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Job request: 21455

Organisation:
The London School of Hygiene & Tropical Medicine
Workspace:
safety-sotrovimab-paxlovid-molnupiravir
ID:
vcua3bp2yudmabog
View repo View project.yaml

This page shows the technical details of what happened when authorised researcher Katie Bechman requested one or more actions to be run against real patient data in the project, within a secure environment.

By cross-referencing the indicated Requested Actions with the Pipeline section below, you can infer what security level various outputs were written to. Outputs marked as highly_sensitive can never be viewed directly by a researcher; they can only request that code runs against them. Outputs marked as moderately_sensitive can be viewed by an approved researcher by logging into a highly secure environment. Only outputs marked as moderately_sensitive can be requested for release to the public, via a controlled output review service.

Jobs

  • Action:
    cox_model
    Status:
    Status: Succeeded
    Job identifier:
    gfclvitoogvs4mna

Pipeline

Show project.yaml 
version: '3.0'

expectations:
  population_size: 50000

actions:

  generate_study_population_control:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_control
    outputs:
      highly_sensitive:
        cohort: output/input_control.csv
        
  generate_study_population_treatment:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_treatment
    outputs:
      highly_sensitive:
        cohort: output/input_treatment.csv
  
  generate_study_population_treatment_sensitivity:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_treatment_sensitivity
    outputs:
      highly_sensitive:
        cohort: output/input_treatment_sensitivity.csv
  
  data_properties:
    run: r:latest analysis/data_properties.R output/input_control.csv output/input_treatment.csv output/data_properties
    needs: [generate_study_population_control, generate_study_population_treatment]
    outputs:
      moderately_sensitive:
        cohort: output/data_properties/input*.txt
        
  define_covariates_combine:
    run: stata-mp:latest analysis/004_define_covariates_combine.do
    needs: [generate_study_population_control, generate_study_population_treatment, generate_study_population_treatment_sensitivity]
    outputs:
      highly_sensitive:
        log: logs/cleaning_dataset_combine.log 
        data: output/data/main.dta
        data1: output/data/sensitivity_analysis.dta

  baseline_characteristic:
    run: stata-mp:latest analysis/101_baseline_characteristics.do
    needs: [define_covariates_combine]
    outputs:
      moderately_sensitive:
        log: logs/baseline_characterisitcs.log 
        data: output/tables/baseline_allpts.csv  
        data1: output/tables/baseline_allpts_sensitivity.csv  

  cox_model:
    run: stata-mp:latest analysis/205_cox_model.do
    needs: [define_covariates_combine]
    outputs:
      moderately_sensitive:
        log: logs/cox_model.log 
        data: output/tables/cox_model_summary.csv 
        data1: output/tables/cox_model_disease.csv 
        data2: output/tables/cox_model_rates.csv 
        data3: output/tables/cox_model_rates_round.csv 
        data4: output/tables/cox_model_summary_sens_1.csv 
        data5: output/tables/cox_model_disease_sens_1.csv 
        data6: output/tables/cox_model_rates_sens_1.csv 
        data7: output/tables/cox_model_rates_round_sens_1.csv 
        data8: output/tables/cox_model_summary_sens_2.csv 
        data9: output/tables/cox_model_rates_sens_2.csv 
        data10: output/tables/cox_model_rates_round_sens_2.csv
        data11: output/tables/cox_model_summary_sens_3.csv 
        data12: output/tables/cox_model_summary_sens_4.csv 
        data13: output/tables/cox_model_rates_sens_4.csv 
        data14: output/tables/cox_model_rates_round_sens_4.csv 
        data15: output/tables/cox_model_summary_sens_5.csv 
        data16: output/tables/cox_model_summary_sens_6.csv 
        data17: output/tables/cox_model_rates_sens_6.csv 
        data18: output/tables/cox_model_rates_round_sens_6.csv
        schoenfeld_ae_all: output/figures/schoenfeld_ae_all.svg
        schoenfeld_ae_all_serious: output/figures/schoenfeld_ae_all_serious.svg
        schoenfeld_ae_spc_all: output/figures/schoenfeld_ae_spc_all.svg
        schoenfeld_ae_spc_serious: output/figures/schoenfeld_ae_spc_serious.svg
        schoenfeld_ae_drug_all: output/figures/schoenfeld_ae_drug_all.svg
        schoenfeld_ae_drug_serious: output/figures/schoenfeld_ae_drug_serious.svg
        schoenfeld_ae_imae_all: output/figures/schoenfeld_ae_imae_all.svg
        schoenfeld_ae_imae_serious: output/figures/schoenfeld_ae_imae_serious.svg
        loglog_plot_ae_all: output/figures/loglog_plot_ae_all.svg
        loglog_plot_ae_all_serious: output/figures/loglog_plot_ae_all_serious.svg
        loglog_plot_ae_spc_all: output/figures/loglog_plot_ae_spc_all.svg
        loglog_plot_ae_spc_serious: output/figures/loglog_plot_ae_spc_serious.svg
        loglog_plot_ae_drug_all: output/figures/loglog_plot_ae_drug_all.svg
        loglog_plot_ae_drug_serious: output/figures/loglog_plot_ae_drug_serious.svg
        loglog_plot_ae_imae_all: output/figures/loglog_plot_ae_imae_all.svg
        loglog_plot_ae_imae_serious: output/figures/loglog_plot_ae_imae_serious.svg

  PS_model:
    run: stata-mp:latest analysis/305_ps_model.do
    needs: [define_covariates_combine]
    outputs:
      moderately_sensitive:
        log: logs/ps_model.log
        data: output/tables/cox_propensity.csv 
        data1: output/tables/cox_propensity_disease.csv 
        histogram_agesex: output/figures/histogram_agesex.svg
        histogram_adj: output/figures/histogram_adj.svg
        histogram_adj2: output/figures/histogram_adj2.svg
        histogram_adj3: output/figures/histogram_adj3.svg
        histogram_adj4: output/figures/histogram_adj4.svg
        balance_agesex: output/figures/balance_agesex.svg
        balance_adj: output/figures/balance_adj.svg
        balance_adj2: output/figures/balance_adj2.svg
        balance_adj3: output/figures/balance_adj3.svg
        balance_adj4: output/figures/balance_adj4.svg
        
  preceed_rate:
    run: stata-mp:latest analysis/406_preceeding_rate.do
    needs: [define_covariates_combine]
    outputs:
      moderately_sensitive:
        log: logs/preceed_rate.log 
        data: output/tables/comparator_rates.csv 
        data1: output/tables/comparator_rates_round.csv 
  
  redacted_table:
    run: stata-mp:latest analysis/501_redacted_table.do
    needs: [define_covariates_combine]
    outputs:
      moderately_sensitive:
        log1: logs/redacted_table.log   
        data: output/tables/baseline_table_redact_bydrug.csv   
        data1: output/tables/baseline_table_redact_mean.csv
        data2: output/tables/baseline_table_redact_bydrug_sens.csv   
        data3: output/tables/baseline_table_redact_mean_sens.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 08:33:25

These timestamps are generated and stored using the UTC timezone on the TPP backend.

Job information

Status
Succeeded
Backend
TPP
Workspace
safety-sotrovimab-paxlovid-molnupiravir
Requested by
Katie Bechman
Branch
main
Force run dependencies
No
Git commit hash
b144e70
Requested actions
  • cox_model

Code comparison

Compare the code used in this Job Request