to affect data collection;

• knowledge of the allocated interventions adequately prevented during the study;

• incomplete outcome data adequately reported;

• selective outcome reporting; and

• other risk of bias.

We will assess each domain as low, unclear or high risk of bias.

Measures of treatment effect

If we include studies in future updates of this review, where possible, we will report dichotomous outcomes using risk ratios (RR) together with 95% confidence intervals (95% CIs). For studies which have used randomisation, we will extract 2x2 data and estimate crude RRs; however, for studies without randomisation, we will extract RRs which would have been adjusted for baseline differences or the ratio of the RR post‐intervention compared to the RR for pre‐intervention. Where studies report other adjusted measures of effect, e.g. odds ratios, we will extract these and report them separately.

Where possible, we will report continuous outcomes using mean differences (MD) together with 95% CIs. For studies which have used randomisation, we will extract raw data and estimate crude MDs; however, for studies without randomisation, we will extract MDs for the absolute change or the relative change, which will have been adjusted for baseline differences.

For studies with a non‐randomised study design, we will consider additional analysis on adjusting for baseline group differences, with appropriate regression analysis based on the form of the outcome variables (continuous or binary).

For studies which have used a controlled ITS design, we will extract quantitative results from either a regression analysis with time trends before and after the intervention, adjusted for autocorrelation and any periodic changes, or from an ARIMA analysis. We will present the results for the outcomes as the change in level (immediate effect of the intervention) and the change in slope (longer‐term effect of the intervention). If the results from a study using a controlled ITS design are only reported as data points in a scanable graph or in a table, we will attempt to re‐analyse the data by contacting study authors for permission to use their raw study data (Ramsay 2003).

Unit of analysis issues

For future updates, if we include studies, we will consider whether any unit of analysis errors were made in the reported analysis for each study. For cluster‐randomised studies, where the analysis may not adjust for the effect of clustering, if we identify a unit‐of‐analysis issue, we will attempt to correct the analysis by re‐analysing the presented data. Or if there is insufficient information presented, we will contact the authors to obtain the necessary information or raw data. If we are not able to re‐analyse the data taking into account clustering, we will report the uncorrected estimates without a measure of uncertainty (e.g. 95% CI) and analyse the results separately from non‐clustered studies. For future updates, if we include studies with multiple‐arm groups, we will only include intervention and comparator groups which are relevant to the systematic review. Since we anticipate that studies will include different comparator groups, where it is appropriate, we will combine different comparator groups together and compare this to the active intervention group in the meta‐analysis. For studies which include multiple intervention groups, we will combine these together and compare this to the comparator group in the meta‐analysis. For further unit of analysis issues, we will analyse these following the recommendation in chapter 23 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021).

For studies that have accounted for repeated measures we aim to report their study measures.

Dealing with missing data

For future updates of this review, if  we include studies and where important data are missing (e.g. standard deviations), we will contact the authors of studies published less than 10 years ago to request additional data. If we are unable to retrieve missing data, we will conduct a sensitivity analysis to compare study outcomes grouped by the amount of missing data: large amount (more than 30%); moderate amount (10% to 30%); low amount (less than 10%). We will then discuss the potential impact of the missing data on the findings of the review.

Assessment of heterogeneity

For future updates of this review, if we include studies, we plan to assess any heterogeneity we identify as follows.

Assessment of reporting biases

Where any future meta‐analysis contains more than 10 studies, we plan to use funnel plots to assess the potential effects of reporting biases. Where funnel plot asymmetry is apparent, we will consider possible sources of asymmetry other than publication bias, e.g. based on domains of methodological quality, and conduct appropriate sensitivity analyses.

Data synthesis

If studies are included in future updates of this review, we plan to initially summarise all included studies using narrative synthesis methods. This will involve the use of narrative text and tables to summarise data based on the type of intervention and according to setting, we will consider outcomes in the light of differences in study designs and address potential sources of bias, potential confounding factors and any further methodological limitations for each of the studies being reviewed, including how these may have impacted on the study findings. We plan then to provide a synthesised summary of the studies, including the range and size of any reported associations and important study characteristics.

We will conduct separate meta‐analyses for RCTs and NRSIs. We will use random‐effects models to conduct meta‐analyses due to anticipated differences in the effectiveness of the intervention by type of intervention, comparator, setting, and populations. We will include all studies in the primary meta‐analyses, irrespective of the risk of bias scores given for each domain.

We will  not include the quantitative findings from studies deemed to have a critical risk of bias in the synthesis (Reeves 2021).

We will perform meta‐analysis using the Review Manager (RevMan) software (RevMan 2020) or Stata version 16 (STATA 2019).

Subgroup analysis and investigation of heterogeneity

If we include studies in future updates of this review, for each meta‐analysis which includes at least five studies, we will perform subgroup analyses based on study‐level variables and report a P value relating to the statistical test for differences between subgroups, where appropriate. We will consider the following characteristics:

• mode of diagnosis for FH (genetic or clinical);

• age of participant (under 10 years of age or 10 years of age and above);

• type of systematic intervention (prospective population screen, retrospective computer search, proactive computer reminders, population‐based case finding);

• type of comparator;

• type of setting (primary medical care, employer‐based clinics, community pharmacists).

We will undertake subgroup analyses using RevMan (RevMan 2020) or Stata version 16 (STATA 2019). We anticipate that due to the complexity of the intervention that most studies would include complex interventions and therefore we grouped studies primarily based on similarities between outcome measures.

Sensitivity analysis

If studies are included in future updates of this review, we plan to assess the impact of methodological quality on the results of the meta‐analyses. We will compare the pooled effect size from this sensitivity analysis to the pooled effect size from the original analyses. For RCTs, the sensitivity analysis would be based on only those studies with an overall low risk of bias; for NRSIs (including controlled ITS designs), the sensitivity analysis would be based on only those with an overall low or moderate risk of bias. We will report sensitivity analyses in table format within this review.

Summary of findings and assessment of the certainty of the evidence

If we include studies in future updates of this review, we will create summary of findings tables for the primary outcomes, following the GRADE approach suggested in chapter 14 of the Cochrane Handbook for Systematic Review of Interventions (Schünemann 2021). This will state the participant population setting, intervention, comparison, and main outcome measures. In addition, the tables would have presented the quality rating of the evidence as ’high’, ’moderate’, ’low’, or ’very low’ using the following five GRADE considerations:

• risk of bias (serious or very serious);

• inconsistency (serious or very serious);

• indirectness (serious or very serious);

• imprecision (serious or very serious);

• publication bias (likely or very likely).

For NRSIs we will also consider the following factors:

• size of effect (large or very large);

• confounding (either reduces the demonstrated effect or increases the effect if no effect was observed (yes or no)).

In GRADE, we will rate NRSIs initially as low quality and downgrade or upgrade according to GRADE guidelines, if appropriate. We will present outcomes for these studies in separate tables from outcomes for the results of RCTs.