*! version 1.0 6 May 2024

Title

sccsdta -- Generating the dataset for the self-controlled case series method (SCCS)

Syntax

sccsdta
varlist(min=2
max=2)
[,
options]

Required
enter Start of the individual observation period.

It is a variable name or a number.

exit Stop of the individual observation period.

It is a variable name or a number.

It is also the end point of the last interval.

riskpoints(numlist sort) End points of intervals at risk.

First value is the starting point of the first at risk interval.

The rest of the values are the last point of an at risk interval.

All intervals include their last end points.

Optional
timepoints(numlist sort) Interval end points for time dependence.

The first time interval starts with enter.

The last time interval ends with exit.

All intervals include their last end points.

id(varname) A variable for the participants id.

Description

The SCCS method examines the association between a time-varying exposure
and an event outcome.

The study samples only cases, and it requires that an event has occurred during
the observation period.

The method doesn't compare incidences for cases with incidences for references.

Instead, it contrasts incidences in periods of risk with incidences in periods
where the case is not at risk.

In this approach, cases serve as their control for fixed confounders.

It's feasible to adjust for time effects such as age.

The intervals are marked by risk, time, and individual.

For each interval, the number of incidences and the width of the interval are
determined.

Examples

Case 3.1 in 2005 Whitaker

Hospital records indicate a association between MMR vaccination and viral meningitis.

Specifically, the use of a certain live mumps vaccine, known as the Urabe strain,
has been linked to an increased risk of viral meningitis.

Instances of viral meningitis were identified in 10 children during their second
year of life.

Get a dataset with an event day (day of meningitis) and a day for exposure
(day of vaccination):

//sccs-studies.info/uploads/1/1/6/4/116436421/oxford.dta", clear"'

This dataset is readable from version 15.1. A version 12 dataset sccsdta mmr.dta with the same data is in the package.

Case 3.1 in 2005 Whitaker continued

The observation period was from the 366th to the 730th day of age.

Evidence led to the definition of the risk period as the 15th to the 35th day
following the administration of the MMR vaccine.

Age groups were 366 to 547 days and 548 to 730 days.

Generate the SCCS dataset:

`". sccsdta eventday exday, enter(365) exit(730) riskpoints(14 35) timepoints(547)"'

We estimate the incidence rate ratio of the risk period versus the no
risk period using a poisson regression and looking at the i._exgr estimate:

`". poisson _nevents i._exgr i._tmgr i._id, exposure(_interval) irr"'

Compare the i._exgr estimate with the Stata output at page 11 in
2005 Whitaker.

We get a better estimate report using the command regmat
(ssc install matrixtools - works for version 13.1)

`". regmat, o(_nevents) e(i._exgr) a("i._tmgr i._id") eform d(3) label btext(irr) names("") base: poisson, exposure(_interval)"'

-----------------------------------------------------------------------------------
irr se(irr) Lower 95% CI Upper 95% CI P value
-----------------------------------------------------------------------------------
Events(#) At risk (no) 1.000
At risk (]14; 35]) 12.037 2.031 3.002 48.259 0.000
-----------------------------------------------------------------------------------

Conclusion

The incidence rate in the risk period is around 12 times higher
than in the no-risk period.

Hence, there is a a association between MMR vaccination and viral meningitis.

Stored results

Created variables

_start Interval start value (not included in interval)

_stop Interval stop value (included in interval)

_nevents Number of events per individual in interval

_exgr Intervals marked by risk groups

_tmgr Intervals marked by time groups

_interval Interval width (the exposure)

References

2005 Whitaker - Tutorial in biostatistics; The self-controlled case series method

2016 Petersen - Self controlled case series methods; An alternative to standard epidemiological study designs

Authors and support

Author:

Niels Henrik Bruun,

Aalborg University Hospital

Support:

niels.henrik.bruun@gmail.com