Negated bio-events: Analysis and identification

Background: Negation occurs frequently in scientific literature, especially in biomedical literature. It has previously been reported that around 13% of sentences found in biomedical research articles contain negation. Historically, the main motivation for identifying negated events has been to ensure their exclusion from lists of extracted interactions. However, recently, there has been a growing interest in negative results, which has resulted in negation detection being identified as a key challenge in biomedical relation extraction. In this article, we focus on the problem of identifying negated bio-events, given gold standard event annotations.Results: We have conducted a detailed analysis of three open access bio-event corpora containing negation information (i.e., GENIA Event, BioInfer and BioNLP'09 ST), and have identified the main types of negated bio-events. We have analysed the key aspects of a machine learning solution to the problem of detecting negated events, including selection of negation cues, feature engineering and the choice of learning algorithm. Combining the best solutions for each aspect of the problem, we propose a novel framework for the identification of negated bio-events. We have evaluated our system on each of the three open access corpora mentioned above. The performance of the system significantly surpasses the best results previously reported on the BioNLP'09 ST corpus, and achieves even better results on the GENIA Event and BioInfer corpora, both of which contain more varied and complex events.Conclusions: Recently, in the field of biomedical text mining, the development and enhancement of event-based systems has received significant interest. The ability to identify negated events is a key performance element for these systems. We have conducted the first detailed study on the analysis and identification of negated bio-events. Our proposed framework can be integrated with state-of-the-art event extraction systems. The resulting systems will be able to extract bio-events with attached polarities from textual documents, which can serve as the foundation for more elaborate systems that are able to detect mutually contradicting bio-events. © 2013 Nawaz et al.; licensee BioMed Central Ltd

Genomic Testing and Therapies for Breast Cancer in Clinical Practice

Despite almost universal testing for HER2, many women with HER2-positive cancer may not receive trastuzumab. Fewer women received newer gene expression profile testing

Predictors of Outcome in a Primary Care Depression Trial

OBJECTIVE: Previous treatment trials have found that approximately one third of depressed patients have persistent symptoms. We examined whether depression severity, comorbid psychiatric illness, and personality factors might play a role in this lack of response. DESIGN: Randomized trial of a stepped collaborative care intervention versus usual care. SETTING: HMO in Seattle, Wash. PATIENTS: Patients with major depression were stratified into severe (N = 149) and mild to moderate depression (N = 79) groups prior to randomization. INTERVENTIONS: A multifaceted intervention targeting patient, physician, and process of care, using collaborative management by a psychiatrist and primary care physician. MEASUREMENTS AND MAIN RESULTS: Patients with more severe depression had a higher risk for panic disorder (odds ratio [OR], 5.8), loneliness (OR, 2.6), and childhood emotional abuse (OR, 2.1). Among those with less severe depression, intervention patients showed significantly improved depression outcomes over time compared with those in usual care (z = −3.06, P < .002); however, this difference was not present in the more severely depressed groups (z = 0.61, NS). Although the group with severe depression showed differences between the intervention and control groups from baseline to 3 months that were similar to the group with less severe depression (during the acute phase of the intervention), these differences disappeared by 6 months. CONCLUSIONS: Initial depression severity, comorbid panic disorder, and other psychosocial vulnerabilities were associated with a decreased response to the collaborative care intervention. Although the intervention was appropriate for patients with moderate depression, individuals with higher levels of depression may require a longer continuation phase of therapy in order to achieve optimal depression outcomes

Randomized Trial of Case-Finding for Depression in Elderly Primary Care Patients

OBJECTIVE: To determine the effect of case-finding for depression on frequency of depression diagnoses, prescriptions for antidepressant medications, prevalence of depression, and health care utilization during 2 years of follow-up in elderly primary care patients. DESIGN: Randomized controlled trial. SETTING: Thirteen primary care medical clinics at the Kaiser Permanente Medical Center, an HMO in Oakland, Calif, were randomly assigned to intervention conditions (7 clinics) or control conditions (6 clinics). PARTICIPANTS: A total of 2,346 patients aged 65 years or older who were attending appointments at these clinics and completed the 15-item Geriatric Depression Scale (GDS). GDS scores of 6 or more were considered suggestive of depression. INTERVENTIONS: Primary care physicians in the intervention clinics were notified of their patients' GDS scores. We suggested that participants with severe depressive symptoms (GDS score ≥ 11) be referred to the Psychiatry Department and participants with mild to moderate depressive symptoms (GDS score of 6 –10) be evaluated and treated by the primary care physician. Intervention group participants with GDS scores suggestive of depression were also offered a series of organized educational group sessions on coping with depression led by a psychiatric nurse. Primary care physicians in the control clinics were not notified of their patients' GDS scores or advised of the availability of the patient education program (usual care). Participants were followed for 2 years. MEASUREMENTS AND MAIN RESULTS: Physician diagnosis of depression, prescriptions for antidepressant medications, prevalence of depression as measured by the GDS at 2-year follow-up, and health care utilization were determined. A total of 331 participants (14%) had GDS scores suggestive of depression (GDS ≥ 6) at baseline, including 162 in the intervention group and 169 in the control group. During the 2-year follow-up period, 56 (35%) of the intervention participants and 58 (34%) of the control participants received a physician diagnosis of depression (odds ratio [OR], 1.0; 95% confidence interval [CI], 0.6 to 1.6; P = .96). Prescriptions for antidepressants were received by 59 (36%) of the intervention participants and 72 (43%) of the control participants (OR, 0.8; 95% CI, 0.5 to 1.2; P = .3). Two-year follow-up GDS scores were available for 206 participants (69% of survivors): at that time, 41 (42%) of the 97 intervention participants and 54 (50%) of the 109 control participants had GDS scores suggestive of depression (OR, 0.7; 95% CI, 0.4 to 1.3; P = .3). Comparing participants in the intervention and control groups, there were no significant differences in mean GDS change scores (−2.4 ± SD 3.7 vs −2.1 SD ± 3.6; P = .5) at the 2-year follow-up, nor were there significant differences in mean number of clinic visits (1.8 ± SD 3.1 vs 1.6 ± SD 2.8; P = .5) or mean number of hospitalizations (1.1 ± SD 1.6 vs 1.0 ± SD 1.4; P =.8) during the 2-year period. In participants with initial GDS scores >11, there was a mean change in GDS score of −5.6 ± SD 3.9 for intervention participants (n =13) and −3.4 ± SD 4.5 for control participants (n = 21). Adjusting for differences in baseline characteristics between groups did not affect results. CONCLUSIONS: We were unable to demonstrate any benefit from case-finding for depression during 2 years of follow-up in elderly primary care patients. Studies are needed to determine whether case-finding combined with more intensive patient education and follow-up will improve outcomes of primary care patients with depression

Recent Care of Common Mental Disorders in the United States

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71815/1/j.1525-1497.2000.9908044.x.pd