Modeling exposure-lag-response associations with distributed lag non-linear models.

In biomedical research, a health effect is frequently associated with protracted exposures of varying intensity sustained in the past. The main complexity of modeling and interpreting such phenomena lies in the additional temporal dimension needed to express the association, as the risk depends on both intensity and timing of past exposures. This type of dependency is defined here as exposure-lag-response association. In this contribution, I illustrate a general statistical framework for such associations, established through the extension of distributed lag non-linear models, originally developed in time series analysis. This modeling class is based on the definition of a cross-basis, obtained by the combination of two functions to flexibly model linear or nonlinear exposure-responses and the lag structure of the relationship, respectively. The methodology is illustrated with an example application to cohort data and validated through a simulation study. This modeling framework generalizes to various study designs and regression models, and can be applied to study the health effects of protracted exposures to environmental factors, drugs or carcinogenic agents, among others

Pitfalls of using the risk ratio in meta‐analysis

For meta-analysis of studies that report outcomes as binomial proportions, the most popular measure of effect is the odds ratio (OR), usually analyzed as log(OR). Many meta-analyses use the risk ratio (RR) and its logarithm, because of its simpler interpretation. Although log(OR) and log(RR) are both unbounded, use of log(RR) must ensure that estimates are compatible with study-level event rates in the interval (0, 1). These complications pose a particular challenge for random-effects models, both in applications and in generating data for simulations. As background we review the conventional random-effects model and then binomial generalized linear mixed models (GLMMs) with the logit link function, which do not have these complications. We then focus on log-binomial models and explore implications of using them; theoretical calculations and simulation show evidence of biases. The main competitors to the binomial GLMMs use the beta-binomial (BB) distribution, either in BB regression or by maximizing a BB likelihood; a simulation produces mixed results. Two examples and an examination of Cochrane meta-analyses that used RR suggest bias in the results from the conventional inverse-variance-weighted approach. Finally, we comment on other measures of effect that have range restrictions, including risk difference, and outline further research

Reproductive factors and subtypes of breast cancer defined by hormone receptor and histology

Reproductive factors are associated with reduced risk of breast cancer, but less is known about whether there is differential protection against subtypes of breast cancer. Assuming reproductive factors act through hormonal mechanisms they should protect predominantly against cancers expressing oestrogen (ER) and progesterone (PR) receptors. We examined the effect of reproductive factors on subgroups of tumours defined by hormone receptor status as well as histology using data from the NIHCD Women's Contraceptive and Reproductive Experiences (CARE) Study, a multicenter case–control study of breast cancer. We estimated odds ratios (ORs) and 95% confidence intervals (CIs) as measures of relative risk using multivariate unconditional logistic regression methods. Multiparity and early age at first birth were associated with reduced relative risk of ER + PR + tumours (P for trend=0.0001 and 0.01, respectively), but not of ER − PR − tumours (P for trend=0.27 and 0.85), whereas duration of breastfeeding was associated with lower relative risk of both receptor-positive (P for trend=0.0002) and receptor-negative tumours (P=0.0004). Our results were consistent across subgroups of women based on age and ethnicity. We found few significant differences by histologic subtype, although the strongest protective effect of multiparity was seen for mixed ductolobular tumours. Our results indicate that parity and age at first birth are associated with reduced risk of receptor-positive tumours only, while lactation is associated with reduced risk of both receptor-positive and -negative tumours. This suggests that parity and lactation act through different mechanisms. This study also suggests that reproductive factors have similar protective effects on breast tumours of lobular and ductal origin

Deletion of Cryptococcus neoformans AIF Ortholog Promotes Chromosome Aneuploidy and Fluconazole-Resistance in a Metacaspase-Independent Manner

Apoptosis is a form of programmed cell death critical for development and homeostasis in multicellular organisms. Apoptosis-like cell death (ALCD) has been described in several fungi, including the opportunistic human pathogen Cryptococcus neoformans. In addition, capsular polysaccharides of C. neoformans are known to induce apoptosis in host immune cells, thereby contributing to its virulence. Our goals were to characterize the apoptotic signaling cascade in C. neoformans as well as its unique features compared to the host machinery to exploit the endogenous fungal apoptotic pathways as a novel antifungal strategy in the future. The dissection of apoptotic pathways revealed that apoptosis-inducing factor (Aif1) and metacaspases (Mca1 and Mca2) are independently required for ALCD in C. neoformans. We show that the apoptotic pathways are required for cell fusion and sporulation during mating, indicating that apoptosis may occur during sexual development. Previous studies showed that antifungal drugs induce ALCD in fungi and that C. neoformans adapts to high concentrations of the antifungal fluconazole (FLC) by acquisition of aneuploidy, especially duplication of chromosome 1 (Chr1). Disruption of aif1, but not the metacaspases, stimulates the emergence of aneuploid subpopulations with Chr1 disomy that are resistant to fluconazole (FLCR) in vitro and in vivo. FLCR isolates in the aif1 background are stable in the absence of the drug, while those in the wild-type background readily revert to FLC sensitivity. We propose that apoptosis orchestrated by Aif1 might eliminate aneuploid cells from the population and defects in this pathway contribute to the selection of aneuploid FLCR subpopulations during treatment. Aneuploid clinical isolates with disomies for chromosomes other than Chr1 exhibit reduced AIF1 expression, suggesting that inactivation of Aif1 might be a novel aneuploidy-tolerating mechanism in fungi that facilitates the selection of antifungal drug resistance

Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): Explanation and Elaboration

The REMARK “elaboration and explanation” guideline, by Doug Altman and colleagues, provides a detailed reference for authors on important issues to consider when designing, conducting, and analyzing tumor marker prognostic studies

Mortality risks in patients with constitutional autosomal chromosome deletions in Britain: a cohort study

Constitutional chromosome deletions result in wide ranging morbidity and often fatality. Information about risks and causes of death in these patients is important for counselling, and may illuminate the functions of the part of the chromosome deleted. There have been no cohort studies analysing mortality risks in persons with specific deletions compared with general population rates. We therefore conducted a cohort study following cause-specific mortality in 2,561 patients with autosomal chromosome deletions diagnosed by light microscopy or fluorescence in situ hybridisation at cytogenetic laboratories across Britain, 1965-2002. The commonest deletions were of 22q (544 patients), 15q (460) and 7q (210) and the least common 19q (0) and 20q (2). The prevalence of visible deletions of different chromosome arms was significantly inversely correlated with gene density of the arm (p 10 for deletions of 1p, 1q, 3p, 4p, 5q and 22q. Overall, 29% of deaths were due to congenital anomalies; significantly raised mortality occurred also from many other causes, varying by chromosome and arm of deletion. The data imply that viability of foetuses with visible chromosome deletions may be inversely related to gene density, and that all visible and fluorescence in situ hybridisation-detectable deletions lead to much raised mortality, but the extent and causes of mortality vary according to the specific deletion