Assessing risk of breast cancer in an ethnically South-East Asia population (results of a multiple ethnic groups study)

10.1186/1471-2407-12-529BMC Cancer12-BCMA

Premenopausal endogenous oestrogen levels and breast cancer risk: a meta-analysis.

BACKGROUND: Many of the established risk factors for breast cancer implicate circulating hormone levels in the aetiology of the disease. Increased levels of postmenopausal endogenous oestradiol (E2) have been found to increase the risk of breast cancer, but no such association has been confirmed in premenopausal women. We carried out a meta-analysis to summarise the available evidence in women before the menopause. METHODS: We identified seven prospective studies of premenopausal endogenous E2 and breast cancer risk, including 693 breast cancer cases. From each study we extracted odds ratios of breast cancer between quantiles of endogenous E2, or for unit or s.d. increases in (log transformed) E2, or (where odds ratios were unavailable) summary statistics for the distributions of E2 in breast cancer cases and unaffected controls. Estimates for a doubling of endogenous E2 were obtained from these extracted estimates, and random-effect meta-analysis was used to obtain a pooled estimate across the studies. RESULTS: Overall, we found weak evidence of a positive association between circulating E2 levels and the risk of breast cancer, with a doubling of E2 associated with an odds ratio of 1.10 (95% CI: 0.96, 1.27). CONCLUSION: Our findings are consistent with the hypothesis of a positive association between premenopausal endogenous E2 and breast cancer risk

A reference relative time-scale as an alternative to chronological age for cohorts with long follow-up

Background: Epidemiologists have debated the appropriate time-scale for cohort survival studies; chronological age or time-on-study being two such time-scales. Importantly, assessment of risk factors may depend on the choice of time-scale. Recently, chronological or attained age has gained support but a case can be made for a ‘reference relative time-scale’ as an alternative which circumvents difficulties that arise with this and other scales. The reference relative time of an individual participant is the integral of a reference population hazard function between time of entry and time of exit of the individual. The objective here is to describe the reference relative time-scale, illustrate its use, make comparison with attained age by simulation and explain its relationship to modern and traditional epidemiologic methods. Results: A comparison was made between two models; a stratified Cox model with age as the time-scale versus an un-stratified Cox model using the reference relative time-scale. The illustrative comparison used a UK cohort of cotton workers, with differing ages at entry to the study, with accrual over a time period and with long follow-up. Additionally, exponential and Weibull models were fitted since the reference relative time-scale analysis need not be restricted to the Cox model. A simulation study showed that analysis using the reference relative time-scale and analysis using chronological age had very similar power to detect a significant risk factor and both were equally unbiased. Further, the analysis using the reference relative time-scale supported fully-parametric survival modelling and allowed percentile predictions and mortality curves to be constructed. Conclusions: The reference relative time-scale was a viable alternative to chronological age, led to simplification of the modelling process and possessed the defined features of a good time-scale as defined in reliability theory. The reference relative time-scale has several interpretations and provides a unifying concept that links contemporary approaches in survival and reliability analysis to the traditional epidemiologic methods of Poisson regression and standardised mortality ratios. The community of practitioners has not previously made this connection

Sutherlandia frutescens: The meeting of science and traditional knowledge

Sutherlandia frutescens (L.) R.Br. (syn. Lessertia frutescens (L.) Goldblatt and J.C. Manning) is an indigenous medicinal plant extensively used in South Africa to treat a variety of health conditions. It is a fairly widespread, drought-resistant plant that grows in the Western, Eastern, and Northern Cape provinces and some areas of KwaZulu-Natal, varying in its chemical and genetic makeup across these geographic areas.1 Sutherlandia is widely used as a traditional medicine. Extensive scientific studies are being carried out on the safety, quality, and the efficacy of this medicinal plant to validate the traditional claims, elucidate the bioactive constituents, and conduct clinical trials. This has resulted in a unique situation in South Africa’s history, where traditional knowledge and science intersect to provide insight into this popular plant. This photoessay attempts to illustrate the interlinkage of science with the indigenous knowledge of traditional healers, the local knowledge of people who care for the sick, product development, and innovation agenda of the country as it relates to this plant.Web of Scienc

A self-report risk index to predict occurrence of dementia in three independent cohorts of older adults: The ANU-ADRI

Background and Aims: The Australian National University AD Risk Index (ANU-ADRI, http://anuadri.anu.edu.au) is a self-report risk index developed using an evidence-based medicine approach to measure risk of Alzheimer's disease (AD). We aimed to evaluate the extent to which the ANU-ADRI can predict the risk of AD in older adults and to compare the ANU-ADRI to the dementia risk index developed from the Cardiovascular Risk Factors, Aging and Dementia (CAIDE) study for middle-aged cohorts. Methods: This study included three validation cohorts, i.e., the Rush Memory and Aging Study (MAP) (n = 903, age ≥53 years), the Kungsholmen Project (KP) (n = 905, age ≥75 years), and the Cardiovascular Health Cognition Study (CVHS) (n = 2496, age ≥65 years) that were each followed for dementia. Baseline data were collected on exposure to the 15 risk factors included in the ANU-ADRI of which MAP had 10, KP had 8 and CVHS had 9. Risk scores and C-statistics were computed for individual participants for the ANU-ADRI and the CAIDE index. Results: For the ANU-ADRI using available data, the MAP study c-statistic was 0.637 (95% CI 0.596-0.678), for the KP study it was 0.740 (0.712-0.768) and for the CVHS it was 0.733 (0.691-0.776) for predicting AD. When a common set of risk and protective factors were used c-statistics were 0.689 (95% CI 0.650-0.727), 0.666 (0.628-0.704) and 0.734 (0.707-0.761) for MAP, KP and CVHS respectively. Results for CAIDE ranged from c-statistics of 0.488 (0.427-0.554) to 0.595 (0.565-0.625). Conclusion: A composite risk score derived from the ANU-ADRI weights including 8-10 risk or protective factors is a valid, self-report tool to identify those at risk of AD and dementia. The accuracy can be further improved in studies including more risk factors and younger cohorts with long-term follow-up. © 2014 Anstey et al

Simulation modeling for stratified breast cancer screening : a systematic review of cost and quality of life assumptions

BACKGROUND: The economic evaluation of stratified breast cancer screening gains momentum, but produces also very diverse results. Systematic reviews so far focused on modeling techniques and epidemiologic assumptions. However, cost and utility parameters received only little attention. This systematic review assesses simulation models for stratified breast cancer screening based on their cost and utility parameters in each phase of breast cancer screening and care. METHODS: A literature review was conducted to compare economic evaluations with simulation models of personalized breast cancer screening. Study quality was assessed using reporting guidelines. Cost and utility inputs were extracted, standardized and structured using a care delivery framework. Studies were then clustered according to their study aim and parameters were compared within the clusters. RESULTS: Eighteen studies were identified within three study clusters. Reporting quality was very diverse in all three clusters. Only two studies in cluster 1, four studies in cluster 2 and one study in cluster 3 scored high in the quality appraisal. In addition to the quality appraisal, this review assessed if the simulation models were consistent in integrating all relevant phases of care, if utility parameters were consistent and methodological sound and if cost were compatible and consistent in the actual parameters used for screening, diagnostic work up and treatment. Of 18 studies, only three studies did not show signs of potential bias. CONCLUSION: This systematic review shows that a closer look into the cost and utility parameter can help to identify potential bias. Future simulation models should focus on integrating all relevant phases of care, using methodologically sound utility parameters and avoiding inconsistent cost parameters

Use of tamoxifen and raloxifene for breast cancer chemoprevention in 2010

PURPOSE: Two selective estrogen receptor modulators (SERMs), tamoxifen and raloxifene, have been shown in randomized clinical trials to reduce the risk of developing primary invasive breast cancer (IBC) in high-risk women. In 1998, the U.S. Food and Drug Administration (FDA) used these studies as a basis for approving tamoxifen for primary breast chemoprevention in both premenopausal and postmenopausal women at high risk. In 2007, the FDA approved raloxifene for primary breast cancer chemoprevention for postmenopausal women. METHODS: Data from the year 2010 National Health Interview Survey (NHIS) were analyzed to estimate the prevalence of tamoxifen and raloxifene use for chemoprevention of primary breast cancers among U.S. women. RESULTS: Prevalence of use of chemopreventive agents for primary tumors was 20,598 (95% CI, 518–114,864) for U.S. women aged 35 to 79 for tamoxifen. Prevalence was 96,890 (95% CI, 41,277–192,391) for U.S. women aged 50 to79 for raloxifene. CONCLUSION: Use of tamoxifen and raloxifene for prevention of primary breast cancers continues to be low. In 2010, women reporting medication use for breast cancer chemoprevention were primarily using the more recently FDA-approved drug raloxifene. Multiple possible explanations for the low use exist, including lack of awareness and/or concern about side effects among primary care physicians and patients

Trends in C-Reactive Protein testing: a retrospective cohort study in paediatric ambulatory care settings

Objectives This study aims to investigate CRP testing practices in paediatric ambulatory care across British primary care and accident and emergency (A&E) departments‎. Design, Setting, Participants: This retrospective cohort study included ‎children <18 years old having ≥1 CRP test at primary care or A&E departments in Oxfordshire between 2007-2021. Outcomes: We estimated the frequency and annual changes in CRP testing in both settings‎, and evaluated referral and admission patterns based on CRP levels: low (<20 mg/L), ‎intermediate, or high (≥80 mg/L). Results Over 15 years, 91,540 CRP tests were requested in 63,226 children, with 33,882 (53.6%) in ‎primary care and 29,344 (46.4%) in A&E. Both settings showed rising trends in test requests, ‎with average annual percentage change of 3.0% (95% CI 1.2 to 4.7) in primary care and ‎‎11.5% (95% CI 8.6 to 14.6) in A&E. The proportion of intermediate/high-test results remained ‎stable. In primary care, 50,709 (95.8%) of tests were <20 mg/L, with 99.0% of these children ‎managed at home. High and intermediate CRP values increased odds of referral versus low CRP ‎(Odds ‎ratio (OR) adjusted for age= 21.80; 95% CI 16.49 to 28.81 and 4.77; 3.78 to 6.02, ‎respectively). At A&E, 27,610 (71.5%) children had CRP <20 mg/L, of whom 42.5% were ‎admitted, while 3,776 (9.8%) had CRP ≥ 80 mg/L with 57.9% admission rate. High and ‎intermediate CRP values increased odds of admission versus low CRP‎ (OR adjusted for age= ‎‎1.90; 95% CI 1.78 to 2.04 and 1.39; 1.32 to 1.46, respectively). Conclusion: There are rising trends of ‎CRP test requests at paediatric ambulatory care settings, with no evidence of increases in proportion of intermediate/high-test results in primary care. Low CRP values at primary care were linked to children managed at home, while almost half of children with low CRP values at A&E were admitted to hospital

The Marker State Space (MSS) Method for Classifying Clinical Samples

The development of accurate clinical biomarkers has been challenging in part due to the diversity between patients and diseases. One approach to account for the diversity is to use multiple markers to classify patients, based on the concept that each individual marker contributes information from its respective subclass of patients. Here we present a new strategy for developing biomarker panels that accounts for completely distinct patient subclasses. Marker State Space (MSS) defines "marker states" based on all possible patterns of high and low values among a panel of markers. Each marker state is defined as either a case state or a control state, and a sample is classified as case or control based on the state it occupies. MSS was used to define multi-marker panels that were robust in cross validation and training-set/test-set analyses and that yielded similar classification accuracy to several other classification algorithms. A three-marker panel for discriminating pancreatic cancer patients from control subjects revealed subclasses of patients based on distinct marker states. MSS provides a straightforward approach for modeling highly divergent subclasses of patients, which may be adaptable for diverse applications. © 2013 Fallon et al

Mammographic density adds accuracy to both the Tyrer-Cuzick and Gail breast cancer risk models in a prospective UK screening cohort

This work was supported by the National Institute for Health Research (NIHR) and Genesis Breast Cancer Prevention Appeal (references GA10-033 and GA13-006). This article presents independent research funded by the NIHR under its Programme Grants for Applied Research (grant RP-PG-0707-10031). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. The authors also acknowledge the support of Medical Research Council Health eResearch Centre grant MR/K006665/1