TobLags.RdPrepare the disease specific functions that describe how a change in tobacco consumption gradually has an effect on the relative risk of disease incidence over time (up to 40 years) since e.g. someone quit smoking
TobLags(
disease_name = c("Pharynx", "Oral_cavity"),
n_years = 40,
lag_data = tobalcepi::tobacco_lag_times,
other_lag_function = "Cancers"
)Character - the name of the disease under consideration.
Integer - the number of years from 1 to n over which the effect of a change in consumption emerges. Defaults to 40 years to fit with the current lag data.
Data table containing the numerical description of the lag function. The data table "tobacco lag times" is embedded within the stapmr package.
Character - the name of the lag function to use for tobacco related conditions that are not categorised as CVD, COPD, or Cancer. Options: c("Cancers", "CVD", "COPD", "immediate"). The default is "Cancers", which gives the most conservative (i.e. slowest) estimate of the rate of decline in the risk of disease after quitting smoking.
Returns a data table with two columns - one for the years since consumption changed, and the other that gives the proportion by which the effect of a change in consumption on an individual's relative risk of disease has so far emerged.
All lag times are taken from a re-analysis of the Cancer prevention II study by Oza et al. (2011) and Kontis et al. (2014) . The values were sent to us on request by Kontis. Lags are smoothed functions over time describing the proportion of the excess risk due to smoking that still remains.
Kontis et al. re-analysed the change in risk after smoking in the ACS-CPS II study from Oza et al., producing three functions to describe the decline in risk after quitting for each of cancers, CVD and COPD. The estimates were informed by data on former smokers with known quit dates who were disease-free at baseline. The results show the proportion of excess relative risk remaining at each time-point since cessation. A cross-check showed that the figures for cancers were broadly consistent with the findings of the International Agency for Research on Cancer's (IARC) 2007 review of the decline in risk after quitting smoking.
The remaining question is how risk declines after quitting smoking for diseases that are not cancers, CVD or COPD. Kontis et al. state that "Randomised trials also indicate that the benefits of behaviour change and pharmacological treatment on diabetes risk occur within a few years, more similar to the CVDs than cancers. Therefore, we used the CVD curve for diabetes." In-line with Kontis, we apply the rate of decline in risk of CVD after quitting smoking to type 2 diabetes. For all remaining conditions we apply the most conservative estimate available and assume that the decline in risk follows the cancer estimate provided by Kontis et al., as this has the slowest decline in risk.
Kontis V, Mathers CD, Rehm J, Stevens GA, Shield KD, Bonita R, Riley LM, Poznyak V, Beaglehole R, Ezzati M (2014). “Contribution of six risk factors to achieving the 25× 25 non-communicable disease mortality reduction target: a modelling study.” The Lancet, 384(9941), 427-437. ISSN 0140-6736.
Oza S, Thun MJ, Henley SJ, Lopez AD, Ezzati M (2011). “How many deaths are attributable to smoking in the United States? Comparison of methods for estimating smoking-attributable mortality when smoking prevalence changes.” Preventive medicine, 52(6), 428-433. ISSN 0091-7435.
if (FALSE) {
TobLags("Pharynx")
TobLags("Low_back_pain", other_lag_function = "immediate")
TobLags("Low_back_pain", other_lag_function = "CVD")
TobLags("Low_back_pain", other_lag_function = "Cancers")
}