Impact of changing US cigarette smoking patterns on incident cancer: Risks of 20 smoking-related cancers among the women and men of the NIH-AARP cohort

Background: Historically, US women started smoking at a later age than men and had lower relative risks for smoking-related cancers. However, more recent birth cohorts of women and men have similar smoking histories and have now reached the high-risk age for cancer. The impact of these changes on cancer incidence has not been systematically examined. Methods: Relative risks (RR), 95% confidence intervals (CI) and attributable fractions were calculated for cigarette smoking and incidence of 20 smoking-related cancers in 186 057 women and 266 074 men of the National Institutes of Health-AARP cohort, aged 50 to 71 years in 1995 and followed for 11 years. Results: In the cohort, which included participants born between 1924 and 1945, most women and men started smoking as teenagers. RRs for current vs never smoking were similar in women and men for the following cancers: lung squamous-cell (RR women: 121.4, 95% CI: 57.3–257.4; RR men:114.6, 95% CI: 61.2–214.4), lung adenocarcinoma (RR women: 11.7, 95% CI: 9.8–14.0; RR men: 15.6, 95% CI: 12.5–19.6), laryngeal (RR women: 37.0, 95% CI: 14.9–92.3; RR men: 13.8, 95% CI: 9.3–20.2), oral cavity-pharyngeal (RR women:4.4, 95% CI: 3.3–6.0; RR men: 3.8, 95% CI: 3.0–4.7), oesophageal squamous cell (RR women: 7.3, 95% CI: 3.5–15.5; RR men: 6.2, 95% CI: 2.8–13.7), bladder (RR women: 4.7, 95% CI: 3.7–5.8; RR men: 4.0, 95% CI: 3.5–4.5), colon (RR women: 1.3, 95% CI: 1.2–1.5; RR men: 1.3, 95% CI: 1.1–1.4), and at other sites, with similar attributable fractions. Conclusions: RRs for current smoking and incidence of many smoking-related cancers are now similar in US women and men, likely reflecting converging smoking patterns

Co-firing of biomass and other wastes in fluidised bed systems

A project on co-firing in large-scale power plants burning coal is currently funded by the European Commission. It is called COPOWER. The project involves 10 organisations from 6 countries. The project involves combustion studies over the full spectrum of equipment size, ranging from small laboratory-scale reactors and pilot plants, to investigate fundamentals and operating parameters, to proving trials on a commercial power plant in Duisburg. The power plant uses a circulating fluidized bed boiler. The results to be obtained are to be compared as function of scale-up. There are two different coals, 3 types of biomass and 2 kinds of waste materials are to be used for blending with coal for co-firing tests. The baseline values are obtained during a campaign of one month at the power station and the results are used for comparison with those to be obtained in other units of various sizes. Future tests will be implemented with the objective to achieve improvement on baseline values. The fuels to be used are already characterized. There are ongoing studies to determine reactivities of fuels and chars produced from the fuels. Reactivities are determined not only for individual fuels but also for blends to be used. Presently pilot-scale combustion tests are also undertaken to study the effect of blending coal with different types of biomass and waste materials. The potential for synergy to improve combustion is investigated. Early results will be reported in the Conference. Simultaneously, studies to verify the availability of biomass and waste materials in Portugal, Turkey and Italy have been undertaken. Techno-economic barriers for the future use of biomass and other waste materials are identified. The potential of using these materials in coal fired power stations has been assessed. The conclusions will also be reported

Antibiotic use and risk of non-Hodgkin's lymphoma: a population-based case–control study

Antibiotic use in 759 non-Hodgkin's lymphoma (NHL) patients and 589 controls was compared. Neither total antibiotic use (odds ratio=0.7, 95% confidence interval=0.5–1.2), nor antibiotic use by site, was associated with total NHL, or NHL subtypes. There were no trends with frequency or age at first use (P trend=0.23 and 0.26, respectively)

Epidemiologic Evaluation of Measurement Data in the Presence of Detection Limits

Quantitative measurements of environmental factors greatly improve the quality of epidemiologic studies but can pose challenges because of the presence of upper or lower detection limits or interfering compounds, which do not allow for precise measured values. We consider the regression of an environmental measurement (dependent variable) on several covariates (independent variables). Various strategies are commonly employed to impute values for interval-measured data, including assignment of one-half the detection limit to nondetected values or of “fill-in” values randomly selected from an appropriate distribution. On the basis of a limited simulation study, we found that the former approach can be biased unless the percentage of measurements below detection limits is small (5–10%). The fill-in approach generally produces unbiased parameter estimates but may produce biased variance estimates and thereby distort inference when 30% or more of the data are below detection limits. Truncated data methods (e.g., Tobit regression) and multiple imputation offer two unbiased approaches for analyzing measurement data with detection limits. If interest resides solely on regression parameters, then Tobit regression can be used. If individualized values for measurements below detection limits are needed for additional analysis, such as relative risk regression or graphical display, then multiple imputation produces unbiased estimates and nominal confidence intervals unless the proportion of missing data is extreme. We illustrate various approaches using measurements of pesticide residues in carpet dust in control subjects from a case–control study of non-Hodgkin lymphoma

Risk Prediction for Breast, Endometrial, and Ovarian Cancer in White Women Aged 50 y or Older: Derivation and Validation from Population-Based Cohort Studies

Background: Breast, endometrial, and ovarian cancers share some hormonal and epidemiologic risk factors. While several models predict absolute risk of breast cancer, there are few models for ovarian cancer in the general population, and none for endometrial cancer. Methods and Findings: Using data on white, non-Hispanic women aged 50+ y from two large population-based cohorts (the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial [PLCO] and the National Institutes of Health–AARP Diet and Health Study [NIH-AARP]), we estimated relative and attributable risks and combined them with age-specific US-population incidence and competing mortality rates. All models included parity. The breast cancer model additionally included estrogen and progestin menopausal hormone therapy (MHT) use, other MHT use, age at first live birth, menopausal status, age at menopause, family history of breast or ovarian cancer, benign breast disease/biopsies, alcohol consumption, and body mass index (BMI); the endometrial model included menopausal status, age at menopause, BMI, smoking, oral contraceptive use, MHT use, and an interaction term between BMI and MHT use; the ovarian model included oral contraceptive use, MHT use, and family history or breast or ovarian cancer. In independent validation data (Nurses' Health Study cohort) the breast and ovarian cancer models were well calibrated; expected to observed cancer ratios were 1.00 (95% confidence interval [CI]: 0.96–1.04) for breast cancer and 1.08 (95% CI: 0.97–1.19) for ovarian cancer. The number of endometrial cancers was significantly overestimated, expected/observed = 1.20 (95% CI: 1.11–1.29). The areas under the receiver operating characteristic curves (AUCs; discriminatory power) were 0.58 (95% CI: 0.57–0.59), 0.59 (95% CI: 0.56–0.63), and 0.68 (95% CI: 0.66–0.70) for the breast, ovarian, and endometrial models, respectively. Conclusions: These models predict absolute risks for breast, endometrial, and ovarian cancers from easily obtainable risk factors and may assist in clinical decision-making. Limitations are the modest discriminatory ability of the breast and ovarian models and that these models may not generalize to women of other races. Please see later in the article for the Editors' Summar

Human Leukocyte Antigen Class I and II Alleles and Overall Survival in Diffuse Large B-Cell Lymphoma and Follicular Lymphoma

Genetic variation in the 6p21 chromosomal region, including human leukocyte antigen (HLA) genes and tumor necrosis factor (TNF), has been linked to both etiology and clinical outcomes of lymphomas. We estimated the effects of HLA class I (A, B, and C), class II DRB1 alleles, and the ancestral haplotype (AH) 8.1 (HLAA*01-B*08-DRB1*03-TNF-308A) on overall survival (OS) among patients with diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) in a population-based study of non-Hodgkin lymphoma. During a median followup of 89 months, 31% (52 of 166) DLBCL and 28% (46 of 165) FL patients died. Using multivariate Cox regression models, we observed statistically significant associations between genetic variants and survival: HLA-Cw*07:01 was associated with poorer OS among DLBCL patients (Hazard ratio [HR] = 1.76, 95% confidence interval [CI] = 1.01–3.05); HLA-A*01:01 was associated with poorer OS (HR = 2.23, 95% CI = 1.24–4.01), and HLA-DRB1*13 (HR = 0.12, 95% CI = 0.02–0.90) and HLA-B Bw4 (HR = 0.36, 95% CI = 0.20–0.63) with better OS among FL patients. These results support a role for HLA in the prognosis of DLBCL and FL and represent a promising class of prognostic factors that warrants further evaluation

Synergistic Effects of Hypofibrinolysis and Genetic and Acquired Risk Factors on the Risk of a First Venous Thrombosis

Frits Rosendaal and colleagues show that the combination of hypofibrinolysis with oral contraceptive use, immobilization, or factor V Leiden results in a risk of venous thrombosis that exceeds the sum of the individual risks