Understanding the association between mixtures of environmental toxicants and time-to-pregnancy (TTP) is an important scientific question as sufficient evidence has emerged about the impact of individual toxicants on reproductive health and that individuals are exposed to a whole host of toxicants rather than an individual toxicant. Assessing mixtures of chemicals effects on TTP poses significant statistical challenges, namely (i) TTP being a discrete survival outcome, typically subject to left truncation and right censoring, (ii) chemical exposures being strongly correlated, (iii) accounting for some chemicals that bind to lipids, (iv) non-linear effects of some chemicals, and (v) high percentage concentration below the limit of detection (LOD) for some chemicals. We propose a discrete frailty modeling framework (named Discnet) that allows selection of correlated exposures while addressing the issues mentioned above. Discnet is shown to have better and stable FN and FP rates compared to alternative methods in various simulation settings. We did a detailed analysis of the LIFE Study, pertaining to polychlorinated biphenyls and time-to-pregnancy and found that older females, female exposure to cotinine (smoking), DDT conferred a delay in getting pregnant, which was consistent across prior sensitivity analyses to account for LOD as well as non-linear associations.
翻译:对环境有毒物质混合物和时间到怀孕(TTP)之间联系的理解是一个重要的科学问题,因为已经就个别有毒物质对生殖健康的影响提出了充分的证据,而且个人暴露于全部有毒物质而不是个别有毒物质,因此,评估化学品混合物对TTP的影响带来了重大的统计挑战,即(一) TTP是一种离散的生存结果,通常会左转和右审查,(二) 化学品接触密切相关,(三) 核算某些与脂质捆绑在一起的化学品,(四) 某些化学品的非线性影响,以及(五) 某些化学品的高浓度低于检测限度(LOD),我们提议建立一个离散的脆弱模型框架(名为Discnet),允许在解决上述问题的同时选择相关的接触。