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cr_analysis_new.do
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cr_analysis_new.do
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********************************************************************************
*
* Do-file: cr_analysis_dataset.do
*
* Project: SGTF CFR
*
* Programmed by: Daniel Grint
* Adapted from COVID/NON-COVID death (Fizz & Krishnan)
*
* Data used: output/input.csv
* lookups/MSOA_lookup.dta
*
* Data created: output/cr_analysis_new.dta (main analysis dataset)
*
* Other output: None
*
********************************************************************************
*
* Purpose: This do-file creates the variables required for the
* main analysis and saves into Stata datasets.
*
********************************************************************************
* Open a log file
cap log close
log using ./logs/cr_analysis_new, replace t
clear
import delimited ./output/input.csv
merge m:1 msoa using ./lookups/MSOA_lookup
drop if _merge==2
drop _merge
rename hiv hiv_code
****************************
* Create required cohort *
****************************
gen study_start = date(sgss_pos_inrange, "YMD")
summ study_start
noi disp "MINIMUM START DATE: " %td r(min)
gen study_end = date("11jan2021", "DMY")
format %td study_start study_end
* DROP IF NO POSITIVE PCR TEST IN SGSS DURING STUDY PERIOD
noi di "NO POSITIVE TEST IN STUDY PERIOD"
drop if sgss_pos_inrange == ""
* DROP IF DIED ON/BEFORE STUDY START DATE
noi di "DIED ON/BEFORE STUDY START DATE:"
drop if date(died_date_ons, "YMD") <= study_start
* DROP IF COVID POSITIVE ON/BEFORE STUDY START DATE
noi di "COVID POSITIVE BEFORE STUDY START DATE:"
drop if date(covid_tpp_probable, "YMD") < study_start
drop if date(first_pos_test_sgss, "YMD") < study_start
* DROP IF VACCINATED ON/BEFORE STUDY START DATE
noi di "VACCINATED ON/BEFORE STUDY START DATE:"
drop if date(covid_vacc_date, "YMD") <= study_start
* Age: Exclude children
*noi di "DROPPING AGE<18:"
*drop if age<18
* Age: Exclude those with implausible ages
assert age<.
noi di "DROPPING AGE>105:"
drop if age>105
* Sex: Exclude categories other than M and F
assert inlist(sex, "M", "F", "I", "U")
noi di "DROPPING GENDER NOT M/F:"
drop if inlist(sex, "I", "U")
**************************
* CREATE SGTF VARIABLE *
**************************
desc sgtf
replace sgtf=99 if sgtf==.
gen has_sgtf=0
replace has_sgtf=1 if inrange(sgtf,0,1)
label define sgtfLab 0 "non-VOC" 1 "VOC" 9 "Unclassified" 99 "Blank"
label values sgtf sgtfLab
******************************
* Convert strings to dates *
******************************
* Covariates
foreach var of varlist bp_sys_date ///
bp_dias_date ///
hba1c_percentage_date ///
hba1c_mmol_per_mol_date ///
hypertension ///
bmi_date_measured ///
chronic_respiratory_disease ///
chronic_cardiac_disease ///
diabetes ///
lung_cancer ///
haem_cancer ///
other_cancer ///
chronic_liver_disease ///
stroke ///
dementia ///
other_neuro ///
organ_transplant ///
dysplenia ///
sickle_cell ///
aplastic_anaemia ///
hiv_date ///
permanent_immunodeficiency ///
temporary_immunodeficiency ///
ra_sle_psoriasis dialysis {
confirm string variable `var'
replace `var' = `var' + "-15"
rename `var' `var'_dstr
replace `var'_dstr = " " if `var'_dstr == "-15"
gen `var'_date = date(`var'_dstr, "YMD")
order `var'_date, after(`var'_dstr)
drop `var'_dstr
format `var'_date %td
}
rename bmi_date_measured_date bmi_date_measured
rename bp_dias_date_measured_date bp_dias_date
rename bp_sys_date_measured_date bp_sys_date
rename hba1c_percentage_date_date hba1c_percentage_date
rename hba1c_mmol_per_mol_date_date hba1c_mmol_per_mol_date
rename hiv_date_date hiv_date
* Dates of: covid tests, ONS death
foreach var of varlist dereg_date died_date_ons covid_tpp_probable covid_vacc_date ///
first_pos_test_sgss sgss_pos_inrange covid_admission_date icu_admission_date ///
covid_discharge_date {
confirm string variable `var'
rename `var' _tmp
gen `var' = date(_tmp, "YMD")
drop _tmp
format %d `var'
}
*******************************
* Recode implausible values *
*******************************
* BMI
* Only keep if within certain time period? using bmi_date_measured ?
* NB: Some BMI dates in future or after cohort entry
* Set implausible BMIs to missing:
replace bmi = . if !inrange(bmi, 15, 50)
* Sex
assert inlist(sex, "M", "F")
gen male = (sex=="M")
drop sex
label define maleLab 0 "F" 1 "M"
label values male maleLab
* Smoking
label define smoke_nomissLab 1 "Never" 2 "Former" 3 "Current"
gen smoke = 1 if smoking_status=="N"
replace smoke = 2 if smoking_status=="E"
replace smoke = 3 if smoking_status=="S"
replace smoke = . if smoking_status=="M"
label values smoke smoke_nomissLab
drop smoking_status
* Ethnicity (5 category)
tab ethnicity, m
replace ethnicity = . if ethnicity==.
label define ethnicityLab 1 "White" ///
2 "Mixed" ///
3 "Asian or Asian British" ///
4 "Black" ///
5 "Other"
label values ethnicity ethnicityLab
* Re-order ethnicity
gen eth5=1 if ethnicity==1
replace eth5=2 if ethnicity==3
replace eth5=3 if ethnicity==4
replace eth5=4 if ethnicity==2
replace eth5=5 if ethnicity==5
replace eth5=6 if ethnicity==.
label define eth5Lab 1 "White" ///
2 "South Asian" ///
3 "Black" ///
4 "Mixed" ///
5 "Other" ///
6 "Missing"
label values eth5 eth5Lab
recode eth5 2/4=5, gen(eth2)
order eth2, after(eth5)
label values eth2 eth5Lab
tab eth2, m
* Ethnicity (16 category)
replace ethnicity_16 = . if ethnicity==.
label define ethnicity_16 ///
1 "British or Mixed British" ///
2 "Irish" ///
3 "Other White" ///
4 "White + Black Caribbean" ///
5 "White + Black African" ///
6 "White + Asian" ///
7 "Other mixed" ///
8 "Indian or British Indian" ///
9 "Pakistani or British Pakistani" ///
10 "Bangladeshi or British Bangladeshi" ///
11 "Other Asian" ///
12 "Caribbean" ///
13 "African" ///
14 "Other Black" ///
15 "Chinese" ///
16 "Other"
label values ethnicity_16 ethnicity_16
* Ethnicity (16 category grouped further)
* Generate a version of the full breakdown with mixed in one group
gen ethnicity_16_combinemixed = ethnicity_16
recode ethnicity_16_combinemixed 4/7 = 4
label define ethnicity_16_combinemixed ///
1 "British or Mixed British" ///
2 "Irish" ///
3 "Other White" ///
4 "All mixed" ///
8 "Indian or British Indian" ///
9 "Pakistani or British Pakistani" ///
10 "Bangladeshi or British Bangladeshi" ///
11 "Other Asian" ///
12 "Caribbean" ///
13 "African" ///
14 "Other Black" ///
15 "Chinese" ///
16 "Other"
label values ethnicity_16_combinemixed ethnicity_16_combinemixed
* STP
tab stp
rename stp stp_old
bysort stp_old: gen stp = 1 if _n==1
replace stp = sum(stp)
drop stp_old
* MSOA/UTLA
egen n_msoa = tag(msoa)
count if n_msoa
bysort msoa: gen count1 = _N
summ count1, d
egen n_utla = tag(utla)
count if n_utla
bysort utla: gen count2 = _N
summ count2, d
* Regroup UTLAs with small case numbers
gen utla_group = utla_name
tab utla_group
replace utla_group = "Redbridge, Barking and Dagenham" if utla_name == "Barking and Dagenham"
replace utla_group = "Redbridge, Barking and Dagenham" if utla_name == "Redbridge"
replace utla_group = "Bucks/Ox/West. Berks/Swindon" if utla_name == "Buckinghamshire"
replace utla_group = "Bucks/Ox/West. Berks/Swindon" if utla_name == "Oxfordshire"
replace utla_group = "Bucks/Ox/West. Berks/Swindon" if utla_name == "Swindon"
replace utla_group = "Bucks/Ox/West. Berks/Swindon" if utla_name == "West Berkshire"
replace utla_group = "Camden and Westminster" if utla_name == "Camden"
replace utla_group = "Camden and Westminster" if utla_name == "Westminster"
replace utla_group = "" if utla_name == "Isles of Scilly"
replace utla_group = "Richmond and Hounslow" if utla_name == "Richmond upon Thames"
replace utla_group = "Richmond and Hounslow" if utla_name == "Hounslow"
replace utla_group = "Rutland and Lincoln" if utla_name == "Rutland"
replace utla_group = "Rutland and Lincoln" if utla_name == "Lincolnshire"
replace utla_group = "Bolton and Tameside" if utla_name == "Bolton"
replace utla_group = "Bolton and Tameside" if utla_name == "Tameside"
tab utla_group, m
* NHS England regions
tab region, m
gen region2=.
replace region2=0 if region=="East"
replace region2=1 if region=="East Midlands"
replace region2=2 if region=="London"
replace region2=3 if region=="North East"
replace region2=4 if region=="North West"
replace region2=5 if region=="South East"
replace region2=6 if region=="South West"
replace region2=7 if region=="West Midlands"
replace region2=8 if region=="Yorkshire and The Humber"
drop region
rename region2 region
label define regionLab 0 "East" ///
1 "East Midlands" ///
2 "London" ///
3 "North East" ///
4 "North West" ///
5 "South East" ///
6 "South West" ///
7 "West Midlands" ///
8 "Yorkshire and the Humber"
label values region regionLab
**************************
* Categorise variables *
**************************
/* Age variables */
noi di "DROPPING IF NO AGE"
drop if age>=.
* Create categorised age
recode age 0/17.9999=0 ///
18/29.9999 = 1 ///
30/39.9999 = 2 ///
40/49.9999 = 3 ///
50/59.9999 = 4 ///
60/69.9999 = 5 ///
70/79.9999 = 6 ///
80/max = 7, gen(agegroup)
label define agegroupLab 0 "0-<18" ///
1 "18-<30" ///
2 "30-<40" ///
3 "40-<50" ///
4 "50-<60" ///
5 "60-<70" ///
6 "70-<80" ///
7 "80+"
label values agegroup agegroupLab
* For subgroup analysis
recode age 0/64.9999=1 ///
65/74.9999=2 ///
75/84.9999=3 ///
85/max=4, gen(agegroupA)
label define agegroupALab 1 "0-<65" ///
2 "65-<75" ///
3 "75-<85" ///
4 "85+"
label values agegroupA agegroupALab
* More age categories
recode age 0/39.9999=0 ///
40/54.9999 = 1 ///
55/64.9999 = 2 ///
65/74.9999 = 3 ///
75/84.9999 = 4 ///
85/max = 5, gen(agegroup6)
label define agegroup6Lab 0 "0-<40" ///
1 "40-<55" ///
2 "55-<65" ///
3 "65-<75" ///
4 "75-<85" ///
5 "85+"
label values agegroup6 agegroup6Lab
* Create binary age
recode age min/69.999=0 70/max=1, gen(age70)
* Check there are no missing ages
assert age<.
assert agegroup<.
assert age70<.
* Create restricted cubic splines for age centred on 65
gen age65 = age - 65
mkspline age = age65, cubic nknots(4)
/* Body Mass Index */
* BMI (NB: watch for missingness)
gen bmicat = .
recode bmicat . = 1 if bmi<18.5
recode bmicat . = 2 if bmi<25
recode bmicat . = 3 if bmi<30
recode bmicat . = 4 if bmi<35
recode bmicat . = 5 if bmi<40
recode bmicat . = 6 if bmi<.
replace bmicat = . if bmi>=.
label define bmicat 1 "Underweight (<18.5)" ///
2 "Normal (18.5-24.9)" ///
3 "Overweight (25-29.9)" ///
4 "Obese I (30-34.9)" ///
5 "Obese II (35-39.9)" ///
6 "Obese III (40+)"
label values bmicat bmicat
* Create more granular categorisation
recode bmicat 1/3 . = 1 4=2 5=3 6=4, gen(obese4cat)
label define obese4catLab 1 "No record of obesity" ///
2 "Obese I (30-34.9)" ///
3 "Obese II (35-39.9)" ///
4 "Obese III (40+)"
label values obese4cat obese4catLab
order obese4cat, after(bmicat)
tab obese4cat, m
/* Smoking */
* Create non-missing 3-category variable for current smoking
recode smoke .=1, gen(smoke_nomiss)
order smoke_nomiss, after(smoke)
label values smoke_nomiss smoke_nomissLab
recode smoke_nomiss 3=2, gen(smoke_nomiss2)
order smoke_nomiss2, after(smoke_nomiss)
label values smoke_nomiss2 smoke_nomissLab
tab smoke_nomiss2, m
/* Asthma */
* Asthma (coded: 0 No, 1 Yes no OCS, 2 Yes with OCS)
rename asthma asthmacat
recode asthmacat 0=1 1=2 2=3 .=1
label define asthmacat 1 "No" 2 "Yes, no OCS" 3 "Yes with OCS"
label values asthmacat asthmacat
gen asthma = (asthmacat==2|asthmacat==3)
/* Blood pressure */
* Categorise
gen bpcat = 1 if bp_sys < 120 & bp_dias < 80
replace bpcat = 2 if inrange(bp_sys, 120, 130) & bp_dias<80
replace bpcat = 3 if inrange(bp_sys, 130, 140) | inrange(bp_dias, 80, 90)
replace bpcat = 4 if (bp_sys>=140 & bp_sys<.) | (bp_dias>=90 & bp_dias<.)
replace bpcat = . if bp_sys>=. | bp_dias>=. | bp_sys==0 | bp_dias==0
label define bpcat 1 "Normal" 2 "Elevated" 3 "High, stage I" ///
4 "High, stage II"
label values bpcat bpcat
recode bpcat .=1, gen(bpcat_nomiss)
label values bpcat_nomiss bpcat
* Create non-missing indicator of known high blood pressure
gen bphigh = (bpcat==4)
order bpcat bphigh, after(bp_dias_date)
/* IMD */
* Group into 5 groups
rename imd imd_o
egen imd = cut(imd_o), group(5) icodes
replace imd = imd + 1
replace imd = . if imd_o==-1
drop imd_o
tab imd
* Reverse the order (so high is more deprived)
recode imd 5=1 4=2 3=3 2=4 1=5 .=.
tab imd
label define imdLab 1 "1 least deprived" 2 "2" 3 "3" 4 "4" 5 "5 most deprived"
label values imd imdLab
noi di "DROPPING IF NO IMD"
drop if imd>=.
/* HOUSEHOLD SIZE */
gen hh_total_cat=.
replace hh_total_cat=1 if household_size >=1 & household_size<=2
replace hh_total_cat=2 if household_size >=3 & household_size<=5
replace hh_total_cat=3 if household_size >=6 & household_size<=10
replace hh_total_cat=4 if household_size >=11 & household_size !=.
label define hh_total_catLab 1 "1-2" ///
2 "3-5" ///
3 "6-10" ///
4 "11+"
label values hh_total_cat hh_total_catLab
tab hh_total_cat, m
/* RURAL OR URBAN */
* Create a 5 category rural urban variable based upon meeting with Roz 21st October
gen rural_urban5=.
replace rural_urban5=1 if rural_urban==1
replace rural_urban5=2 if rural_urban==2
replace rural_urban5=3 if rural_urban==3|rural_urban==4
replace rural_urban5=4 if rural_urban==5|rural_urban==6
replace rural_urban5=5 if rural_urban==7|rural_urban==8
label define rural_urban5Lab 1 "Urban major conurbation" ///
2 "Urban minor conurbation" ///
3 "Urban city and town" ///
4 "Rural town and fringe" ///
5 "Rural village and dispersed"
label values rural_urban5 rural_urban5Lab
tab rural_urban5, m
/* CARE HOME TYPE */
tab care_home_type, m
gen home_bin=0
replace home_bin=1 if care_home_type=="PC" | care_home_type=="PN" | care_home_type=="PS"
tab care_home_type home_bin, m
label define home_binLab 0 "Private home" ///
1 "Care home"
label values home_bin home_binLab
/* Centred age, sex, IMD, ethnicity (for adjusted KM plots) */
* Centre age (linear)
summ age
gen c_age = age-r(mean)
* "Centre" sex to be coded -1 +1
recode male 0=-1, gen(c_male)
* "Centre" IMD
gen c_imd = imd - 3
* "Centre" ethnicity
gen c_ethnicity = ethnicity - 3
**************************************************
* Create binary comorbidity indices from dates *
**************************************************
* Comorbidities ever before study_start
foreach var of varlist chronic_respiratory_disease_date ///
chronic_cardiac_disease_date ///
diabetes_date ///
chronic_liver_disease_date ///
stroke_date ///
dementia_date ///
other_neuro_date ///
organ_transplant_date ///
aplastic_anaemia_date ///
hypertension_date ///
dysplenia_date ///
sickle_cell_date ///
hiv_date ///
permanent_immunodeficiency_date ///
temporary_immunodeficiency_date ///
ra_sle_psoriasis_date dialysis_date {
local newvar = substr("`var'", 1, length("`var'") - 5)
gen `newvar' = (`var'< study_start)
order `newvar', after(`var')
}
**************************
* Epidemiological week *
**************************
gen start_week = 54 if study_start <= date("11jan2021", "DMY")
replace start_week = 53 if study_start <= date("03jan2021", "DMY")
replace start_week = 52 if study_start <= date("27dec2020", "DMY")
replace start_week = 51 if study_start <= date("20dec2020", "DMY")
replace start_week = 50 if study_start <= date("13dec2020", "DMY")
replace start_week = 49 if study_start <= date("06dec2020", "DMY")
replace start_week = 48 if study_start <= date("29nov2020", "DMY")
replace start_week = 47 if study_start <= date("22nov2020", "DMY")
tab start_week, m
replace start_week = start_week-46
label define start_weekLab 1 "16Nov-22Nov" ///
2 "23Nov-29Nov" ///
3 "30Nov-06Dec" ///
4 "07Dec-13Dec" ///
5 "14Dec-20Dec" ///
6 "21Dec-27Dec" ///
7 "28Dec-03Jan" ///
8 "04Jan-11Jan"
label values start_week start_weekLab
tab start_week, m
* Recode small epi weeks 1 and 2 for epi week interaction
recode start_week 1=2, gen(start_weekA)
label define start_weekLabA 2 "16Nov-29Nov" ///
3 "30Nov-06Dec" ///
4 "07Dec-13Dec" ///
5 "14Dec-20Dec" ///
6 "21Dec-27Dec" ///
7 "28Dec-03Jan" ///
8 "04Jan-11Jan"
label values start_weekA start_weekLabA
tab start_week start_weekA
***************************
* Grouped comorbidities *
***************************
/* Neurological */
* Stroke and dementia
egen stroke_dementia = rowmax(stroke dementia)
order stroke_dementia, after(dementia_date)
/* Spleen */
* Spleen problems (dysplenia/splenectomy/etc and sickle cell disease)
egen spleen = rowmax(dysplenia sickle_cell)
order spleen, after(sickle_cell)
/* Cancer */
label define cancer 1 "Never" 2 "Last year" 3 "2-5 years ago" 4 "5+ years"
local fiveybefore = study_start-5*365.25
local oneybefore = study_start-365.25
* Haematological malignancies
gen cancer_haem_cat = 4 if inrange(haem_cancer_date, d(1/1/1900), `fiveybefore')
replace cancer_haem_cat = 3 if inrange(haem_cancer_date, `fiveybefore', `oneybefore')
replace cancer_haem_cat = 2 if inrange(haem_cancer_date, `oneybefore', study_start)
recode cancer_haem_cat . = 1
label values cancer_haem_cat cancer
* All other cancers
gen cancer_exhaem_cat = 4 if inrange(lung_cancer_date, d(1/1/1900), `fiveybefore') | ///
inrange(other_cancer_date, d(1/1/1900), `fiveybefore')
replace cancer_exhaem_cat = 3 if inrange(lung_cancer_date, `fiveybefore', `oneybefore') | ///
inrange(other_cancer_date, `fiveybefore', `oneybefore')
replace cancer_exhaem_cat = 2 if inrange(lung_cancer_date, `oneybefore', study_start) | ///
inrange(other_cancer_date, `oneybefore', study_start)
recode cancer_exhaem_cat . = 1
label values cancer_exhaem_cat cancer
* Put variables together
order cancer_exhaem_cat cancer_haem_cat, after(other_cancer_date)
/* Immunosuppression */
* Immunosuppressed:
* HIV, permanent immunodeficiency ever, OR
* temporary immunodeficiency or aplastic anaemia last year
gen temp1 = max(hiv, permanent_immunodeficiency)
gen temp2 = inrange(temporary_immunodeficiency_date, `oneybefore', study_start)
gen temp3 = inrange(aplastic_anaemia_date, `oneybefore', study_start)
egen other_immunosuppression = rowmax(temp1 temp2 temp3)
drop temp1 temp2 temp3
order other_immunosuppression, after(temporary_immunodeficiency)
/* Hypertension */
gen htdiag_or_highbp = bphigh
recode htdiag_or_highbp 0 = 1 if hypertension==1
************
* eGFR *
************
* Set implausible creatinine values to missing (Note: zero changed to missing)
replace creatinine = . if !inrange(creatinine, 20, 3000)
* Divide by 88.4 (to convert umol/l to mg/dl)
gen SCr_adj = creatinine/88.4
gen min=.
replace min = SCr_adj/0.7 if male==0
replace min = SCr_adj/0.9 if male==1
replace min = min^-0.329 if male==0
replace min = min^-0.411 if male==1
replace min = 1 if min<1
gen max=.
replace max=SCr_adj/0.7 if male==0
replace max=SCr_adj/0.9 if male==1
replace max=max^-1.209
replace max=1 if max>1
* egfr calculated using CKD-EPI formula with no eth
gen egfr=min*max*141
replace egfr=egfr*(0.993^age)
replace egfr=egfr*1.018 if male==0
* Categorise into ckd stages
* CKD stage calc without eth
egen egfr_cat = cut(egfr), at(0, 15, 30, 45, 60, 5000)
recode egfr_cat 0=5 15=4 30=3 45=2 60=0, generate(ckd)
* 0 = "No CKD" 2 "stage 3a" 3 "stage 3b" 4 "stage 4" 5 "stage 5"
label define ckd 0 "No CKD" 1 "CKD"
label values ckd ckd
* Convert into CKD group
*recode ckd 2/5=1, gen(chronic_kidney_disease)
*replace chronic_kidney_disease = 0 if creatinine==.
recode ckd 0=1 2/3=2 4/5=3, gen(reduced_kidney_function_cat)
replace reduced_kidney_function_cat = 1 if creatinine==.
label define reduced_kidney_function_catlab ///
1 "None" 2 "Stage 3a/3b egfr 30-60 " 3 "Stage 4/5 egfr<30"
label values reduced_kidney_function_cat reduced_kidney_function_catlab
*More detailed version incorporating stage 5 or dialysis as a separate category
recode ckd 0=1 2/3=2 4=3 5=4, gen(reduced_kidney_function_cat2)
replace reduced_kidney_function_cat2 = 1 if creatinine==.
replace reduced_kidney_function_cat2 = 4 if dialysis==1
label define reduced_kidney_function_cat2lab ///
1 "None" 2 "Stage 3a/3b egfr 30-60 " 3 "Stage 4 egfr 15-<30" 4 "Stage 5 egfr <15 or dialysis"
label values reduced_kidney_function_cat2 reduced_kidney_function_cat2lab
***********
* Hba1c *
***********
/* Diabetes severity */
* Set zero or negative to missing
replace hba1c_percentage = . if hba1c_percentage<=0
replace hba1c_mmol_per_mol = . if hba1c_mmol_per_mol<=0
local fifteenmbefore = study_start-15*(365.25/12)
* Only consider measurements in last 15 months
replace hba1c_percentage = . if hba1c_percentage_date < `fifteenmbefore'
replace hba1c_mmol_per_mol = . if hba1c_mmol_per_mol_date < `fifteenmbefore'
/* Express HbA1c as percentage */
* Express all values as perecentage
noi summ hba1c_percentage hba1c_mmol_per_mol
gen hba1c_pct = hba1c_percentage
replace hba1c_pct = (hba1c_mmol_per_mol/10.929)+2.15 if hba1c_mmol_per_mol<.
* Valid % range between 0-20
replace hba1c_pct = . if !inrange(hba1c_pct, 0, 20)
replace hba1c_pct = round(hba1c_pct, 0.1)
/* Categorise hba1c and diabetes */
* Group hba1c
gen hba1ccat = 0 if hba1c_pct < 6.5
replace hba1ccat = 1 if hba1c_pct >= 6.5 & hba1c_pct < 7.5
replace hba1ccat = 2 if hba1c_pct >= 7.5 & hba1c_pct < 8
replace hba1ccat = 3 if hba1c_pct >= 8 & hba1c_pct < 9
replace hba1ccat = 4 if hba1c_pct >= 9 & hba1c_pct !=.
label define hba1ccat 0 "<6.5%" 1">=6.5-7.4" 2">=7.5-7.9" 3">=8-8.9" 4">=9"
label values hba1ccat hba1ccat
tab hba1ccat
* Create diabetes, split by control/not
gen diabcat = 1 if diabetes==0
replace diabcat = 2 if diabetes==1 & inlist(hba1ccat, 0, 1)
replace diabcat = 3 if diabetes==1 & inlist(hba1ccat, 2, 3, 4)
replace diabcat = 4 if diabetes==1 & !inlist(hba1ccat, 0, 1, 2, 3, 4)
label define diabcat 1 "No diabetes" ///
2 "Controlled diabetes" ///
3 "Uncontrolled diabetes" ///
4 "Diabetes, no hba1c measure"
label values diabcat diabcat
* Delete unneeded variables
drop hba1c_pct hba1c_percentage hba1c_mmol_per_mol
******************************
* Aggregated comorbidities *
******************************
/*
Create a comorbidities variable based upon Fizz's JCVI work that has 0, 1, 2 or more of
the following comorbdities:
(1) respiratory disease, (2) severe asthma, (3) chronic cardiac disease, (4) diabetes,
(5) non-haematological cancer (diagnosed in last year), (6) haematological cancer (diagnosed within 5 years),
(7) liver disease, (8) stroke, (9) dementia, (10) poor kidney function, (11) organ transplant,
(12) asplenia, (13) other immunosuppression.
*/
*(1) respiratory disease
tab chronic_respiratory_disease
*think I need level "3" of this, as this is asthma that requires OCS
*(2) severe asthma
tab asthmacat
generate asthma_severe=0
replace asthma_severe=1 if asthmacat==3
tab asthma_severe
*(3) cardiac disease
tab chronic_cardiac_disease
*(4) diabetes
tab diabcat
tab diabcat, nolabel
generate dm=0
replace dm=1 if diabcat>1
tab dm
tab dm diabcat
*(5) non-haem cancer (in previous year)
tab cancer_exhaem
tab cancer_exhaem, nolab
generate cancer_nonhaemPrevYear=0
replace cancer_nonhaemPrevYear=1 if cancer_exhaem_cat==2
tab cancer_nonhaemPrevYear
*(6) haem cancer (within previous 5 years)
tab cancer_haem
tab cancer_haem, nolab
generate cancer_haemPrev5Years=0
replace cancer_haemPrev5Years=1 if inrange(cancer_haem_cat,2,3)
tab cancer_haemPrev5Years
*(7) liver disease
tab chronic_liver_disease
*(8 and 9) stroke or dementia
tab stroke_dementia
*(10) poor kidney function
tab reduced_kidney_function_cat2
tab reduced_kidney_function_cat2, nolabel
gen egfr60 = 0
replace egfr60 = 1 if reduced_kidney_function_cat2 > 1
tab egfr60 reduced_kidney_function_cat2
*(11) organ transplant
tab organ_transplant
*(12) asplenia
tab spleen
*(13) other immunosuppression
tab other_immuno
*create a total comborb var
order chronic_respiratory_disease asthma_severe chronic_cardiac_disease dm cancer_nonhaemPrevYear cancer_haemPrev5Years chronic_liver_disease stroke_dementia egfr60 organ_transplant spleen other_immuno
egen totComorbsOfInterest=rowtotal(chronic_respiratory_disease - other_immuno)
summ totComorbsOfInterest, d
order totComorbsOfInterest
*create the covariate var I need
generate comorb_cat=.
replace comorb_cat=0 if totComorbsOfInterest==0
replace comorb_cat=1 if totComorbsOfInterest==1
replace comorb_cat=2 if totComorbsOfInterest>1
label define comorb_catLab 0 "No comorbidity" ///
1 "1 comorbidity" ///
2 "2+ comorbidities"
label values comorb_cat comorb_catLab
tab comorb_cat, m
********************************
* Outcomes and survival time *
********************************
/* 28-day risk censoring dates */
noi di "REMEMBER TO UPDATE DATE OF ONS DATA UPLOAD"
gen ons_data_date = date("5may2021", "DMY")
gen ons_data_cens = ons_data_date-14 // Censor 14 days prior to ONS death data upload
gen risk_28_days = study_start+28
gen risk_40_days = study_start+40
* 28-day risk population
gen risk_pop = (risk_28_days <= ons_data_cens) // Indicator for has 28-days follow-up
gen time_check_28 = ons_data_cens-study_start
summ time_check_28 if risk_pop == 1, d
* 40-day risk population
gen risk_pop_40 = (risk_40_days <= ons_data_cens) // Indicator for has 40-days follow-up
gen time_check_40 = ons_data_cens-study_start
summ time_check_40 if risk_pop_40 == 1, d
/* Outcomes */
* 28-day risk indicator
gen died_pre_cens = (died_date_ons < ons_data_cens)
gen death_time = died_date_ons-study_start if died_pre_cens == 1
summ death_time, d
gen risk_28 = (death_time <= 28)
tab died_pre_cens risk_28, row
* 40-day risk indicator
gen risk_40 = (death_time <= 40)
tab died_pre_cens risk_40, row
/* Survival time */
* Censoring date for Cox
gen vacc_cens = covid_vacc_date - 7 if covid_vacc_date != .
gen cox_pop = (study_start < vacc_cens) // Exclude if vaccinated within 7 days
* Censor at death, ons data censor, or 7 days prior to vaccine
gen stime_death = min(died_date_ons, ons_data_cens, vacc_cens)
gen cox_death = (died_date_ons < .)
replace cox_death = 0 if (died_date_ons > stime_death)
gen cox_time = stime_death-study_start
gen cox_time_d = stime_death-study_start if cox_death==1
/* Hospital and ICU admission */
gen stime_hosp_test = min(covid_admission_date, dereg_date, vacc_cens)
gen end_hosp_test = (covid_admission_date < .)
replace end_hosp_test = 0 if (covid_admission_date > stime_hosp_test) // censor
gen time_hosp_test = stime_hosp_test-study_start
gen stime_icu_test = min(icu_admission_date, dereg_date, vacc_cens)
gen end_icu_test = (icu_admission_date < .)
replace end_icu_test = 0 if (icu_admission_date > stime_icu_test) // censor
gen time_icu_test = stime_icu_test-study_start
* Death given hospital
gen end_death_hosp = cox_death
gen time_death_hosp = (stime_death-covid_admission_date)+1