Development and comparative assessment of Raman spectroscopic classification algorithms for lesion discrimination in stereotactic breast biopsies with microcalcifications

Microcalcifications are an early mammographic sign of breast cancer and a target for stereotactic breast needle biopsy. Here, we develop and compare different approaches for developing Raman classification algorithms to diagnose invasive and in situ breast cancer, fibrocystic change and fibroadenoma that can be associated with microcalcifications. In this study, Raman spectra were acquired from tissue cores obtained from fresh breast biopsies and analyzed using a constituent‐based breast model. Diagnostic algorithms based on the breast model fit coefficients were devised using logistic regression, C4.5 decision tree classification, k‐nearest neighbor (k ‐NN) and support vector machine (SVM) analysis, and subjected to leave‐one‐out cross validation. The best performing algorithm was based on SVM analysis (with radial basis function), which yielded a positive predictive value of 100% and negative predictive value of 96% for cancer diagnosis. Importantly, these results demonstrate that Raman spectroscopy provides adequate diagnostic information for lesion discrimination even in the presence of microcalcifications, which to the best of our knowledge has not been previously reported. (© 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

A hybrid model for nonignorable dropout in longitudinal binary responses

This article presents a likelihood-based method for handling nonignorable dropout in longitudinal studies with binary responses. The methodology developed is appropriate when the target of inference is the marginal distribution of the response at each occasion and its dependence on covariates. A "hybrid" model is formulated, which is designed to retain advantageous features of the selection and pattern-mixture model approaches. This formulation accommodates a variety of assumed forms of nonignorable dropout, while maintaining transparency of the constraints required for identifying the overall model. Once appropriate identifying constraints have been imposed, likelihood-based estimation is conducted via the EM algorithm. The article concludes by applying the approach to data from a randomized clinical trial comparing two doses of a contraceptive.     

Maximum likelihood estimation of marginal pairwise associations with multiple source predictors

Researchers interested in the association of a predictor with an outcome will often collect information about that predictor from more than one source. Standard multiple regression methods allow estimation of the effect of each predictor on the outcome while controlling for the remaining predictors. The resulting regression coefficient for each predictor has an interpretation that is conditional on all other predictors. In settings in which interest is in comparison of the marginal pairwise relationships between each predictor and the outcome separately (e.g., studies in psychiatry with multiple informants or comparison of the predictive values of diagnostic tests), standard regression methods are not appropriate. Instead, the generalized estimating equations (GEE) approach can be used to simultaneously estimate, and make comparisons among, the separate pairwise marginal associations. In this paper, we consider maximum likelihood (ML) estimation of these marginal relationships when the outcome is binary. ML enjoys benefits over GEE methods in that it is asymptotically efficient, can accommodate missing data that are ignorable, and allows likelihood-based inferences about the pairwise marginal relationships. We also explore the asymptotic relative efficiency of ML and GEE methods in this setting.     

A randomised controlled trial and cost effectiveness study of systematic screening (targeted and total population screening) versus routine practice for the detection of atrial fibrillation in the over 65s: (SAFE) [ISRCTN19633732]

Background

Atrial fibrillation (AF) has been recognised as an important independent risk factor for thromboembolic disease, particularly stroke for which it provides a five-fold increase in risk. This study aimed to determine the baseline prevalence and the incidence of AF based on a variety of screening strategies and in doing so to evaluate the incremental cost-effectiveness of different screening strategies, including targeted or whole population screening, compared with routine clinical practice, for detection of AF in people aged 65 and over. The value of clinical assessment and echocardiography as additional methods of risk stratification for thromboembolic disease in patients with AF were also evaluated.

Methods

The study design was a multi-centre randomised controlled trial with a study population of patients aged 65 and over from 50 General Practices in the West Midlands. These purposefully selected general practices were randomly allocated to 25 intervention practices and 25 control practices. GPs and practice nurses within the intervention practices received education on the importance of AF detection and ECG interpretation. Patients in the intervention practices were randomly allocated to systematic (n = 5000) or opportunistic screening (n = 5000). Prospective identification of pre-existing risk factors for AF within the screened population enabled comparison between high risk targeted screening and total population screening. AF detection rates in systematically screened and opportunistically screened populations in the intervention practices were compared to AF detection rate in 5,000 patients in the control practices.     

Protocol for Birmingham Atrial Fibrillation Treatment of the Aged study (BAFTA): a randomised controlled trial of warfarin versus aspirin for stroke prevention in the management of atrial fibrillation in an elderly primary care population [ISRCTN89345269]

Background

Statins effectively lower blood cholesterol and the risk of cardiovascular death. Immunomodulatory actions, independent of their lipid-lowering effect, have also been ascribed to these compounds. Since macrophages participate in several vascular pathologies, we examined the effect of statin treatment on the survival and differentiation of primary human monocytes.

Methods

Peripheral blood mononuclear cells (PBMCs) from healthy individuals were cultured in the presence or absence of mevastatin. Apoptosis was monitored by annexin V / PI staining and flow cytometry. In parallel experiments, cultures were stimulated with LPS in the presence or absence of mevastatin and the release of IL-1β and IL-1Ra was measured by ELISA.

Results

Among PBMCs, mevastatin-treated monocytes were particularly susceptible to apoptosis, which occurred at doses >1 microM and was already maximal at 5 microM. However, even at the highest mevastatin dose used (10 microM), apoptosis occurred only after 24 h of culture, possibly reflecting a requirement for cell commitment to differentiation. After 72 h of treatment the vast majority (>50%) of monocytes were undergoing apoptosis. Stimulation with LPS revealed that mevastatin-treated monocytes retained the high IL-1β output characteristic of undifferentiated cells; conversely, IL-1Ra release was inhibited. Concurrent treatment with mevalonolactone prevented the induction of apoptosis and suppressed both IL-1β and IL-1Ra release in response to LPS, suggesting a rate-limiting role for HMG-CoA reductase in monocyte differentiation.

Conclusions

Our findings indicate that statins arrest the functional differentiation of monocytes into macrophages and steer these cells into apoptosis, suggesting a novel mechanism for the vasculoprotective properties of HMG-CoA reductase inhibitors.