Choosing Between Extraction 1 and Extraction 2 in Covidence

Here’s a tip for getting the most out of data extraction in Covidence.

For background, the MSK Library has an institutional account to Covidence, an online software platform used for systematic and other related reviews. Covidence offers teams a collaborative space to screen, appraise, and extract data from articles, and our institutional account means anyone at MSK can use this platform for their review projects.

Once you’re within the Covidence page for your review, you’ll see there are four stages below Review Summary, with Extraction at the end. When you click on Settings to the right of Review Summary, you’ll have the option of selecting between Extraction 1 and Extraction 2.

Both extraction options offer a customizable data extraction template, so which to choose?

Covidence offers the FAQ: How to decide when to use Extraction 1 vs Extraction 2.

  • Extraction 1 is designed for intervention reviews with a standardized PICO(T) structure, as it offers a structured format for organized data collection, which makes meta-analysis easier. This structure allows it to automatically fill in data extraction fields with suggestions you can review. Results can be exported to CSV, Excel, and RevMan.
  • Extraction 2 offers an unstructured format for flexible data collection and is fully customizable. It doesn’t offer automated extraction suggestions and only exports to CSV.

Learn more about data extraction and templates for these two options in the Covidence Knowledge Base. If you prefer to be hands-on, Covidence offers a demo review, and you can test both extraction options there before choosing which one is best for your project.

Learn more about reviews, Covidence, and the way MSK librarians can support you within the guide to our Systematic Review Service.

Effective July 1, 2025 – New NIH Public Access Policy

It was announced on April 30, 2025, that the 2024 NIH Public Access Policy, originally planned to come into effect at the end of 2025 will now be effective as of July 1, 2025.

A key difference between the 2008 and the new 2024 NIH Public Access Policy has to do with how quickly a full-text PMC version of the research article is required to be made publicly available.

In the 2008 version of the policy, the PMC copy had up to 12 months after official publication to become publicly available. The 2024 version of the policy removes the 12-month publisher embargo option and requires the article’s PMC version to become available immediately upon official publication. The new policy will apply to all NIH-funded research articles submitted for journal publication starting on July 1st.

From: https://www.nih.gov/about-nih/who-we-are/nih-director/statements/accelerating-access-research-results-new-implementation-date-2024-nih-public-access-policy

“While the 2008 Policy allowed for an up to 12-month delay before such articles were required to be made publicly available, in 2024, NIH revised the Public Access Policy to remove the embargo period so that researchers, students, and members of the public have rapid access to these findings.”

From: NOT-OD-25-101- Revision: Notice of Updated Effective Date for the 2024 NIH Public Access Policy:

“NIH’s default position is maximum transparency regarding research and research findings. This Notice updates the Effective Date of the 2024 NIH Public Access Policy, NOT-OD-25-047to July 1, 2025 at which time it will replace the 2008 Public Access Policy. All other aspects of the Policy remain the same.“

From: NOT-OD-25-047 – 2024 NIH Public Access Policy:

Regarding submission to PubMed Central, compliance with the Policy may be achieved through either:

  • Submission of the electronic version of the Author Accepted Manuscript to PubMed Central upon its acceptance for publication, for public availability without embargo upon the Official Date of Publication, or
  • Submission of the Final Published Article to PubMed Central from journals or publishers with formal agreements with NLM, upon the Official Date of Publication, for public availability without embargo.

Learn more about how to comply with the NIH Pubic Access Policy or Ask Us your questions.

ClinicalTrials.gov – Discovery Tool and Research Data Source

As ClinicalTrials.gov celebrates its 25th anniversary, reaches its half-million registered studies milestone, and completes its modernization, it’s a good time to appreciate this invaluable research tool that has been around since 2000. In 2008, NLM launched the ClinicalTrials.gov results database, which now (as of 12/2024) has >70K registered studies posted with results.

Openly available to all with “about 90 thousand visitors per day and 2 million unique visitors every month”, ClinicalTrials.gov is a registry where individuals can identify both ongoing and completed registered trials from “50 States and in 229 countries and territories”.

Some functionality that has been added over the last few years (related to how you can search the database using Complex Search Queries and how you can download and use the search results/records from ClinicalTrials.gov) has made this database increasingly attractive as a data source for answering research questions.

From: https://clinicaltrials.gov/find-studies 

In addition to having search functionality that allows for very precise searching, it is now possible to download search results from ClinicalTrials.gov in the RIS file format that can be imported into citation management tools like EndNote and Covidence (used for managing systematic review projects).

It is important to note that the data fields included in the RIS download (which is not customizable), differ from those included in the CSV file download data fields (which a user can select from a menu of options), which differ from the JSON format (which can include every available data field for each study being downloaded). The ClinicalTrials.gov API option allows the ClinicalTrials.gov database to be accessed on a large scale, automated way by researchers and developers.

From: https://clinicaltrials.gov/find-studies/how-to-use-search-results

Examples of research projects that have leveraged ClinicalTrials.gov data:

  1. Alhajahjeh A, Rotter LK, Stempel JM, Grimshaw AA, Bewersdorf JP, Blaha O, Kewan T, Podoltsev NA, Shallis RM, Mendez L, Stahl M, Zeidan AM. Global Disparities in the Characteristics and Outcomes of Leukemia Clinical Trials: A Cross-Sectional Study of the ClinicalTrials.gov Database. JCO Glob Oncol. 2024 Nov;10:e2400316. doi: 10.1200/GO-24-00316. Epub 2024 Dec 2. PMID: 39621951.

  2. Chen D, Parsa R, Chauhan K, Lukovic J, Han K, Taggar A, Raman S. Review of brachytherapy clinical trials: a cross-sectional analysis of ClinicalTrials.gov. Radiat Oncol. 2024 Feb 13;19(1):22. doi: 10.1186/s13014-024-02415-8. PMID: 38351013; PMCID: PMC10863227.

  3. Falade AS, Adeoye O, Van Loon K, Buckle GC. Clinical Trials in Gastroesophageal Cancers: An Analysis of the Global Landscape of Interventional Trials From ClinicalTrials.gov. JCO Glob Oncol. 2024 Aug;10:e2400169. doi: 10.1200/GO.24.00169. PMID: 39173083.

  4. Pearce FJ, Cruz Rivera S, Liu X, Manna E, Denniston AK, Calvert MJ. The role of patient-reported outcome measures in trials of artificial intelligence health technologies: a systematic evaluation of ClinicalTrials.gov records (1997-2022). Lancet Digit Health. 2023 Mar;5(3):e160-e167. doi: 10.1016/S2589-7500(22)00249-7. PMID: 36828608.

  5. Yang A, Baxi S, Korenstein D. ClinicalTrials.gov for Facilitating Rapid Understanding of Potential Harms of New Drugs: The Case of Checkpoint Inhibitors. J Oncol Pract. 2018 Feb;14(2):72-76. doi: 10.1200/JOP.2017.025114. Epub 2018 Jan 3. PMID: 29298113; PMCID: PMC5812307.

Questions? Ask Us at the MSK Library!