In our large pooled analysis, we confirmed results from previous studies showing that smoking is associated with increased risk of colorectal cancer. Excess risks remained up to about 25 years after quitting smoking, but risk starts to decline immediately after quitting smoking for proximal colon and rectal cancer and about 20 years later for distal colon cancer. Further, we observed marginal statistically significant additive interactions of smoking with both BMI and fruit consumption.
There remains debate in the literature about the impact of time since quitting smoking on risk of colorectal cancer. Some studies have suggested that excess risk of colorectal cancer persists indefinitely among former smokers (14
), whereas other studies have suggested that the higher risk of colorectal cancer for former smokers is attenuated and eventually becomes comparable to that of never smokers (11
); however, results are not consistent on when the risk starts to decline and when the excess risk is fully eliminated. When we evaluated this questions consistently across studies, we found that compared to current smokers, former smokers experienced a lower risk of colorectal cancer soon after quitting, although they still had a higher risk compared to never smokers up to about 25 years since quitting. Further, we observed differences in this pattern by cancer subsite: risk started to decline among former smokers right after quitting smoking for proximal colon and rectal cancer and about 20 years later for distal colon cancer. Growing evidence suggests that there are the substantial subsite differences in colorectal cancer by genetic etiology, gene expression, molecular pathogenesis, and protein profiles.(2
) These disparities may contribute to the observed different associations with time since quitting by cancer subsite. In particular, recent studies have indicated that smoking is more strongly associated with a particular molecular phenotype of colorectal tumors, those that are microsatellite instability (MSI) high and possess mutations in the BRAF gene (37
), as well as with the relevant precursor lesions.(39
) As these tumors are seen more frequently in the proximal than in the distal colon (35
), smoking cessation may benefit proximal more than distal tumors. As we observed, however, our failure to find different risks associated with smoking in the distal and proximal colon suggests that additional factors may be involved. Further research is required to explore the mechanism underlying the difference in our findings by cancer subsite. Our large pooled analysis suggests that the risk in former smokers remains increased for a long time compared to never smokers.
It has been suggested that pack-years of smoking, a combination of smoking intensity and duration, may misrepresent the individual effects of these two characteristics because they may not equally contribute to disease risk.(40
) Thus, we evaluated the effects of smoking intensity and duration separately while controlling one variable for the other. Our results suggested that both duration and intensity increased colorectal cancer risk and that patterns with both variables appeared nonlinear. This non-linear plateau effect is consistent with some previous studies (12
) and has been observed for other cancers (e.g. lung, liver, kidney, pancreas, and bladder cancer (43
)). This finding may point to potential molecular mechanisms such as saturation of smoking-derived carcinogen activation pathways.(45
We were able to investigate interactions of smoking with various environmental risk factors. We observed statistical evidence for additive interaction between fruit intake and smoking status on risk of colorectal cancer. An interaction with plant foods has been reported for other cancers as well (e.g. lung cancer (47
) and pancreatic cancer (48
)). The potential biological mechanism for this interaction may be that anticarcinogenic components in fruits modify the effects of smoking through reducing DNA damage and mutation from smoking carcinogens (49
). We also found a borderline statistically significant additive interaction between BMI and smoking status. The biologic mechanism for the interaction between BMI and smoking status is unclear, but possible explanations include the pro-oxidant and inflammatory effects of increased insulin, glucose, insulin-like growth factors (IGF), and related compounds that accompany overweight and obesity which, in turn, may enhance the rate of accumulation of DNA damage due to smoking (50
), and that immunosuppressive effects of specific free fatty acids (FFA) from adipocytes may increase the susceptibility to cancer triggered by smoking.(51
) However, given the marginal significance of our findings, it will be important that these results are replicated in other large studies, such as available in the Cohort Consortium.(52
) We note that when exploring interactions on the multiplicative scale we observed no interaction. Rothman and others (53
) have remarked that assessment of interaction should mainly be based on an additive scale and it has been illustrated that under causal pie models biological interaction results in departure from additivity of disease rates.(55
This pooled analysis has several strengths, including the large sample size and the availability of individual-level data from each study on detailed smoking exposures, major confounders, and potential effect modifiers. The availability of individual data permitted us to consistently and flexibly evaluate exposure-disease relationship, potential confounding, and interaction effects. We observed little evidence for heterogeneity and risk estimates overall did not vary substantially between studies. Our results were not dominated by a single study and did not vary by study design (case-control vs. cohort studies).
There are also some limitations to this analysis. Because we restricted the analysis to non-Hispanic white participants with available DNA as the parent-study from which these data were drawn (GECCO) is focused on genetic and environmental factors, it is likely that our study populations do not represent the full range of social-economic status or racial and ethnic groups. However, effect estimates of smoking status and the relationship with pack-years are consistent with those from previous meta-analyses.(9
) Additionally, similar association between CRC and smoking was observed in Asians.(56
) Case-control studies could be affected by recall bias. However, studies showed that recalled information on tobacco use is valid and reliable (58
) and furthermore, results from case-control and cohort studies were similar. The reference time at which smoking exposure was assessed for HPFS and NHS was at time of blood draw rather than time of enrollment. Accordingly, prevalent cases may bias smoking effect estimates in the two studies. Nevertheless, dropping prevalent cases (n=91) in these two studies did not influence our results. Due to the difference in study design, current smoking was defined differently in cohort vs. case-control studies. However, this has not led to obvious heterogeneity in results. We adjusted for BMI as a potential confounder in our study but BMI could be either a confounder or a mediator of the association between smoking and CRC given the impact of smoking on BMI. However, the results without adjustment for BMI are similar to those with BMI adjustment and our conclusions don’t change. When evaluating additive interaction, we used asymptotic variance estimates from linear odds ratio models in meta-analysis approach and calculated Wald-type confidence intervals for pooled estimates of additive interaction effects. Some researchers indicated that Wald-type confidence interval based on asymptotic variance may have poor coverage at typical sample size and likelihood-based confidence interval may be preferred.(60
) However, studies showed that in large sample sizes or at disease prevalence below 10%, Wald-type confidence interval works well and is similar to likelihood-based confidence interval.(30
In summary, our findings confirmed previous results of positive association between smoking and colorectal cancer. We evaluated the effect of time since quitting smoking in detail and found that the increased risk persisted for about 25 years after quitting smoking; however, risk started to decline immediately after quitting smoking for proximal colon and rectal cancer and about 25 year later for distal colon cancer. The observed effect modification of smoking and colorectal cancer by BMI and fruit consumption, if replicated in future independent studies, could contribute to better understanding of the mechanisms and potentially improving strategies for colorectal cancer prevention.