Stochasticity in Physiologically Based Kinetics Models: Implications for Cancer Risk Assessment

In case of low-dose exposure to a substance, its concentration in cells is likely to be stochastic. Assessing the consequences of this stochasticity in toxicological risk assessment requires the coupling of macroscopic dynamics models describing whole-body kinetics with microscopic tools designed to simulate stochasticity. In this article, we propose an approach to approximate stochastic cell concentration of butadiene in the cells of diverse organs. We adapted the dynamics equations of a physiologically based pharmacokinetic (PBPK) model and used a stochastic simulator for the system of equations that we derived. We then coupled kinetics simulations with a deterministic hockey stick model of carcinogenicity. Stochasticity induced substantial modifications relative to dose-response curve, compared with the deterministic situation. In particular, there was nonlinearity in the response and the stochastic apparent threshold was lower than the deterministic one. The approach that we developed could easily be extended to other biological studies to assess the influence of stochasticity at macroscopic scale for compound dynamics at the cell level.     

An ecological investigation of the incidence of cancer in Welsh children for the period 1985–1994 in relation to residence near the coastline

An alarming report from an environmental pressure group raised concerns about childhood leukaemia and the Irish Sea. In response, this ecological study explores the hypotheses that childhood cancer rates are increased by living near the coast of Wales, especially in the north, and in particular near estuaries and mud-flats. Using Poisson regression to adjust for possible confounding variables, no evidence was found for a coastline proximity effect at the level of census wards (5 km). Moreover the rates were significantly lower near estuaries than for the rest of the coast, but there was a small but non-significant increase near mud-flats. Case–control modelling of postcoded cases living within the coastal wards using Stone's method also failed to detect any monotonic reduction in relative risk near the coastline.     

The Value of Reducing Cancer Risks at Contaminated Sites: Are More Knowledgeable People Willing to Pay More?

We use conjoint choice questions to investigate people's tastes for cancer risk reductions and income in the context of public programs that would provide for remediation at abandoned industrial contaminated sites. Our survey was self-administered using the computer by persons living in the vicinity of an important contaminated site on the Italian National Priority List. The value of a prevented case of cancer is €2.6 million, but this figure does vary with income, perceived exposure to contaminants, and respondent opinions about priorities that should be pursued by cleanup programs.     

Bayesian assessment of times to diagnosis in breast cancer screening

Breast cancer is one of the diseases with the most profound impact on health in developed countries and mammography is the most popular method for detecting breast cancer at a very early stage. This paper focuses on the waiting period from a positive mammogram until a confirmatory diagnosis is carried out in hospital. Generalized linear mixed models are used to perform the statistical analysis, always within the Bayesian reasoning. Markov chain Monte Carlo algorithms are applied for estimation by simulating the posterior distribution of the parameters and hyperparameters of the model through the free software WinBUGS.     

Building multivariable prognostic and diagnostic models: transformation of the predictors by using fractional polynomials

To be useful to clinicians, prognostic and diagnostic indices must be derived from accurate models developed by using appropriate data sets. We show that fractional polynomials, which extend ordinary polynomials by including non-positive and fractional powers, may be used as the basis of such models. We describe how to fit fractional polynomials in several continuous covariates simultaneously, and we propose ways of ensuring that the resulting models are parsimonious and consistent with basic medical knowledge. The methods are applied to two breast cancer data sets, one from a prognostic factors study in patients with positive lymph nodes and the other from a study to diagnose malignant or benign tumours by using colour Doppler blood flow mapping. We investigate the problems of biased parameter estimates in the final model and overfitting using cross-validation calibration to estimate shrinkage factors. We adopt bootstrap resampling to assess model stability. We compare our new approach with conventional modelling methods which apply stepwise variables selection to categorized covariates. We conclude that fractional polynomial methodology can be very successful in generating simple and appropriate models.     

肝癌患者个体特征、症状困扰对疾病不确定感的影响

应用自行设计的个体特征奈目、症状困扰量表（SDS）和疾病不确定感量表（MUIS）对71例肝癌患者进行调查。结果显示，肝癌患者在住院期间的疾病不确定感属于中等的程度．“疲惫”为其症状困扰之最；栓塞次数及酒精注射次数与疾病不确定感呈负相关（P〈0．05），症状困扰与整体不确定感及“不明确性”雏度呈正相关（P〈0．01）。     

Examining Associations between Occupation and Health by using Routinely Collected Data

When examining a large number of associations simultaneously, as happens when routinely collected data are used to assess associations between occupation and health, it is not obvious how best to identify associations requiring further investigation since some risks may be high, or low, by chance alone. We have developed an approach to deal with this problem which is relatively easy to apply and appropriate to applications where data are not too sparse. Observed to expected ratios are estimated using an empirical Bayes procedure. Anomalous associations can be seen as outliers in a normal probability plot of the log-ratios. The method is illustrated in the analysis of 252 000 cancers registered in men in England during 1981–87.     

How Tautological Are Interspecies Correlations of Carcinogenic Potencies?

Crouch and Wilson demonstrated a strong correlation between carcinogenic potencies in rats and mice, supporting the extrapolation from mouse to man. Bernstein et al. , however, show that the observed correlation is mainly a statistical artifact of bioassay design. Crouch et al. have a comeback. This paper will review the arguments and present some new data. The correlation is largely (but not totally) tautological, confirming results in Bernstein et al.     

Ambiguous carcinogens and their regulation

Examination of five animal and one human studies suggest that certain agents increase the incidence of some cancers but simultaneously reduce the incidence of other cancers. Yellow die #3, for example, sharply increases the incidence of liver tumors but practically eliminates naturally occurring leukemia/lymphoma in F-344 male rates. Such ambiguity in the action of presumed carcinogens suggests that caution must be used by regulatory bodies in proscribing suspected carcinogens, or even in recommending changes in lifestyle or dietary habits as a means of reducing incidence of cancer.     

Biological Models of Carcinogenesis and Quantitative Cancer Risk Assessment

Biologically-based models of carcinogenesis were originally developed to explain certain quanti-tative phenomena associated with carcinogenesis, and to provide a framework within which questions regarding the process could be addressed. Some limitations in the use of these models for quantitative cancer risk assessment are discussed.