Division of Psychiatry, University of Western Australia, Crawley, Western Australia, 6009, Australia.
School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia.
BMC Cancer. 2021 Feb 25;21(1):197. doi: 10.1186/s12885-021-07924-3.
Age-adjusted US total pediatric cancer incidence rates (TPCIR) rose 49% 1975-2015 for unknown reasons. Prenatal cannabis exposure has been linked with several pediatric cancers which together comprise the majority of pediatric cancer types. We investigated whether cannabis use was related spatiotemporally and causally to TPCIR.
State-based age-adjusted TPCIR data was taken from the CDC Surveillance, Epidemiology and End Results cancer database 2003-2017. Drug exposure was taken from the nationally-representative National Survey of Drug Use and Health, response rate 74.1%. Drugs included were: tobacco, alcohol, cannabis, opioid analgesics and cocaine. This was supplemented by cannabinoid concentration data from the Drug Enforcement Agency and ethnicity and median household income data from US Census.
TPCIR rose while all drug use nationally fell, except for cannabis which rose. TPCIR in the highest cannabis use quintile was greater than in the lowest (β-estimate = 1.31 (95%C.I. 0.82, 1.80), P = 1.80 × 10) and the time:highest two quintiles interaction was significant (β-estimate = 0.1395 (0.82, 1.80), P = 1.00 × 10). In robust inverse probability weighted additive regression models cannabis was independently associated with TPCIR (β-estimate = 9.55 (3.95, 15.15), P = 0.0016). In interactive geospatiotemporal models including all drug, ethnic and income variables cannabis use was independently significant (β-estimate = 45.67 (18.77, 72.56), P = 0.0009). In geospatial models temporally lagged to 1,2,4 and 6 years interactive terms including cannabis were significant. Cannabis interactive terms at one and two degrees of spatial lagging were significant (from β-estimate = 3954.04 (1565.01, 6343.09), P = 0.0012). The interaction between the cannabinoids THC and cannabigerol was significant at zero, 2 and 6 years lag (from β-estimate = 46.22 (30.06, 62.38), P = 2.10 × 10). Cannabis legalization was associated with higher TPCIR (β-estimate = 1.51 (0.68, 2.35), P = 0.0004) and cannabis-liberal regimes were associated with higher time:TPCIR interaction (β-estimate = 1.87 × 10, (2.9 × 10, 2.45 × 10), P = 0.0208). 33/56 minimum e-Values were > 5 and 6 were infinite.
Data confirm a close relationship across space and lagged time between cannabis and TPCIR which was robust to adjustment, supported by inverse probability weighting procedures and accompanied by high e-Values making confounding unlikely and establishing the causal relationship. Cannabis-liberal jurisdictions were associated with higher rates of TPCIR and a faster rate of TPCIR increase. Data inform the broader general consideration of cannabinoid-induced genotoxicity.
1975 年至 2015 年,美国儿科癌症总发病率(TPCIR)在调整年龄后上升了 49%,原因不明。产前大麻暴露与几种儿科癌症有关,这些癌症共同构成了大多数儿科癌症类型。我们调查了大麻使用是否与 TPCIR 在时空上有关,并存在因果关系。
从疾病预防控制中心监测、流行病学和最终结果癌症数据库(2003-2017 年)获取基于州的年龄调整 TPCIR 数据。药物暴露情况取自全国代表性的国家药物使用和健康调查,应答率为 74.1%。包括的药物有:烟草、酒精、大麻、阿片类镇痛药和可卡因。此外,还补充了来自毒品执法局的大麻素浓度数据以及来自美国人口普查局的种族和家庭中位数收入数据。
TPCIR 上升,而全国所有药物使用都下降,只有大麻上升。在大麻使用最高的五分位数中,TPCIR 高于最低五分位数(β 估计值=1.31(95%CI,0.82,1.80),P=1.80×10),并且时间:最高两个五分位数的交互作用具有统计学意义(β 估计值=0.1395(0.82,1.80),P=1.00×10)。在稳健的逆概率加权加性回归模型中,大麻与 TPCIR 独立相关(β 估计值=9.55(3.95,15.15),P=0.0016)。在包括所有药物、种族和收入变量的交互式地理时空模型中,大麻的使用具有统计学意义(β 估计值=45.67(18.77,72.56),P=0.0009)。在包括时间滞后 1、2、4 和 6 年的地理空间模型中,包括大麻的交互项具有统计学意义。大麻的一和二阶空间滞后交互项具有统计学意义(从β估计值=3954.04(1565.01,6343.09),P=0.0012)。大麻素 THC 和大麻二醇之间的相互作用在零、2 和 6 年的滞后时间上具有统计学意义(从β估计值=46.22(30.06,62.38),P=2.10×10)。大麻合法化与 TPCIR 升高有关(β 估计值=1.51(0.68,2.35),P=0.0004),大麻宽松制度与时间:TPCIR 交互作用升高有关(β 估计值=1.87×10,(2.9×10,2.45×10),P=0.0208)。33/56 个最小 e-值大于 5,6 个无穷大。
数据证实大麻与 TPCIR 之间存在密切的时空关系,且经过反概率加权程序的调整后仍然具有稳健性,并伴有高 e-值,这使得混杂因素不太可能发生,并确定了因果关系。大麻宽松制度与更高的 TPCIR 率和更快的 TPCIR 增长率有关。数据为大麻素诱导的遗传毒性的更广泛的一般考虑提供了信息。