Inconsistent Classification Research Articles

Drug reformulations and repositioning in pharmaceutical industry and its impact on market access: reassessment of nomenclature

Background: Medicinal products that have been developed and approved for one disease may be the object of additional clinical development in other disease areas or of additional pharmaceutical development for new and different formulations. The newly developed products can be named as repositioned or reformulated products, respectively. Market access of repositioned or reformulated products in Europe and the United States is an interesting object of study as it may provide clarity about which parameters are assessed and considered to bring added value, other than the molecule itself. As such, we aim to evaluate if the added value of repositioned or reformulated medicinal products can be systematically described, quantified, and predicted. As a first step toward investigating the impact of market access on drug research and development trends for repositioned and reformulated products, it is necessary to have consistency in the designations for the case studies evaluated in this project. In an attempt to achieve that consistency, the current study aims to propose harmonized definitions for the repositioning and reformulation strategies and to propose a taxonomy for the medicinal products derived thereof.Methods: A systematic literature review was conducted to collect information on existing cases of repositioning or reformulation. A search strategy was developed by defining the search objectives, targeted data sources, search keywords, and inclusion/exclusion criteria for the retrieved documents.Results: A total of 505 publications were retrieved through a search of the main data sources. The screenings and the ad hoc search led to a total of 56 publications to be used for the case study data extraction. In total, 87 repositioning and/or reformulation cases were found described in the literature, 23 of which presented different definitions and/or classifications by different authors.Conclusion: Given the disparity and inconsistency of terminologies and classifications in the literature, a harmonized nomenclature for drug repositioning, reformulation, and combination cases will allow for a robust analysis of the added value and market access conditions attributed for each strategy and case type as assessed by regulators and payors in Europe and the United States. After evaluation of the existing terminologies and given the absence of clear and consistent definitions for drug reformulation and repositioning in the literature, we propose a global terminology and taxonomy in order to cover all of the previously unclear definitions and classifications for repositioned and reformulated products.

A Novel Method for Elimination of Inconsistencies in Ordinal Classification with Monotonicity Constraints

In order to handle inconsistencies in ordinal and monotonic information systems, several relaxed versions of the Dominance-based Rough Set Approach DRSA have been proposed, e.g., VC-DRSA. These versions use special consistency measures to admit some inconsistent objects in the lower approximations. The minimal consistency level that has to be attained by objects included in the lower approximations is defined using a prior knowledge or a trial-and-error procedure. In order to avoid dependence on prior knowledge, an alternative way of handling inconsistencies is to iteratively eliminate the most inconsistent objects according to some measure until the information system becomes consistent. This idea is a base of a new method of handling inconsistencies presented in this paper and called TIPStoC. The TIPStoC algorithm is illustrated by an example from the area of telecommunication and the efficiency of the new method is proved by a computational experiment.

Missed and inconsistent classification of current drinkers: results from the 2005 US National Alcohol Survey

This study compares current 12-month drinkers who do not report drinking in the last 30 days with current drinkers who drank in the last 30 days and assesses possible misclassification errors from use of a 30-day consumption measure. Data are from the 2005 US National Alcohol Survey (n = 6919), a national household probability survey. Telephone interviews were used to measure alcohol use and alcohol-related problems. This study compared 1300 current drinkers who did not drink in the last 30 days with 2956 current drinkers who drank in the last 30 days. Volume was measured by quantity/frequency scales (12-month and 30-day) and a graduated frequency scale (12-month). Both groups were compared by demographic, alcohol volume, days of five or more drinks, social consequences and dependence measures. Results indicate a significantly lower prevalence rate of current drinking for 30-day measures-47.3% (45.8%, 48.8%) versus 67.3% (66.0%, 68.7%) with 12-month measures. Further, 385 non-30-day drinkers reported 12-month drinking frequencies of once a month or more often, suggesting possible inconsistent reporting of their alcohol use. When this group of 'inconsistent' respondents is compared with the 915 non-30-day current drinkers who reported less than monthly drinking, they reported significantly higher yearly volume, days of five or more drinks, mean social consequences and proportion reporting alcohol dependence. In population surveys assessing alcohol use, asking about the previous 12 months rather than the past 30 days provides higher estimates of current use, including more days of heavy episodic use.

Identification of Mild Cognitive Impairment in ACTIVE: Algorithmic Classification and Stability

Rates of mild cognitive impairment (MCI) have varied substantially, depending on the criteria used and the samples surveyed. The present investigation used a psychometric algorithm for identifying MCI and its stability to determine if low cognitive functioning was related to poorer longitudinal outcomes. The Advanced Cognitive Training of Independent and Vital Elders (ACTIVE) study is a multi-site longitudinal investigation of long-term effects of cognitive training with older adults. ACTIVE exclusion criteria eliminated participants at highest risk for dementia (i.e., Mini-Mental State Examination < 23). Using composite normative for sample- and training-corrected psychometric data, 8.07% of the sample had amnestic impairment, while 25.09% had a non-amnestic impairment at baseline. Poorer baseline functional scores were observed in those with impairment at the first visit, including a higher rate of attrition, depressive symptoms, and self-reported physical functioning. Participants were then classified based upon the stability of their classification. Those who were stably impaired over the 5-year interval had the worst functional outcomes (e.g., Instrumental Activities of Daily Living performance), and inconsistency in classification over time also appeared to be associated increased risk. These findings suggest that there is prognostic value in assessing and tracking cognition to assist in identifying the critical baseline features associated with poorer outcomes.

Administrative Coding of Type 1 and Type 2 Diabetes: Assessment of Validity

Background: Accurate diagnostic coding of diabetes diagnosis is critical in health services research using administrative data. Type 1 (T1DM) and type 2 diabetes (T2DM) are not always easily clinically distinguished though do have distinct ICD-10 diagnostic codes. It is not known whether diagnostic coding in practice accurately identifies the type of diabetes. Purpose: to assess the quality of administrative coding of diabetes among patients discharged from hospital. Methods: All patients admitted to hospital with myocardial infarction anddiabetes in 2006were identified using theAPPROACH database. A chart review of identified patients was conducted. Clinical data reflecting the presence of T1DM vs. T2DM was extracted (age at diagnosis of diabetes, BMI, mode of treatment at admission) along with data provoking uncertainty (e.g. use of different diabetes classification on the same chart). If all discriminatoryclinical datawaspresent, the codeddiagnosiswas considered “certain”; if incomplete the coded diagnosis was considered “uncertain”. Results: 141 charts met selection criteria, 38 (27%) were considered to have an “uncertain” diagnosis. Of the uncertain cases, 47.4% had insufficient documentation of clinical data to ascribe with any certainty whether these individuals had T1DM or T2DM. Inconsistent nomenclature (31.6%) and inconsistent diabetes classification (19.4%) were also more common among the “uncertain” cases. Conclusions: This study identifies significant concerns with the quality of diabetes coding, largely stemming from physician documentation. Standardized diabetes data forms on hospital charts might mitigate the uncertainty around phenotypic definition, for more accurate diagnostic discrimination and outcome evaluation.

Biometric analysis of fetal cerebellum

BackgroundCerebellar malformations are one of the main referral reasons for fetal magnetic resonance imaging, with recent studies suggesting associated impairments in higher cognitive functions. The lack of biometric data, motion...

Where is the consensus? A proposed foundation for moving ecosystem service concepts into practice

Inconsistent terms, definitions, and classifications hinder advancement of the study and application of ecosystem services. A unified approach among disciplines involved in researching and implementing ecosystem services is imperative to moving concepts into practice. An operational definition needs to be adopted by the ecosystem service community as the basis of a classification system so that ecosystem goods and services may be measured by ecologists, valued by economists, and utilized by decision-makers. We propose a transdisciplinary approach centered upon shared principles, an ecosystem services definition, and a classification system. This shared foundation provides a common set of ecosystem goods and services that serves as the focus for and connection among multiple disciplines. This foundation is specific enough to be operational while remaining relevant to a multitude of ecosystem service objectives for which frameworks and implementation plans may be developed. Although numerous ecosystem service frameworks exist in the literature, many of them are non-operational or are focused toward a single discipline. An evaluation of these frameworks identifies knowledge gaps and suggests how we may advance ecosystem services into practice. Our evaluation demonstrates that foundational concepts (especially a definition and classification system, and community involvement) are often poorly addressed in ecosystem service frameworks.

Evaluation of land-use planning in greenbelts based on intrinsic characteristics and stakeholder values

Legislation of greenbelts adjacent to cities is a common method to contain sprawl and protect land for multiple purposes e.g., agriculture, environment and recreation. However, greenbelt planning lacks an effective approach which can combine multiple intrinsic land characteristics with diverse stakeholder values to quantitatively identify a desired long term mix of land uses and the criteria upon which changes in land use can be judged. The research aimed to create a quantitative, community-engaged basis for the evolution of multiple land-uses. It evaluates a process to simultaneously develop multiple land-use designations e.g., for agriculture and environmental preservation, based on combining spatial multi-criteria modelling using MCAS-S software and stakeholder judgment. Trialling the process on a 129,000ha portion of the Toronto Greenbelt demonstrated that it effectively identifies land that has embedded attributes or value and provides a real-time tool for assessing land-use scenarios. Maps of these attributes and focus-group scenarios did not coincide with the existing boundary of the Toronto Greenbelt. The MCAS-S composites that simultaneously address the multiple purposes of greenbelts (agriculture, environment, etc.) were likely to be helpful for policy-makers and researchers to identify land that was highly valued for several purposes and therefore likely to be contested, but they were less helpful than simple composites addressing one purpose as a basis of explanation and guiding community discussion. The method is unlikely to be scalable across large heterogeneous areas, other than to assist professionals and identify inconsistencies in land-use classification, because local knowledge is desirable for consensus on land-use scenarios.

Molecular Pattern Discovery Based on Penalized Matrix Decomposition

A reliable and precise identification of the type of tumors is crucial to the effective treatment of cancer. With the rapid development of microarray technologies, tumor clustering based on gene expression data is becoming a powerful approach to cancer class discovery. In this paper, we apply the penalized matrix decomposition (PMD) to gene expression data to extract metasamples for clustering. The extracted metasamples capture the inherent structures of samples belong to the same class. At the same time, the PMD factors of a sample over the metasamples can be used as its class indicator in return. Compared with the conventional methods such as hierarchical clustering (HC), self-organizing maps (SOM), affinity propagation (AP) and nonnegative matrix factorization (NMF), the proposed method can identify the samples with complex classes. Moreover, the factor of PMD can be used as an index to determine the cluster number. The proposed method provides a reasonable explanation of the inconsistent classifications made by the conventional methods. In addition, it is able to discover the modules in gene expression data of conterminous developmental stages. Experiments on two representative problems show that the proposed PMD-based method is very promising to discover biological phenotypes.

San Francisco Syncope Rule to predict short-term serious outcomes: a systematic review.

The San Francisco Syncope Rule has been proposed as a clinical decision rule for risk stratification of patients presenting to the emergency department with syncope. It has been validated across various populations and settings. We undertook a systematic review of its accuracy in predicting short-term serious outcomes. We identified studies by means of systematic searches in seven electronic databases from inception to January 2011. We extracted study data in duplicate and used a bivariate random-effects model to assess the predictive accuracy and test characteristics. We included 12 studies with a total of 5316 patients, of whom 596 (11%) experienced a serious outcome. The prevalence of serious outcomes across the studies varied between 5% and 26%. The pooled estimate of sensitivity of the San Francisco Syncope Rule was 0.87 (95% confidence interval [CI] 0.79-0.93), and the pooled estimate of specificity was 0.52 (95% CI 0.43-0.62). There was substantial between-study heterogeneity (resulting in a 95% prediction interval for sensitivity of 0.55-0.98). The probability of a serious outcome given a negative score with the San Francisco Syncope Rule was 5% or lower, and the probability was 2% or lower when the rule was applied only to patients for whom no cause of syncope was identified after initial evaluation in the emergency department. The most common cause of false-negative classification for a serious outcome was cardiac arrhythmia. The San Francisco Syncope Rule should be applied only for patients in whom no cause of syncope is evident after initial evaluation in the emergency department. Consideration of all available electrocardiograms, as well as arrhythmia monitoring, should be included in application of the San Francisco Syncope Rule. Between-study heterogeneity was likely due to inconsistent classification of arrhythmia.

P1-511 Inconsistencies in racial classification and food insecurity among Brazil's low-income population

IntroductionRace has been widely used in studies on health and healthcare inequalities. Validity and reliability problems with race measurement are of concern in public health. This study investigated the agreement...

Why Is There a Lack of Consensus on Molecular Subgroups of Glioblastoma? Understanding the Nature of Biological and Statistical Variability in Glioblastoma Expression Data

IntroductionGene expression patterns characterizing clinically-relevant molecular subgroups of glioblastoma are difficult to reproduce. We suspect a combination of biological and analytic factors confounds interpretation of glioblastoma expression data. We seek to clarify the nature and relative contributions of these factors, to focus additional investigations, and to improve the accuracy and consistency of translational glioblastoma analyses.MethodsWe analyzed gene expression and clinical data for 340 glioblastomas in The Cancer Genome Atlas (TCGA). We developed a logic model to analyze potential sources of biological, technical, and analytic variability and used standard linear classifiers and linear dimensional reduction algorithms to investigate the nature and relative contributions of each factor.ResultsCommonly-described sources of classification error, including individual sample characteristics, batch effects, and analytic and technical noise make measurable but proportionally minor contributions to inconsistent molecular classification. Our analysis suggests that three, previously underappreciated factors may account for a larger fraction of classification errors: inherent non-linear/non-orthogonal relationships among the genes used in conjunction with classification algorithms that assume linearity; skewed data distributions assumed to be Gaussian; and biologic variability (noise) among tumors, of which we propose three types.ConclusionsOur analysis of the TCGA data demonstrates a contributory role for technical factors in molecular classification inconsistencies in glioblastoma but also suggests that biological variability, abnormal data distribution, and non-linear relationships among genes may be responsible for a proportionally larger component of classification error. These findings may have important implications for both glioblastoma research and for translational application of other large-volume biological databases.

How Do We Value Our Reefs? Risks and Tradeoffs Across Scales in “Biomass-Based” Economies

This review examines how local and regional coral reef management can be better informed by economic valuations. Results from the Western Indian Ocean show that supporting services are underrepresented, while cultural and provisioning services, where clear markets exist, are overrepresented in both the number of studies conducted and values assigned. These services are generally assessed using different methods meaning comparisons cannot be made across services. The largest number of services flows to beneficiaries at a local scale, consequently the cumulative value of ecosystem services is largest at this scale. However, the average value of a single service appears greatest, when flowing to beneficiaries at a global scale, creating biases in ecosystem service assessments. Furthermore, inconsistencies in classification and definition, particularly concerning regulating and option services exist. Findings suggest that if regional managers are to base their decisions on current valuation studies, their choices are likely to result in unexpected and undesirable tradeoffs. There is a need for (1) new and standardized methods that adequately account for supporting services; (2) studies to consider multiple ecosystem services simultaneously and across scales; and (3) a greater interdisciplinary understanding of how and why ecosystem services contribute to human well-being, under differing social contexts.

Surgery for chronic ischemic mitral regurgitation – which mitral intervention?

Surgical management of ischemic mitral regurgitation is associated with higher operative mortality, increased morbidity and poorer long-term survival. Selection of the most appropriate surgical treatment to maximize survival could be challenging due to factors such as inconsistent usage of contemporary surgical techniques, inconsistent classification schemes for the entity, paucity of long-term data in order to compare alternatives and an absence of randomized trials of valve repair versus valve replacement. In addition, there is a lack of patient-reported outcome measures and functional data parameters that take into consideration the patient’s perspective in refining the decision making of the therapeutic strategy. In fact, such trials are difficult and if they were to be conducted there would be a high risk of dubious conclusions owing to clustering of outcomes with surgical expertise. This article aims to review the options for surgical management of chronic ischemic mitral regurgitation. It also attempts to identify areas of future research in order to clarify which of these are of priority and will realistically seek for relevant answers. Mitral intervention in this patient group seems to improve survival, although it is dependent on producing a competent mitral apparatus. There is no convincing evidence that repair is superior to replacement, and there is the possibility that the literature has been biased against replacement as the treatment of choice.

CORE: A Phylogenetically-Curated 16S rDNA Database of the Core Oral Microbiome

Comparing bacterial 16S rDNA sequences to GenBank and other large public databases via BLAST often provides results of little use for identification and taxonomic assignment of the organisms of interest. The human microbiome, and in particular the oral microbiome, includes many taxa, and accurate identification of sequence data is essential for studies of these communities. For this purpose, a phylogenetically curated 16S rDNA database of the core oral microbiome, CORE, was developed. The goal was to include a comprehensive and minimally redundant representation of the bacteria that regularly reside in the human oral cavity with computationally robust classification at the level of species and genus. Clades of cultivated and uncultivated taxa were formed based on sequence analyses using multiple criteria, including maximum-likelihood-based topology and bootstrap support, genetic distance, and previous naming. A number of classification inconsistencies for previously named species, especially at the level of genus, were resolved. The performance of the CORE database for identifying clinical sequences was compared to that of three publicly available databases, GenBank nr/nt, RDP and HOMD, using a set of sequencing reads that had not been used in creation of the database. CORE offered improved performance compared to other public databases for identification of human oral bacterial 16S sequences by a number of criteria. In addition, the CORE database and phylogenetic tree provide a framework for measures of community divergence, and the focused size of the database offers advantages of efficiency for BLAST searching of large datasets. The CORE database is available as a searchable interface and for download at http://microbiome.osu.edu.

The legal classification of race in Australia

The varied legal classifications, descriptions or definitions of Aborigines and 'half-castes' in Australia put forth since the time of European settlement to the present for each jurisdiction are presented. It is suggested that the inconsistent and arbitrary classifications were aimed at suppressing the Aborigines' rights on the basis of perceived white superiority.

Complexity and the problem of ill-posed questions in ecology

This journal concerns itself with ecological complexity and theoretical ecology. In order to study complex systems it is often necessary to make categorizations, simplifying assumptions and analogies, and to use particular model structures and statistical tools. Such operations on the raw sensory data of nature may or may not be valid, and can make it difficult to evaluate the validity of a study. In this viewpoint article, I illustrate how ill-posed questions can confound the study of complex ecological systems. I offer several suggestions for overcoming this particular difficulty. Ill-posed questions are questions for which there are either no answers or only ambiguous (non-unique) answers. It is suggested that ill-posed questions are a particular problem in Ecology. Several types of ill-posed questions are discussed. Unobservable and uncountable phenomena (e.g., What happened before the Big Bang? How many stars are there?) are pervasive in Ecology because of the spatially and temporally diffuse interactions that characterize ecological systems. Vague terminology creates ill-posed discourse because different people use “fragmentation” or “niche” in different ways. Untestable theories are a common problem. Theories may be untestable because the objects of the theory are idealized and cannot be related to the real world, because terminology is vague, or for other reasons. Divergent metrics create ill-posed measurement problems. For example, many real world objects approximate fractal objects, at least at some scales, but they may be measured with an arbitrary length scale which differs between different studies. This means that metrics and conclusions from different studies are not comparable. Inconsistent classification systems are an issue. For example, map classifications lose rare habitat types when larger scale maps are created and thus habitat diversity metrics change with different levels of map resolution. Finally, statistical ill-posedness is a problem. This arises when the statistical test does not test or prove what it is thought to. A review of a selection of literature is used to illustrate the issues raised. Suggestions are offered for recognizing and dealing with ill-posed questions in Ecology.

Prognostic Factors for Cutaneous and Subcutaneous Soft Tissue Sarcomas in Dogs

Soft tissue sarcomas (STSs) develop from mesenchymal cells of soft tissues, and they commonly occur in the skin and subcutis of the dog. Although phenotypically diverse with frequently controversial histogenesis, STSs are considered as a group because they have similar features microscopically and clinically. Following resection, local recurrence rates are low in general but vary according to histologic grade and completeness of surgical margins. Complete margins predict nonrecurrence. Even most grade I STSs with "close" margins will not recur, but propensity for recurrence increases with grade. The frequency of metastasis has not been accurately estimated, but it is believed to be rare for grade I STSs and most likely to occur with grade III STSs. However, metastasis does not necessarily equate with poor survival. High mitotic index is prognostic for reduced survival time. Further research is needed to determine more precise estimates for recurrence rates and survival as related to completeness of surgical margins and to delineate potential differences in metastatic rate and median survival time between grades. Other potential indicators of prognosis that presently require further investigation include histologic type, tumor dimension, location, invasiveness, stage, markers of cellular proliferation, and cytogenetic profiles. Common issues limiting prognostic factor evaluation include biases from retrospective studies, small sample sizes, poor verification of metastasis, inconsistent STS classification and use of nomenclature, difficulties in differentiating STS phenotype, and diversity of the study population (stage of disease and treatment status).

A Primer-Test Centered Equating Method for Setting Cut-off Scores

This study evaluated the use of a new primary field test method based on test equating to address inconsistent classification among field tests. We analyzed students' information on the Progressive Aerobic Cardiovascular Endurance Run (PACER), mile run (MR), and VO2max from three data sets (college: n = 94; middle school: n = 39; elementary school: n = 96). Using the college and elementary school data, the equivalent relationship between PACER and MR scores was first established by the Kernel equating method. This yielded MR scores derived from PACER (mile run PACER equated [MR PEQ]), which were used to predict maximal oxygen uptake (VO2max) and classify students according to the FITNESSGRAM® Healthy Fitness Zones™. We compared the results to the predictions and classifications based on measured VO2max, MR, and PACER-predicted VO2max and cross-validated the relationships using the middle school data. We found the test conversion to be accurate and that the MR PEQ scores functioned similarly to the original MR scores. Both performed better than the original PACER scores in predicting VO2max and classifying students. The middle school data generally supported these results. The proposed method is accurate and effective in setting a new field test onto the same scale of a primary field test and determining its cut-off scores.

A Primer-Test Centered Equating Method for Setting Cut-off Scores

This study evaluated the use of a new primary field test method based on test equating to address inconsistent classification among field tests. We analyzed students' information on the Progressive Aerobic Cardiovascular Endurance Run (PACER), mile run (MR), and VO2max from three data sets (college: n = 94; middle school: n = 39; elementary school: n = 96). Using the college and elementary school data, the equivalent relationship between PACER and MR scores was first established by the Kernel equating method. This yielded MR scores derived from PACER (mile run PACER equated [MR PEQ]), which were used to predict maximal oxygen uptake (VO2max) and classify students according to the FITNESSGRAM® Healthy Fitness Zones™. We compared the results to the predictions and classifications based on measured VO2max, MR, and PACER-predicted VO2max and cross-validated the relationships using the middle school data. We found the test conversion to be accurate and that the MR PEQ scores functioned similarly to the original MR scores. Both performed better than the original PACER scores in predicting VO2max and classifying students. The middle school data generally supported these results. The proposed method is accurate and effective in setting a new field test onto the same scale of a primary field test and determining its cut-off scores.