Long term outcomes of prostate cancer patients undergoing non-interventional management

• Analytics use case(s): Characterization
• Study type: Clinical Application
• Tags: cancer
• Study lead: Giorgio Gandaglia
• Study lead forums tag: please refer to keesvanbochove
• Study start date: 09-Mar-2021
• Study end date: -
• Protocol: -
• Publications: -
• Results explorer: -

The aim of this study is to assess the long-term outcomes of prostate cancer patients managed with non-curative intent therapies in different disease risk profiles. The impact of life expectancy and comorbidities on the risk of recurrence and disease-free and overall survival will be assessed.

This study is undertaken by the joint prostate cancer studyathon of the IMI PIONEER project, the IMI EHDEN project and the OHDSI community (see announcement).

How to run

1. Requirements for executing this package:

   • DatabaseConnector ( >= 3.0.0 )
   • SqlRender ( >= 1.6.8 )

2. The package needs to be installed into the R environment.

   • with the devtools package inside a R session it could be done with

        devtools::install_github("ohdsi-studies/PioneerWatchfulWaiting")

   • from the command line on linux machines it could be done with

         R CMD build PioneerWatchfulWaiting
         R CMD INSTALL PioneerWatchfulWaiting_0.0.1.tar.gz

3. Then, within an interactive R session, execute the adapted commands below. The commands below can also be found in extras/codeToRun.R

      library(PIONEER)
   
      connectionDetails <-  DatabaseConnector::createConnectionDetails(
        dbms = "",     ### Name of dialect (Type ?DatabaseConnector::createConnectionDetails to see how your dialect should be written)
        server = "",	  ### Server URL or IP
        user = "",	  ### Username
        password = "", ### Password
        port = 5439)
   
      cdmDatabaseSchema <- ""    ### Name of the schema where the CDM data are located
      targetDatabaseSchema <- "" ### Name of the schema where the results of the package will be saved
      cohortTable <- "pioneer"   ### Name of the table where the cohort data will be saved
      oracleTempSchema <- NULL   ### (Only for Oracle users)Name of temp schema
      outputFolder <- ""         ### Name of the folder the output will be saved (it should named after the database)
      days_offset <- 180         ### Days added to the index event start date
   
      con <- DatabaseConnector::connect(connectionDetails)
   
      PIONEER::execute(connection = con,
                      cdmDatabaseSchema = cdmDatabaseSchema,
                      targetDatabaseSchema = targetDatabaseSchema,
                      oracleTempSchema = oracleTempSchema,
                      cohortTable = cohortTable,
                      outputFolder = outputFolder,
                      createCohorts = T,
                      days_offset
      )