Predicted risk of lung cancer based on the UK Biobank risk prediction model

This repository provides Stata code to calculate the predicted risk of
lung cancer based on supplied information and the UK Biobank risk
prediction model.

How to use this code

You will need a copy of Stata, version 12 or higher, with the
user-written commands stpm2 and rcsgen installed (ssc install stpm2, ssc install rcsgen). Open stata
and change directory to the root of this repository. Running

do predict_lca_risk.do

will calculate the predicted risk of lung cancer. By default this will
take covariate information from the file 'input.csv', calculate the
2-year cumulative probability of lung cancer for each record therein,
and save the results in the file 'output.csv'. These default input,
output, and time-horizons can be changed by editing the parameters in
the configuration block at the beginning of the file
'predict_lca_risk.do'.

Input specification

The input file must be an ASCII plain text CSV file, and must contain
the following variables:

variable name	description	type	valid values
age	age in years	real	[40,70]
smoke_stat	smoking status	integer	0 (never smoker), 1 (former smoker), 2 (current smoker)
male	male sex	integer	0 (female), 1 (male)
previous_cancer	Previously diagnosed with an invasive cancer	integer	0 (no), 1 (yes)
fhist_lungca	one or more first-degree relatives who have been diagnosed with lung cancer	integer	0 (no), 1 (yes)
emph_bronch	history of emphysema or bronchitis	integer	0 (no), 1 (yes)
allergy	history of hayfever, allergic rhinitis, or eczema	integer	0 (no), 1 (yes)
fev1_max	forced expiratory volume in one second (FEV1)	real	[0.5,10]
smkfmr_quitage	for former smokers only, the age at which they quit	real	less than current age
ncig	for current and former smokers only, the average number of cigarettes smoked per day	real	(0,80]
stop1day_easy	for current smokers only, how difficult would it be to not smoke for one day	integer	0 (difficult or very difficult), 1 (easy or very easy)

Other variables can be included in the input file, but they are
ignored by the program.

Output file

The output file contains the same variables as the input file, with
the addition of the variable 'cif_lung' which contains the predicted
probability (Cumulative Incidence Function evaluated at a given time
horizon) for each input observation.