Is there a way to add filters such as article type ("only show meta-analysis/systematic reviews") to a PubMed / Entrez Esearch API search?
2
0
Entering edit mode
16 months ago
kolja.o37 • 0

Thanks for taking the time to read this. I would like to know if it is possible to filter results from the PubMed API by e.g. article type (only show meta analysis/clinical trial/etc) or use the additional filters such as species

My code:

import requests
import json
db = 'pubmed'
domain = 'https://eutils.ncbi.nlm.nih.gov/entrez/eutils'  
query = "cancer"
retmode='json'

queryLinkSearch = f'{domain}/esearch.fcgi?db={db}&retmode={retmode}&term={query}&sort=relevance'  
response = requests.get(queryLinkSearch)
pubmedJson = response.json()

print(pubmedJson)

It works and is giving me a list of IDs. What I would like to do is add a filter now, e.g. to only show meta-analyses.

I didn't see anything regarding filtering in the API docs. When I check the link of the website it adds the following filter:

https://pubmed.ncbi.nlm.nih.gov/?term=cancer**&filter=pubt.meta-analysis**

But when I try to add this filter to my query I get the error:

{'ERROR': 'Invalid filter key: pubt.meta-analysis'}}

Does somebody know if this is possible? Thank you!

pubmed-api pubmed entrez esearch python • 1.9k views
ADD COMMENT
2
Entering edit mode
16 months ago
LauferVA 4.5k

kolja.o37 , try the Entrez and Medline functionality in the Bio package in python3.

For instance, we could write:

from Bio import Entrez
from Bio import Medline
import pandas as pd

def filterPubmedArticles(keyword, start_year, end_year, pubtype):
    handle = Entrez.esearch(db='pubmed', term=f'("{keyword}"[Title/Abstract]) AND ("{start_year}"[Date - Publication] : "{end_year}"[Date - Publication]) AND "{pubtype}"[Publication Type]', retmax=1000)
    record = Entrez.read(handle)
    handle.close()

    id_list = record['IdList']
    if not id_list:
        print("No articles found - consider broadening query terms.")
        return
    else: 
        handle = Entrez.efetch(db='pubmed', id=id_list, rettype='medline', retmode='text')
        records = Medline.parse(handle)
        articles = []

# loop through records; grab desired fields (here just title & abstract)
        for record in records:
            title = record.get('TI', '')
            abstract = record.get('AB', '')
            articles.append({'Title': title, 'Abstract': abstract})

# now use pandas to write the resulting records to a DataFrame.
        df = pd.DataFrame(articles)
        df.to_excel('review_articles.xlsx', index=False)
        print(f"{len(articles)} review articles found. Output saved to 'review_articles.xlsx'.")

# Set values for the function inputs for demonstration purposes:
keyword = 'Pangenome'
start_year = '2021'
end_year = '2023'
pubtype = 'review'

filterPubmedArticles(keyword, start_year, end_year, pubtype)

If that doesn't work, consider putting meta-analysis in the keyword section, rather than article type, etc.

ADD COMMENT
1
Entering edit mode
16 months ago
GenoMax 147k

You can use Entrezdirect with following filter types. PubMed guide offers many ways of limiting searches.

$ esearch -db pubmed -query "cancer AND systematic review [PT]" 
<ENTREZ_DIRECT>
  <Db>pubmed</Db>
  <QueryKey>1</QueryKey>
  <Count>40601</Count>
  <Step>1</Step>
</ENTREZ_DIRECT>

You can get information about the articles by using

$ esearch -db pubmed -query "cancer AND systematic review [PT]" |esummary | xtract -pattern DocumentSummary -element Title,Value 
Prevalence and severity of anxiety and depression in Chinese patients with breast cancer: a systematic review and meta-analysis.    37448492    PMC10336240 pmc-id: PMC10336240;    10.3389/fpsyt.2023.1080413
Traditional herbal medicine for anorexia in patients with cancer: a systematic review and meta-analysis of randomized controlled trials.    37441530    PMC10333490 pmc-id: PMC10333490;    10.3389/fphar.2023.1203137

$ esearch -db pubmed -query "cancer AND meta-analysis [PT]"
<ENTREZ_DIRECT>
  <Db>pubmed</Db>
  <QueryKey>1</QueryKey>
  <Count>40282</Count>
  <Step>1</Step>
</ENTREZ_DIRECT>
ADD COMMENT

Login before adding your answer.

Traffic: 1663 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6