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004_define_covariates_combine.do
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004_define_covariates_combine.do
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********************************************************************************
*
* Do-file: define covariates.do
* Project: Sotrovimab-Paxlovid-Molnupiravir
* Date: 15/2/23
* Programmed by: Katie Bechman
* Description: data management, reformat variables, categorise variables, label variables
* Data used: data in memory (from output/input.csv)
* Data created: analysis main.dta (main analysis dataset)
* Other output: logfiles, printed to folder $Logdir
* User installed ado: (place .ado file(s) in analysis folder)
****************************************************************************************************************
**Set filepaths
// global projectdir "C:\Users\k1635179\OneDrive - King's College London\Katie\OpenSafely\Safety mAB and antivirals\Safety-Sotrovimab-Paxlovid-Molnupiravir"
global projectdir `c(pwd)'
di "$projectdir"
capture mkdir "$projectdir/output/data"
capture mkdir "$projectdir/output/figures"
capture mkdir "$projectdir/output/tables"
global logdir "$projectdir/logs"
di "$logdir"
* Open a log file
cap log close
log using "$logdir/cleaning_dataset_combine.log", replace
*Set Ado file path
adopath + "$projectdir/analysis/ado"
***********************************************************************************************************************
** MAIN ANALYSIS **
***********************************************************************************************************************
* Import control dataset
import delimited "$projectdir/output/input_control.csv", clear
gen control_dataset=1
drop variant_recorded
drop sgtf
* Convert control strings to dates *
foreach var of varlist pre_covid_hosp_date ///
pre_covid_hosp_discharge ///
covid_test_positive_date ///
covid_test_positive_date2 ///
covid_test_positive_date3 ///
prior_covid_date ///
sotrovimab ///
molnupiravir ///
paxlovid ///
remdesivir ///
casirivimab ///
sotrovimab_not_start ///
molnupiravir_not_start ///
paxlovid_not_start ///
date_treated ///
start_date ///
drugs_paxlovid_interaction ///
drugs_nirmatrelvir_interaction ///
drugs_paxlovid_contraindication ///
last_vaccination_date ///
death_date ///
dereg_date ///
bmi_date_measured ///
creatinine_ctv3_date ///
creatinine_snomed_date ///
creatinine_short_snomed_date ///
ae_diverticulitis_icd ///
ae_diverticulitis_icd_prim ///
ae_diverticulitis_snomed ///
ae_diverticulitis_ae ///
ae_diarrhoea_snomed ///
ae_diarrhoea_icd ///
ae_diarrhoea_icd_prim ///
ae_diarrhoeal_icd ///
ae_diarrhoeal_icd_prim ///
ae_taste_snomed ///
ae_taste_icd ///
ae_taste_icd_prim ///
ae_rash_snomed ///
ae_rash_ae ///
ae_rash_icd ///
ae_rash_icd_prim ///
ae_bronchospasm_snomed ///
ae_contactderm_snomed ///
ae_contactderm_icd ///
ae_contactderm_icd_prim ///
ae_contactderm_ae ///
ae_dizziness_snomed ///
ae_dizziness_icd ///
ae_dizziness_icd_prim ///
ae_dizziness_ae ///
ae_nausea_vomit_snomed ///
ae_nausea_vomit_icd ///
ae_nausea_vomit_icd_prim ///
ae_headache_snomed ///
ae_headache_icd ///
ae_headache_icd_prim ///
ae_headache_ae ///
ae_anaphylaxis_icd ///
ae_anaphylaxis_icd_prim ///
ae_anaphylaxis_snomed ///
ae_anaphlaxis_ae ///
ae_severedrug_icd ///
ae_severedrug_icd_prim ///
ae_severedrug_sjs_icd ///
ae_severedrug_sjs_icd_prim ///
ae_severedrug_snomed ///
ae_severedrug_ae ///
ae_nonsevere_drug_snomed ///
ae_nonsevere_drug_ae ///
ae_rheumatoid_arthritis_icd ///
ae_rheumatoid_arthritis_icd_prim ///
ae_rheumatoid_arthritis_snomed ///
ae_rheumatoid_arthritis_ae ///
ae_sle_icd ///
ae_sle_icd_prim ///
ae_sle_ae ///
ae_sle_ctv ///
ae_psoriasis_icd ///
ae_psoriasis_icd_prim ///
ae_psoriasis_ae ///
ae_psoriasis_snomed ///
ae_psa_icd ///
ae_psa_icd_prim ///
ae_psa_snomed ///
ae_psa_ae ///
ae_psa_snomed ///
ae_axspa_icd ///
ae_axspa_icd_prim ///
ae_axspa_ctv ///
ae_axspa_ae ///
ae_ibd_icd ///
ae_ibd_icd_prim ///
ae_ibd_ctv ///
ae_ibd_ae ///
pre_diverticulitis_icd ///
pre_diverticulitis_icd_prim ///
pre_diverticulitis_snomed ///
pre_diverticulitis_ae ///
pre_diarrhoea_snomed ///
pre_diarrhoea_icd ///
pre_diarrhoea_icd_prim ///
pre_diarrhoeal_icd ///
pre_diarrhoeal_icd_prim ///
pre_taste_icd ///
pre_taste_icd_prim ///
pre_taste_snomed ///
pre_rash_snomed ///
pre_rash_ae ///
pre_rash_icd ///
pre_rash_icd_prim ///
pre_bronchospasm_snomed ///
pre_contactderm_snomed ///
pre_contactderm_icd ///
pre_contactderm_icd_prim ///
pre_contactderm_ae ///
pre_dizziness_snomed ///
pre_dizziness_icd ///
pre_dizziness_icd_prim ///
pre_dizziness_ae ///
pre_nausea_vomit_snomed ///
pre_nausea_vomit_icd ///
pre_nausea_vomit_icd_prim ///
pre_headache_snomed ///
pre_headache_icd ///
pre_headache_icd_prim ///
pre_headache_ae ///
pre_anaphylaxis_icd_prim ///
pre_anaphylaxis_icd ///
pre_anaphylaxis_snomed ///
pre_anaphlaxis_ae ///
pre_severedrug_icd ///
pre_severedrug_icd_prim ///
pre_severedrug_sjs_icd ///
pre_severedrug_sjs_icd_prim ///
pre_severedrug_snomed ///
pre_severedrug_ae ///
pre_nonsevere_drug_snomed ///
pre_nonsevere_drug_ae ///
pre_rheumatoid_icd_prim ///
pre_sle_icd_prim ///
pre_sle_ctv ///
pre_sle_icd ///
pre_sle_ae ///
pre_rheumatoid_arthritis_icd ///
pre_rheumatoid_icd_prim ///
pre_rheumatoid_arthritis_ae ///
pre_rheumatoid_arthritis_snomed ///
pre_psoriasis_icd ///
pre_psoriasis_icd_prim ///
pre_psoriasis_snomed ///
pre_psoriasis_ae ///
pre_psa_icd ///
pre_psa_icd_prim ///
pre_psa_ae ///
pre_psa_snomed ///
pre_axspa_icd ///
pre_axspa_icd_prim ///
pre_axspa_ctv ///
pre_axspa_ae ///
pre_ibd_ae ///
pre_ibd_ctv ///
pre_ibd_icd ///
pre_ibd_icd_prim ///
covid_hosp_discharge ///
any_covid_hosp_discharge ///
preg_36wks_date ///
{
capture confirm string variable `var'
if _rc==0 {
rename `var' a
gen `var' = date(a, "YMD")
drop a
format %td `var'
}
}
tab control_dataset
save "$projectdir/output/data/control.dta", replace
* import treatment dataset
import delimited "$projectdir/output/input_treatment.csv", clear
gen treatment_dataset=1
drop variant_recorded
drop sgtf
* Convert control strings to dates *
foreach var of varlist pre_covid_hosp_date ///
pre_covid_hosp_discharge ///
covid_test_positive_date ///
covid_test_positive_date2 ///
covid_test_positive_date3 ///
prior_covid_date ///
sotrovimab ///
molnupiravir ///
paxlovid ///
remdesivir ///
casirivimab ///
sotrovimab_not_start ///
molnupiravir_not_start ///
paxlovid_not_start ///
date_treated ///
start_date ///
drugs_paxlovid_interaction ///
drugs_nirmatrelvir_interaction ///
drugs_paxlovid_contraindication ///
last_vaccination_date ///
death_date ///
dereg_date ///
bmi_date_measured ///
creatinine_ctv3_date ///
creatinine_snomed_date ///
creatinine_short_snomed_date ///
ae_diverticulitis_icd ///
ae_diverticulitis_icd_prim ///
ae_diverticulitis_snomed ///
ae_diverticulitis_ae ///
ae_diarrhoea_snomed ///
ae_diarrhoea_icd ///
ae_diarrhoea_icd_prim ///
ae_diarrhoeal_icd ///
ae_diarrhoeal_icd_prim ///
ae_taste_snomed ///
ae_taste_icd ///
ae_taste_icd_prim ///
ae_rash_snomed ///
ae_rash_ae ///
ae_rash_icd ///
ae_rash_icd_prim ///
ae_bronchospasm_snomed ///
ae_contactderm_snomed ///
ae_contactderm_icd ///
ae_contactderm_icd_prim ///
ae_contactderm_ae ///
ae_dizziness_snomed ///
ae_dizziness_icd ///
ae_dizziness_icd_prim ///
ae_dizziness_ae ///
ae_nausea_vomit_snomed ///
ae_nausea_vomit_icd ///
ae_nausea_vomit_icd_prim ///
ae_headache_snomed ///
ae_headache_icd ///
ae_headache_icd_prim ///
ae_headache_ae ///
ae_anaphylaxis_icd ///
ae_anaphylaxis_icd_prim ///
ae_anaphylaxis_snomed ///
ae_anaphlaxis_ae ///
ae_severedrug_icd ///
ae_severedrug_icd_prim ///
ae_severedrug_sjs_icd ///
ae_severedrug_sjs_icd_prim ///
ae_severedrug_snomed ///
ae_severedrug_ae ///
ae_nonsevere_drug_snomed ///
ae_nonsevere_drug_ae ///
ae_rheumatoid_arthritis_icd ///
ae_rheumatoid_arthritis_icd_prim ///
ae_rheumatoid_arthritis_snomed ///
ae_rheumatoid_arthritis_ae ///
ae_sle_icd ///
ae_sle_icd_prim ///
ae_sle_ae ///
ae_sle_ctv ///
ae_psoriasis_icd ///
ae_psoriasis_icd_prim ///
ae_psoriasis_ae ///
ae_psoriasis_snomed ///
ae_psa_icd ///
ae_psa_icd_prim ///
ae_psa_snomed ///
ae_psa_ae ///
ae_psa_snomed ///
ae_axspa_icd ///
ae_axspa_icd_prim ///
ae_axspa_ctv ///
ae_axspa_ae ///
ae_ibd_icd ///
ae_ibd_icd_prim ///
ae_ibd_ctv ///
ae_ibd_ae ///
pre_diverticulitis_icd ///
pre_diverticulitis_icd_prim ///
pre_diverticulitis_snomed ///
pre_diverticulitis_ae ///
pre_diarrhoea_snomed ///
pre_diarrhoea_icd ///
pre_diarrhoea_icd_prim ///
pre_diarrhoeal_icd ///
pre_diarrhoeal_icd_prim ///
pre_taste_icd ///
pre_taste_icd_prim ///
pre_taste_snomed ///
pre_rash_snomed ///
pre_rash_ae ///
pre_rash_icd ///
pre_rash_icd_prim ///
pre_bronchospasm_snomed ///
pre_contactderm_snomed ///
pre_contactderm_icd ///
pre_contactderm_icd_prim ///
pre_contactderm_ae ///
pre_dizziness_snomed ///
pre_dizziness_icd ///
pre_dizziness_icd_prim ///
pre_dizziness_ae ///
pre_nausea_vomit_snomed ///
pre_nausea_vomit_icd ///
pre_nausea_vomit_icd_prim ///
pre_headache_snomed ///
pre_headache_icd ///
pre_headache_icd_prim ///
pre_headache_ae ///
pre_anaphylaxis_icd_prim ///
pre_anaphylaxis_icd ///
pre_anaphylaxis_snomed ///
pre_anaphlaxis_ae ///
pre_severedrug_icd ///
pre_severedrug_icd_prim ///
pre_severedrug_sjs_icd ///
pre_severedrug_sjs_icd_prim ///
pre_severedrug_snomed ///
pre_severedrug_ae ///
pre_nonsevere_drug_snomed ///
pre_nonsevere_drug_ae ///
pre_rheumatoid_icd_prim ///
pre_sle_icd_prim ///
pre_sle_ctv ///
pre_sle_icd ///
pre_sle_ae ///
pre_rheumatoid_arthritis_icd ///
pre_rheumatoid_icd_prim ///
pre_rheumatoid_arthritis_ae ///
pre_rheumatoid_arthritis_snomed ///
pre_psoriasis_icd ///
pre_psoriasis_icd_prim ///
pre_psoriasis_snomed ///
pre_psoriasis_ae ///
pre_psa_icd ///
pre_psa_icd_prim ///
pre_psa_ae ///
pre_psa_snomed ///
pre_axspa_icd ///
pre_axspa_icd_prim ///
pre_axspa_ctv ///
pre_axspa_ae ///
pre_ibd_ae ///
pre_ibd_ctv ///
pre_ibd_icd ///
pre_ibd_icd_prim ///
covid_hosp_discharge ///
any_covid_hosp_discharge ///
preg_36wks_date ///
{
capture confirm string variable `var'
if _rc==0 {
rename `var' a
gen `var' = date(a, "YMD")
drop a
format %td `var'
}
}
tab treatment_dataset
*****************************************************************
* APPEND DATASETS *
*****************************************************************
append using "$projectdir/output/data/control.dta"
duplicates tag patient_id, gen(duplicate_patient_id)
bys patient_id (treatment_dataset duplicate_patient_id): gen n=_n
tab n // should be no one in both datasets
drop if n>1 // drops duplicate patient id and in control group
tab control_dataset,m
tab treatment_dataset,m
count if start_date==.
count if start_date!=covid_test_positive_date & treatment_dataset==1
count if start_date!=covid_test_positive_date & control_dataset==1
gen dataset = 0 if control_dataset==1
replace dataset= 1 if treatment_dataset==1
label define dataset 0 "control" 1 "drug"
label values dataset dataset
*******************************************************************
* START AND END DATES *
*******************************************************************
gen campaign_start=mdy(12,16,2021)
gen study_end_date=mdy(06,26,2023)
gen start_date_29 = start_date + 29
gen study_end_date_29 = study_end_date + 29
format campaign_start study_end_date start_date_29 %td
****************************
* OUTCOME *
****************************
*** AESI, IMAE and some Drug reaction
gen new_ae_ra_icd = ae_rheumatoid_arthritis_icd if rheumatoid_arthritis_nhsd_snomed==0
gen new_ae_ra_icd_prim = ae_rheumatoid_arthritis_icd_prim if rheumatoid_arthritis_nhsd_snomed==0
gen new_ae_ra_snomed = ae_rheumatoid_arthritis_snomed if rheumatoid_arthritis_nhsd_snomed==0
gen new_ae_ra_ae = ae_rheumatoid_arthritis_ae if rheumatoid_arthritis_nhsd_snomed==0
count if rheumatoid_arthritis_nhsd_snomed!=0
count if ae_rheumatoid_arthritis_icd!=.
count if new_ae_ra_icd!=.
count if ae_rheumatoid_arthritis_icd_prim!=.
count if new_ae_ra_icd_prim!=.
count if ae_rheumatoid_arthritis_snomed!=.
count if new_ae_ra_snomed!=.
count if ae_rheumatoid_arthritis_ae!=.
count if new_ae_ra_ae!=.
gen new_ae_sle_icd = ae_sle_icd if sle_nhsd_ctv==0
gen new_ae_sle_icd_prim = ae_sle_icd_prim if sle_nhsd_ctv==0
gen new_ae_sle_ctv = ae_sle_ctv if sle_nhsd_ctv==0
gen new_ae_sle_ae = ae_sle_ae if sle_nhsd_ctv==0
count if sle_nhsd_ctv!=0
count if ae_sle_icd!=.
count if new_ae_sle_icd!=.
count if ae_sle_icd_prim!=.
count if new_ae_sle_icd_prim!=.
count if ae_sle_ctv!=.
count if new_ae_sle_ctv!=.
count if ae_sle_ae!=.
count if new_ae_sle_ae!=.
gen new_ae_psoriasis_icd = ae_psoriasis_icd if psoriasis_nhsd==0
gen new_ae_psoriasis_icd_prim = ae_psoriasis_icd_prim if psoriasis_nhsd==0
gen new_ae_psoriasis_snomed = ae_psoriasis_snomed if psoriasis_nhsd==0
gen new_ae_psoriasis_ae = ae_psoriasis_ae if psoriasis_nhsd==0
count if psoriasis_nhsd!=0
count if ae_psoriasis_icd!=.
count if new_ae_psoriasis_icd!=.
count if ae_psoriasis_icd_prim!=.
count if new_ae_psoriasis_icd_prim!=.
count if ae_psoriasis_snomed!=.
count if new_ae_psoriasis_snomed!=.
count if ae_psoriasis_ae!=.
count if new_ae_psoriasis_ae!=.
gen new_ae_psa_icd = ae_psa_icd if psoriatic_arthritis_nhsd==0
gen new_ae_psa_icd_prim = ae_psa_icd_prim if psoriatic_arthritis_nhsd==0
gen new_ae_psa_snomed = ae_psa_snomed if psoriatic_arthritis_nhsd==0
gen new_ae_psa_ae = ae_psa_ae if psoriatic_arthritis_nhsd==0
count if psoriatic_arthritis_nhsd!=0
count if ae_psa_icd!=.
count if new_ae_psa_icd!=.
count if ae_psa_icd_prim!=.
count if new_ae_psa_icd_prim!=.
count if ae_psa_snomed!=.
count if new_ae_psa_snomed!=.
count if ae_psa_ae!=.
count if new_ae_psa_ae!=.
gen new_ae_axspa_icd = ae_axspa_icd if ankylosing_spondylitis_nhsd==0
gen new_ae_axspa_icd_prim = ae_axspa_icd_prim if ankylosing_spondylitis_nhsd==0
gen new_ae_axspa_ctv = ae_axspa_ctv if ankylosing_spondylitis_nhsd==0
gen new_ae_axspa_ae = ae_axspa_ae if ankylosing_spondylitis_nhsd==0
count if ankylosing_spondylitis_nhsd!=0
count if ae_axspa_icd!=.
count if new_ae_axspa_icd!=.
count if ae_axspa_icd_prim!=.
count if new_ae_axspa_icd_prim!=.
count if ae_axspa_ctv!=.
count if new_ae_axspa_ctv!=.
count if ae_axspa_ae!=.
count if new_ae_axspa_ae!=.
gen new_ae_ibd_icd = ae_ibd_icd if ibd_ctv==0
gen new_ae_ibd_icd_prim = ae_ibd_icd_prim if ibd_ctv==0
gen new_ae_ibd_ctv = ae_ibd_ctv if ibd_ctv==0
gen new_ae_ibd_ae = ae_ibd_ae if ibd_ctv==0
count if ibd_ctv!=0
count if ae_ibd_icd!=.
count if new_ae_ibd_icd!=.
count if ae_ibd_icd_prim!=.
count if new_ae_ibd_icd_prim!=.
count if ae_ibd_ctv!=.
count if new_ae_ibd_ctv!=.
count if ae_ibd_ae!=.
count if new_ae_ibd_ae!=.
*** comparison of ICD admission primary diagnosis and all diagnoses
count if ae_diverticulitis_icd!=.
count if ae_diverticulitis_icd_prim!=.
count if ae_taste_icd!=.
count if ae_taste_icd_prim!=.
count if ae_rash_icd!=.
count if ae_rash_icd_prim!=.
count if ae_diarrhoea_icd!=.
count if ae_diarrhoea_icd_prim!=.
count if ae_diarrhoeal_icd!=.
count if ae_diarrhoeal_icd_prim!=.
count if ae_contactderm_icd!=.
count if ae_contactderm_icd_prim!=.
count if ae_dizziness_icd!=.
count if ae_dizziness_icd_prim!=.
count if ae_nausea_vomit_icd!=.
count if ae_nausea_vomit_icd_prim!=.
count if ae_headache_icd!=.
count if ae_headache_icd_prim!=.
count if ae_anaphylaxis_icd!=.
count if ae_anaphylaxis_icd_prim!=.
count if ae_severedrug_icd!=.
count if ae_severedrug_icd_prim!=.
count if ae_severedrug_sjs_icd!=.
count if ae_severedrug_sjs_icd_prim!=.
*** combined all AEs from GP, hosp and A&E
egen ae_diverticulitis = rmin(ae_diverticulitis_snomed ae_diverticulitis_ae ae_diverticulitis_icd_prim)
egen ae_diarrhoea = rmin(ae_diarrhoea_snomed ae_diarrhoea_icd_prim ae_diarrhoeal_icd_prim)
egen ae_taste = rmin(ae_taste_snomed ae_taste_icd_prim)
egen ae_rash = rmin(ae_rash_snomed ae_rash_ae ae_rash_icd_prim)
egen ae_bronchospasm = rmin(ae_bronchospasm_snomed)
egen ae_contactderm = rmin(ae_contactderm_snomed ae_contactderm_icd_prim ae_contactderm_ae)
egen ae_dizziness = rmin(ae_dizziness_snomed ae_dizziness_ae ae_dizziness_icd_prim)
egen ae_nausea_vomit = rmin(ae_nausea_vomit_snomed ae_nausea_vomit_icd_prim)
egen ae_headache = rmin(ae_headache_snomed ae_headache_ae ae_headache_icd_prim)
egen ae_anaphylaxis = rmin(ae_anaphylaxis_snomed ae_anaphlaxis_ae ae_anaphylaxis_icd_prim)
egen ae_drugreaction = rmin(ae_severedrug_icd_prim ae_severedrug_sjs_icd_prim ae_severedrug_snomed ae_severedrug_ae ae_nonsevere_drug_snomed ae_nonsevere_drug_ae)
egen ae_ra = rmin(new_ae_ra_snomed new_ae_ra_icd_prim new_ae_ra_ae)
egen ae_sle = rmin(new_ae_sle_ctv new_ae_sle_icd_prim new_ae_sle_ae)
egen ae_psorasis = rmin(new_ae_psoriasis_icd_prim new_ae_psoriasis_snomed new_ae_psoriasis_ae)
egen ae_psa = rmin(new_ae_psa_icd_prim new_ae_psa_snomed new_ae_psa_ae)
egen ae_axspa = rmin(new_ae_axspa_icd_prim new_ae_axspa_ctv new_ae_axspa_ae)
egen ae_ibd = rmin(new_ae_ibd_icd_prim new_ae_ibd_ctv new_ae_ibd_ae)
*** combined serious AEs from hosp and A&E
egen ae_diverticulitis_serious = rmin(ae_diverticulitis_icd_prim)
egen ae_diarrhoea_serious = rmin(ae_diarrhoea_icd_prim ae_diarrhoeal_icd_prim)
egen ae_taste_serious = rmin(ae_taste_icd_prim)
egen ae_rash_serious = rmin(ae_rash_icd_prim)
egen ae_contactderm_serious = rmin(ae_contactderm_icd_prim)
egen ae_dizziness_serious = rmin(ae_dizziness_icd_prim)
egen ae_nausea_vomit_serious = rmin(ae_nausea_vomit_icd_prim)
egen ae_headache_serious = rmin(ae_headache_icd_prim)
egen ae_anaphylaxis_serious = rmin(ae_anaphylaxis_icd_prim)
egen ae_drugreaction_serious = rmin(ae_severedrug_icd_prim ae_severedrug_sjs_icd_prim)
egen ae_ra_serious = rmin(new_ae_ra_icd_prim)
egen ae_sle_serious = rmin(new_ae_sle_icd_prim)
egen ae_psorasis_serious = rmin(new_ae_psoriasis_icd_prim)
egen ae_psa_serious = rmin(new_ae_psa_icd_prim)
egen ae_axspa_serious = rmin(new_ae_axspa_icd_prim)
egen ae_ibd_serious = rmin(new_ae_ibd_icd_prim)
*** combined AEs by spc, drug and imae
egen ae_spc_all = rmin(ae_diverticulitis ae_diarrhoea ae_rash ae_taste ae_bronchospasm ae_contactderm ae_dizziness ae_nausea_vomit ae_headache)
egen ae_spc_serious = rmin(ae_diverticulitis_serious ae_diarrhoea_serious ae_taste_serious ae_rash_serious ae_contactderm_serious ae_dizziness_serious ae_nausea_vomit_serious ae_headache_serious)
egen ae_drug_all = rmin(ae_anaphylaxis ae_drugreaction)
egen ae_drug_serious = rmin(ae_anaphylaxis_serious ae_drugreaction_serious)
egen ae_imae_all = rmin(ae_ra ae_sle ae_psorasis ae_psa ae_axspa ae_ibd)
egen ae_imae_serious = rmin(ae_ra_serious ae_sle_serious ae_psorasis_serious ae_psa_serious ae_axspa_serious ae_ibd_serious)
egen ae_all = rmin(ae_spc_all ae_drug_all ae_imae_all)
egen ae_all_serious = rmin(ae_spc_serious ae_drug_serious ae_imae_serious)
*** global all ae
global ae_disease ae_diverticulitis ///
ae_diarrhoea ///
ae_taste ///
ae_rash ///
ae_bronchospasm ///
ae_contactderm ///
ae_dizziness ///
ae_nausea_vomit ///
ae_headache ///
ae_anaphylaxis ///
ae_drugreaction ///
ae_ra ///
ae_sle ///
ae_psorasis ///
ae_psa ///
ae_axspa ///
ae_ibd
global ae_disease_serious ae_diverticulitis_serious ///
ae_diarrhoea_serious ///
ae_taste_serious ///
ae_rash_serious ///
ae_contactderm_serious ///
ae_dizziness_serious ///
ae_nausea_vomit_serious ///
ae_headache_serious ///
ae_anaphylaxis_serious ///
ae_drugreaction_serious ///
ae_ra_serious ///
ae_sle_serious ///
ae_psorasis_serious ///
ae_psa_serious ///
ae_axspa_serious ///
ae_ibd_serious
global ae_combined ae_all ///
ae_all_serious ///
ae_spc_all ///
ae_spc_serious ///
ae_drug_all ///
ae_drug_serious ///
ae_imae_all ///
ae_imae_serious
****************************
* COVARIATES *
****************************
* Demographics*
* Age
sum age, det
gen age_group=(age>=40)+(age>=60)
label define age_group 0 "18-39" 1 "40-59" 2 ">=60"
label values age_group age_group
egen age_5y_band=cut(age), at(18,25,30,35,40,45,50,55,60,65,70,75,80,85,110) label
tab age_group,m
tab age_5y_band,m
* Sex
gen male = 1 if sex == "M"
replace male = 0 if sex == "F"
rename sex sex_str
gen sex=0 if sex_str=="M"
replace sex=1 if sex_str=="F"
label define sex 0 "Male" 1 "Female"
label values sex sex
tab sex
* Ethnicity
tab ethnicity,m
rename ethnicity ethnicity_str
encode ethnicity_str, gen(ethnicity)
label list ethnicity
replace ethnicity=. if ethnicity==2
tab ethnicity
gen ethnicity_with_missing=ethnicity
replace ethnicity_with_missing=9 if ethnicity_with_missing==.
label define ethnicity_with_missing 1 "Black" 3 "Mixed" 4 "Other" 5 "South Asian" 6 "White" 9 "Missing", replace
label values ethnicity_with_missing ethnicity_with_missing
tab ethnicity_with_missing
gen White=1 if ethnicity==6
replace White=0 if ethnicity!=6ðnicity!=.
tab White
gen White_with_missing=White
replace White_with_missing=9 if White==.
tab White_with_missing
* IMD
tab imdq5,m
replace imdq5="." if imdq5=="Unknown"
replace imdq5="1" if imdq5=="1 (most deprived)"
replace imdq5="5" if imdq5=="5 (least deprived)"
destring imdq5, replace
recode imdq5 5 = 1 4 = 2 3 = 3 2 = 4 1 = 5 // Reverse the order (so 5 is more deprived)
label define imdq5 1 "1 least deprived" 2 "2" 3 "3" 4 "4" 5 "5 most deprived", replace
label values imdq5 imdq5
gen imd_with_missing=imdq5
replace imd_with_missing=9 if imdq5==.
tab imdq5,m
* Region
tab region_nhs,m
rename region_nhs region_nhs_str
encode region_nhs_str, gen(region_nhs)
label list region_nhs
tab region_covid_therapeutics,m
rename region_covid_therapeutics region_covid_therapeutics_str
encode region_covid_therapeutics_str, gen(region_covid_therapeutics)
label list region_covid_therapeutics
tab stp,m
rename stp stp_str
encode stp_str,gen(stp)
label list stp
label values stp stp
by stp, sort: gen stp_N=_N if stp!=. //combine stps with low N (<100) as "Other"
replace stp=99 if stp_N<100
tab stp,m
* BMI
tabstat bmi, stat(mean p25 p50 p75 min max)
replace bmi=. if bmi<10|bmi>60
gen bmi_10y=bmi if bmi_date_measured!=. & bmi_date_measured>=start_date-365*10 & (age+((bmi_date_measured-start_date)/365)>=18)
gen bmi_5y=bmi if bmi_date_measured!=. & bmi_date_measured>=start_date-365*5 & (age+((bmi_date_measured-start_date)/365)>=18)
gen bmi_2y=bmi if bmi_date_measured!=. & bmi_date_measured>=start_date-365*2 & (age+((bmi_date_measured-start_date)/365)>=18)
gen bmi_group=(bmi>=18.5)+(bmi>=25.0)+(bmi>=30.0) if bmi!=.
label define bmi_group 0 "underweight" 1 "normal" 2 "overweight" 3 "obese"
label values bmi_group bmi_group
gen bmi_group_with_missing=bmi_group
replace bmi_group_with_missing=9 if bmi_group==.
gen bmi_25=(bmi>=25) if bmi!=.
gen bmi_30=(bmi>=30) if bmi!=.
* Comorbidities
tab diabetes,m
tab chronic_cardiac_disease,m
tab hypertension,m
tab chronic_respiratory_disease,m
* Other comorbidites
tab autism,m
tab care_home,m
tab dementia_all,m
tab learning_disability,m
tab autism,m
tab serious_mental_illness,m
gen dementia = 1 if dementia_all==1 & age >39
recode dementia .=0
* Vaccination
tab vaccination_status,m
rename vaccination_status vaccination_status_group
gen vaccination_status=0 if vaccination_status_g=="Un-vaccinated"|vaccination_status_g=="Un-vaccinated (declined)"
replace vaccination_status=1 if vaccination_status_g=="One vaccination"
replace vaccination_status=2 if vaccination_status_g=="Two vaccinations"
replace vaccination_status=3 if vaccination_status_g=="Three vaccinations"
replace vaccination_status=4 if vaccination_status_g=="Four or more vaccinations"
label define vaccination_status 0 "Un-vaccinated" 1 "One vaccination" 2 "Two vaccinations" 3 "Three vaccinations" 4 "Four or more vaccinations"
label values vaccination_status vaccination_status
gen vaccination_3_plus=1 if vaccination_status==3|vaccination_status==4
replace vaccination_3_plus=0 if vaccination_status<3
* time between vaccine and covid positive test or treatment
gen days_vacc_covid=covid_test_positive_date - last_vaccination_date if (covid_test_positive_date>last_vaccination_date)
sum days_vacc_covid,de
gen days_vacc_treat=date_treated - last_vaccination_date if (date_treated>last_vaccination_date)
sum days_vacc_treat,de
gen month_vacc_covid=ceil(days_vacc_covid/30)
gen month_vacc_treat=ceil(days_vacc_treat/30)
tab month_vacc_covid,m
*Calendar time*
gen day_after_campaign=start_date-mdy(12,15,2021)
sum day_after_campaign,de
gen month_after_campaign=ceil((start_date-mdy(12,15,2021))/30)
tab month_after_campaign,m
tab start_date if month_after_campaign>100
//drop if month_after_campaign>100
* Prior infection / check Bang code
tab prior_covid, m
gen prior_covid_index=1 if prior_covid==1 & prior_covid_date<campaign_start
tab prior_covid_index,m
replace prior_covid_index=0 if prior_covid_index==.
* Calculating egfr: adapted from https://github.com/opensafely/COVID-19-vaccine-breakthrough/blob/updates-feb/analysis/data_process.R*
tabstat creatinine_ctv3, stat(mean p25 p50 p75 min max)
replace creatinine_ctv3=. if !inrange(creatinine_ctv3, 20, 3000)|creatinine_ctv3_date>start_date
tabstat creatinine_ctv3, stat(mean p25 p50 p75 min max)
replace creatinine_ctv3 = creatinine_ctv3/88.4
gen min_creatinine_ctv3=.
replace min_creatinine_ctv3 = (creatinine_ctv3/0.7)^-0.329 if sex==1
replace min_creatinine_ctv3 = (creatinine_ctv3/0.9)^-0.411 if sex==0
replace min_creatinine_ctv3 = 1 if min_creatinine_ctv3<1
gen max_creatinine_ctv3=.
replace max_creatinine_ctv3 = (creatinine_ctv3/0.7)^-1.209 if sex==1
replace max_creatinine_ctv3 = (creatinine_ctv3/0.9)^-1.209 if sex==0
replace max_creatinine_ctv3 = 1 if max_creatinine_ctv3>1
gen egfr_creatinine_ctv3 = min_creatinine_ctv3*max_creatinine_ctv3*141*(0.993^age_creatinine_ctv3) if age_creatinine_ctv3>0&age_creatinine_ctv3<=120
replace egfr_creatinine_ctv3 = egfr_creatinine_ctv3*1.018 if sex==1
tabstat creatinine_snomed, stat(mean p25 p50 p75 min max)
replace creatinine_snomed = . if !inrange(creatinine_snomed, 20, 3000)| creatinine_snomed_date>start_date
replace creatinine_snomed_date = creatinine_short_snomed_date if missing(creatinine_snomed)
replace creatinine_operator_snomed = creatinine_operator_short_snomed if missing(creatinine_snomed)
replace age_creatinine_snomed = age_creatinine_short_snomed if missing(creatinine_snomed)
replace creatinine_snomed = creatinine_short_snomed if missing(creatinine_snomed)
replace creatinine_snomed = . if !inrange(creatinine_snomed, 20, 3000)| creatinine_snomed_date>start_date
replace creatinine_snomed = creatinine_snomed/88.4
gen min_creatinine_snomed=.
replace min_creatinine_snomed = (creatinine_snomed/0.7)^-0.329 if sex==1
replace min_creatinine_snomed = (creatinine_snomed/0.9)^-0.411 if sex==0
replace min_creatinine_snomed = 1 if min_creatinine_snomed<1
gen max_creatinine_snomed=.
replace max_creatinine_snomed = (creatinine_snomed/0.7)^-1.209 if sex==1
replace max_creatinine_snomed = (creatinine_snomed/0.9)^-1.209 if sex==0
replace max_creatinine_snomed = 1 if max_creatinine_snomed>1
gen egfr_creatinine_snomed = min_creatinine_snomed*max_creatinine_snomed*141*(0.993^age_creatinine_snomed) if age_creatinine_snomed>0&age_creatinine_snomed<=120
replace egfr_creatinine_snomed = egfr_creatinine_snomed*1.018 if sex==1
gen egfr_60 = 1 if (egfr_creatinine_ctv3<60&creatinine_operator_ctv3!="<")|(egfr_creatinine_snomed<60&creatinine_operator_snomed!="<")|(egfr_record<60&egfr_record>0&egfr_operator!=">"&egfr_operator!=">=")|(egfr_short_record<60&egfr_short_record>0&egfr_short_operator!=">"&egfr_short_operator!=">=")
gen egfr_30 = 1 if (egfr_creatinine_ctv3<30&creatinine_operator_ctv3!="<")|(egfr_creatinine_snomed<30&creatinine_operator_snomed!="<")|(egfr_record<30&egfr_record>0&egfr_operator!=">"&egfr_operator!=">=")|(egfr_short_record<30&egfr_short_record>0&egfr_short_operator!=">"&egfr_short_operator!=">=")
count if egfr_60==1
count if egfr_30==1
*Paxlovid interactions*
count if drugs_paxlovid_contraindication<=start_date
count if drugs_paxlovid_contraindication<=start_date&drugs_paxlovid_contraindication>=(start_date-3*365.25)
count if drugs_paxlovid_contraindication<=start_date&drugs_paxlovid_contraindication>=(start_date-365.25)
count if drugs_paxlovid_contraindication<=start_date&drugs_paxlovid_contraindication>=(start_date-180)
gen drugs_paxlovid_cont=(drugs_paxlovid_contraindication<=start_date&drugs_paxlovid_contraindication>=(start_date-180))
* Drug contraindicated
gen paxlovid_contraindicated = 1 if egfr_30==1 | dialysis==1
replace paxlovid_contraindicated = 1 if liver_disease==1
replace paxlovid_contraindicated = 1 if organ_transplant==1
replace paxlovid_contraindicated = 1 if drugs_paxlovid_contraindication<=start_date&drugs_paxlovid_contraindication>=(start_date-180)
recode paxlovid_contraindicated . = 0
count if paxlovid_contraindicated==1
********************************************************
* INCLUSION ONLY WITH POSITIVE COVID TEST *
********************************************************
** inclusion criteria*
keep if age>=18 & age<110
keep if sex==0 | sex==1
keep if has_died==0
tab dataset
** exclusion criteria*
count if start_date!=.
count if start_date>dereg_date & start_date!=.
count if start_date>death_date & start_date!=.
//drop if start_date>death_date | start_date>dereg_date
//drop if start_date>study_end_date
tab dataset
** positive covid test
count if covid_test_positive_date!=.
count if covid_test_positive_date==.
keep if covid_test_positive_date!=.
** check covid positive and not repeat covid test after an infection within 30 days prior
tab covid_positive_previous_30_days
drop if covid_positive_previous_30_days==1
********************************************************
* EXPOSURE *
********************************************************
** removing individuals who did not have a covid test within 5 days of treatment
tab dataset
gen pre_drug_test_time = date_treated-covid_test_positive_date if dataset==1
sum pre_drug_test_time, det
gen pre_drug_test=0 if dataset==1 & pre_drug_test_time==0
replace pre_drug_test=1 if dataset==1 & pre_drug_test_time==1
replace pre_drug_test=2 if dataset==1 & pre_drug_test_time==2
replace pre_drug_test=3 if dataset==1 & pre_drug_test_time==3
replace pre_drug_test=4 if dataset==1 & pre_drug_test_time==4
replace pre_drug_test=5 if dataset==1 & pre_drug_test_time==5
replace pre_drug_test=6 if dataset==1 & pre_drug_test_time>=6 & pre_drug_test_time<=7
replace pre_drug_test=7 if dataset==1 & pre_drug_test_time>=7 & pre_drug_test_time<=21
replace pre_drug_test=8 if dataset==1 & pre_drug_test_time<0 | pre_drug_test_time>21
replace pre_drug_test=9 if dataset==1 & (covid_test_positive_date==. | date_treated==.) & dataset==1
label define pre_drug_test 0 "0 days" 1 "1 days" 2 "2 days" 3 "3 days" 4 "4 days" 5 "5 days" 6 "6-7 days" 7 ">7 days & <21 days" 8 ">21 or <0 days" 9 "no test/no treatment date", replace
label values pre_drug_test pre_drug_test
tab pre_drug_test_time if pre_drug_test<=5
tab pre_drug_test dataset,m
count if dataset==1 & pre_drug_test>5
drop if dataset==1 & pre_drug_test>5
sum pre_drug_test_time, det
**delay between covid test and treatment
gen covid_test_5d = 1 if pre_drug_test<=5 & dataset==1
sum pre_drug_test_time if covid_test_5d==1, det
egen median_delay_treatment = median(pre_drug_test_time) if covid_test_5d==1
egen median_delay_all= max(median_delay_treatment)
** removing individuals who did not start therapy
tab treatment_dataset
count if date_treated!=.
foreach var of varlist sotrovimab molnupiravir paxlovid {
display "`var'"
count if `var'!=.
count if `var'==date_treated & `var'!=. & date_treated!=.
count if `var'==date_treated & `var'!=. & date_treated!=. & `var'_not_start!=.
gen `var'_start = 1 if `var'==date_treated & `var'!=. & date_treated!=. & `var'_not_start==.
replace `var'_start = 0 if `var'==date_treated & `var'!=. & date_treated!=. & `var'_not_start!=.
tab `var'_start, m
}
** removing individuals start two or more drugs (i.e sotrovimab and paxlovid dates both on treat date and no code for not starting drug)
gen sotrovimab_start_clean = 1 if sotrovimab_start==1 & paxlovid_start!=1 & molnupiravir_start!=1
replace sotrovimab_start_clean = 0 if sotrovimab_start==1 & (paxlovid_start==1 | molnupiravir_start==1)
tab sotrovimab_start_clean sotrovimab_start
gen paxlovid_start_clean = 1 if paxlovid_start==1 & sotrovimab_start!=1 & molnupiravir_start!=1
replace paxlovid_start_clean = 0 if paxlovid_start==1 & (sotrovimab_start==1 | molnupiravir_start==1)
tab paxlovid_start_clean paxlovid_start
gen molnupiravir_start_clean = 1 if molnupiravir_start==1 & sotrovimab_start!=1 & paxlovid_start!=1
replace molnupiravir_start_clean = 0 if molnupiravir_start==1 & (sotrovimab_start==1 | paxlovid_start==1)
tab molnupiravir_start_clean molnupiravir_start
* remove if had remdesivir or casirivimab
gen drug=4 if remdesivir==date_treated&remdesivir!=.&date_treated!=.
replace drug=5 if casirivimab==date_treated&casirivimab!=.&date_treated!=.
tab drug,m
* patient who started sotrovimab, paxlovid, molnupiravir
replace drug=1 if sotrovimab_start_clean==1
replace drug=2 if paxlovid_start_clean==1
replace drug=3 if molnupiravir_start_clean==1
tab drug,m
replace drug=0 if drug==.
label define drug 0 "control" 1 "sotrovimab" 2 "paxlovid" 3"molnupiravir" 4 "remdesivir" 5 "casirivimab", replace
label values drug drug
tab drug, m
* for flow sheet for treatment arm
bys dataset: tab drug,m
drop if drug>0 & dataset==0
drop if drug==0 & dataset==1
bys dataset: tab drug,m
* drop if i) treatment not started ii) combination treatment iii) remdesivir or casirivimab
drop if drug>3 & dataset==1
bys dataset: tab drug,m
********************************************************
* CONTROL *
********************************************************
** cleaning eligibility criteria - ensure IMID on drug >4 pred scripts
tab high_risk_cohort_nhsd,m
tab high_risk_cohort_nhsd drug
count if imid_on_drug==1 & imid_nhsd==1 & imid_drug==0 //should be 0
count if imid_on_drug==1 & imid_nhsd==0 & imid_drug==1 //should be 0
count if imid_on_drug==1 & imid_nhsd==1 & imid_drug==1 & downs_syndrome==0 &solid_cancer==0 &haem_disease==0 &renal_disease==0 &liver_disease==0 &immunosuppression==0 &hiv_aids==0 &organ_transplant==0 &rare_neuro==0
count if oral_steroid_drug_nhsd_6m_count<4 &oral_steroid_drugs_nhsd==1
count if oral_steroid_drug_nhsd_6m_count<4 &oral_steroid_drugs_nhsd==1 &immunosuppresant==0 &methotrexate==0 &ciclosporin==0 &mycophenolate==0
count if oral_steroid_drug_nhsd_6m_count<4 &oral_steroid_drugs_nhsd==1 &immunosuppresant==0 &methotrexate==0 &ciclosporin==0 &mycophenolate==0 &imid_on_drug==1
count if oral_steroid_drug_nhsd_6m_count<4 &oral_steroid_drugs_nhsd==1 &immunosuppresant==0 &methotrexate==0 &ciclosporin==0 &mycophenolate==0 &imid_on_drug==1 &downs_syndrome==0 &solid_cancer==0 &haem_disease==0 &renal_disease==0 &liver_disease==0 &immunosuppression==0 &hiv_aids==0 &organ_transplant==0 &rare_neuro==0
count if oral_steroid_drug_nhsd_6m_count<4 &oral_steroid_drugs_nhsd==1 &immunosuppresant==0 &methotrexate==0 &ciclosporin==0 &mycophenolate==0 &imid_on_drug==1 &downs_syndrome==0 &solid_cancer==0 &haem_disease==0 &renal_disease==0 &liver_disease==0 &immunosuppression==0 &hiv_aids==0 &organ_transplant==0 &rare_neuro==0&dataset==0
replace imid_drug=0 if oral_steroid_drug_nhsd_6m_count<4 &oral_steroid_drugs_nhsd==1 &immunosuppresant==0 &methotrexate==0 &ciclosporin==0 &mycophenolate==0 &imid_on_drug==1 //ignore if steriods<4 scripts in 6m & not coded other imid drug
replace oral_steroid_drugs_nhsd=0 if oral_steroid_drug_nhsd_6m_count<4 &oral_steroid_drugs_nhsd==1 //ignore if steriods<4 scripts in 6m
count if imid_on_drug==1 & imid_nhsd==1 & imid_drug==0
replace imid_on_drug=0 if imid_nhsd==1 & imid_drug==0 //ignore if steriods<4 & not coded other imid drug
replace imid_on_drug=0 if imid_nhsd==0 & imid_drug==1
gen high_risk_cohort_codelist=((downs_syndrome + solid_cancer + haem_disease + renal_disease + liver_disease + imid_on_drug + immunosuppression + hiv_aids + organ_transplant + rare_neuro )>0)
tab high_risk_cohort_codelist dataset,m
drop if high_risk_cohort_codelist==0 & dataset==0 //should be same number dropped as change above
tab high_risk_cohort_codelist dataset
** cleaning ensure not hospitalised or discharge on day on covid test
bys dataset: tab drug,m
count if drug==0 & start_date==covid_test_positive_date
count if drug==0 & start_date!=covid_test_positive_date
** control patient ever hospitalised
count if drug==0 & pre_covid_hosp_date!=.
** control patient hospitalised on day of positive test
count if drug==0 & covid_test_positive_date==pre_covid_hosp_date
** control patient hospitalised & still in hospital (not discharged)
count if drug==0 & pre_covid_hosp_date!=. & pre_covid_hosp_discharge==.
count if drug==0 & pre_covid_hosp_date!=. & pre_covid_hosp_discharge==. & (start_date-pre_covid_hosp_date<29)
count if drug==0 & pre_covid_hosp_date!=. & pre_covid_hosp_discharge==. & (start_date-pre_covid_hosp_date<366)
** control patient, hospitalised & still in hospital (not discharged) - discharge date preceed admission
count if drug==0 & pre_covid_hosp_date>pre_covid_hosp_discharge & pre_covid_hosp_date!=. & pre_covid_hosp_discharge!=.
count if drug==0 & pre_covid_hosp_date>pre_covid_hosp_discharge & pre_covid_hosp_date!=. & pre_covid_hosp_discharge!=. & (start_date-pre_covid_hosp_date<29)
count if drug==0 & pre_covid_hosp_date>pre_covid_hosp_discharge & pre_covid_hosp_date!=. & pre_covid_hosp_discharge!=. & (start_date-pre_covid_hosp_date<366)
** control patient discharged on day of positive covid test
count if drug==0 & covid_test_positive_date==pre_covid_hosp_discharge
** control patient's discharged 1 day before positive covid test
count if drug==0 & (covid_test_positive_date-pre_covid_hosp_discharge<=1) & (covid_test_positive_date-pre_covid_hosp_discharge>=0)
* for flow sheet for treatment arm
** remove if hospitalised on day of positive test
drop if drug==0 & covid_test_positive_date==pre_covid_hosp_date
** remove if discharged on day of positive covid test
drop if drug==0 & covid_test_positive_date==pre_covid_hosp_discharge
** remove if discharged on 1 day before positive covid test
drop if drug==0 & (covid_test_positive_date-pre_covid_hosp_discharge<=1) & (covid_test_positive_date-pre_covid_hosp_discharge>=0)
bys dataset: tab drug,m
** high risk cohort from blueteq therapeutics
tab high_risk_cohort_therapeutics dataset,m
gen downs_syndrome_therap= 1 if strpos(high_risk_cohort_therapeutics, "Downs syndrome")
gen solid_cancer_therap=1 if strpos(high_risk_cohort_therapeutics, "solid cancer")
gen haem_disease_therap=1 if strpos(high_risk_cohort_therapeutics, "haematological malignancies")
replace haem_disease_therap=1 if strpos(high_risk_cohort_therapeutics, "haematologic malignancy")
replace haem_disease_therap=1 if strpos(high_risk_cohort_therapeutics, "sickle cell disease")
replace haem_disease_therap=1 if strpos(high_risk_cohort_therapeutics, "haematological diseases")
replace haem_disease_therap=1 if strpos(high_risk_cohort_therapeutics, "stem cell transplant")
gen renal_disease_therap= 1 if strpos(high_risk_cohort_therapeutics, "renal disease")
gen liver_disease_therap= 1 if strpos(high_risk_cohort_therapeutics, "liver disease")
gen imid_on_drug_therap= 1 if strpos(high_risk_cohort_therapeutics, "IMID")
gen immunosuppression_therap= 1 if strpos(high_risk_cohort_therapeutics, "primary immune deficiencies")
gen hiv_aids_therap= 1 if strpos(high_risk_cohort_therapeutics, "HIV or AIDS")
gen organ_transplant_therap= 1 if strpos(high_risk_cohort_therapeutics, "solid organ recipients")
replace organ_transplant_therap= 1 if strpos(high_risk_cohort_therapeutics, "solid organ transplant")
gen rare_neuro_therap= 1 if strpos(high_risk_cohort_therapeutics, "rare neurological conditions")
count if high_risk_cohort_therapeutics!=""&high_risk_cohort_therapeutics!="other"& min(downs_syndrome_therap,solid_cancer_therap,haem_disease_therap,renal_disease_therap,liver_disease_therap,imid_on_drug_therap,immunosuppression_therap,hiv_aids_therap,organ_transplant_therap,rare_neuro_therap)==. //check if all diseases have been captured
tab high_risk_cohort_therapeutics if high_risk_cohort_therapeutics!=""&high_risk_cohort_therapeutics!="other"& min(downs_syndrome_therap,solid_cancer_therap,haem_disease_therap,renal_disease_therap,liver_disease_therap,imid_on_drug_therap,immunosuppression_therap,hiv_aids_therap,organ_transplant_therap,rare_neuro_therap)==.
gen high_risk_cohort_ther= 1 if high_risk_cohort_therapeutics!=""&high_risk_cohort_therapeutics!="other"
foreach var of varlist downs_syndrome_therap solid_cancer_therap haem_disease_therap renal_disease_therap liver_disease_therap imid_on_drug_therap immunosuppression_therap hiv_aids_therap organ_transplant_therap rare_neuro_therap{
replace `var'=0 if `var'==.
}
** combine two high risk cohorts into one
foreach var of varlist downs_syndrome solid_cancer haem_disease renal_disease liver_disease imid_on_drug immunosuppression hiv_aids organ_transplant rare_neuro {
gen `var'_comb = `var'
replace `var'_comb = 1 if `var'_therap==1
tab `var' `var'_therap
tab dataset `var'_comb
}
gen eligible = 0 if downs_syndrome_comb==.&solid_cancer_comb==.& haem_disease_comb==.& renal_disease_comb==.& liver_disease_comb==.& imid_on_drug_comb==.& immunosuppression_comb==.& hiv_aids_comb==.& organ_transplant_comb==.& rare_neuro_comb==.
recode eligible . = 1
tab drug eligible
********************************************************
* FINAL NUMBERS *
********************************************************
tab dataset
tab drug