Are decision trees a feasible knowledge representation to guide extraction of critical information from randomized controlled trial reports?

<p>Abstract</p> <p>Background</p> <p>This paper proposes the use of decision trees as the basis for automatically extracting information from published randomized controlled trial (RCT) reports. An exploratory analysis of RCT abstracts is undertaken to investigate the feasibility of using decision trees as a semantic structure. Quality-of-paper measures are also examined.</p> <p>Methods</p> <p>A subset of 455 abstracts (randomly selected from a set of 7620 retrieved from Medline from 1998 – 2006) are examined for the quality of RCT reporting, the identifiability of RCTs from abstracts, and the completeness and complexity of RCT abstracts with respect to key decision tree elements. Abstracts were manually assigned to 6 sub-groups distinguishing whether they were primary RCTs versus other design types. For primary RCT studies, we analyzed and annotated the reporting of intervention comparison, population assignment and outcome values. To measure completeness, the frequencies by which complete intervention, population and outcome information are reported in abstracts were measured. A qualitative examination of the reporting language was conducted.</p> <p>Results</p> <p>Decision tree elements are manually identifiable in the majority of primary RCT abstracts. 73.8% of a random subset was primary studies with a single population assigned to two or more interventions. 68% of these primary RCT abstracts were structured. 63% contained pharmaceutical interventions. 84% reported the total number of study subjects. In a subset of 21 abstracts examined, 71% reported numerical outcome values.</p> <p>Conclusion</p> <p>The manual identifiability of decision tree elements in the abstract suggests that decision trees could be a suitable construct to guide machine summarisation of RCTs. The presence of decision tree elements could also act as an indicator for RCT report quality in terms of completeness and uniformity.</p

Publication bias in gastroenterological research – a retrospective cohort study based on abstracts submitted to a scientific meeting

BACKGROUND: The aim of this study was to examine the determinants of publication and whether publication bias occurred in gastroenterological research. METHODS: A random sample of abstracts submitted to DDW, the major GI meeting (1992–1995) was evaluated. The publication status was determined by database searches, complemented by a mailed survey to abstract authors. Determinants of publication were examined by Cox proportional hazards model and multiple logistic regression. RESULTS: The sample included abstracts on 326 controlled clinical trials (CCT), 336 other clinical research reports (OCR), and 174 basic science studies (BSS). 392 abstracts (47%) were published as full papers. Acceptance for presentation at the meeting was a strong predictor of subsequent publication for all research types (overall, 54% vs. 34%, OR 2.3, 95% CI 1.7 to 3.1). In the multivariate analysis, multi-center status was found to predict publication (OR 2.8, 95% CI 1.6–4.9). There was no significant association between direction of study results and subsequent publication. Studies were less likely to be published in high impact journals if the results were not statistically significant (OR 0.5, 95 CI 95% 0.3–0.6). The author survey identified lack of time or interest as the main reason for failure to publish. CONCLUSIONS: Abstracts which were selected for presentation at the DDW are more likely to be followed by full publications. The statistical significance of the study results was not found to be a predictor of publication but influences the chances for high impact publication