Assessment of Corneal Epithelial Thickness in Asymmetric Keratoconic Eyes and Normal Eyes Using Fourier Domain Optical Coherence Tomography

Purpose. To compare the characteristics of asymmetric keratoconic eyes and normal eyes by Fourier domain optical coherence tomography (OCT) corneal mapping. Methods. Retrospective corneal and epithelial thickness OCT data for 74 patients were compared in three groups of eyes: keratoconic (n=22) and normal fellow eyes (n=22) in patients with asymmetric keratoconus and normal eyes (n=104) in healthy subjects. Areas under the curve (AUC) of receiver operator characteristic (ROC) curves for each variable were compared across groups to indicate their discrimination capacity. Results. Three variables were found to differ significantly between fellow eyes and normal eyes (all < 0.05 ): minimum corneal thickness, thinnest corneal point, and central corneal thickness. These variables combined showed a high discrimination power to differentiate fellow eyes from normal eyes indicated by an AUC of 0.840 (95% CI: 0.762–0.918). Conclusions. Our findings indicate that topographically normal fellow eyes in patients with very asymmetric keratoconus differ from the eyes of healthy individuals in terms of their corneal epithelial and pachymetry maps. This type of information could be useful for an early diagnosis of keratoconus in topographically normal eyesS

Analysing visual receptive fields through generalised additive models with interactions

Visual receptive fields (RFs) are small areas of the visual field where a stimulus induces a responses of a particular neuron from the visual system. RFs can be mapped using reverse crosscorrelation technique, which produces raw matrices containing both spatial and temporal information about the RF. Though this technique is frequently used in electrophysiological experiments, it does not allow formal comparisons between RFs obtained under different experimental conditions. In this paper we propose the use of Generalised Additive Models (GAM) including complex interactions, to obtain smoothed spatio-temporal versions of RFs. Moreover, the proposed methodology also allow for the statistical comparisons of the RFs obtained across various experimental conditions. Data analysed here derive from studies of neurons' activity in the visual cortex of behaving monkeys. Our results suggest that the GAM-based technique proposed in this paper can be a flexible and powerful tool for assessing receptive field properties

GsymPoint: An R Package to Estimate the Generalized Symmetry Point, an Optimal Cut-off Point for Binary Classification in Continuous Diagnostic Tests

In clinical practice, it is very useful to select an optimal cutpoint in the scale of a continuous biomarker or diagnostic test for classifying individuals as healthy or diseased. Several methods for choosing optimal cutpoints have been presented in the literature, depending on the ultimate goal. One of these methods, the generalized symmetry point, recently introduced, generalizes the symmetry point by incorporating the misclassification costs. Two statistical approaches have been proposed in the literature for estimating this optimal cutpoint and its associated sensitivity and specificity measures, a parametric method based on the generalized pivotal quantity and a nonparametric method based on empirical likelihood. In this paper, we introduce GsymPoint, an R package that implements these methods in a user-friendly environment, allowing the end-user to calculate the generalized symmetry point depending on the levels of certain categorical covariates. The practical use of this package is illustrated using three real biomedical datasetsThis research has been supported by several Grants from the Spanish Ministry of Science and Innovation. M. López-Ratón and C. Cadarso-Suárez acknowledge support to MTM2011-15849-E, MTM2011-28285-C02-00, MTM2014-52975-C2-1-R and MTM2015-69068-REDT. E.M. Molanes-López acknowledges support to MTM2011-28285-C02-02, ECO2011-25706, MTM2011-15849-E and MTM2015-69068-REDT. E. Letón acknowledges support to MTM2011-15849-E, MTM2011-28285-C02-02, PI13/02446 and MTM2015-69068-REDTS

Application of receiver operating characteristic (ROC) methodology in biological studies on marine resources: sex determination of Paracentrotus lividus (Lamarck, 1816)

The receiver operating characteristic (ROC) curve is usually used in biomedicine as an indicator of the accuracy of diagnostic tests. However, this measure of discrimination has been little used in other areas, such as animal biology or ecology. We present a novel application of an ROC analysis in which gonad colour was used to determine the sex of Paracentrotus lividus (Lamarck, 1816), a sea urchin of considerable commercial interest. A better classifier than gonad colour was obtained by transforming these colours through flexible logistic generalized additive models.Peer Reviewe

Application of Generalized Additive Models to the Evaluation of Continuous Markers for Classification Purposes

Background: Receiver operating characteristic (ROC) curve and derived measures as the Area Under the Curve (AUC) are often used for evaluating the discriminatory capability of a continuous biomarker in distinguishing between alternative states of health. However, if the marker shows an irregular distribution, with a dominance of diseased subjects in noncontiguous regions, classification using a single cutpoint is not appropriate, and it would lead to erroneous conclusions. This study sought to describe a procedure for improving the discriminatory capacity of a continuous biomarker, by using generalized additive models (GAMs) for binary data.Methods: A new classification rule is obtained by using logistic GAM regression models to transform the original biomarker, with the predicted probabilities being the new transformed continuous biomarker. We propose using this transformed biomarker to establish optimal cut-offs or intervals on which to base the classification. This methodology is applied to different controlled scenarios, and to real data from a prospective study of patients undergoing surgery at a University Teaching Hospital, for examining plasma glucose as postoperative infection biomarker.Results: Both, theoretical scenarios and real data results show that when the risk marker-disease relationship is not monotone, using the new transformed biomarker entails an improvement in discriminatory capacity. Moreover, in these situations, an optimal interval seems more reasonable than a single cutpoint to define lower and higher disease-risk categories.Conclusions: Using statistical tools which allow for greater flexibility (e.g., GAMs) can optimize the classificatory capacity of a potential marker using ROC analysis. So, it is important to question linearity in marker-outcome relationships, in order to avoid erroneous conclusions

Modelling spatial patterns of distribution and abundance of mussel seed using Structured Additive Regression models

As mussel farming depends on sources of natural mussel seed, knowledge of factors is required to regulate both the spatial distribution and abundance of this resource. These spatial patterns were modelled using Bayesian STructured Additive Regression (STAR) models for categorical data, based on a mixed-model representation. We used Bayesian penalized splines for modelling the continuous covariate effects and a Markov random field prior for estimating the spatial effects

BioStatNet: an interdisciplinary biostatistics network

Biostatistics has become a major scientific component of biomedical research with a strong interdisciplinary basis. This endeavour is essentially interdisciplinary, therefore, training of future biostatisticians must focus its efforts on the development of successful mechanisms of communication and cooperation between researchers from different disciplines. The Biostatistics National Network, BioStatNet, has been created aiming to link together Spanish and foreign researchers in Biostatistics with an integrative and open attitude. It also intends to serve as a platform for the adequate training of biostatisticians as a means towards achieving effective interdisciplinarity.Peer ReviewedPostprint (published version

Application of receiver operating characteristic (ROC) methodology in biological studies on marine resources : sex determination of Paracentrotus lividus (Lamarck, 1816)

The receiver operating characteristic (ROC) curve is usually used in biomedicine as an indicator of the accuracy of diagnostic tests. However, this measure of discrimination has been little used in other areas, such as animal biology or ecology. We present a novel application of an ROC analysis in which gonad colour was used to determine the sex of Paracentrotus lividus (Lamarck, 1816), a sea urchin of considerable commercial interest. A better classifier than gonad colour was obtained by transforming these colours through flexible logistic generalized additive models

Glycemic Variability and Its Association With Demographics and Lifestyles in a General Adult Population

Objective: The objective was to investigate glycemic variability indices in relation to demographic factors and common environmental lifestyles in a general adult population. Methods: The A Estrada Glycation and Inflammation Study is a cross-sectional study covering 1516 participants selected by sampling of the population aged 18 years and over. A subsample of 622 individuals participated in the Glycation project, which included continuous glucose monitoring procedures. Five glycemic variability indices were analyzed, that is, SD, MAGE, MAG, CONGA1, and MODD. Results: Participants had a mean age of 48 years, 62% were females, and 12% had been previously diagnosed with diabetes. In the population without diabetes, index distributions were not normal but skewed to the right. Distributional regression models that adjusted for age, gender, BMI, alcohol intake, smoking status, and physical activity confirmed that all indices were positively and independently associated with fasting glucose levels and negatively with heavy drinking. SD, MAGE, and CONGA1 were positively associated with aging, and MAG was negatively associated with BMI. None of the GVI studied were influenced by physical activity. Age-group-specific reference values are given for the indices. Conclusions: This study yielded age-specific reference values for glucose variability indices in a general adult population. Significant increases were observed with aging. Heavy drinking of more than 140 g/week was associated with significant decreases in variability indices. No differences were found between males and females. These normative ranges provide a guide for clinical care, and may offer an alternative treatment target among persons with diabetesThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research project was supported by grants from Spain’s Carlos III Institute of Health (Instituto de Salud Carlos III/ISCIII) (PI11/02219 & PI13/02594) and the European Regional Development Fund (FEDER). PDV and MAS were supported by ISCIII Preventive Activity & Health Promotion Research Network (Red de Investigación en Actividades Preventivas y de Promoción de Salud/redIAPP) grants RD06/0018/0006 & RD12/0005/0007, respectively. CCS has been partially supported by the Spanish Ministry of Science and Innovation (MTM2015-69068-REDT)S