Investigating heterogeneous protein annotations toward cross-corpora utilization

<p>Abstract</p> <p>Background</p> <p>The number of corpora, collections of structured texts, has been increasing, as a result of the growing interest in the application of natural language processing methods to biological texts. Many named entity recognition (NER) systems have been developed based on these corpora. However, in the biomedical community, there is yet no general consensus regarding named entity annotation; thus, the resources are largely incompatible, and it is difficult to compare the performance of systems developed on resources that were divergently annotated. On the other hand, from a practical application perspective, it is desirable to utilize as many existing annotated resources as possible, because annotation is costly. Thus, it becomes a task of interest to integrate the heterogeneous annotations in these resources.</p> <p>Results</p> <p>We explore the potential sources of incompatibility among gene and protein annotations that were made for three common corpora: GENIA, GENETAG and AIMed. To show the inconsistency in the corpora annotations, we first tackle the incompatibility problem caused by corpus integration, and we quantitatively measure the effect of this incompatibility on protein mention recognition. We find that the F-score performance declines tremendously when training with integrated data, instead of training with pure data; in some cases, the performance drops nearly 12%. This degradation may be caused by the newly added heterogeneous annotations, and cannot be fixed without an understanding of the heterogeneities that exist among the corpora. Motivated by the result of this preliminary experiment, we further qualitatively analyze a number of possible sources for these differences, and investigate the factors that would explain the inconsistencies, by performing a series of well-designed experiments. Our analyses indicate that incompatibilities in the gene/protein annotations exist mainly in the following four areas: the boundary annotation conventions, the scope of the entities of interest, the distribution of annotated entities, and the ratio of overlap between annotated entities. We further suggest that almost all of the incompatibilities can be prevented by properly considering the four aspects aforementioned.</p> <p>Conclusion</p> <p>Our analysis covers the key similarities and dissimilarities that exist among the diverse gene/protein corpora. This paper serves to improve our understanding of the differences in the three studied corpora, which can then lead to a better understanding of the performance of protein recognizers that are based on the corpora.</p

Transition to the new race/ethnicity data collection standards in the Department of Veterans Affairs

BACKGROUND: Patient race in the Department of Veterans Affairs (VA) information system was previously recorded based on an administrative or clinical employee's observation. Since 2003, the VA started to collect self-reported race in compliance with a new federal guideline. We investigated the implications of this transition for using race/ethnicity data in multi-year trends in the VA and in other healthcare data systems that make the transition. METHODS: All unique users of VA healthcare services with self-reported race/ethnicity data in 2004 were compared with their prior observer-recorded race/ethnicity data from 1997 – 2002 (N = 988,277). RESULTS: In 2004, only about 39% of all VA healthcare users reported race/ethnicity values other than "unknown" or "declined." Females reported race/ethnicity at a lower rate than males (27% vs. 40%; p < 0.001). Over 95% of observer-recorded data agreed with self-reported data. Compared with the patient self-reported data, the observer-recorded White and African American races were accurate for 98% (kappa = 0.89) and 94% (kappa = 0.93) individuals, respectively. Accuracy of observer-recorded races was much worse for other minority groups with kappa coefficients ranging between 0.38 for American Indian or Alaskan Natives and 0.79 for Hispanic Whites. When observer-recorded race/ethnicity values were reclassified into non-African American groups, they agreed with the self-reported data for 98% of all individuals (kappa = 0.93). CONCLUSION: For overall VA healthcare users, the agreement between observer-recorded and self-reported race/ethnicity was excellent and observer-recorded and self-reported data can be used together for multi-year trends without creating serious bias. However, this study also showed that observation was not a reliable method of race/ethnicity data collection for non-African American minorities and racial disparity might be underestimated if observer-recorded data are used due to systematic patterns of inaccurate race/ethnicity assignments

Physician preferences and attitudes regarding different models of cancer survivorship care: a comparison of primary care providers and oncologists.

PurposeNew strategies for delivering cancer follow-up care are needed. We surveyed primary care providers (PCPs) and oncologists to assess how physician attitudes toward and self-efficacy with cancer follow-up affect preferences for different cancer survivorship models.MethodsThe survey of physician attitudes regarding the care of cancer survivors was mailed to a randomly selected national sample of PCPs and oncologists to evaluate their perspectives regarding physician roles, knowledge about survivorship care processes, and views on cancer surveillance. Multinomial logistic regression models were constructed to examine how physician attitudes towards, and self-efficacy with, their own skills affected preferences for different cancer survivorship care models.ResultsOf 3,434 physicians identified, a total of 2,026 participants provided eligible responses: 938 PCPs and 1,088 oncologists. Most PCPs (51&nbsp;%) supported a PCP/shared care model; whereas, the majority of specialists (59&nbsp;%) strongly endorsed an oncologist-based model (p &lt; 0.001). Less than a quarter of PCPs and oncologists preferred specialized survivor clinics. A significant proportion of oncologists (87&nbsp;%) did not feel that PCPs should take on the primary role of cancer follow-up. Most PCPs believed that they were better able to perform breast and colorectal cancer follow-up (57&nbsp;%), detect recurrent cancers (74&nbsp;%), and offer psychosocial support (50&nbsp;%), but only a minority (32&nbsp;%) was willing to assume primary responsibility. PCPs already involved with cancer surveillance (43&nbsp;%) were more likely to prefer a PCP/shared care than oncologist-based survivorship model (OR, 2.08; 95&nbsp;% CI, 1.34-3.23).Conclusions and implications for cancer survivorsPCPs and oncologists have different preferences for models of cancer survivorship care. Prior involvement with cancer surveillance was one of the strongest predictors of PCPs' willingness to assume this responsibility

Accuracy and completeness of mortality data in the Department of Veterans Affairs

<p>Abstract</p> <p>Background</p> <p>One of the national mortality databases in the U.S. is the Beneficiary Identification and Record Locator Subsystem (BIRLS) Death File that contains death dates of those who have received any benefits from the Department of Veterans Affairs (VA). The completeness of this database was shown to vary widely from cohort to cohort in previous studies. Three other sources of death dates are available in the VA that can complement the BIRLS Death File. The objective of this study is to evaluate the completeness and accuracy of death dates in the four sources available in the VA and to examine whether these four sources can be combined into a database with improved completeness and accuracy.</p> <p>Methods</p> <p>A random sample of 3,000 was drawn from 8.3 million veterans who received benefits from the VA between 1997 and 1999 and were alive on January 1, 1999 according to at least one source. Death dates found in BIRLS Death File, Medical SAS Inpatient Datasets, Medicare Vital Status, and Social Security Administration (SSA) Death Master File were compared with dates obtained from the National Death Index. A combined dataset from these sources was also compared with National Death Index dates.</p> <p>Results</p> <p>Compared with the National Death Index, sensitivity (or the percentage of death dates correctly recorded in a source) was 77.4% for BIRLS Death File, 12.0% for Medical SAS Inpatient Datasets, 83.2% for Medicare Vital Status, and 92.1% for SSA Death Master File. Over 95% of death dates in these sources agreed exactly with dates from the National Death Index. Death dates in the combined dataset demonstrated 98.3% sensitivity and 97.6% exact agreement with dates from the National Death Index.</p> <p>Conclusion</p> <p>The BIRLS Death File is not an adequate source of mortality data for the VA population due to incompleteness. When the four sources of mortality data are carefully combined, the resulting dataset can provide more timely data for death ascertainment than the National Death Index and has comparable accuracy and completeness.</p

Bacterial toxins in musculoskeletal infections

Musculoskeletal infections (MSKIs) remain a major health burden in orthopaedics. Bacterial toxins are foundational to pathogenesis in MSKI, but poorly understood by the community of providers that care for patients with MSKI, inducing an international group of microbiologists, infectious diseases specialists, orthopaedic surgeons and biofilm scientists to review the literature in this field to identify key topics and compile the current knowledge on the role of toxins in MSKI, with the goal of illuminating potential impact on biofilm formation and dispersal as well as therapeutic strategies. The group concluded that further research is needed to maximize our understanding of the effect of toxins on MSKIs, including: (i)further research to identify the roles of bacterial toxins in MSKIs, (ii)establish the understanding of the importance of environmental and host factors and in vivo expression of toxins throughout the course of an infection, (iii)establish the principles of drug-ability of antitoxins as antimicrobial agents in MSKIs, (iv)have well-defined metrics of success for antitoxins as antiinfective drugs, (v)design a cocktail of antitoxins against specific pathogens to (a) inhibit biofilm formation and (b) inhibit toxin release. The applicability of antitoxins as potential antimicrobials in the era of rising antibiotic resistance could meet the needs of day-to-day clinicians.</p

Is fertility declining in Benin?

This study analyzes reproductive changes in Benin, a West African country with high fertility and low prevalence of use of modern contraceptive methods, using a combination of quantitative and qualitative approaches. Findings indicate that an irreversible fertility transition has started as the result of an emerging pattern of birth limitation and continued desire for the traditional long birth intervals. The data suggest that changes in childhood mortality in combination with an increase in women's education, although modest, have created a demand for fertility control among women; that induced abortion may be one of the means through which such demand is being met, particularly in urban areas; and that the economic crisis of the 1980s was the main catalyst that precipitated the onset of transition. Changes in reproductive preferences and practice suggest a diffusion process, from urban and more educated women to rural and less-educated ones