Cox L A
Cox Associates, Denver, Colorado 80218, USA.
Risk Anal. 1995 Jun;15(3):359-68. doi: 10.1111/j.1539-6924.1995.tb00329.x.
The traditional multistage (MS) model of carcinogenesis implies several empirically testable properties for dose-response functions. These include convex (linear or upward-curving) cumulative hazards as a function of dose; symmetric effects on lifetime tumor probability of transition rates at different stages; cumulative hazard functions that increase without bound as stage-specific transition rates increase without bound; and identical tumor probabilities for individuals with identical parameters and exposures. However, for at least some chemicals, cumulative hazards are not convex functions of dose. This paper shows that none of these predicted properties is implied by the mechanistic assumptions of the MS model itself. Instead, they arise from the simplifying "rare-tumor" approximations made in the usual mathematical analysis of the model. An alternative exact probabilistic analysis of the MS model with only two stages is presented, both for the usual case where a carcinogen acts on both stages simultaneously, and also for idealized initiation-promotion experiments in which one stage at a time is affected. The exact two-stage model successfully fits bioassay data for chemicals (e.g., 1,3-butadiene) with concave cumulative hazard functions that are not well-described by the traditional MS model. Qualitative properties of the exact two-stage model are described and illustrated by least-squares fits to several real datasets. The major contribution is to show that properties of the traditional MS model family that appear to be inconsistent with empirical data for some chemicals can be explained easily if an exact, rather than an approximate model, is used. This suggests that it may be worth using the exact model in cases where tumor rates are not negligible (e.g., in which they exceed 10%). This includes the majority of bioassay experiments currently being performed.
传统的多阶段致癌模型意味着剂量反应函数具有几个可通过实验验证的特性。这些特性包括作为剂量函数的凸形(线性或向上弯曲)累积风险;不同阶段的转变率对终生肿瘤概率的对称影响;随着阶段特异性转变率无界增加而无界增加的累积风险函数;以及具有相同参数和暴露的个体具有相同的肿瘤概率。然而,至少对于某些化学物质而言,累积风险并非剂量的凸函数。本文表明,这些预测特性均不是多阶段模型本身的机制假设所隐含的。相反,它们源于在该模型的常规数学分析中所做的简化“罕见肿瘤”近似。本文给出了仅包含两个阶段的多阶段模型的另一种精确概率分析,既适用于致癌物同时作用于两个阶段的常规情况,也适用于理想化的启动 - 促进实验,即每次只影响一个阶段的情况。精确的两阶段模型成功拟合了传统多阶段模型无法很好描述的具有凹形累积风险函数的化学物质(例如1,3 - 丁二烯)的生物测定数据。通过对几个实际数据集的最小二乘法拟合来描述和说明精确两阶段模型的定性特性。主要贡献在于表明,如果使用精确模型而非近似模型,那么传统多阶段模型家族中那些似乎与某些化学物质的实验数据不一致的特性就很容易得到解释。这表明在肿瘤发生率不可忽略(例如超过10%)的情况下,使用精确模型可能是值得的。这包括目前正在进行的大多数生物测定实验。