Author Archives: Marina

Cochrane Library Keyword Search

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Cochrane Library is a collection of databases produced by the Cochrane Collaboration, that include Cochrane Systematic Reviews, Cochrane CENTRAL Register of Controlled Trials, and more.

Although Cochrane Library offers a MeSH search functionality, many searchers use just keyword searching so that not to duplicate the effort if they’ve already searched with MeSH in Pubmed or with Emtree terms in Embase (these 2 databases are major sources of Cochrane CENTRAL content).

There are four main ways to search Cochrane Library using keywords. The main difference between these four types of keyword searches is what is going on behind the scenes and how much control is given to the user in creating their search.

Basic Search

Cochrane’s most basic search is the search bar found on their homepage. It defaults to searching title, abstract, and keyword – however it gives little ability to modify searches or create comprehensive search strategies.

This search should only be used for the most basic and general searches, and not for conducting any type of literature review search.

The basic search also offers users to browse pre-set topics. These topics will automatically execute search on that topic to find Cochrane Reviews and Review Protocols, but it will not include results found in Trials.

Once a search is conducted using the basic search bar, the results are immediately displayed but also, the search string will appear within the advanced search page and the options below will become available for searches going forward.

Search Tab

The Search tab can be found by clicking on Advanced Search on the Cochrane homepage, just under the basic search bar; this takes you to the advanced search tabs. The main Search tab allows for more control of how and what is searched.

First, it allows for multiple search lines (that can be combined with Boolean operators), so you can combine multiple terms/concepts together easily. By clicking on the + it adds a new search box and from there you can identify what Boolean operator (AND, OR, NOT) you wish to use to combine the terms.

The advanced search tab also allows users to search a specific field (as opposed to just title/abstract/keyword). It also has search limit ability, to focus results by publication date or content type.

The one limitation of the search tab is it has limits on the length of search string used, similarly to basic search. The solution is to select Send to Search Manager instead of clicking Run Search.

Search Using Word Variations

One benefit of using the Search Tab (as compared to using the more functionally complex Search Manager), is that searches conducted in this tab are searched with word variations (except for the truncated terms), based on a Cochrane algorithm. In these instances, the Cochrane Library provides a note after the search string: (Word variations have been searched).

For example, if you search on “artificial intelligence” the algorithm will also include the phrase “artificially intelligent” to your search strategy. If you want to include these word variations in a complex search in Search Manager you must use the Search tab and then send the executed search to Search Manager to be included in your larger search strategy.

Search Manager will then format that search by enclosing it in parentheses and adding the field codes that were selected in the search tab (ex. ti,ab,kw) followed by the note (Word variations have been searched).

NOTE: Since word variations are ONLY added when the search is initiated from the Search tab, results will differ if the same search strategy is run in the Search tab as opposed to Search Manager. See example below to understand how results can differ in different circumstances:

Start from Search Tab
1. Enter terms and run search:
          breast cancer AND hormone therapy

Results: 7,643 (split between Cochrane Reviews: 45 and Trials: 7,596)


2. Enter terms and send to search manager:
          breast cancer AND hormone therapy

What is returned:
     (breast cancer AND hormone therapy):ti,ab,kw
     (Word variations have been searched)

Results: 7,643

----------------------------------------------------------------------

Start from Search Manager
1. Enter terms and run from Search Manager:
     breast cancer AND hormone therapy

Results: 5,772

2. Enter terms and run from Search Manager:
     (breast cancer AND hormone therapy):ti,ab,kw

Results: 5,412

Search Manager

The Search Manager is located within the Advanced Search tabs. Search Manager allows users to create and save complex multi-line searches. It supports the use of MeSH terms, logical operators, field labels, nesting, and wildcards. It also allows for unlimited search lines, and results can be viewed by search line (helpful to determine where issues might be in a strategy).

The search manager also allows for combining search lines by using their number (e.g. #1 AND #2; #1 OR #2) instead of the full content of each line, which can save time and space. It also can make it easier to see where and how concepts are being combined when developing complex searches.

Searches conducted in the search tab can be sent to search manager, The search manager is necessary for conducting and saving complex searches, especially those for large literature reviews and systematic reviews. The search manager is the only type of search in Cochrane Library that allows capturing your search history – for that you need to click Print search history icon.

In order to save searches you have to be signed in your account from within your institutionally subscribed to Cochrane Library (Sign in is located in the right upper corner of the Search Manager Screen). Registering for an account allows you to set up email alerts based on your searches.

The Medical terms (MeSH) tab can also be used to search for relevant MeSH terms to add to your search, and then sent to the search manager.

PICO Search

The last advanced search tab is the PICO search which allows users to build a search according to the PICO framework (population, intervention, comparison, outcome). When using the PICO search as you type in search terms it will identify the specific “PICO vocabulary” that is relevant. This is necessary when using the PICO search as it will direct the terms to the specific PICO concept.

Other Search Functionalities in Cochrane

Boolean Operators

As in most online databases, Cochrane Library allows for users to search and combine terms using the Boolean Operators: AND, OR and NOT.

Exact Phrases

If you are searching for exact phrases, they should be enclosed in double quotations.

Proximity Operators

Cochrane Library allows for the use of Proximity operators, including: NEAR, NEAR/X and NEXT. Finds terms within close proximity to each other in the article or field(s) being searched.

NEAR
Finds the terms when they are within 6 words of each other. Terms can appear in either order.

cancer NEAR lung

Finds "lung cancer" and "cancer in the patient's lung"

NEAR/X
Finds the terms when they are within X words of each other where X = the maximum number of words between search terms. Terms can appear in either order.

cancer NEAR/3 lung

Finds "lung cancer" and "cancer of the lung", but NOT "cancer in the patient's lung"

NEXT
Finds the terms when they appear next to each other. Terms must appear in the order specified. Use the NEXT operator for phrase searching with wildcards.

cancer NEXT lung

Finds "lung cancer" but not "cancer of the lung" or "cancer in the patient's lung"

Truncation & Wildcards

Truncating a word means using a wildcard (*} which allows retrieving results with various ending of the word after truncation.

Do not use double quotes with truncation (*) anywhere in Cochrane Library searches, as truncation is ignored by Cochrane Library if used within double quotes. To overcome this, use the NEXT operator to search for an exact phrase with truncation.

Ex: instead of "heart transplant*" use (heart NEXT transplant*)

If you are interested in learning more about how to best use and search the Cochrane Library collection of databases, take a look at their e-books How to Search in Cochrane Library or Cochrane Library User Guide.

What are the Differences Between Google Scholar, OneSearch and Bibliographic Databases When Looking for Journal Articles?

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Bibliographic databases contain references to journal articles (as well as sometimes other formats such as book chapters, etc.) with metadata that may typically include a title, authors, publisher, publication date and place, pages, abstract, index terms, etc. Examples: PubMed, Embase, Web of Science, Scopus, and PsycINFO.

When you search bibliographic databases you are actually searching for metadata, so you can specify what “field” you want your search terms to be found in (eg. title, abstract, author, journal, etc.). Available full text is linked to references/bibliographic records but cannot be searched.

Advantages to Searching Bibliographic Databases

  • The ability to use database functionality to do the best quality search and retrieve the best results. Such functionality in biomedical databases includes advanced functionality such as subject heading (e.g. MeSH) mapping.
  • Searching only essential information (title, abstract, author supplied keywords, index terms/subject headings) when searching on a topic may be a safeguard against overwhelming a searcher with an abundance of results.

    Unlike in bibliographic databases, searching for journal articles via OneSearch (the library’s catalog found on our homepage) or Google Scholar involves searching the full text of journal articles.

    Searching OneSearch
  • OneSearch is a library catalog plus, available at many Libraries, including MSK Library, that allows finding journals and other serials, books, etc., and also databases, newspapers, dissertations, and other print and electronic media typically available in the library’s catalog.
  • It also is able to search the full-text content of e-journals and e-books (owned/subscribed to by the Library) such as journal articles and book chapters.
  • Advanced Search also allows keyword searching in the Title, Author or Subject fields alone, as well as searching in Any Field, which includes the full text of an article.
  • OneSearch relies on keywords and phrases (using quotations), but does not include any mapping or controlled vocabulary.


Searching Google Scholar

  • In Google Scholar you can find journal articles by searching within their full text.
  • Google Scholar includes multidisciplinary content (e.g. Medicine, Physics, Computer Science, Humanities)
  • The articles come from journals that Google Scholar has authority to search regardless of and well beyond any institutional subscription.
  • You have poor control of how you design and execute the search and view your search results (no proper search tools, no abundance of limits and sorting options typical to bibliographic databases).
  • As you are searching the whole “universe” of journals with Google Scholar search, you will find articles that your institution does and does not have access to. An older MSK Library blog post explains how to get access to the full text or request the full text.

Disadvantages of Searching OneSearch and Google Scholar

-The lack of advanced search functionality. While essential search functionality is available (better in OneSearch, worse in Google Scholar) it is still not as advanced as in major biomedical databases.

-Searching the full text in either OneSearch or Google Scholar may end up in the overwhelming number of search results because you are searching the full text of journal articles.

Takeaways and Recommendations

  • Using OneSearch or Google Scholar involves searching the full text of journal articles.
  • To find journal articles, use bibliographic databases as the first choice; use OneSearch and Google Scholar as complementary to using bibliographic journal literature databases.
  • Searching OneSearch and GoogleScholar are most effective when the content being searched is likely not found in the title or the abstract, and thus searching full-text is required.

Non-Smokers At Higher Risk of Resistance to Lung Cancer Treatment, Low Risk of Secondary Cancers in Patients on CAR-T Cell Therapy And More

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  • Researchers from University College London, the Francis Crick Institute, AstraZeneca, etc., identified the genetic basis of an increased risk of resistance to treatment of non-small cell lung cancer (NSCLC) in non-smokers. The study was published in Nature Communications.
  • The Institute for Bioengineering of Catalonia (IBEC) study showed that different physical properties of colorectal cancer cells had different potential for cancer metastasis. The study was published in Nature Communications.
  • Researchers from Stanford University found that, contrary to an earlier FDA warning, the risk of secondary cancers in patients on CAR-T cell therapy is low. The study was published in the New England Journal of Medicine.
  • A study found that statins (in particular, pitavastatin), a class of drugs used to lower cholesterol, may be instrumental in suppressing chronic inflammation, a finding that could help prevent inflammatory-related cancers, e.g., pancreatic cancer. The study was published in Nature Communications.
  • “Father of tamoxifen”, Pharmacologist V. Craig Jordan, a professor of Breast and Medical Oncology and Molecular and Cellular Oncology at The University of Texas MD Anderson Cancer Center who discovered selective estrogen receptor modulators and developed breakthrough breast cancer treatment died last week.
  • Note: Kendra contributed this entry. The National Institutes of Health is developing a fairly simple (in today’s terms) model to predict whether a given cancer patient will likely respond to immunotherapy. This is a far cry from a large foundational model, but there’s still value in training simpler classifiers. The current state for predicting patient responses to immunotherapy is that one or both biomarkers approved by the FDA will be measured for a particular patient to help oncologists select the drugs most likely to work. 
    The model in beta right now is described in Nature Cancer (lead author Tian-Gen Chang). The model “makes predictions based on five clinical features that are routinely collected from patients: a patient’s age, cancer type, history of systemic therapy, blood albumin level, and blood neutrophil-to-lymphocyte ratio, a marker of inflammation. The model also considers tumor mutational burden.” The model has shown decent predictive ability and is available here: https://loris.ccr.cancer.gov.