Beta Blockers
David A Springate, Darren M Aschroft, Evangelos Kontopantelis, Tim Doran, Ronan Ryan, David Reeves
PH642 / 1284 Clinical-Coded Phenotype
Overview
Phenotype TypeDrugSexBothValid Event Date Range01/01/19997 - 31/12/2006Coding SystemGPRD product codesData SourcesDoctors Independent Network , CPRD GOLDCollectionsClinicalCodes RepositoryPhenotype LibraryTagsNo dataDefinition
Objectives:
To conduct a fully independent, external validation of a research study based on one electronic health record database using a different database sampling from the same population.
Design:
Retrospective cohort analysis of β-blocker therapy and all-cause mortality in patients with cancer.
Setting:
Two UK national primary care databases (PCDs): the Clinical Practice Research Datalink (CPRD) and Doctors’ Independent Network (DIN).
Participants:
CPRD data for 11 302 patients with cancer compared with published results from DIN for 3462 patients; study period January 1997 to December 2006.
Primary and secondary outcome measures:
All-cause mortality: overall; by treatment subgroup (β-blockers only, β-blockers plus other blood pressure lowering medicines (BPLM), other BPLMs only); and by cancer site.
Results:
Using CPRD, β-blocker use was not associated with mortality (HR=1.03, 95% CI 0.93 to 1.14, vs patients prescribed other BPLMs only), but DIN β-blocker users had significantly higher mortality (HR=1.18, 95% CI 1.04 to 1.33). However, these HRs were not statistically different (p=0.063), but did differ for patients on β-blockers alone (CPRD=0.94, 95% CI 0.82 to 1.07; DIN=1.37, 95% CI 1.16 to 1.61; p<0 .001). analyses, and be both but by cancer cancers. certain could databases.< defined differed for identically in individual mortality not only p pancreas prostate robust sensitivity significantly sites study, that under was we were>
Conclusions:
We found a complex pattern of similarities and differences between databases. Overall treatment effect estimates were not statistically different, adding to a growing body of evidence that different UK PCDs produce comparable effect estimates. However, individually the two studies lead to different conclusions regarding the safety of β-blockers and some subgroup effects differed significantly. Single studies using even internally wellvalidated databases do not guarantee generalisable results, especially for subgroups, and confirmatory studies using at least one other independent data source are strongly recommended.
Implementation
No dataImplementation
Clinical Code List
PUBLISHED - 403 Codes
Publication
David A Springate, Darrent M Aschroft, Evangelos Kontopantelis, Tim Doran, Ronan Ryan, David Reeves, Can analyses of electronic patient records be independently and externally validated? Study 2—the effect of β-adrenoceptor blocker therapy on cancer survival a retrospective cohort study. BMJ Open, 5(e007299), 2014.
No dataCitation Requirements
API
To Export Phenotype Details:
Format API JSON site_root/api/v1/phenotypes/PH642/version/1284/detail/?format=json R Package library(ConceptLibraryClient)
# Connect to API
client = ConceptLibraryClient::Connection$new(public=TRUE)
# Get details of phenotype
phenotype_details = client$phenotypes$get_detail(
'PH642',
version_id=1284
)Py Package from pyconceptlibraryclient import Client
# Connect to API
client = Client(public=True)
# Get codelist of phenotype
phenotype_codelist = client.phenotypes.get_detail(
'PH642',
version_id=1284
)To Export Phenotype Code List:
Format API JSON site_root/api/v1/phenotypes/PH642/version/1284/export/codes/?format=json CSV site_root/phenotypes/PH642/version/1284/export/codes/ R Package library(ConceptLibraryClient)
# Connect to API
client = ConceptLibraryClient::Connection$new(public=TRUE)
# Get codelist of phenotype
phenotype_codelist = client$phenotypes$get_codelist(
'PH642',
version_id=1284
)Py Package from pyconceptlibraryclient import Client
# Connect to API
client = Client(public=True)
# Get codelist of phenotype
phenotype_codelist = client.phenotypes.get_codelist(
'PH642',
version_id=1284
)Version History