Search Filters for Finding Prognostic and Diagnostic Prediction Studies in Medline to Enhance Systematic Reviews

Background: The interest in prognostic reviews is increasing, but to properly review existing evidence an accurate search filer for finding prediction research is needed. The aim of this paper was to validate and update two previously introduced search filters for finding prediction research in Medline: the Ingui filter and the Haynes Broad filter. Methodology/Principal Findings: Based on a hand search of 6 general journals in 2008 we constructed two sets of papers. Set 1 consisted of prediction research papers (n = 71), and set 2 consisted of the remaining papers (n = 1133). Both search filters were validated in two ways, using diagnostic accuracy measures as performance measures. First, we compared studies in set 1 (reference) with studies retrieved by the search strategies as applied in Medline. Second, we compared studies from 4 published systematic reviews (reference) with studies retrieved by the search filter as applied in Medline. Next -using word frequency methods - we constructed an additional search string for finding prediction research. Both search filters were good in identifying clinical prediction models: sensitivity ranged from 0.94 to 1.0 using our hand search as reference, and 0.78 to 0.89 using the systematic reviews as reference. This latter performance measure even increased to around 0.95 (range 0.90 to 0.97) when either search filter was combined with the additional string that we developed. Retrieval rate of explorative prediction research was poor, both using our hand search or our systematic review as reference, and even combined with our additional search string: sensitivity ranged from 0.44 to 0.85. Conclusions/Significance: Explorative prediction research is difficult to find in Medline, using any of the currently available search filters. Yet, application of either the Ingui filter or the Haynes broad filter results in a very low number missed clinical prediction model studie

Excluding pulmonary embolism in primary care using the Wells-rule in combination with a point-of care D-dimer test: a scenario analysis

ABSTRACT: BACKGROUND: In secondary care the Wells clinical decision rule (CDR) combined with a quantitative D-dimer test can exclude pulmonary embolism (PE) safely. The introduction of point-of-care (POC) D-dimer tests facilitates a similar diagnostic strategy in primary care. We estimated failure-rate and efficiency of a diagnostic strategy using the Wells-CDR combined with a POC-D-dimer test for excluding PE in primary care. We considered ruling out PE safe if the failure rate was <2% with a maximum upper confidence limit of 2.7%. METHODS: We performed a scenario-analysis on data of 2701 outpatients suspected of PE. We used test characteristics of two qualitative POC-D-dimer tests, as derived from a meta-analysis and combined these with the Wells-CDR-score. RESULTS: In scenario 1 (SimpliRed-D-dimer sensitivity 85%, specificity 74%) PE was excluded safely in 23.8% of patients but only by lowering the cut-off value of the Wells rule to <2. (failure rate: 1.4%, 95% CI 0.6-2.6%) In scenario 2 (Simplify-D-dimer sensitivity 87%, specificity 62%) PE was excluded safely in 12.4% of patients provided that the Wells-cut-off value was set at 0. (failure rate: 0.9%, 95% CI 0.2-2.6%) CONCLUSION: Theoretically a diagnostic strategy using the Wells-CDR combined with a qualitative POC-D-dimer test can be used safely to exclude PE in primary care albeit with only moderate efficienc

Imaging in assessing hepatic and peritoneal metastases of gastric cancer: a systematic review

<p>Abstract</p> <p>Background</p> <p>Hepatic and peritoneal metastases of gastric cancer are operation contraindications. Systematic review to provide an overview of imaging in predicting the status of liver and peritoneum pre-therapeuticly is essential.</p> <p>Methods</p> <p>A systematic review of relevant literatures was performed in Pubmed/Medline, Embase, The Cochrane Library and the China Biological Medicine Databases. QUADAS was used for assessing the methodological quality of included studies and the bivariate model was used for this meta-analysis.</p> <p>Results</p> <p>Totally 33 studies were included (8 US studies, 5 EUS studies, 22 CT studies, 2 MRI studies and 5 18F-FDG PET studies) and the methodological quality of included studies was moderate. The result of meta-analysis showed that CT is the most sensitive imaging method [0.74 (95% CI: 0.59-0.85)] with a high rate of specificity [0.99 (95% CI: 0.97-1.00)] in detecting hepatic metastasis, and EUS is the most sensitive imaging modality [0.34 (95% CI: 0.10-0.69) ] with a specificity of 0.96 (95% CI: 0.87-0.99) in detecting peritoneal metastasis. Only two eligible MRI studies were identified and the data were not combined. The two studies found that MRI had both high sensitivity and specificity in detecting liver metastasis.</p> <p>Conclusion</p> <p>US, EUS, CT and ¹⁸F-FDG PET did not obtain consistently high sensitivity and specificity in assessing liver and peritoneal metastases of gastric cancer. The value of laparoscopy, PET/CT, DW-MRI, and new PET tracers such as ¹⁸F-FLT needs to be studied in future.</p

Influence of tumor characteristics on the accuracy of endoscopic ultrasonography in staging cancer of the esophagus and esophagogastric junction

Background and Study Aims: Endoscopic ultrasonography (EUS) is the most accurate method of assessing the locoregional extent of cancer of the esophagus and esophagogastric junction. The aim of this study was to evaluate the influence of tumor-related factors such as length and location on the accuracy of EUS in staging these tumors. Patients and Methods: Between January 1997 and September 2002, 280 consecutive patients underwent preoperative EUS for staging cancer of the esophagus and esophagogastric junction. The influence of histopathology, the presence of Barrett's dysplasia or stenosis, and the location and length of the primary tumor on the accuracy of EUS for T, N, and M staging were studied. Results: The overall accuracy rates of EUS for assessing the T, N, and M stages were 73%, 80%, and 78%, respectively. The influence of the tumor's histopathology and the presence of Barrett's dysplasia or stenosis was minimal. The accuracy of EUS was greater in tumors 5 cm or less in size than in tumors larger than 5 cm (82 % vs. 52 % for the T stage, P <0.05; 88 % vs. 59 % for the N stage, P <0.05; and 92 % vs. 56 % for the M stage, P <0.001). The low accuracy of T staging in larger tumors may be due to the exclusion of patients with local unresectability or distant metastases. EUS was also significantly better in esophageal tumors, particularly for identifying celiac trunk metastases (93% vs. 63%; P <0.001). Conclusions: The accuracy of EUS for staging esophageal cancer is lower in tumors larger than 5 cm and in esophagogastric junction tumors than in tumors 5 cm in size or less and in esophageal tumors. These findings should be considered when treatment decisions are being taken