The accuracy of pathological data for the prediction of insignificant prostate cancer

Introduction: The widespread screening programs prompted a decrease in prostate cancer stage at diagnosis, and active surveillance is an option for patients who may harbor clinically insignificant prostate cancer (IPC). Pathologists include the possibility of an IPC in their reports based on the Gleason score and tumor volume. This study determined the accuracy of pathological data in the identification of IPC in radical prostatectomy (RP) specimens. Materials and Methods: Of 592 radical prostatectomy specimens examined in our laboratory from 2001 to 2010, 20 patients harbored IPC and exhibited biopsy findings suggestive of IPC. These biopsy features served as the criteria to define patients with potentially insignificant tumor in this population. The results of the prostate biopsies and surgical specimens of the 592 patients were compared. Results: The twenty patients who had IPC in both biopsy and RP were considered real positive cases. All patients were divided into groups based on their diagnoses following RP: true positives (n = 20), false positives (n = 149), true negatives (n = 421), false negatives (n = 2). The accuracy of the pathological data alone for the prediction of IPC was 91.4%, the sensitivity was 91% and the specificity was 74%. Conclusion: The identification of IPC using pathological data exclusively is accurate, and pathologists should suggest this in their reports to aid surgeons, urologists and radiotherapists to decide the best treatment for their patients.

Class-specific metrics for multidimensional data projection applied to CBIR

Content-based image retrieval is still a challenging issue due to the inherent complexity of images and choice of the most discriminant descriptors. Recent developments in the field have introduced multidimensional projections to burst accuracy in the retrieval process, but many issues such as introduction of pattern recognition tasks and deeper user intervention to assist the process of choosing the most discriminant features still remain unaddressed. In this paper, we present a novel framework to CBIR that combines pattern recognition tasks, class-specific metrics, and multidimensional projection to devise an effective and interactive image retrieval system. User interaction plays an essential role in the computation of the final multidimensional projection from which image retrieval will be attained. Results have shown that the proposed approach outperforms existing methods, turning out to be a very attractive alternative for managing image data sets.

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data

Background: This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results: The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions: We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

Accuracy of Screening for Potentially Malignant Disorders of the Oral Mucosa by Dentists in Primary Care

Purpose: To examine the accuracy of a screening programme for potentially malignant disorders of the oral mucosa by visual inspection in primary health care. Materials and Methods: The study was based on secondary data from the Primary Care Information System maintained by seven units of family health in Sao Paulo City managed by a non-governmental agency. The reference population was composed of 15,072 residents 50 years old or more of both genders. The study population comprised 2,980 individuals. During screening in community settings, the oral mucosa was examined by trained dentists and distributed into two categories: (a) screen negative (b) screen positive. All participants underwent comprehensive clinical exams by a general dental practitioner supervised by a specialist. Individual records were grouped in a working dataset. Point and 95% confidence interval estimates were calculated regarding measures of sensitivity (Se), specificity (Sp) and positive and negative predictive values (PPV and NPV, respectively). Results: 18.0% of the population was considered screen positive. A total of 133 lesions (4.5%) were identified and 8 cases of oral cancer were confirmed, which corresponded to a prevalence rate of 27 cases in 10,000 people, a much higher rate than expected. The measures found were Se: 91.7% (85.3-95.6), Sp: 85.4% (84.1-86.7), PPV: 22.7% (19.3-26.5), NPV: 99.5% (99.2-99.8). The visual screen presented high accuracy. Conclusion: The test presented high sensibility and specificity values. From a public health point of view, the high accuracy levels showed the importance of oral health teams on family health strategy for more comprehensive primary care. Targeting risk groups and delegating the screening to community health agents may improve PPV and coverage.

Accuracy of Timed Up and Go Test for screening risk of falls among community-dwelling elderly

Objective: To determine the accuracy of the Timed Up and Go Test (TUGT) for screening the risk of falls among community-dwelling elderly individuals. Method: This is a prospective cohort study with a randomly by lots without reposition sample stratified by proportional partition in relation to gender involving 63 community-dwelling elderly individuals. Elderly individuals who reported having Parkinson's disease, a history of transitory ischemic attack, stroke and with a Mini Mental State Exam lower than the expected for the education level, were on a wheelchair and that reported a single fall in the previous six months were excluded. The TUGT, a mobility test, was the measure of interested and the occurrence of falls was the outcome. The performance of basic activities of daily living (ADL) and instrumental activities of daily living (IADL) was determined through the Older American Resources and Services, and the socio-demographic and clinical data were determined through the use of additional questionnaires. Receiver Operating Characteristic Curves were used to analyze the sensitivity and specificity of the TUGT. Results: Elderly individuals who fell had greater difficulties in ADL and IADL (p<0.01) and a slower performance on the TUGT (p=0.02). No differences were found in socio-demographic and clinical characteristics between fallers and non- fallers. Considering the different sensitivity and specificity, the best predictive value for discriminating elderly individuals who fell was 12.47 seconds [(RR= 3.2) 95% CI: 1.3- 7.7]. Conclusions: The TUGT proved to be an accurate measure for screening the risk of falls among elderly individuals. Although different from that reported in the international literature, the 12.47 second cutoff point seems to be a better predictive value for Brazilian elderly individuals.

Accuracy of positron emission tomography/computed tomography and clinical assessment in the detection of complete rectal tumor regression after neoadjuvant chemoradiation Long-Term Results of a Prospective Trial (National Clinical Trial 00254683)

BACKGROUND: Neoadjuvant chemoradiation (CRT) therapy may result in significant tumor regression in patients with rectal cancer. Patients who develop complete tumor regression have been managed by treatment strategies that are alternatives to standard total mesorectal excision. Therefore, assessment of tumor response with positron emission tomography/computed tomography (PET/CT) after neoadjuvant treatment may offer relevant information for the selection of patients to receive alternative treatment strategies. METHODS: Patients with clinical T2 (cT2) through cT4NxM0 rectal adenocarcinoma were included prospectively. Neoadjuvant therapy consisted of 54 grays of radiation and 5-fluorouracil-based chemotherapy. Baseline PET/CT studies were obtained before CRT followed by PET/CT studies at 6 weeks and 12 weeks after the completion of CRT. Clinical assessment was performed at 12 weeks after CRT completion. PET/CT results were compared with clinical and pathologic data. RESULTS: In total, 99 patients were included in the study. Twenty-three patients were complete responders (16 had a complete clinical response, and 7 had a complete pathologic response). The PET/CT response evaluation at 12 weeks indicated that 18 patients had a complete response, and 81 patients had an incomplete response. There were 5 false-negative and 10 false-positive PET/CT results. PET/CT for the detection of residual cancer had 93% sensitivity, 53% specificity, a 73% negative predictive value, an 87% positive predictive value, and 85% accuracy. Clinical assessment alone resulted in an accuracy of 91%. PET/CT information may have detected misdiagnoses made by clinical assessment alone, improving overall accuracy to 96%. CONCLUSIONS: Assessment of tumor response at 12 weeks after CRT completion with PET/CT imaging may provide a useful additional tool with good overall accuracy for the selection of patients who may avoid unnecessary radical resection after achieving a complete clinical response. Cancer 2012;35013511. (C) 2011 American Cancer Society.

Multivariate analyses of UV-Vis absorption spectral data from cachaca wood extracts: a model to classify aged Brazilian cachacas according to the wood species used

Multivariate analyses of UV-Vis spectral data from cachaca wood extracts provide a simple and robust model to classify aged Brazilian cachacas according to the wood species used in the maturation barrels. The model is based on inspection of 93 extracts of oak and different Brazilian wood species by a non-aged cachaca used as an extraction solvent. Application of PCA (Principal Components Analysis) and HCA (Hierarchical Cluster Analysis) leads to identification of 6 clusters of cachaca wood extracts (amburana, amendoim, balsamo, castanheira, jatoba, and oak). LDA (Linear Discriminant Analysis) affords classification of 10 different wood species used in the cachaca extracts (amburana, amendoim, balsamo, cabreuva-parda, canela-sassafras, castanheira, jatoba, jequitiba-rosa, louro-canela, and oak) with an accuracy ranging from 80% (amendoim and castanheira) to 100% (balsamo and jequitiba-rosa). The methodology provides a low-cost alternative to methods based on liquid chromatography and mass spectrometry to classify cachacas aged in barrels that are composed of different wood species.

Utility Harmonic Impedance Measurement Based on Data Selection

Determination of the utility harmonic impedance based on measurements is a significant task for utility power-quality improvement and management. Compared to those well-established, accurate invasive methods, the noninvasive methods are more desirable since they work with natural variations of the loads connected to the point of common coupling (PCC), so that no intentional disturbance is needed. However, the accuracy of these methods has to be improved. In this context, this paper first points out that the critical problem of the noninvasive methods is how to select the measurements that can be used with confidence for utility harmonic impedance calculation. Then, this paper presents a new measurement technique which is based on the complex data-based least-square regression, combined with two techniques of data selection. Simulation and field test results show that the proposed noninvasive method is practical and robust so that it can be used with confidence to determine the utility harmonic impedances.

On the impact of disproportional samples in credit scoring models: An application to a Brazilian bank data

Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification model can be evaluated based on measures such as sensitivity, specificity, predictive values, accuracy, correlation coefficients and information theoretical measures, such as relative entropy and mutual information. In this paper we analyze the performance of a naive logistic regression model (Hosmer & Lemeshow, 1989) and a logistic regression with state-dependent sample selection model (Cramer, 2004) applied to simulated data. Also, as a case study, the methodology is illustrated on a data set extracted from a Brazilian bank portfolio. Our simulation results so far revealed that there is no statistically significant difference in terms of predictive capacity between the naive logistic regression models and the logistic regression with state-dependent sample selection models. However, there is strong difference between the distributions of the estimated default probabilities from these two statistical modeling techniques, with the naive logistic regression models always underestimating such probabilities, particularly in the presence of balanced samples. (C) 2012 Elsevier Ltd. All rights reserved.

Accuracy of five electronic foramen locators with different operating systems: na ex vivo study

Objective: The aim of this study was to evaluate, ex vivo, the precision of five electronic root canal length measurement devices (ERCLMDs) with different operating systems: the Root ZX, Mini Apex Locator, Propex II, iPex, and RomiApex A-15, and the possible influence of the positioning of the instrument tips short of the apical foramen. Material and Methods: Forty-two mandibular bicuspids had their real canal lengths (RL) previously determined. Electronic measurements were performed 1.0 mm short of the apical foramen (-1.0), followed by measurements at the apical foramen (0.0). The data resulting from the comparison of the ERCLMD measurements and the RL were evaluated by the Wilcoxon and Friedman tests at a significance level of 5%. Results: Considering the measurements performed at 0.0 and -1.0, the precision rates for the ERCLMDs were: 73.5% and 47.1% (Root ZX), 73.5% and 55.9% (Mini Apex Locator), 67.6% and 41.1% (Propex II), 61.7% and 44.1% (iPex), and 79.4% and 44.1% (RomiApex A-15), respectively, considering ±0.5 mm of tolerance. Regarding the mean discrepancies, no differences were observed at 0.0; however, in the measurements at -1.0, the iPex, a multi-frequency ERCLMD, had significantly more discrepant readings short of the apical foramen than the other devices, except for the Propex II, which had intermediate results. When the ERCLMDs measurements at -1.0 were compared with those at 0.0, the Propex II, iPex and RomiApex A-15 presented significantly higher discrepancies in their readings. Conclusions: Under the conditions of the present study, all the ERCLMDs provided acceptable measurements at the 0.0 position. However, at the -1.0 position, the ERCLMDs had a lower precision, with statistically significant differences for the Propex II, iPex, and RomiApex A-15.

Connecting accuracy of interchanged prosthetic abutments to different dental implants using scanning electron microscopy

The present study evaluated the interchangeability of prosthetic components for external hexagon implants by measuring the precision of the implant/abutment (I/A) interface with scanning electron microscopy. Ten implants for each of three brands (SIN, Conexão, Neodent) were tested with their respective abutments (milled CoCr collar rotational and non-rotational) and another of an alternative manufacturer (Microplant) in randomly arranged I/A combinations. The degree of interchangeability between the various brands of components was defined using the original abutment interface gap with its respective implant as the benchmark dimension. Accordingly, when the result for a given component placed on an implant was equal to or smaller then that gap measured when the original component of the same brand as the implant was positioned, interchangeability was considered valid. Data were compared with the Kruskal-Wallis test at 5% significance level. Some degree of misfit was observed in all specimens. Generally, the non-rotational component was more accurate than its rotational counterpart. The latter samples ranged from 0.6-16.9 µm, with a 4.6 µm median; and the former from 0.3-12.9 µm, with a 3.4 µm median. Specimens with the abutment and fixture from Conexão had larger microgap than the original set for SIN and Neodent (p<0.05). Even though the latter systems had similar results with their respective components, their interchanged abutments did not reproduce the original accuracy. The results suggest that the alternative brand abutment would have compatibility with all systems while the other brands were not completely interchangeable.