OpenVigil v1.2.7-CANADIAN-nightly-20150913

This is a preview version of OpenVigil. Maybe, some calculations and buttons will not work as expected!

This version operates on Canadian pharmacovigilance data - please use english (pardonnez-moi) MedDRA terms for adverse events and INN or USAN drugnames! Note that the user interface is not yet completely updated. Please ignore the FDA-specific terminology.




This web application permits you to access pharmacovigilance data and process a query on it, e.g. extracting individual safety reports (ISR) or counts or disproportionality analyses on selected cases. Visit openvigil.sf.net for the Legalese, info on cave-ats, tutorials and analysis examples as well as other tools for accessing, extracting, mining and analysing pharmacovigilance data like OpenVigil 2 (includes drugname mapping and advanced filtering options) or OpenVigilFDA (uses up-to-date cleaned data via the openFDA API.

Press to display more information about the database structure and content. Refer to this overview of this installation to obtain detailed information for citation of data extracted by this installation.
Registered tables are:
Interesting fields for novice users might be DRUG.DRUGNAME (=name given by the pharmacovigilance data source, e.g., USAN or INN, but other names are used (list), too) and REAC.PT (the adverse reaction coded as MedDRA Preferred Term (click here for a list).

For advanced users: a description of the content of tables and columns in these tables can be found in chapters B. FILE DESCRIPTIONS, C. DATA ELEMENT DESCRIPTIONS, D. DATA ELEMENT CONTENTS AND MAXIMUM LENGTHS of the FDA Asc_nts.doc database description document (created by the FDA and can also be found in the archive of the original FDA AERS quaterly data file packages). Note that DEMO.CASE is called DEMO.CASENO in OpenVigil 1. OpenVigil 1 uses a DMAP table (which is automatically generated when using cleaned pharmacovigilance data (e.g., German or Canadian data). When using U.S. american FDA AERS ASCII data, mapping (e.g., via RxNorm) is necessary. OpenVigil 2 and OpenVigilFDA provide automatic drugname mapping. Import failures from the original pharmacovigilance data source into this database can be found in the data import table from aers2sql for this instance of OpenVigil.
Pitfalls and shortcomings of pharmacovigilance data analyses are described in the OpenVigil Cave-At document.


Step 1: Chose how to construct your query. Which data do you have? E.g., drug or adverse event of interest, possibly focussed on a certain indication or subpopulation (gender, age). What do you want to know? E.g., single reports, counts of reports or disproportionality analyses of two conditions (e.g., drug x event). Create query...
Step 2: Construct a SQL query and enter it in the text box below. Here is an example that shows you the SQL syntax, database table and field adressing and how to link the tables by forcing the ISR numbers to be the same for U.S. american data (MySQL is explained in the MySQL manual):
SELECT D.* FROM DRUG AS D, REAC AS R WHERE D.ISR=R.ISR AND (R.PT="DIZZINESS" AND DRUGNAME="HALOPERIDOL");
select * from DEMO where ISR = any(select ISR from DRUG where Drugname = "DARVOCET") and ISR = any(select ISR from DRUG where Drugname = "CHAMPIX" OR Drugname = "CHANTIX" OR Drugname = "Varenicline") and ISR = any(select ISR from REAC where PT = "ABNORMAL DREAMS") and ( DSRC="DEMO08Q1" or DSRC="DEMO08Q2" or DSRC="DEMO08Q3" or DSRC="DEMO08Q4") ;
Type your SQL query to AERS here:



Please enter additionally the SQL user password for this installation:
Step 2: Select either a drugname or an adverse event for which an analysis of disproportionality shall be conducted!
Due to the uncleaned raw data this is depreciated. Consider using OpenVigil 2!

Drugname
Adverse event

Step 2: Enter a ISR number to get all records associated with this case!


Step 2: Provide at least one of the fields below to filter out the cases you are interested in. As result, you will get either a list of case numbers (ISR number) which you can click to get further information about every reported case or statistics on the frequency. Note that this search more is not very powerful; consider watching the tutorial and using the Wizard in professional mode or writing SQL queries yourself! Also note that you have to use the generic drug name and that both indication and adverse event are named according to the MedDRA terminology. OpenVigil will attempt to find the best match for the drugname and/or the adverse event that you have entered.

Drugname Matching: Use
Adverse event Matching: Use
Show results as as raw data (i.e., a list of each single individual safety report)
as statistics (likelihood that a drug is connected to an adverse event*)

*) i.e., if either drugname or adverse event is given, a sorted list of the number of occurences of each adverse event linked to drug or - vice versa - of each drug linked to an adverse event; if both drugname and adverse event are given, a proportional reporting rating for this drug and this putative adverse reaction.
Step 2: Select the filtering conditions! Which records shall be extracted? E.g., focus on a specific drugname (DRUG.DRUGNAME is equal HALOPERIDOL) or adverse reaction (REAC.PT is equal DIZZINESS).

concat.database fieldoperatorvalue


Step 3: Select whether the above filtered records shall be extracted as raw data or whether this data shall be postprocessed. If you want to analyse the data (a horizontalized table) yourself, select raw data, otherwise request a statistical analysis:

Step 4: Select which data fields shall be put into the horizontalized table. E.g., if you filtered for a certain drugname (DRUG.DRUGNAME is equal HALOPERIDOL) you might be interested which adverse reactions were reported (select REAC.PT), or vice versa.


This analysis module is currently very basic. Consider exporting your query results and using a real statistics program like Gnumeric/R.

Step 4a: You can select a data field from which categories/groups shall be made (a so called "factor"). Each group is counted and the number of records per group is presented. If you want this, select a data field here:



Step 4b: The numerical data in a data field can be descriptive-statistically analysed (average, standard deviation, minimum, maximum). If you want this, select a data field here:
If a factor is selected, each group will be analyzed.



Note: You can also use both factor and descriptive statistics simultanously.




Export results as human readable HTML or standard CSV or Microsoft Excel CSV?
Please note that no pictures (e.g., PRR/ChiSquare charts or pie charts) can be exported via CSV!
Basic mode: Counting mode

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Depending on query complexity and server load your query might take some seconds to several minutes to complete. There is no progress indicator, so please wait! Once the results are ready, the new window will show the results. You can start a new query in the meantime in this window.