Background and Aims Colorectal cancer (CRC) is a heterogeneous disease that can develop via several pathways. Different CRC subtypes, identified based on tumor markers, have been proposed to reflect ...these pathways. We evaluated the significance of these previously proposed classifications to survival. Methods Participants in the population-based Seattle Colon Cancer Family Registry were diagnosed with invasive CRC from 1998 through 2007 in western Washington State (N = 2706), and followed for survival through 2012. Tumor samples were collected from 2050 participants and classified into 5 subtypes based on combinations of tumor markers: type 1 (microsatellite instability MSI–high, CpG island methylator phenotype CIMP –positive, positive for BRAF mutation, negative for KRAS mutation); type 2 (microsatellite stable MSS or MSI-low, CIMP-positive, positive for BRAF mutation, negative for KRAS mutation); type 3 (MSS or MSI low, non-CIMP, negative for BRAF mutation, positive for KRAS mutation); type 4 (MSS or MSI-low, non-CIMP, negative for mutations in BRAF and KRAS ); and type 5 (MSI-high, non-CIMP, negative for mutations in BRAF and KRAS ). Multiple imputation was used to impute tumor markers for those missing data on 1–3 markers. We used Cox regression to estimate hazard ratios (HR) and 95% confidence intervals (CI) for associations of subtypes with disease-specific and overall mortality, adjusting for age, sex, body mass, diagnosis year, and smoking history. Results Compared with participants with type 4 tumors (the most predominant), participants with type 2 tumors had the highest disease-specific mortality (HR = 2.20, 95% CI: 1.47–3.31); subjects with type 3 tumors also had higher disease-specific mortality (HR = 1.32, 95% CI: 1.07–1.63). Subjects with type 5 tumors had the lowest disease-specific mortality (HR = 0.30, 95% CI: 0.14–0.66). Associations with overall mortality were similar to those with disease-specific mortality. Conclusions Based on a large, population-based study, CRC subtypes, defined by proposed etiologic pathways, are associated with marked differences in survival. These findings indicate the clinical importance of studies into the molecular heterogeneity of CRC.
Although high-risk mutations in identified major susceptibility genes (DNA mismatch repair genes and
) account for some familial aggregation of colorectal cancer, their population prevalence and the ...causes of the remaining familial aggregation are not known.
We studied the families of 5,744 colorectal cancer cases (probands) recruited from population cancer registries in the United States, Canada, and Australia and screened probands for mutations in mismatch repair genes and
We conducted modified segregation analyses using the cancer history of first-degree relatives, conditional on the proband's age at diagnosis. We estimated the prevalence of mutations in the identified genes, the prevalence of HR for unidentified major gene mutations, and the variance of the residual polygenic component.
We estimated that 1 in 279 of the population carry mutations in mismatch repair genes (
= 1 in 1,946,
= 1 in 2,841,
= 1 in 758,
= 1 in 714), 1 in 45 carry mutations in
, and 1 in 504 carry mutations associated with an average 31-fold increased risk of colorectal cancer in unidentified major genes. The estimated polygenic variance was reduced by 30% to 50% after allowing for unidentified major genes and decreased from 3.3 for age <40 years to 0.5 for age ≥70 years (equivalent to sibling relative risks of 5.1 to 1.3, respectively).
Unidentified major genes might explain one third to one half of the missing heritability of colorectal cancer.
Our findings could aid gene discovery and development of better colorectal cancer risk prediction models.
.
Summary
Chemoprevention is proposed as a clinical analogue of population prevention, aimed at reducing likelihood of disease progression. Cardiovascular chemoprevention is successful but ...chemoprevention of cancer is an almost universal failure. This review presents the evidence and asks why.
Chemoprevention is proposed as a clinical analogue of population prevention, aimed at reducing likelihood of disease progression, not across the population, but in identified high-risk individuals and not by behavioral or lifestyle modification, but by the use of pharmaceutical agents. Cardiovascular chemoprevention is successful via control of hyperlipidemias and hypertension. However, chemoprevention of cancer is an almost universal failure: not only are some results null; even more frequently, there is an excess of disease, including disease that the agents were chosen specifically to reduce. A brief introduction is followed by the evidence for a wide variety of agents and their largely deleterious, sometimes null, and in one case, largely beneficial, consequences as possible chemopreventives. The agents include (i) those that are food derived and their synthetic analogues: β-carotene, folic acid, retinol and retinoids, vitamin E, multivitamin supplements, vitamin C, calcium and selenium and (ii) agents targeted at metabolic and hormonal pathways: statins, estrogen and antagonists, 5α-reductase inhibitors. There are two agents for which there is good evidence of benefit when the strategy is focused on those at defined high risk but where wider application is much more problematic: aspirin and tamoxifen. The major problems with cancer chemoprevention are presented. This is followed by a hypothesis to explain the failure of cancer chemoprevention as an enterprise, arguing that the central tenets that underpin it are flawed and showing why, far from doing good, cancer chemoprevention causes harm.
Guidelines for initiating colorectal cancer (CRC) screening are based on family history but do not consider lifestyle, environmental, or genetic risk factors. We developed models to determine risk of ...CRC, based on lifestyle and environmental factors and genetic variants, and to identify an optimal age to begin screening.
We collected data from 9748 CRC cases and 10,590 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colorectal Transdisciplinary study, from 1992 through 2005. Half of the participants were used to develop the risk determination model and the other half were used to evaluate the discriminatory accuracy (validation set). Models of CRC risk were created based on family history, 19 lifestyle and environmental factors (E-score), and 63 CRC-associated single-nucleotide polymorphisms identified in genome-wide association studies (G-score). We evaluated the discriminatory accuracy of the models by calculating area under the receiver operating characteristic curve values, adjusting for study, age, and endoscopy history for the validation set. We used the models to project the 10-year absolute risk of CRC for a given risk profile and recommend ages to begin screening in comparison to CRC risk for an average individual at 50 years of age, using external population incidence rates for non-Hispanic whites from the Surveillance, Epidemiology, and End Results program registry.
In our models, E-score and G-score each determined risk of CRC with greater accuracy than family history. A model that combined both scores and family history estimated CRC risk with an area under the receiver operating characteristic curve value of 0.63 (95% confidence interval, 0.62–0.64) for men and 0.62 (95% confidence interval, 0.61–0.63) for women; area under the receiver operating characteristic curve values based on only family history ranged from 0.53 to 0.54 and those based only E-score or G-score ranged from 0.59 to 0.60. Although screening is recommended to begin at age 50 years for individuals with no family history of CRC, starting ages calculated based on combined E-score and G-score differed by 12 years for men and 14 for women, for individuals with the highest vs the lowest 10% of risk.
We used data from 2 large international consortia to develop CRC risk calculation models that included genetic and environmental factors along with family history. These determine risk of CRC and starting ages for screening with greater accuracy than the family history only model, which is based on the current screening guideline. These scoring systems might serve as a first step toward developing individualized CRC prevention strategies.
Display omitted
Summary Background Overweight and obesity are increasing worldwide. To help assess their relevance to mortality in different populations we conducted individual-participant data meta-analyses of ...prospective studies of body-mass index (BMI), limiting confounding and reverse causality by restricting analyses to never-smokers and excluding pre-existing disease and the first 5 years of follow-up. Methods Of 10 625 411 participants in Asia, Australia and New Zealand, Europe, and North America from 239 prospective studies (median follow-up 13·7 years, IQR 11·4–14·7), 3 951 455 people in 189 studies were never-smokers without chronic diseases at recruitment who survived 5 years, of whom 385 879 died. The primary analyses are of these deaths, and study, age, and sex adjusted hazard ratios (HRs), relative to BMI 22·5–<25·0 kg/m2. Findings All-cause mortality was minimal at 20·0–25·0 kg/m2 (HR 1·00, 95% CI 0·98–1·02 for BMI 20·0–<22·5 kg/m2 ; 1·00, 0·99–1·01 for BMI 22·5–<25·0 kg/m2 ), and increased significantly both just below this range (1·13, 1·09–1·17 for BMI 18·5–<20·0 kg/m2 ; 1·51, 1·43–1·59 for BMI 15·0–<18·5) and throughout the overweight range (1·07, 1·07–1·08 for BMI 25·0–<27·5 kg/m2 ; 1·20, 1·18–1·22 for BMI 27·5–<30·0 kg/m2 ). The HR for obesity grade 1 (BMI 30·0–<35·0 kg/m2 ) was 1·45, 95% CI 1·41–1·48; the HR for obesity grade 2 (35·0–<40·0 kg/m2 ) was 1·94, 1·87–2·01; and the HR for obesity grade 3 (40·0–<60·0 kg/m2 ) was 2·76, 2·60–2·92. For BMI over 25·0 kg/m2 , mortality increased approximately log-linearly with BMI; the HR per 5 kg/m2 units higher BMI was 1·39 (1·34–1·43) in Europe, 1·29 (1·26–1·32) in North America, 1·39 (1·34–1·44) in east Asia, and 1·31 (1·27–1·35) in Australia and New Zealand. This HR per 5 kg/m2 units higher BMI (for BMI over 25 kg/m2 ) was greater in younger than older people (1·52, 95% CI 1·47–1·56, for BMI measured at 35–49 years vs 1·21, 1·17–1·25, for BMI measured at 70–89 years; pheterogeneity <0·0001), greater in men than women (1·51, 1·46–1·56, vs 1·30, 1·26–1·33; pheterogeneity <0·0001), but similar in studies with self-reported and measured BMI. Interpretation The associations of both overweight and obesity with higher all-cause mortality were broadly consistent in four continents. This finding supports strategies to combat the entire spectrum of excess adiposity in many populations. Funding UK Medical Research Council, British Heart Foundation, National Institute for Health Research, US National Institutes of Health.
Research methods for biomarker evaluation lag behind those for evaluating therapeutic treatments. Although a phased approach to development of biomarkers exists and guidelines are available for ...reporting study results, a coherent and comprehensive set of guidelines for study design has not been delineated. We describe a nested case–control study design that involves prospective collection of specimens before outcome ascertainment from a study cohort that is relevant to the clinical application. The biomarker is assayed in a blinded fashion on specimens from randomly selected case patients and control subjects in the study cohort. We separately describe aspects of the design that relate to the clinical context, biomarker performance criteria, the biomarker test, and study size. The design can be applied to studies of biomarkers intended for use in disease diagnosis, screening, or prognosis. Common biases that pervade the biomarker research literature would be eliminated if these rigorous standards were followed.
Aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) show indisputable promise as chemopreventive agents. Possible targets include cancers of the colon, stomach, breast and lung. However, ...recent studies raise concern about potential cardiovascular toxicity associated with the use of NSAIDs that specifically target the enzyme cyclooxygenase 2. These findings, and others that show that inherited genetic characteristics might determine preventive success, argue for new strategies that are tailored to individual medical history and genetic make-up.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Humans have lived from equator to poles for millennia but are now increasingly intruding into the wild spaces of other species and steadily extruding ourselves from our own wild spaces, with a ...profound impact on: our relationship with the natural world; survival of other species; pollution; climate change; etc. We have yet to grasp how these changes directly impact our own health. The primary focus of this paper is on the beneficial influence of proximity to the natural environment. We summarize the evidence for associations between exposure to green space and blue space and improvements in health. In contrast, grey space – the urban landscape – largely presents hazards as well as reducing exposure to green and blue space and isolating us from the natural environment. We discuss various hypotheses that might explain why green, blue, and grey space affect health and focus particularly on the importance of the biodiversity hypothesis and the role of microbiota. We discuss possible mechanisms and exposure routes – air, soil, and water. We highlight the problem of exposure assessment, noting that many of our current tools are not fit for the purpose of understanding exposure to green and blue space, aerosols, soils, and water. We briefly discuss possible differences between indigenous perspectives on the nature of our relationship with the environment and the more dominant international-science view. Finally, we present research gaps and discuss future directions, particularly focusing on the ways in which we might – even in the absence of a full understanding of the mechanisms by which blue, green, and grey space affect our health – begin to implement policies to restore some balance to our environment of with the aim of reducing the large global burden of ill health.
Display omitted
•We are increasingly excluding ourselves from our wild spaces.•There are health consequences of this loss of exposure to green and blue spaces.•This loss is severing the connection between human and environmental microbiota.•We need better tools to quantify aspects of exposure to environment.•We need a major focus on increasing human exposure to the natural environment.
PDF
