Repeated interviews are much better for drug exposure assessment than a single baseline interview,

Association between cardiorespiratory fitness and colorectal cancer in the UK Biobank Abstract Increased cardiorespiratory fitness is related to decreased risk of major chronic illnesses, including cardiovascular disease, type 2 diabetes, and cancer, but its association with colorectal cancer specifically has received very little attention. We examined the relation of cardiorespiratory fitness to colorectal cancer in 59,191 UK Biobank participants aged 39–70 years without prevalent cancer at baseline, followed from 2009 to 2014. Submaximal bicycle ergometry was conducted at study entry, and cardiorespiratory fitness was defined as physical work capacity at 75% of the maximum heart rate, standardised to body mass (PWC75%). Multivariable Cox proportional hazards regression was performed to obtain hazard ratios (HR) and corresponding 95% confidence intervals (CI). During a mean follow-up of 4.6 years, 232 participants developed colorectal cancer (151 colon cancers; 79 rectal cancers). When comparing the 75th to the 25th percentiles of PWC75%, the multivariable-adjusted HR of colorectal cancer was 0.78 (95% CI 0.62–0.97). That relation was largely driven by an inverse association with colon cancer (HR 0.74, 95% CI 0.56–0.97) and less so with rectal cancer (HR 0.88, 95% CI 0.62–1.26; p value for difference by colorectal cancer endpoint = 0.056). The inverse relation of cardiorespiratory fitness with colorectal cancer was more evident in men (HR 0.72, 95% CI 0.55–0.94) than women (HR 0.99, 95% CI 0.71–1.38), although the gender difference was not statistically significant (p value for interaction = 0.192). Increased cardiorespiratory fitness is associated with decreased risk of colorectal cancer. Potential heterogeneity by colorectal cancer anatomic subsite and gender requires further study.

Rationale and Design of the Hamburg City Health Study Abstract The Hamburg City Health Study (HCHS) is a large, prospective, long-term, population-based cohort study and a unique research platform and network to obtain substantial knowledge about several important risk and prognostic factors in major chronic diseases. A random sample of 45,000 participants between 45 and 74 years of age from the general population of Hamburg, Germany, are taking part in an extensive baseline assessment at one dedicated study center. Participants undergo 13 validated and 5 novel examinations primarily targeting major organ system function and structures including extensive imaging examinations. The protocol includes validate self-reports via questionnaires regarding lifestyle and environmental conditions, dietary habits, physical condition and activity, sexual dysfunction, professional life, psychosocial context and burden, quality of life, digital media use, occupational, medical and family history as well as healthcare utilization. The assessment is completed by genomic and proteomic characterization. Beyond the identification of classical risk factors for major chronic diseases and survivorship, the core intention is to gather valid prevalence and incidence, and to develop complex models predicting health outcomes based on a multitude of examination data, imaging, biomarker, psychosocial and behavioral assessments. Participants at risk for coronary artery disease, atrial fibrillation, heart failure, stroke and dementia are invited for a visit to conduct an additional MRI examination of either heart or brain. Endpoint assessment of the overall sample will be completed through repeated follow-up examinations and surveys as well as related individual routine data from involved health and pension insurances. The study is targeting the complex relationship between biologic and psychosocial risk and resilience factors, chronic disease, health care use, survivorship and health as well as favorable and bad prognosis within a unique, large-scale long-term assessment with the perspective of further examinations after 6 years in a representative European metropolitan population.

Effect heterogeneity and variable selection for standardizing causal effects to a target population Abstract The participants in randomized trials and other studies used for causal inference are often not representative of the populations seen by clinical decision-makers. To account for differences between populations, researchers may consider standardizing results to a target population. We discuss several different types of homogeneity conditions that are relevant for standardization: Homogeneity of effect measures, homogeneity of counterfactual outcome state transition parameters, and homogeneity of counterfactual distributions. Each of these conditions can be used to show that a particular standardization procedure will result in an unbiased estimate of the effect in the target population, given assumptions about the relevant scientific context. We compare and contrast the homogeneity conditions, in particular their implications for selection of covariates for standardization and their implications for how to compute the standardized causal effect in the target population. While some of the recently developed counterfactual approaches to generalizability rely upon homogeneity conditions that avoid many of the problems associated with traditional approaches, they often require adjustment for a large (and possibly unfeasible) set of covariates.

Trends in surgical treatment for breast cancer in Germany after the implementation of the mammography screening program Abstract In Germany, the nationwide population-based mammography screening program (MSP) was introduced in 2005 and is full-running since 2010. By 2014, incidence rates for invasive breast cancer were very similar to those of the pre-screening era. Therefore, the ongoing effect of the MSP on breast cancer surgery rates can now be investigated. We analyzed population-based breast-conserving (BCS) and mastectomy (MET) surgery rates (per 100,000) among women aged < 50, 50–69 (eligible for the MSP), and 70+ years among women with in situ and invasive breast cancer during 2005–2015. For invasive breast cancer, both BCS and MET rates slightly increased in the age group < 50 years (38.3 in 2005 vs 42.5 in 2015 and 15.7 vs 18.2, respectively). In contrast, MET rates considerably decreased among women aged 50–69 and 70+ years (92 vs 65.4 and 155.4 vs 122.1, respectively), while BCS rates increased in both age groups (210.6 vs 254.4 and 147.2 vs 187, respectively). For in situ breast cancer, MET rates slightly increased in all age groups. BCS rates slightly increased in women aged < 50, but nearly doubled for women aged 50–69 (26.9 vs 49.1) and markedly increased in the 70+ age group (11.5 vs 16.1). During and after the implementation of MSP, there was a strong shift towards BCS within the screening-eligible age group and for women aged 70+ . Women with invasive breast cancer in these age groups may profit from screening with a decline of MET rates in favor of BCS rates at the expense of higher surgery rates for in situ breast cancer.

Commonly used estimates of the genetic contribution to disease are subject to the same fallacies as bad luck estimates Abstract The scientific debate following the initial formulation of the “bad luck” hypothesis in cancer development highlighted how measures based on analysis of variance are inappropriately used for risk communication. The notion of “explained” variance is not only used to quantify randomness, but also to quantify genetic and environmental contribution to disease in heritability coefficients. In this paper, we demonstrate why such quantifications are generally as problematic as bad luck estimates. We stress the differences in calculation and interpretation between the heritability coefficient and the population attributable fraction, the estimated fraction of all disease events that would not occur if an intervention could successfully prevent the excess genetic risk. We recommend using the population attributable fraction when communicating results regarding the genetic contribution to disease, as this measure is both more relevant from a public health perspective and easier to understand.

Do replicable profiles of multimorbidity exist? Systematic review and synthesis Abstract This systematic review aimed to synthesise multimorbidity profiling literature to identify replicable and clinically meaningful groupings of multimorbidity. We searched six electronic databases (Medline, EMBASE, PsycINFO, CINAHL, Scopus, and Web of Science) for articles reporting multimorbidity profiles. The identified profiles were synthesised with multidimensional scaling, stratified by type of statistical analysis used in the derivation of profiles. The 51 studies that met inclusion criteria reported results of 98 separate analyses of multimorbidity profiling, with a total of 407 multimorbidity profiles identified. The statistical techniques used to identify multimorbidity profiles were exploratory factor analysis, cluster analysis of diseases, cluster analysis of people, and latent class analysis. Reporting of methodological details of statistical methods was often incomplete. The discernible groupings of multimorbidity took the form of both discrete categories and continuous dimensions. Mental health conditions and cardio-metabolic conditions grouped along identifiable continua in the synthesised results of all four methods. Discrete groupings of chronic obstructive pulmonary disease with asthma, falls and fractures with sensory deficits and of Parkinson’s disease and cognitive decline where partially replicable (identifiable in the results of more than one method), while clustering of musculoskeletal conditions and clustering of reproductive systems were each observed only in one statistical approach. The two most replicable multimorbidity profiles were mental health conditions and cardio-metabolic conditions. Further studies are needed to understand aetiology and evolution of these multimorbidity groupings. Guidelines for strengthening the reporting of multimorbidity profiling studies are proposed.

A multi-state model based reanalysis of the Framingham Heart Study: Is dementia incidence really declining? Abstract Recent research by Satizabal and colleagues using data from the Framingham Heart Study demonstrated a linear decline in dementia incidence since the 1970s. The aim of this study is to re-examine these findings, given concerns that bias resulted from failure to account for the probability of acquiring dementia between the last dementia-free observation and death. This analysis included 5118 persons 60+ years of age, and determined the 5-year dementia incidence during four non-overlapping epochs. In addition to a replication using Cox proportional hazards, we applied separate Cox models (given unequal hazards across epochs) and a Spline-based penalized likelihood approach based on the illness-death multi-state model. In addition, we present a simulation study demonstrating the bias associated with the use of standard survival models. The simulation showed that estimates of disease incidence derived from the multi-state model-based approach were consistent with the true disease incidence, whereas Cox regression ‘censoring’ observations at death or at last observation consistently underestimated it. Using the Framingham data, the 5-year age- and sex-adjusted cumulative hazard rates for dementia as derived from the multi-state model-based approach were 3.84, 2.66, 3.29 and 3.13 per 100 persons in epochs 1, 2, 3 and 4 respectively. The findings do not support the conclusion that dementia incidence has declined in the Framingham Heart Study over the given time period. Previous findings of a decline may have been an artefact resulting from improper treatment of those cases in which death precluded the observation of dementia onset.

Authors’ reply to ‘Multiple comparisons controversies are about context and costs, not frequentism versus Bayesianism’

Biography and biological capital Abstract At the crossroads between sciences, epidemiology brings together the social and the biological to examine social inequalities in health. The concept of biological capital represents the accumulated history of biological experiences, alongside the other forms of accumulated capital, notably cultural, economic and social. The ability to access the three other forms of individual capital and therefore position in life depends on inherited biological health/skills, epigenetic imprinting and the accumulation of embodied biological changes that make an individual more or less successful in life. We present results from analyses carried out within the Lifepath consortium, showing that the socioeconomic environment, from early life and over the lifecourse, is an important risk factor for health and partly works through its effects on biological mechanisms. We show that socially stratified pre-disease states related to ageing may be examined using biomarkers, and help underline areas and mechanisms to promote healthy ageing.