Pleural mesothelioma and lung cancer risks in relation to occupational history and asbestos lung burden.

BACKGROUND: We have conducted a population-based study of pleural mesothelioma patients with occupational histories and measured asbestos lung burdens in occupationally exposed workers and in the general population. The relationship between lung burden and risk, particularly at environmental exposure levels, will enable future mesothelioma rates in people born after 1965 who never installed asbestos to be predicted from their asbestos lung burdens. METHODS: Following personal interview asbestos fibres longer than 5 µm were counted by transmission electron microscopy in lung samples obtained from 133 patients with mesothelioma and 262 patients with lung cancer. ORs for mesothelioma were converted to lifetime risks. RESULTS: Lifetime mesothelioma risk is approximately 0.02% per 1000 amphibole fibres per gram of dry lung tissue over a more than 100-fold range, from 1 to 4 in the most heavily exposed building workers to less than 1 in 500 in most of the population. The asbestos fibres counted were amosite (75%), crocidolite (18%), other amphiboles (5%) and chrysotile (2%). CONCLUSIONS: The approximate linearity of the dose-response together with lung burden measurements in younger people will provide reasonably reliable predictions of future mesothelioma rates in those born since 1965 whose risks cannot yet be seen in national rates. Burdens in those born more recently will indicate the continuing occupational and environmental hazards under current asbestos control regulations. Our results confirm the major contribution of amosite to UK mesothelioma incidence and the substantial contribution of non-occupational exposure, particularly in women

Bladder cancer mortality of workers exposed to aromatic amines: analysis of models of carcinogenesis.

The effects of various factors were evaluated on both relative risk (multiplicative model), and absolute excess risk (additive model) of bladder cancer among 664 workers of a dyestuff factory in Northern Italy. These workers were exposed to aromatic amines in fairly constant working conditions from 1922 to 1970, and were employed for at least one year. They were followed up till the end of 1981 for a total of 12,302 man-years at risk. Under both models, the risk was greater for workers directly involved in aromatic amine manufacture than for those with only intermittent exposure. There was no marked effect of age at first exposure on the absolute excess risk of bladder cancer, but the relative risk was strongly and negatively related to age at first exposure. Under the multistage theory of carcinogenesis, this pattern of risk indicates an early stage effect. Absolute excess risk increased sharply during exposure, and continued to rise, although less sharply, after exposure had ceased. Relative risk, however, decreased after cessation of exposure, indicating a possible late stage effect. Thus, the results derived from both additive and multiplicative models are not in contrast when interpreted in terms of the multistage theory of carcinogenesis, though they are not totally consistent with a single-stage effect, either early or late. Aromatic amines may act on a stage somewhere between the first and penultimate, or on more than one stage of the process of carcinogenesis. Alternatively, it is possible that imprecision in the job classification or other observational problems may obscure the trends, or produce fictitious trends in the effects of variables such as age at first exposure and time since last exposure. Finally, such a pattern of trends could emerge if there were only two stages and the first and penultimate stage were the same

The expected burden of mesothelioma mortality in Great Britain from 2002 to 2050

The British mesothelioma register contains all deaths from 1968 to 2001 where mesothelioma was mentioned on the death certificate. These data were used to predict the future burden of mesothelioma mortality in Great Britain. Poisson regression analysis was used to model male mesothelioma deaths from 1968 to 2001 as a function of the rise and fall of asbestos exposure during the 20th century, and hence to predict numbers of male deaths in the years 2002–2050. The annual number of mesothelioma deaths in Great Britain has risen increasingly rapidly from 153 deaths in 1968 to 1848 in 2001 and, using our preferred model, is predicted to peak at around 1950 to 2450 deaths per year between 2011 and 2015. Following this peak, the number of deaths is expected to decline rapidly. The eventual death rate will depend on the background level and any residual asbestos exposure. Between 1968 and 2050, there will have been approximately 90 000 deaths from mesothelioma in Great Britain, 65 000 of which will occur after 2001

Design and analysis of randomized clinical trials requiring prolonged observation of each patient. I. Introduction and design.

The Medical Research Council has for some years encouraged collaborative clinical trials in leukaemia and other cancers, reporting the results in the medical literature. One unreported result which deserves such publication is the development of the expertise to design and analyse such trials. This report was prepared by a group of British and American statisticians, but it is intended for people without any statistical expertise. Part I, which appears in this issue, discusses the design of such trials; Part II, which will appear separately in the January 1977 issue of the Journal, gives full instructions for the statistical analysis of such trials by means of life tables and the logrank test, including a worked example, and discusses the interpretation of trial results, including brief reports of 2 particular trials. Both parts of this report are relevant to all clinical trials which study time to death, and wound be equally relevant to clinical trials which study time to other particular classes of untoward event: first stroke, perhaps, or first relapse, metastasis, disease recurrence, thrombosis, transplant rejection, or death from a particular cause. Part I, in this issue, collects together ideas that have mostly already appeared in the medical literature, but Part II, next month, is the first simple account yet published for non-statistical physicians of how to analyse efficiently data from clinical trials of survival duration. Such trials include the majority of all clinical trials of cancer therapy; in cancer trials,however, it may be preferable to use these statistical methods to study time to local recurrence of tumour, or to study time to detectable metastatic spread, in addition to studying total survival. Solid tumours can be staged at diagnosis; if this, or any other available information in some other disease is an important determinant of outcome, it can be used to make the overall logrank test for the whole heterogeneous trial population more sensitive, and more intuitively satisfactory, for it will then only be necessary to compare like with like, and not, by chance, Stage I with Stage III

Design and analysis of randomized clinical trials requiring prolonged observation of each patient. II. analysis and examples.

Part I of this report appeared in the previous issue (Br. J. Cancer (1976) 34,585), and discussed the design of randomized clinical trials. Part II now describes efficient methods of analysis of randomized clinical trials in which we wish to compare the duration of survival (or the time until some other untoward event first occurs) among different groups of patients. It is intended to enable physicians without statistical training either to analyse such data themselves using life tables, the logrank test and retrospective stratification, or, when such analyses are presented, to appreciate them more critically, but the discussion may also be of interest to statisticians who have not yet specialized in clinical trial analyses

Bladder cancer mortality of workers exposed to aromatic amines: an updated analysis.

none6nonePIOLATTO G; NEGRI E; LAVECCHIA C; PIRA E; DECARLI A; PETO JPIOLATTO G; NEGRI E; LAVECCHIA C; PIRA E; DECARLI A; PETO

Tempus volat, hora fugit: A survey of tie‐oriented dynamic network models in discrete and continuous time

Given the growing number of available tools for modeling dynamic networks, the choice of a suitable model becomes central. The goal of this survey is to provide an overview of tie‐oriented dynamic network models. The survey is focused on introducing binary network models with their corresponding assumptions, advantages, and shortfalls. The models are divided according to generating processes, operating in discrete and continuous time. First, we introduce the temporal exponential random graph model (TERGM) and the separable TERGM (STERGM), both being time‐discrete models. These models are then contrasted with continuous process models, focusing on the relational event model (REM). We additionally show how the REM can handle time‐clustered observations, that is, continuous‐time data observed at discrete time points. Besides the discussion of theoretical properties and fitting procedures, we specifically focus on the application of the models on two networks that represent international arms transfers and email exchange, respectively. The data allow to demonstrate the applicability and interpretation of the network models

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infectivity by Viral Load, S Gene Variants and Demographic Factors, and the Utility of Lateral Flow Devices to Prevent Transmission

BACKGROUND: How SARS-CoV-2 infectivity varies with viral load is incompletely understood. Whether rapid point-of-care antigen lateral flow devices (LFDs) detect most potential transmission sources despite imperfect clinical sensitivity is unknown. METHODS: We combined SARS-CoV-2 testing and contact tracing data from England between 01-September-2020 and 28-February-2021. We used multivariable logistic regression to investigate relationships between PCR-confirmed infection in contacts of community-diagnosed cases and index case viral load, S gene target failure (proxy for B.1.1.7 infection), demographics, SARS-CoV-2 incidence, social deprivation, and contact event type. We used LFD performance to simulate the proportion of cases with a PCR-positive contact expected to be detected using one of four LFDs. RESULTS: 231,498/2,474,066(9%) contacts of 1,064,004 index cases tested PCR-positive. PCR-positive results in contacts independently increased with higher case viral loads (lower Ct values) e.g., 11.7%(95%CI 11.5-12.0%) at Ct=15 and 4.5%(4.4-4.6%) at Ct=30. B.1.1.7 infection increased PCR-positive results by ~50%, (e.g. 1.55-fold, 95%CI 1.49-1.61, at Ct=20). PCR-positive results were most common in household contacts (at Ct=20.1, 8.7%[95%CI 8.6-8.9%]), followed by household visitors (7.1%[6.8-7.3%]), contacts at events/activities (5.2%[4.9-5.4%]), work/education (4.6%[4.4-4.8%]), and least common after outdoor contact (2.9%[2.3-3.8%]). Contacts of children were the least likely to test positive, particularly following contact outdoors or at work/education. The most and least sensitive LFDs would detect 89.5%(89.4-89.6%) and 83.0%(82.8-83.1%) of cases with PCR-positive contacts respectively. CONCLUSIONS: SARS-CoV-2 infectivity varies by case viral load, contact event type, and age. Those with high viral loads are the most infectious. B.1.1.7 increased transmission by ~50%. The best performing LFDs detect most infectious cases

1. The fraction of cancer attributable to lifestyle and environmental factors in the UK in 2010: Introduction

The overall objective of the study is to estimate the percentage of cancers (excluding non-melanoma skin cancer) in the UK in 2010 that were the result of exposure to 14 major lifestyle, dietary and environmental risk factors: tobacco, alcohol, four elements of diet (consumption of meat, fruit and vegetables, fibre and salt), overweight, lack of physical exercise, occupation, infections, radiation (ionising and solar), use of hormones and reproductive history (breast feeding). The number of new cases attributable to suboptimal exposure levels in the past, relative to a theoretical optimum exposure distribution, is evaluated. For most of the exposures, the attributable fraction was calculated based on the distribution of exposure prevalence (around 2000), the difference from the theoretical optimum (by age group and sex) and the relative risk per unit difference. For tobacco smoking, the method developed by Peto et al (1992) was used, which relies on the ratio between observed incidence of lung cancer in smokers and that in non-smokers, to calibrate the risk. This article outlines the structure of the supplement – a section for each of the 14 exposures, followed by a Summary chapter, which considers the relative contributions of each factor to the total number of cancers diagnosed in the UK in 2010 that were, in theory, avoidable