Type: | Package |
Title: | FDA Adverse Event Reporting System Quarterly Data Extracting Tool |
Version: | 1.2.0 |
Maintainer: | Luis Garcez <luisgarcez1@gmail.com> |
Description: | An easy framework to read FDA Adverse Event Reporting System XML/ASCII files https://www.fda.gov/drugs/questions-and-answers-fdas-adverse-event-reporting-system-faers/fda-adverse-event-reporting-system-faers-latest-quarterly-data-files. |
License: | GPL (≥ 3) |
Imports: | data.table, tibble, xml2, tableone, tidyr, dplyr, stringr, stats, utils |
Encoding: | UTF-8 |
LazyData: | true |
Depends: | R (≥ 3.5.0) |
Suggests: | testthat (≥ 3.0.0) |
Config/testthat/edition: | 3 |
RoxygenNote: | 7.2.3 |
NeedsCompilation: | no |
Packaged: | 2024-06-22 21:57:36 UTC; jjferreira-admin |
Author: | Luis Garcez |
Repository: | CRAN |
Date/Publication: | 2024-06-22 22:10:02 UTC |
faersquarterlydata: FDA Adverse Event Reporting System Quarterly Data Extracting Tool
Description
An easy framework to read FDA Adverse Event Reporting System XML/ASCII files https://www.fda.gov/drugs/questions-and-answers-fdas-adverse-event-reporting-system-faers/fda-adverse-event-reporting-system-faers-latest-quarterly-data-files.
Author(s)
Maintainer: Luis Garcez luisgarcez1@gmail.com (ORCID) [copyright holder]
List ASCII data example
Description
A list containing data from FDA website. The list only contains safety reports which the ADR primary suspect drug was indicated for ALS. List originated from retrieve_faersascii
Usage
als_faers_data
Format
A data frame with 200 rows and 38 columns:
Source
<https://www.fda.gov/drugs/questions-and-answers-fdas-adverse-event-reporting-system-faers/fda-adverse-event-reporting-system-faers-latest-quarterly-data-files>
Tabular ASCII data example
Description
A subset of data from FAERS data. One row corresponds to one adverse drug reaction. All the ADR in this subset have a primary suspect drug indicated for ALS. Data frame originated from unify_tabular_ascii
Usage
als_faers_data_unified
Format
A data frame with 1635 rows and 40 columns.
Convert a date string into a date format
Description
Convert a date string into a date format
Usage
arrange_date(date_string)
Arguments
date_string |
A string vector with multiple formats (8, 6 or 4 digits) |
Value
A converted Date
Examples
arrange_date("2020")
arrange_date("202006")
arrange_date("20200601")
Estimate Chi-Squared test with yates correction
Description
Estimate Chi-Squared test with yates correction
Usage
estimate_chisq(n11, n10, n01, n00)
Arguments
n11 |
Number of events of interest within the group of interest |
n10 |
Number of events of interest from all groups |
n01 |
Number of all events within the group of interest |
n00 |
Number of all events from all groups |
Value
list with Chi-squared statistic and p-value
Examples
estimate_chisq(n11 = 20, n10 = 10, n01 = 200, n00 = 200)
Estimate Information Component
Description
Estimate Information Component
Usage
estimate_infoc(n11, n10, n01, n00)
Arguments
n11 |
Number of events of interest within the group of interest |
n10 |
Number of events of interest from all groups |
n01 |
Number of all events within the group of interest |
n00 |
Number of all events from all groups |
Value
List with Information Component estimate and its 0.95 IC
Examples
estimate_infoc(n11 = 20, n10 = 10, n01 = 200, n00 = 200)
Estimate Proportional Reporting Odds Ratio
Description
Estimate Proportional Reporting Odds Ratio
Usage
estimate_prr(n11, n10, n01, n00, ic_range = 0.95)
Arguments
n11 |
Number of events of interest within the group of interest |
n10 |
Number of events of interest from all groups |
n01 |
Number of all events within the group of interest |
n00 |
Number of all events from all groups |
ic_range |
Confidence Interval range |
Value
Proportional Reporting Odds Ratio
Examples
estimate_prr(n11 = 20, n10 = 10, n01 = 200, n00 = 200)
Estimate Reporting Odds Ratio
Description
Estimate Reporting Odds Ratio
Usage
estimate_ror(n11, n10, n01, n00, ic_range = 0.95)
Arguments
n11 |
Number of events of interest within the group of interest |
n10 |
Number of events of interest from all groups |
n01 |
Number of all events within the group of interest |
n00 |
Number of all events from all groups |
ic_range |
Confidence Interval range |
Value
list with ROR estimate and a vector with the IC boundaries
Examples
estimate_ror(n11 = 20, n10 = 10, n01 = 200, n00 = 200, ic_range = 0.90)
Estimate Measures of Association
Description
Estimate Measures of Association
Usage
estimate_ror_bygroup(
tabular_faers_data,
group_of_interest_col = NULL,
group_of_interest_ref = NULL,
rename_vector = NULL,
event_of_interest_col = NULL,
...
)
Arguments
tabular_faers_data |
FAERS tabular format. Output of function retrieve_faersxml or retrieve_faersxml_all |
group_of_interest_col |
a string, specifying the group of interest. Must me a column name of 'tabular_faers_data', and this columns should only contain two unique values. |
group_of_interest_ref |
a string, specifying the group of interest reference. Must me a value from the group of interest column. |
rename_vector |
optional. named vector to rename the group of interest, in order to show up in a |
event_of_interest_col |
a string, specifying the event of interest. Must me a column name of 'tabular_faers_data'. |
... |
arguments passed to 'estimate_ror' like 'ic_range'. |
Value
tibble with the event of interest counts, group of interest counts and the respective estimated measures of association (ROR and its IC, PRR and its IC, Information Component and Chi-squared statisti with Yates correction.
Examples
estimate_ror_bygroup(tabular_faers_data = dplyr::filter(als_faers_data_unified,
sex %in% c("M", "F") ),
group_of_interest_col = "sex",
group_of_interest_ref = "M",
event_of_interest_col = "pt")
Convert FAERS xml to an R list
Description
Convert FAERS xml to an R list
Usage
faersxml_to_r(xml_address)
Arguments
xml_address |
XML address file |
Value
a list containing all the elements from 'xml_address'
Get duplicated caseIDs
Description
Retrieve the duplicated caseIDs to remove from the analysis.
Usage
get_duplicate_caseids(duplicates_dir = NULL)
Arguments
duplicates_dir |
directory path where the text files with the duplicates information are. |
Value
an integer vector with all the caseids to be removed
List of approved products by FDA
Description
List of approved products by FDA
Usage
products_fda
Format
A data frame.
Source
<https://www.fda.gov/drugs/drug-approvals-and-databases/drugsfda-data-files>
Read FAERS ascii files
Description
Read ASCII files from a directory, removing the duplicates.
Usage
retrieve_faersascii(
ascii_dir,
cache_path = NULL,
drug_indication_pattern = NULL,
drug_pattern = NULL,
primary_suspect = TRUE,
...
)
Arguments
ascii_dir |
directory path where ascii files are |
cache_path |
(optional) a string. Must have a ".Rdata" extension to save the read tabular formats in each loop. |
drug_indication_pattern |
(optional) a string.filter ADRs with a specific drug indication pattern (**stringr** sintax) |
drug_pattern |
(optional) a string. filter ADRs with a specific drug name pattern (**stringr** sintax) |
primary_suspect |
(optional) a string. |
... |
directory with duplicate information to be passed to get_duplicate_caseids |
Value
A list with binded tibbles retrieved from files.
Convert FAERS xml to tabular format
Description
Convert FAERS xml to tabular format
Usage
retrieve_faersxml(
xml_address,
reaction_wise = TRUE,
drug_wise = FALSE,
drug_indication_pattern = NULL
)
Arguments
xml_address |
XML address to be read |
reaction_wise |
each row corresponds to a reaction (if TRUE, drug_wise cannot be TRUE) |
drug_wise |
each row corresponds to a drug (if TRUE, reaction_wise cannot be TRUE) |
drug_indication_pattern |
filter by ADR with a specific drug indication pattern (**stringr** sintax) |
Value
A tibble corresponding to the XML file
Convert FAERS a number of xml files to tabular format
Description
Convert FAERS a number of xml files to tabular format
Usage
retrieve_faersxml_all(xml_address_vector, ..., cache_path = NULL)
Arguments
xml_address_vector |
Vector with XML addresses to be read |
... |
arguments to be passed to retrieve_faersxml |
cache_path |
a string. Must have a ".Rdata" extension to save the read tabular formats in each loop. |
Value
A binded tibble with all the tibbles returned from 'retrieve_faersxml'
Retrieve unique drug and ADR information values from XML files
Description
Retrieve unique drug and ADR information values from XML files
Usage
retrieve_unique_info(xml_address_vector, ...)
Arguments
xml_address_vector |
Vector with XML addresses to be read |
... |
arguments to be passed to retrieve_faersxml |
Value
A list with all the unique information on FAERS variables
FAERS description
Description
FAERS description
Usage
summary_faersdata(tabular_faers_data)
Arguments
tabular_faers_data |
a tibble corresponding to the unified FAERS tabular format. Output of function unify_tabular_ascii |
Value
A list with a findings summary
Examples
summary_faersdata(als_faers_data_unified)
Unify the list to a tabular format
Description
Turn the list elements returned from retrieve_faersascii into a tabular format
Usage
unify_tabular_ascii(ascii_list)
Arguments
ascii_list |
list from retrieve_faersascii |
Value
A data frame representing FAERS data, with all components from the list joined.
Examples
unify_tabular_ascii(ascii_list = als_faers_data)
Unzip FAERS zip folders
Description
Unzip FAERS zip folders
Usage
unzip_faerszip(zip_folders_dir, ex_dir)
Arguments
zip_folders_dir |
directory containing FAERS zip folders |
ex_dir |
directory to be exported the unzipped files |
Value
None. Just unzips the folders to a specified location.