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Excluded, not dismissed: enhancing benefit in clinical research.

ABSTRACT: Participation in clinical research projects may allow an opportunity for early detection of covert diseases and subclinical disorders in asymptomatic volunteers from study-specific screening process. Exclusion of a potential participant due to failure to meet inclusion criteria eliminates any possibility of potential for research related benefit, as may exist for those that are deemed eligible and allowed to proceed with participation in the specific research study. Although the institutional bodies overseeing conduct of clinical research strive to ensure an ongoing scrutiny and prioritization of participants' wellbeing, we perceive that these mechanisms fall short as regards the interests of those volunteers who are subsequently excluded from participation in clinical research of relevance. While provision of ancillary care to address health concerns that are unmasked during the screening process may be an optimal strategy, the likelihood of successfully implementing this latter concept in current times of fiscal constraints is slim to nonexistent. Through this submission, we hope to initiate a dialogue within the research community regarding whether the current paradigm of conduct of clinical research be modified to include some degree of consideration for the screened out. We herein propose that for those volunteering for disease/disorder specific clinical research, some added degree of benefit can be assured to the screened out population through the provision of targeted health education or counseling.

SUBMITTER: Nardell M

PROVIDER: S-EPMC3525712 | biostudies-other | 2013 Jan

REPOSITORIES: biostudies-other

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Excluded, not dismissed: enhancing benefit in clinical research.

Nardell Maria M Chhabra Akansha A Pal Lubna L

Contemporary clinical trials 20120907 1

Participation in clinical research projects may allow an opportunity for early detection of covert diseases and subclinical disorders in asymptomatic volunteers from study-specific screening process. Exclusion of a potential participant due to failure to meet inclusion criteria eliminates any possibility of potential for research related benefit, as may exist for those that are deemed eligible and allowed to proceed with participation in the specific research study. Although the institutional bo ...[more]

PMID: 22981957

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Project description:The harm benefit analysis (HBA) is the cornerstone of animal research regulation and is considered to be a key ethical safeguard for animals. The HBA involves weighing the anticipated benefits of animal research against its predicted harms to animals but there are doubts about how objective and accountable this process is.i. To explore the harms to animals involved in pre-clinical animal studies and to assess these against the benefits for humans accruing from these studies; ii. To test the feasibility of conducting this type of retrospective HBA.Data on harms were systematically extracted from a sample of pre-clinical animal studies whose clinical relevance had already been investigated by comparing systematic reviews of the animal studies with systematic reviews of human studies for the same interventions (antifibrinolytics for haemorrhage, bisphosphonates for osteoporosis, corticosteroids for brain injury, Tirilazad for stroke, antenatal corticosteroids for neonatal respiratory distress and thrombolytics for stroke). Clinical relevance was also explored in terms of current clinical practice. Harms were categorised for severity using an expert panel. The quality of the research and its impact were considered. Bateson's Cube was used to conduct the HBA.The most common assessment of animal harms by the expert panel was 'severe'. Reported use of analgesia was rare and some animals (including most neonates) endured significant procedures with no, or only light, anaesthesia reported. Some animals suffered iatrogenic harms. Many were kept alive for long periods post-experimentally but only 1% of studies reported post-operative care. A third of studies reported that some animals died prior to endpoints. All the studies were of poor quality. Having weighed the actual harms to animals against the actual clinical benefits accruing from these studies, and taking into account the quality of the research and its impact, less than 7% of the studies were permissible according to Bateson's Cube: only the moderate bisphosphonate studies appeared to minimise harms to animals whilst being associated with benefit for humans.This is the first time the accountability of the HBA has been systematically explored across a range of pre-clinical animal studies. The regulatory systems in place when these studies were conducted failed to safeguard animals from severe suffering or to ensure that only beneficial, scientifically rigorous research was conducted. Our findings indicate a pressing need to: i. review regulations, particularly those that permit animals to suffer severe harms; ii. reform the processes of prospectively assessing pre-clinical animal studies to make them fit for purpose; and iii. systematically evaluate the benefits of pre-clinical animal research to permit a more realistic assessment of its likely future benefits.

Project description:BACKGROUND:Community-acquired pneumonia is a leading cause of pediatric morbidity. Administrative data are often used to conduct comparative effectiveness research (CER) with sufficient sample sizes to enhance detection of important outcomes. However, such studies are prone to misclassification errors because of the variable accuracy of discharge diagnosis codes. OBJECTIVE:The aim of this study was to develop an automated, scalable, and accurate method to determine the presence or absence of pneumonia in children using chest imaging reports. METHODS:The multi-institutional PHIS+ clinical repository was developed to support pediatric CER by expanding an administrative database of children's hospitals with detailed clinical data. To develop a scalable approach to find patients with bacterial pneumonia more accurately, we developed a Natural Language Processing (NLP) application to extract relevant information from chest diagnostic imaging reports. Domain experts established a reference standard by manually annotating 282 reports to train and then test the NLP application. Findings of pleural effusion, pulmonary infiltrate, and pneumonia were automatically extracted from the reports and then used to automatically classify whether a report was consistent with bacterial pneumonia. RESULTS:Compared with the annotated diagnostic imaging reports reference standard, the most accurate implementation of machine learning algorithms in our NLP application allowed extracting relevant findings with a sensitivity of .939 and a positive predictive value of .925. It allowed classifying reports with a sensitivity of .71, a positive predictive value of .86, and a specificity of .962. When compared with each of the domain experts manually annotating these reports, the NLP application allowed for significantly higher sensitivity (.71 vs .527) and similar positive predictive value and specificity . CONCLUSIONS:NLP-based pneumonia information extraction of pediatric diagnostic imaging reports performed better than domain experts in this pilot study. NLP is an efficient method to extract information from a large collection of imaging reports to facilitate CER.

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Excluded, not dismissed: enhancing benefit in clinical research.

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Excluded, not dismissed: enhancing benefit in clinical research.

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