Background: Cannabis use is increasing, including among smokers, an at-risk population for cancer. Research is equivocal on whether using cannabis inhibits quitting cigarettes. The current longitudinal study investigated associations between smoking cannabis and subsequently quitting cigarettes. Methods: Participants were 4,535 adult cigarette smokers from a cohort enrolled in the American Cancer Society’s Cancer Prevention Study-3 in 2009–2013. Cigarette quitting was assessed on a follow-up survey in 2015–2017, an average of 3.1 years later. Rates of quitting cigarettes at follow-up were examined by retrospectively assessed baseline cannabis smoking status (never, former, recent), and by frequency of cannabis smoking among recent cannabis smokers (low: ≤3 days/month; medium: 4–19 days/month; high: ≥20 days/month). Logistic regression models adjusted for sociodemographic factors, smoking- and health-related behaviors, and time between baseline and follow-up. Results: Adjusted cigarette quitting rates at follow-up did not differ significantly by baseline cannabis smoking status [never 36.2%, 95% confidence interval (CI), 34.5–37.8; former 34.1%, CI, 31.4–37.0; recent 33.6%, CI, 30.1–37.3], nor by frequency of cannabis smoking (low 31.4%, CI, 25.6–37.3; moderate 36.7%, CI, 30.7–42.3; high 34.4%, CI, 28.3–40.2) among recent baseline cannabis smokers. In cross-sectional analyses conducted at follow-up, the proportion of cigarette smokers intending to quit smoking cigarettes in the next 30 days did not differ by cannabis smoking status (P ¼ 0.83). Conclusions: Results do not support the hypothesis that cannabis smoking inhibits quitting cigarette smoking among adults. Impact: Future longitudinal research should include follow-ups of >1 year, and assess effects of intensity/frequency of cannabis use and motivation to quit on smoking cessation.

Genome-wide association studies (GWAS) have led to the identification of hundreds of susceptibility loci across cancers, but the impact of further studies remains uncertain. Here we analyse summary-level data from GWAS of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) and underlying effect-size distribution. All cancers show a high degree of polygenicity, involving at a minimum of thousands of loci. We project that sample sizes required to explain 80% of GWAS heritability vary from 60,000 cases for testicular to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores (PRS), compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that PRS have potential for risk stratification for cancers of breast, colon and prostate, but less so for others because of modest heritability and lower incidence.