Enhancing the QUAlity and Transparency Of health Research

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Reporting guidelines under development for observational studies

Reporting guidelines under development for observational studies or STROBE extensions

(year of development in brackets)

STROBE checklist for conference abstracts (2011)

Guideline for Reporting Environmental Epidemiology aNalyses (GREEN) (2016)

Standardized Protocol Items: Recommendations for Observational Studies (SPIROS) (2017)

Framework for Enhanced Reporting of Interrupted TimeSeries (FERITS) (2018)

Guidelines On Assessments in LMIC Settings (GOALS) (2018)

SPoRTIER: Social Prescribing Reporting Template to Improve Evaluation and Replication (2018)

STROBE extension – Diagnostics involving metagenomics (2018)

PARAMEDICS-CARE: A consensus-based guideline for publishing pre-hospital case reports (2018)

CARE for Acupuncture (2018)

DAQCORD – Data Access Quality and Curation for Observational Research Designs (Guidelines for the design, reporting and data quality assessment for large observational clinical data collection) (2019)

EPI-FORGE – Epidemic Forecasting Reporting Guidelines (2019)

STROPS – The STrengthening the Reporting Of Pharmacogenetic Studies guideline: checklist of items for reporting pharmacogenetic studies (2019)

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STROBE checklist for conference abstracts

The STROBE Group have recently developed a checklist for conference abstracts.

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Guideline for Reporting Environmental Epidemiology aNalyses (GREEN) (registered 20 December 2016)

This guideline will encompass studies that report on association between environmental exposures and health outcomes.

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Standardized Protocol Items: Recommendations for Observational Studies (SPIROS) (registered 7 February 2017)

The guidelines aim to define comprehensive set of standard protocol items for observational studies, and by doing so facilitates and encourages researchers to prepare a study protocol of sufficient quality, prior to data collection.

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Framework for Enhanced Reporting of Interrupted Time Series (FERITS) (registered 22 May 2018)

Reporting guidelines for interrupted time series studies. These are generally applied for the evaluation of public health interventions.

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Guidelines On Assessments in LMIC Settings (GOALS) (registered 28 August 2018)

Outcome-based and observational metrics in surgical studies conducted in Lower-Middle Income Countries (LMICs).

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SPoRTIER: Social Prescribing Reporting Template to Improve Evaluation and Replication (registered 28 August 2018)

This guideline is being developed by researchers at the Centre for Health Services Studies, University of Kent to improve the quality and completeness of reporting for Social Prescribing programmes. Social prescribing provides a non-medical referral option to improve health and wellbeing. Referrals can be to a range of programmes from befriending schemes, volunteering opportunities, supported education, arts, physical activity, as well as support with employment or legal advice.

Different Social Prescribing models have evolved across England reflecting local needs, service provider expertise and commissioning contracts. Consequently models vary greatly in terms of aims of the service, delivery partners, referral pathways, staffing, and service user outcomes making it difficult to identify features of a successful model, for whom social prescribing benefits, and under what circumstances.

SPoRTIER will provide a standardised useable template to capture contextual details on different programmes and how these programmes are being implemented to aid understanding of how social prescribing contributes to changes in health and wellbeing.
Development of SPoRTIER is based on the EQUATOR Network methodological framework for developing reporting guidelines.

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STROBE extension – Diagnostics involving metagenomics (registered 28 August 2018)

There has been an exponential increase in studies applying metagenomic diagnostics, such as 16S PCR and deep-sequencing. The aim of this extension is to adapt the STROBE statement to be more applicable to these types of diagnostics, and to ensure transparency in publications on the same.

There will be a broad focus on metagenomics, and appendices on 1) Neurological infections, 2) Antimicrobial Resistance and 3) the Gut Microbiome.

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PARAMEDICS-CARE: A consensus-based guideline for publishing pre-hospital case reports (registered 4 October 2018)

PARAMEDICS-CARE is a consensus-based guideline under development for publishing pre-hospital case reports. It will be an extension to the CAse REport (CARE) clinical case reporting guideline.

Currently, case reports published on pre-hospital care rarely follow the CARE guideline. The quality of these publications is highly variable. The aim of the PARAMEDICS-CARE guideline is to improve the quality of pre-hospital care case reports.

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CARE for Acupuncture – Consensus-based Clinical Case Reporting Guideline Development Extension: CARE for Acupuncture

Case reports are still an important source to provide evidence on acupuncture to clinicians and researchers. They can better present the real situation of clinical practice, reflect the individualized treatment characteristics of acupuncture treatment, and inherit the experience of prominent traditional medicine doctors.

CARE is a reporting guideline for case reports. The aim of the CARE for Acupuncture project is to develop an extension of CARE focused on acupuncture areas, which can enhance the transparency and quality of case reports on acupuncture.

The study design will refer to the methodology recommended by the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) Network, modified as appropriate. A literature review will be conducted, and an international multidisciplinary team is established, including a Development Group, a Delphi Panellists Group and an Advisory Group. From 1st October, 2018, the group started literatures and draft the item checklists. Three rounds of modified Delphi surveys, face-to-face consensus meetings, consultations with advisors, pilot tests of the draft list of reports and promotion of the checklist are under development. The group plans to update the reporting guideline regularly. The group intends to publish the reporting guideline on 2019, as an open access document.

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DAQCORD – Data Access Quality and Curation for Observational Research Designs (Guidelines for the design, reporting and data quality assessment for large observational clinical data collection) (registered on 11 February 2019)

Data quality assurance and curation of large observational clinical studies is difficult, particularly when the data to be collected is heterogeneous. Such studies may consist of a diverse mixture of data types as well as combination of single, repeated measures as well as time series which may have irregular sampling. The involvement of multiple sites, particularly where these are international, may introduce further data variances due to local interpretation of procedures and linguistic misunderstandings. As a result, the curation of resultant datasets may be very complex and involved. Poor attention to detail from design through execution including quality control and curation may severely limit data interpretation and consequently re-use and transparency. Furthermore lack of attention to accurate meta-data documentation and failure to adhere to data definitions may severely compromise data quality and hamper quality control at study run-time.

The Data Access Quality and Curation for Observational Research Designs (DAQCORD) tool aims: to provide a framework/toolkit for robust study design (and electronic case report form- eCRF- design in particular) and quality management; to provide a framework by which early study plans can be systematically appraised (for example by funding organisations) in terms of their approach to data quality; and to provide a reporting framework with which to describe the steps taken to ensure data quality in the final study publication.

The authors have already undertaken three Delphi rounds with international experts in conducting/designing/curating largescale observational clinical data collection, in which they discussed issues and examples of good practice. The results have been preliminary analysed and the group aims to publish the guideline by mid-2019, as an open access publication. The DAQCORD team gratefully acknowledge the support of One Mind and the NIH/NINDS.

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EPI-FORGE – Epidemic Forecasting Reporting Guidelines – Establishing a set of standards for the reporting of epidemic forecasting/prediction studies (Registered on 25 February 2019)

There is a wide range of epidemic models which forecast epidemiological phenomena during epidemics. These are frequently published in peer reviewed academic journals. Such forecasts are critical to inform response planning, risk communication and the use and intensity of interventions.

The EPI-FORGE guideline will establish a set of standards for the reporting of epidemic forecasting and prediction studies. The domains of reporting may include reproducibility, transparency, validity, interpretability, funding and sponsorship. EPI-FORGE aims to improve the consistency of epidemic forecasting reporting, the reproducibility of forecasting results, the quality of epidemic forecasting practice, and the transparency of forecasting practice.

The proposed target audience of these guidelines includes epidemic model developers and validators, journal reviewers, journal editors, and epidemiology and biostatistics training programs. These guidelines may also benefit end-users and other epidemic forecast stakeholders.

The EPI-FORGE development process will follow guideline development best practice as recommended by the EQUATOR network. The group plans to publish the guidelines as an open access document.

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STROPS – The STrengthening the Reporting Of Pharmacogenetic Studies guideline: checklist of items for reporting pharmacogenetic studies (Registered on 15 March 2019)

Pharmacogenetic studies investigate associations between genetic variants (SNPs) and treatment response for a particular drug of interest, in terms of both benefits (therapeutic effect) and harms (adverse effects). The aim of performing such studies is to identify ways that drug efficacy may be maximised, and that toxicity may be minimised.  If a significant association between a genetic variant and a treatment response outcome is identified, patients may eventually be genotyped in clinical practice before being prescribed a certain treatment. The health care provider may then refer to the results of the genotyping test when determining whether to prescribe the drug, and if prescribed, the appropriate dosage of the drug. Such an approach is known as “personalised medicine”.

Outcomes from pharmacogenetic studies are often likely to be complex traits; genetic influence may be explained by several genetic variants each having only a small effect on outcome. Consequently, large sample sizes are typically required to detect statistically significant associations between a genetic variant and treatment response. Meta-analysis improves sample size and consequently increases the power to detect significant genetic effects. However, significant differences are often observed between pharmacogenetic studies in terms of the genetic variants investigated, definition of genetic subgroups and outcomes, and assumptions made in the analyses for example about the underlying mode of inheritance. This can significantly reduce the number of studies available to contribute to a single meta-analysis. This problem is compounded by poor reporting of key data in study reports.

The aim of the project is to develop a guideline for the reporting of pharmacogenetic studies and an explanatory document using the approach proposed by EQUATOR. Such a guideline would facilitate the conduct of high-quality systematic reviews and meta-analyses, thus improving power to detect genetic associations.

The Steering Committee started the development of the guideline for pharmacogenetic studies in February 2018, and plans to conduct the work in five stages:

  1. Establish a preliminary checklist of reporting items to be considered for inclusion in the reporting guideline for pharmacogenetic studies (finished).
  2. Conduct a Delphi survey to gain consensus opinion on reporting items to be considered within a reporting guideline for pharmacogenetic studies (started).
  3. Hold a Steering Committee meeting to consider the results of the Delphi survey and to finalise the list of items for the reporting guideline.
  4. Develop and publish a high-quality reporting guideline and a detailed explanatory document.
  5. Disseminate the published guideline.

The steering committee is a 6-member panel of statisticians, methodologists and clinicians, with areas of expertise including statistical methods for pharmacogenetic data, systematic review methodology, consensus methodology and development of reporting guidelines (Marty Richardson, Jamie Kirkham, Kerry Dwan, Derek J Sloan, Geraint Davies, Andrea L Jorgensen).

The group plans to finish the work on mid-late 2020, and to publish the new guidelines as an open access document. The protocol was submitted to publication.

 

Page last updated on: 15 March 2019