An assessment of existing models for individualized breast cancer risk estimation in a screening program in Spain

Background: The aim of this study was to evaluate the calibration and discriminatory power of three predictive models of breast cancer risk. Methods: We included 13,760 women who were first-time participants in the Sabadell-Cerdanyola Breast Cancer Screening Program, in Catalonia, Spain. Projections of risk were obtained at three and five years for invasive cancer using the Gail, Chen and Barlow models. Incidence and mortality data were obtained from the Catalan registries. The calibration and discrimination of the models were assessed using the Hosmer-Lemeshow C statistic, the area under the receiver operating characteristic curve (AUC) and the Harrell’s C statistic. Results: The Gail and Chen models showed good calibration while the Barlow model overestimated the number of cases: the ratio between estimated and observed values at 5 years ranged from 0.86 to 1.55 for the first two models and from 1.82 to 3.44 for the Barlow model. The 5-year projection for the Chen and Barlow models had the highest discrimination, with an AUC around 0.58. The Harrell’s C statistic showed very similar values in the 5-year projection for each of the models. Although they passed the calibration test, the Gail and Chen models overestimated the number of cases in some breast density categories. Conclusions: These models cannot be used as a measure of individual risk in early detection programs to customize screening strategies. The inclusion of longitudinal measures of breast density or other risk factors in joint models of survival and longitudinal data may be a step towards personalized early detection of BC.This study was funded by grant PS09/01340 and The Spanish Network on Chronic Diseases REDISSEC (RD12/0001/0007) from the Health Research Fund (Fondo de Investigación Sanitaria) of the Spanish Ministry of Health

Contemporary accuracy of death certificates for coding prostate cancer as a cause of death : Is reliance on death certification good enough? A comparison with blinded review by an independent cause of death evaluation committee

BACKGROUND: Accurate cause of death assignment is crucial for prostate cancer epidemiology and trials reporting prostate cancer-specific mortality outcomes. METHODS: We compared death certificate information with independent cause of death evaluation by an expert committee within a prostate cancer trial (2002-2015). RESULTS: Of 1236 deaths assessed, expert committee evaluation attributed 523 (42%) to prostate cancer, agreeing with death certificate cause of death in 1134 cases (92%, 95% CI: 90%, 93%). The sensitivity of death certificates in identifying prostate cancer deaths as classified by the committee was 91% (95% CI: 89%, 94%); specificity was 92% (95% CI: 90%, 94%). Sensitivity and specificity were lower where death occurred within 1 year of diagnosis, and where there was another primary cancer diagnosis. CONCLUSIONS: UK death certificates accurately identify cause of death in men with prostate cancer, supporting their use in routine statistics. Possible differential misattribution by trial arm supports independent evaluation in randomised trials

Modeling causes of death: an integrated approach using CODEm

Background: Data on causes of death by age and sex are a critical input into health decision-making. Priority setting in public health should be informed not only by the current magnitude of health problems but by trends in them. However, cause of death data are often not available or are subject to substantial problems of comparability. We propose five general principles for cause of death model development, validation, and reporting.Methods: We detail a specific implementation of these principles that is embodied in an analytical tool - the Cause of Death Ensemble model (CODEm) - which explores a large variety of possible models to estimate trends in causes of death. Possible models are identified using a covariate selection algorithm that yields many plausible combinations of covariates, which are then run through four model classes. The model classes include mixed effects linear models and spatial-temporal Gaussian Process Regression models for cause fractions and death rates. All models for each cause of death are then assessed using out-of-sample predictive validity and combined into an ensemble with optimal out-of-sample predictive performance.Results: Ensemble models for cause of death estimation outperform any single component model in tests of root mean square error, frequency of predicting correct temporal trends, and achieving 95% coverage of the prediction interval. We present detailed results for CODEm applied to maternal mortality and summary results for several other causes of death, including cardiovascular disease and several cancers.Conclusions: CODEm produces better estimates of cause of death trends than previous methods and is less susceptible to bias in model specification. We demonstrate the utility of CODEm for the estimation of several major causes of death

A simulation model approach to analysis of the business case for eliminating health care disparities

<p>Abstract</p> <p>Background</p> <p>Purchasers can play an important role in eliminating racial and ethnic disparities in health care. A need exists to develop a compelling "business case" from the employer perspective to put, and keep, the issue of racial/ethnic disparities in health care on the quality improvement agenda for health plans and providers.</p> <p>Methods</p> <p>To illustrate a method for calculating an employer business case for disparity reduction and to compare the business case in two clinical areas, we conducted analyses of the direct (medical care costs paid by employers) and indirect (absenteeism, productivity) effects of eliminating known racial/ethnic disparities in mammography screening and appropriate medication use for patients with asthma. We used Markov simulation models to estimate the consequences, for defined populations of African-American employees or health plan members, of a 10% increase in HEDIS mammography rates or a 10% increase in appropriate medication use among either adults or children/adolescents with asthma.</p> <p>Results</p> <p>The savings per employed African-American woman aged 50-65 associated with a 10% increase in HEDIS mammography rate, from direct medical expenses and indirect costs (absenteeism, productivity) combined, was $50. The findings for asthma were more favorable from an employer point of view at approximately$1,660 per person if raising medication adherence rates in African-American employees or dependents by 10%.</p> <p>Conclusions</p> <p>For the employer business case, both clinical scenarios modeled showed positive results. There is a greater potential financial gain related to eliminating a disparity in asthma medications than there is for eliminating a disparity in mammography rates.</p

Effect of prostaglandin analogs on matrix metalloproteinases and tissue inhibitor of metalloproteinases in eyelid muscle specimens

Sapir Karli, Juan Alfredo Ayala-Haedo, William J Feuer, Maria Fernandez, Sander Dubovy, Sara T Wester Bascom Palmer Eye Institute, Miami, FL, USA Purpose: To characterize the effect of prostaglandin analogs (PAs) on tissue specific expression of matrix metalloproteinases (MMPs) and tissue inhibitor of metalloproteinases (TIMPs) in levator aponeurosis resections (LAR) and conjunctiva-Muller muscle resections (CMMR).Methods: Specimens from LAR and CMMR of PA users and non-users were analyzed for tissue specific expression of MMP-3, MMP-7, MMP-9 and TIMP-2 using immunohistochemistry. PA use, marginal reflex distances, levator function and palpebral fissure were documented through chart review. The associations between MMP expression, PA exposure time and ocular characteristics were evaluated with a two-factor analysis of variance and multiple correlation analysis.Results: We observed a tissue specific pattern of expression of MMPs and TIMP-2 in relation to PA exposure between CMMR and LAR specimens. There was increased MMP-7 and TIMP-2 expression in muscle compared to collagen and adipose tissue (P&le;0.005), as well as a statistically significant difference in the relationship of MMP-3, MMP-9 and TIMP-2 levels to PA exposure in the two types of muscles (all P&le;0.011). Adipose tissue had a PA-dependent reduced expression of MMP-3 (P&lt;0.022), which was seen in both LAR and CMMR. Decreased expression of MMP-3 in collagen correlated with increased dermatochalasis (P&lt;0.045) and steatoblepharon (P&lt;0.018).Conclusion: PA exposure may affect MMP and TIMP expression in a tissue specific manner, and decreased expression of certain MMPs in collagen correlates to increased clinical measures of prostaglandin associated periorbitopathy (PAP). Further studies with larger samples are needed to ascertain if the changes associated with PAP are due to MMP/TIMP changes or to structural changes. Keywords: MMP, matrix metalloproteinase, prostaglandin associated periorbitopathy, PAP, prostaglandin analog, periorbitopath

Molecular basis for G-actin binding to RPEL motifs from the serum response factor coactivator MAL

Serum response factor transcriptional activity is controlled through interactions with regulatory cofactors such as the coactivator MAL/MRTF-A (myocardin-related transcription factor A). MAL is itself regulated in vivo by changes in cellular actin dynamics, which alter its interaction with G-actin. The G-actin-sensing mechanism of MAL/MRTF-A resides in its N-terminal domain, which consists of three tandem RPEL repeats. We describe the first molecular insights into RPEL function obtained from structures of two independent RPELMAL peptide:G-actin complexes. Both RPEL peptides bind to the G-actin hydrophobic cleft and to subdomain 3. These RPELMAL:G-actin structures explain the sequence conservation defining the RPEL motif, including the invariant arginine. Characterisation of the RPELMAL:G-actin interaction by fluorescence anisotropy and cell reporter-based assays validates the significance of actin-binding residues for proper MAL localisation and regulation in vivo. We identify important differences in G-actin engagement between the two RPELMAL structures. Comparison with other actin-binding proteins reveals an unexpected similarity to the vitamin-D-binding protein, extending the G-actin-binding protein repertoire