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Meta-analyses often combine covariate-adjusted effect estimates (odds ratios or relative risks) and confidence intervals relating a specified endpoint to a given exposure. Standard techniques are available to do this where the exposure is a simple presence/absence variable, or can be expressed in defined units. However, where the definition of exposure is qualitative and may vary between studies, meta-analysis is less straightforward. We introduce a new “Uniform Scale” approach allowing expression of effect estimates in a consistent manner, comparing individuals with the most and least possible exposure. In 2008, we presented methodology and made available software to obtain estimates for specific pairwise comparisons of exposure, such as any versus none, where the source paper provides estimates for multiple exposure categories, expressed relative to a common reference group. This methodology takes account of the correlation between the effect estimates for the different levels. We have now extended our software, available in Excel, SAS and R, to obtain effect estimates per unit of exposure, whether the exposure is defined or is to be expressed in the “Uniform Scale”. Examples of its use are presented.

ObjectivesThe study aimed to review the epidemiological evidence relating environmental tobacco smoke exposure to stroke in never smokers.MethodsThe study is similar to our review in 2006, with searches extended to March 2016.ResultsTwelve further studies were identified. A total of 28 studies varied considerably in design, exposure indices used, and disease definition. Based on 39 sex-specific estimates and the exposure index current spousal exposure (or nearest equivalent), the meta-analysis gave an overall fixed-effect relative risk estimate of 1.23 (95% confidence interval: 1.16-1.31), with significant (P

No previous review has formally modelled the decline in IHD risk following quitting smoking. From PubMed searches and other sources we identified 15 prospective and eight case-control studies that compared IHD risk in current smokers, never smokers, and quitters by time period of quit, some studies providing separate blocks of results by sex, age or amount smoked. For each of 41 independent blocks, we estimated, using the negative exponential model, the time, H, when the excess risk reduced to half that caused by smoking. Goodness-of-fit to the model was adequate for 35 blocks, others showing a non-monotonic pattern of decline following quitting, with a variable pattern of misfit. After omitting one block with a current smoker RR 1.0, the combined H estimate was 4.40 (95% CI 3.26–5.95) years. There was considerable heterogeneity, H being 10years for 12. H increased (p

Epidemiological studies relating a particular exposure to a specified disease may present their results in a variety of ways. Often, results are presented as estimated odds ratios (or relative risks) and confidence intervals (CIs) for a number of categories of exposure, for example, by duration or level of exposure, compared with a single reference category, often the unexposed. For systematic literature review, and particularly meta-analysis, estimates for an alternative comparison of the categories, such as any exposure versus none, may be required. Obtaining these alternative comparisons is not straightforward, as the initial set of estimates is correlated. This paper describes a method for estimating these alternative comparisons based on the ideas originally put forward by Greenland and Longnecker, and provides implementations of the method, developed using Microsoft Excel and SAS. Examples of the method based on studies of smoking and cancer are given. The method also deals with results given by categories of disease (such as histological types of a cancer). The method allows the use of a more consistent comparison when summarizing published evidence, thus potentially improving the reliability of a meta-analysis.

Context: In 2006, we reviewed the evidence on environmental tobacco smoke (ETS) and breast cancer in nonsmoking women. Since then various studies and reviews have been published but opinion remains divided. Objective: To provide an updated review. Methods: We extracted study details, derived relative risk (RR) estimates with confidence intervals (CIs) for various ETS exposure indices, and conducted meta-analyses. Results: The update increased the number of studies from 22 to 47. Using an index for each study most closely equivalent to “spouse ever smoked”, a weak but significant association was seen (random-effects RR = 1.15, 95% CI = 1.07–1.23). However, the estimates were heterogeneous: higher for Asian studies than for North American or European studies, higher for studies adjusting for fewer potential confounding variables, and close to 1.0 for prospective studies, regardless of whether or not they asked detailed questions on ETS exposure. The RR for eight prospective studies asking detailed questions was 1.003, 95% CI = 0.96–1.05. Risk was increased in premenopausal women (RR = 1.36, 95% CI = 1.15–1.60), but not postmenopausal women. Dose–response findings were similarly heterogeneous. No significant increase was seen for childhood or workplace exposure, but an increase was seen for total exposure (RR = 1.22, 95% CI = 1.09–1.37). Conclusions: Increases mainly derived from case-control studies are prone to recall bias. Study weaknesses and possible publication bias limit interpretation. Considering also the weak association of smoking with breast cancer, and the much lower exposures from ETS than from smoking, our analyses do not clearly demonstrate that ETS exposure increases risk of breast cancer in nonsmokers. More research is needed.

Recent authoritative reviews consider smoking has no effect on breast cancer risk, but some studies report an increase from environmental tobacco smoke (ETS). We reviewed the overall evidence on ETS and breast cancer in nonsmoking women. We extracted details of available studies, derived relative risk (RR) estimates with confidence intervals (CIs) for various ETS exposure indices and conducted meta-analyses. Using an index for each study most closely equivalent to "spouse ever smoked," a weak, but significant, association was seen (random-effects RR = 1.12, 95% CI = 1.02-1.24, n = 22). However, the estimates were heterogeneous: close to 1.0 for prospective, North American and larger studies, and those adjusting for many potential confounders, but significantly (p.05) elevated in case-control, European, and smaller studies, and those accounting for fewer potential confounders. Risk was increased in premenopausal women (RR = 1.54, 95% CI = 1.16-2.05, n = 10), but not postmenopausal women. Dose-response findings were similarly heterogeneous. No significant increase was seen for ETS in childhood or the workplace or from the spouse specifically, but an increase was seen for total exposure (RR = 1.54, 95% CI = 1.17-2.04, n = 6). Increases mainly derive from case-control studies asking detailed ETS histories, where RRs depend heavily on who is classified in the totally unexposed reference group, and may be prone to recall bias. Results from prospective studies using similar histories are needed. Study weaknesses and possible publication bias also limit interpretation. Because of the inherent implausibility that ETS exposure might cause breast cancer, given the similar risks of smokers and nonsmokers, one cannot confidently conclude ETS exposure increases risk in nonsmokers.

John S Fry, Peter N Lee, Jan S HamlingPN Lee Statistics and Computing, Sutton, UKAbstract: In long-term carcinogenicity studies, the Peto test is the standard method for analyzing lesions that are not observable in life, taking into account differential between-group mortality. This method requires knowledge for each animal in each group of when the animal died, whether a lesion was seen postmortem, and the context of observation (ie, whether the lesion was fatal [considered to have contributed to its death] or whether it was incidental [seen in an animal dying for an unrelated reason]). The Peto test was not designed to take severity of the lesion into account. Age-adjusted analysis taking severity into account can be carried out using a stratified version of the Kruskal–Wallis one-way analysis of variance by ranks, but this does not take context of observation into account. Here, we describe an extended version of the stratified Kruskal–Wallis test that both allows analysis of lesions graded on severity and takes fatality of the lesion into account. This includes both a test for between-group heterogeneity and a test for dose-related trend, and provides a powerful method for analyzing such data. The Peto and Kruskal–Wallis tests may be considered special cases of this more general test. The test may be applied not only to nonneoplastic lesions (such as chronic progressive nephropathy), where pathologists often grade severity on a 5-point scale, but also to preneoplastic and neoplastic lesions, carrying out a single analysis of focal hyperplasia, benign tumor, and malignant tumor of a specific histological type, regarding these as successive stages of a progressive condition.Keywords: carcinogenicity tests, survival analysis, heterogeneity, trend, stratified analysis

Background Reduced FEV1 is known to predict increased lung cancer risk, but previous reviews are limited. To quantify this relationship more precisely, and study heterogeneity, we derived estimates of β for the relationship RR(diff) = exp(βdiff), where diff is the reduction in FEV1 expressed as a percentage of predicted (FEV1%P) and RR(diff) the associated relative risk. We used results reported directly as β, and as grouped levels of RR in terms of FEV1%P and of associated measures (e.g. FEV1/FVC). Methods Papers describing cohort studies involving at least three years follow-up which recorded FEV1 at baseline and presented results relating lung cancer to FEV1 or associated measures were sought from Medline and other sources. Data were recorded on study design and quality and, for each data block identified, on details of the results, including population characteristics, adjustment factors, lung function measure, and analysis type. Regression estimates were converted to β estimates where appropriate. For results reported by grouped levels, we used the NHANES III dataset to estimate mean FEV1%P values for each level, regardless of the measure used, then derived β using regression analysis which accounted for non-independence of the RR estimates. Goodness-of-fit was tested by comparing observed and predicted lung cancer cases for each level. Inverse-variance weighted meta-analysis allowed derivation of overall β estimates and testing for heterogeneity by factors including sex, age, location, timing, duration, study quality, smoking adjustment, measure of FEV1 reported, and inverse-variance weight of β. Results Thirty-three publications satisfying the inclusion/exclusion criteria were identified, seven being rejected as not allowing estimation of β. The remaining 26 described 22 distinct studies, from which 32 independent β estimates were derived. Goodness-of-fit was satisfactory, and exp(β), the RR increase per one unit FEV1%P decrease, was estimated as 1.019 (95%CI 1.016-1.021). The estimates were quite consistent (I2 =29.6%). Mean age was the only independent source of heterogeneity, exp(β) being higher for age Conclusions Although the source papers present results in various ways, complicating meta-analysis, they are very consistent. A decrease in FEV1%P of 10% is associated with a 20% (95%CI 17%-23%) increase in lung cancer risk.

Background Interest is rising in smokeless tobacco as a safer alternative to smoking, but published reviews on smokeless tobacco and cancer are limited. We review North American and European studies and compare effects of smokeless tobacco and smoking. Methods We obtained papers from MEDLINE searches, published reviews and secondary references describing epidemiological cohort and case-control studies relating any form of cancer to smokeless tobacco use. For each study, details were abstracted on design, smokeless tobacco exposure, cancers studied, analysis methods and adjustment for smoking and other factors. For each cancer, relative risks or odds ratios with 95% confidence intervals were tabulated. Overall, and also for USA and Scandinavia separately, meta-analyses were conducted using all available estimates, smoking-adjusted estimates, or estimates for never smokers. For seven cancers, smoking-attributable deaths in US men in 2005 were compared with deaths attributable to introducing smokeless tobacco into a population of never-smoking men. Results Eighty-nine studies were identified; 62 US and 18 Scandinavian. Forty-six (52%) controlled for smoking. Random-effects meta-analysis estimates for most sites showed little association. Smoking-adjusted estimates were only significant for oropharyngeal cancer (1.36, CI 1.04–1.77, n = 19) and prostate cancer (1.29, 1.07–1.55, n = 4). The oropharyngeal association disappeared for estimates published since 1990 (1.00, 0.83–1.20, n = 14), for Scandinavia (0.97, 0.68–1.37, n = 7), and for alcohol-adjusted estimates (1.07, 0.84–1.37, n = 10). Any effect of current US products or Scandinavian snuff seems very limited. The prostate cancer data are inadequate for a clear conclusion. Some meta-analyses suggest a possible effect for oesophagus, pancreas, larynx and kidney cancer, but other cancers show no effect of smokeless tobacco. Any possible effects are not evident in Scandinavia. Of 142,205 smoking-related male US cancer deaths in 2005, 104,737 are smoking-attributable. Smokeless tobacco-attributable deaths would be 1,102 (1.1%) if as many used smokeless tobacco as had smoked, and 2,081 (2.0%) if everyone used smokeless tobacco. Conclusion An increased risk of oropharyngeal cancer is evident most clearly for past smokeless tobacco use in the USA, but not for Scandinavian snuff. Effects of smokeless tobacco use on other cancers are not clearly demonstrated. Risk from modern products is much less than for smoking.

We compared risk of lung cancer and chronic obstructive pulmonary disease (COPD) associated with flue-cured and blended cigarettes. Mortality and smoking data were collected for 1971-2000 by sex, age, and period for three countries with a mainly flue-cured market and four with a blended market. Epidemiological relative risk estimates for current and ex smoking were summarized. Smoking statistics and mortality were compared between flue-cured cigarette and blended cigarette countries. Unadjusted mortality rates were generally lower in blended cigarette countries early on, with the difference diminishing or reversing by the 1990s. Differences by cigarette type were rarely significant, due to variations, particularly for COPD, between countries within cigarette type. Current smoking prevalence was generally lower in blended cigarette countries in 1971-1975, with the difference reducing over time. Differences by type were never significant, with blended cigarette countries varying markedly. Ex-smoking increased over time and was lower for blended cigarette countries, generally not significantly. Consumption per smoker was somewhat lower for blended cigarette countries. Relative risk estimates for smoking, derived mainly from U.S. and UK studies, varied little by cigarette type. Conclusions based on estimated smoking-related excess mortality were similar to those based on unadjusted mortality rates. There was little indication of any difference between flue-cured and blended cigarettes on risk of lung cancer or COPD. Our approach could have detected differences of about 40% for male lung cancer, or twofold differences for females or for COPD, had they existed. Between-country differences in rates of two major diseases predominantly caused by smoking cannot materially be explained by whether the countries use flue-cured or blended cigarettes.