Category Archives: Resource Highlights

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Sub-grouping PubMed Records by Their Linkages to Other NIH Resources

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The National Library of Medicine (NLM), which is part of the NIH, is responsible for a wide array of information/data resources. In addition to biomedical literature databases like PubMed, PubMed Central, and the clinical trial registry, ClinicalTrials.gov, NLM also includes computational molecular biology resources and human genome resources among its database offerings, all of which are freely-available to everyone.

One of the great strengths of NLM’s resources is that they have been designed with maximum accessibility/linkages in mind. If you are searching in one database and there is information in another NLM resource that might also be relevant, chances are pretty good that the database record you are consulting will include meaningful embedded links-out to the other tools.

These connections between resources are particularly valuable for conducting specialized searches of the biomedical literature. The ability to sub-group PubMed records according to their inclusion in a “secondary source” means that you can limit a search within PubMed to a more relevant portion of PubMed, which is a powerful way to increase the precision of your search results.

Following are two different use cases where this sub-grouping functionality can be super-useful if you are carrying out targeted information retrieval projects.

Case 1: ClinicalTrials.gov

In ClinicalTrials.gov, each registered clinical trial record includes a “Study Results” tab where searchers can find publication lists (when available). These lists of article citations link back to PubMed records, which in turn are indexed with ClinicalTrials.gov identifiers. As a result of this set-up, if a searcher wishes to start in PubMed and search on their favorite topic across the published clinical trial study results identified in ClinicalTrials.gov, they can do so by adding the following to their PubMed search strategy:

Clinicaltrials.gov[si]  

For example: clinicaltrials.gov[si] AND sarcoma – Search Results – PubMed (nih.gov)

(Note: The ClinicalTrial.gov linkage will appear in the PubMed Abstract record in the “Associated data” section.)

Case 2: GeneRIF (Gene Reference into Function)

Another specialized literature search that is often tricky to carry out is one that limits the search results to those publications that describe a gene’s function. Luckily, NLM already has a program called GeneRIF (Gene Reference into Function) that “provides a simple mechanism to allow scientists to add to the functional annotation of genes described in Gene.” By leveraging these gene-PMID connections developed for the Gene database, PubMed searchers can limit their search results to only those PubMed records that have been tagged with a GeneRIF identifier. They can do this by adding the following to their PubMed search strategy:

“pubmed gene rif” [Filter]

For example: “pubmed gene rif” [Filter] AND sarcoma – Search Results – PubMed (nih.gov)

(Note: The GeneRIF linkage will appear in the PubMed Abstract record in the “Related information” section.) 

If you have any questions or would like some additional guidance on designing specialized literature searches, feel free to Ask Us at the MSK Library.

 

PRISMA 2020 Replaces PRISMA 2009

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At the end of March 2021, the PRISMA 2020 guideline update was simultaneously published in five journals, officially marking the replacement of the PRISMA 2009 with the updated PRISMA 2020 guideline:

Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE, Chou R, Glanville J, Grimshaw JM, Hróbjartsson A, Lalu MM, Li T, Loder EW, Mayo-Wilson E, McDonald S, McGuinness LA, Stewart LA, Thomas J, Tricco AC, Welch VA, Whiting P, Moher D. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews.

  • BMJ 2021 Mar 29;372:n71. doi: 10.1136/bmj.n71. PMID: 33782057; PMCID: PMC8005924.
  • Syst Rev. 2021 Mar 29;10(1):89. doi: 10.1186/s13643-021-01626-4. PMID: 33781348.
  • J Clin Epidemiol. 2021 Mar 17:S0895-4356(21)00073-1. doi: 10.1016/j.jclinepi.2021.03.001. PMID: 33789819.
  • Int J Surg. 2021 Apr;88:105906. doi: 10.1016/j.ijsu.2021.105906. Epub 2021 Mar 29.PMID: 33789826.
  • PLoS Med. 2021 Mar 29;18(3):e1003583. doi: 10.1371/journal.pmed.1003583. eCollection 2021 Mar. PMID: 33780438.

Published translations of this guideline into other languages are forthcoming.

For the most detailed description of the new PRISMA 2020 guideline, this accompanying “explanation and elaboration” article was also published:

  • Page MJ, Moher D, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE, Chou R, Glanville J, Grimshaw JM, Hróbjartsson A, Lalu MM, Li T, Loder EW, Mayo-Wilson E, McDonald S, McGuinness LA, Stewart LA, Thomas J, Tricco AC, Welch VA, Whiting P, McKenzie JE. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ. 2021 Mar 29;372:n160. doi: 10.1136/bmj.n160. PMID: 33781993; PMCID: PMC8005925.

  • For details about the process that was used to develop the PRISMA 2020 update:

    Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Moher D. Updating guidance for reporting systematic reviews: development of the PRISMA 2020 statement. J Clin Epidemiol. 2021 Feb 9;134:103-112. doi: 10.1016/j.jclinepi.2021.02.003. Epub ahead of print. PMID: 33577987.

Noteworthy Changes in the PRISMA 2020 Update

Among the key PRISMA 2020 guideline changes are: more inclusive wording so that it’s more accommodating to other methods from different fields (ex., methods beyond randomized trials of health interventions); some of the categories have been broken down into more granular sub-items that are more explicit and provide more clarity about what exactly should be reported, some new items and sub-items have been introduced or expanded upon; and some of the items have been slightly re-ordered in the checklist.

The new PRISMA 2020 guideline is meant to reflect the changing reality of the current research climate. For example, now that more people are registering their protocols as is recommended by PRISMA, there is a sub-item added to address the clear reporting of potential protocol amendments. Also – in line with the open science movement, there are sub-items related to reporting about the availability of data and statistical code, etc. Furthermore, with automation tools starting to be considered for use in SRs, more explicit reporting in this area is also recommended, as well as the reporting of conflicts of interest of review authors, something which is becoming a more common requirement in all areas of scholarly publishing.

There also has been an obvious push towards greater transparency in the methods, with recommendations to include the full search strategies and number of results for all information resources searched (which is in accordance with the PRISMA-S extension also published this year), as well as to provide the full citations for all of the included studies and citations for the studies that were excluded at the full-text stage, with reasons.

This latest version of PRISMA also appears to recognize that often in SRs, the synthesis of the results includes the grouping or sub-grouping of studies for the analysis, which the guideline suggests should be better reported upon. PRISMA 2020 makes a more explicit request for the reporting of criteria and processes used to group studies. Related to this, PRISMA 2020 also encourages that the reporting of characteristics and risk of bias be handled not for all included studies as a whole but rather to be considered among sub-grouped studies contributing to each synthesis.


New Tools and Templates for PRISMA 2020

It should be noted that the PRISMA guidelines are recommendations and not every item in the checklist applies to every situation. (In fact, it is for that very reason that PRISMA extensions exist and should still be used in conjunction with PRISMA 2020 as not all of these have been perfectly harmonized as of yet.) As such – this guidance should be viewed as useful suggestions for improving the quality of reporting of a systematic review – keeping in mind, however, that not every item is always applicable and mandatory.

This spirit of flexibility is reflected in the increased template options made available on the PRISMA Statement website to accommodate different scenarios. Both the PRISMA 2020 Checklist and Flow Diagram template options are now available for viewing and downloading. In addition to the PDF and Word templates, Shiny App computer applications have also been created that can be used to more easily generate the completed checklist and flow diagram by inputting data.

To learn more, please view a recent presentation on PRISMA 2020 by the first author (Dr. Matthew Page, Monash University) responsible for the update and feel free to send us your questions at Ask Us at the MSK Library or to explore the Systematic Review Service LibGuide.

Two Types of Author Profiles: Auto-Generated or Opt-In

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Author profiles are extremely useful vehicles for increasing the visibility and discoverability of your published work. Although it is more popular in the business world, many researchers now have LinkedIn profiles that they may use to push out information about their research and publications to their professional community.

However, there are also some more scholarly options that are worthy of investigation, as they may increase your chances of having your work discovered online by other researchers who may be interested in building on your research or in engaging with you in scholarly collaboration.

There are two types of author profiles: 1) auto-generated ones and 2) “opt-in” ones.

1) Auto-generated Author Profiles:

In the case of auto-generated Author Profiles, when the author publishes a new work, the database producer will automatically add the new citation record to the profile, without further author involvement needed. All profiles are available for viewing by searchers of the database and often include some research impact metrics. (Note: It is a good idea to periodically check your Scopus and Web of Science database profiles for accuracy as errors may negatively-impact the research impact metrics being reported on your Author Profile.)

Examples:

  • Synapse (MSK Authored Works) – https://synapse.mskcc.org/synapse
    Synapse is a database of citations to MSK-authored works (e.g., journal articles, meeting abstracts, book chapters, etc.) that includes some traditional research metrics and alternative metrics (embedded/sourced from a vendor called Dimensions).

  • Scopus Author Profiles – https://libguides.mskcc.org/scopus
    Scopus Author Profiles include metrics (e.g. H-Index) that are generated via citation analysis of the contents of the Scopus database, which includes “Times Cited” data.

  • Web of Science Author Profiles – https://libguides.mskcc.org/webofscience
    Similar to Scopus Author Profiles, however, the new version of Web of Science will include additional details that may speak to an individual author’s research impact, for example, Author Position information (First or Last author, etc.).

2) Opt-In Author Profiles:

In the case of opt-in Author Profiles, the author can choose to register for an account with a particular service and create a profile. It is the author’s responsibility to add citations to the profile and to update it whenever they publish new works. The author can also decide to make the profile public or private (i.e., they are in control over who/what gets viewed).

Examples:

  • ORCID – https://orcid.org/
    ORCID (Open Researcher and Contributor ID) is an independent, not-for-profit, non-proprietary Author Profile resources that does not provide metrics, a reporting interface, or a collaboration portal, but they enable other organizations to provide these services. Many journal publishers and database providers have started integrating ORCID links/info into their products. For example, the ORCID symbol is often included as a hyperlink (on HTML and PDF of articles) that leads to that author’s ORCID profile, allowing readers of this paper to immediately discover other works by that author.

  • Publons (via Web of Science) – https://publons.com/about/home/
    The source of research impact metrics data in this resource is its sister product, Web of Science. A unique feature of Publons is that it allows authors to get verified credit for their participation in the peer-review process.

  • Google Scholar – https://scholar.google.com/
    Google Scholar’s greatest advantage is that it is free and not behind a paywall, as are Scopus and Web of Science.

ORCID@MSK App

Since your ORCID profile is “opt-in”, it is not automatically updated with your new works. Recognizing that keeping opt-in Author Profiles up-to-date can be time-consuming, the MSK Library has created an app that makes it easy to push items from your “auto-generated” Synapse profile to your “opt-in” ORCID profile. You can use the ORCID@MSK app to connect your Synapse profile to your ORCID profile. Since Synapse is automatically updated, you can periodically login to ORCID@MSK and pass on the new items added to Synapse to your ORCID profile so that it also stays up-to-date.

Be sure to check out the MSK Library‘s training class on Measuring Research Impact or to Ask Us if you have any questions about Author Profiles.