Difference between revisions of "Identifying Links between Studies"

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===Introduction===
 
===Introduction===
 
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One of the issues that has to be tackled during aggregation of data from different sources is the fact that the same study can be found, and in tens of thousands of cases ''is'' found, in more than one study based source, and that it will have a different persistent identifier in each source. Partly this is because studies can be registered in more than one trial registry, especially when local regulations mandate a registration for any study carried out within a particular country or region. This is especially the case with the EU, which insists all trials involving medicinal products must be registered in the EUCTR. About a third of these studies, however, are also registered in other registries, especially Clinicaltrials.gov. In addition, within a data repository, studies will usually be referenced by a local id rather than a pre-existing registry id.<br/>
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Study titles cannot be relied upon to identify the same study in different source locations. A study title is often expressed slightly differently in different contexts, and cannot in any case be relied upon to be unique (even within the same source). It may be that further research will indicate how titles could be reframed (e.g. to a smaller number of words, expressed in a fixed order) to allow duplicate entries to be discovered using text, but for the moment the only easy way of doing this is by using the 'other identifiers' material found in the source data. Almost all sources contain this material, which usually include any registry ids, other than that used in the registry entry itself, as well as sponsor and funder ids.<br/>
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These 'other registry ids' can be used to build up a table of study-study links which can then be used during the aggregation process to identify when duplicate studies are being added. In fact the creation of this table is always the first stage of any aggregation. This page describes this process in detail.
  
 
===The Preferred Source concept===
 
===The Preferred Source concept===

Revision as of 15:04, 18 November 2020

Introduction

One of the issues that has to be tackled during aggregation of data from different sources is the fact that the same study can be found, and in tens of thousands of cases is found, in more than one study based source, and that it will have a different persistent identifier in each source. Partly this is because studies can be registered in more than one trial registry, especially when local regulations mandate a registration for any study carried out within a particular country or region. This is especially the case with the EU, which insists all trials involving medicinal products must be registered in the EUCTR. About a third of these studies, however, are also registered in other registries, especially Clinicaltrials.gov. In addition, within a data repository, studies will usually be referenced by a local id rather than a pre-existing registry id.
Study titles cannot be relied upon to identify the same study in different source locations. A study title is often expressed slightly differently in different contexts, and cannot in any case be relied upon to be unique (even within the same source). It may be that further research will indicate how titles could be reframed (e.g. to a smaller number of words, expressed in a fixed order) to allow duplicate entries to be discovered using text, but for the moment the only easy way of doing this is by using the 'other identifiers' material found in the source data. Almost all sources contain this material, which usually include any registry ids, other than that used in the registry entry itself, as well as sponsor and funder ids.
These 'other registry ids' can be used to build up a table of study-study links which can then be used during the aggregation process to identify when duplicate studies are being added. In fact the creation of this table is always the first stage of any aggregation. This page describes this process in detail.

The Preferred Source concept

Initial Links Data Collection

Data Processing to remove duplicates

Exclusion of One-to-Many links

Final Steps