Bias in trials comparing paired continuous tests can cause researchers to choose the wrong screening modality

<p>Abstract</p> <p>Background</p> <p>To compare the diagnostic accuracy of two continuous screening tests, a common approach is to test the difference between the areas under the receiver operating characteristic (ROC) curves. After study participants are screened with both screening tests, the disease status is determined as accurately as possible, either by an invasive, sensitive and specific secondary test, or by a less invasive, but less sensitive approach. For most participants, disease status is approximated through the less sensitive approach. The invasive test must be limited to the fraction of the participants whose results on either or both screening tests exceed a threshold of suspicion, or who develop signs and symptoms of the disease after the initial screening tests.</p> <p>The limitations of this study design lead to a bias in the ROC curves we call <it>paired screening trial bias</it>. This bias reflects the synergistic effects of inappropriate reference standard bias, differential verification bias, and partial verification bias. The absence of a gold reference standard leads to inappropriate reference standard bias. When different reference standards are used to ascertain disease status, it creates differential verification bias. When only suspicious screening test scores trigger a sensitive and specific secondary test, the result is a form of partial verification bias.</p> <p>Methods</p> <p>For paired screening tests with bivariate normally distributed scores, we give formulae and programs to quantify the effect of <it>paired screening trial bias </it>on a paired comparison of area under the curves. We fix the prevalence of disease, and the chance a diseased subject manifests signs and symptoms. We derive the formulas for true sensitivity and specificity, and those for the sensitivity and specificity observed by the study investigator.</p> <p>Results</p> <p>The observed area under the ROC curves is quite different from the true area under the ROC curves. The typical direction of the bias is a strong inflation in sensitivity, paired with a concomitant slight deflation of specificity.</p> <p>Conclusion</p> <p>In paired trials of screening tests, when area under the ROC curve is used as the metric, bias may lead researchers to make the wrong decision as to which screening test is better.</p

Strategies for Searching the Internet for Orthopedic Surgeons: Tips and Tricks

Internet provides access to large amounts of information quickly, provides a flexible learning platform, and is easily accessible from anywhere, especially with new technologies. Web-based search engines and bibliographic databases, have already become part of a doctor\u27s everyday life. However, even well-published researchers often fail to appreciate the background knowledge required to conduct a good literature search on the internet. Using the right techniques can improve the ability to search for relevant information This chapter briefly outlines the internet as an information resources such as Google, Google Scholar, PubMed, Cochrane for orthopedic surgeons. Also the subsequent sections of the chapter offers combining search engines tips and tricks for a best search that orthopedic surgeons can use to improve their use of web-based information and learning resources

Data and programming code from the studies on the learning curve for radical prostatectomy

Our group analyzed a multi-institutional data set to address the question of how the outcomes of surgery for prostate cancer are affected by surgeon-specific factors. The cohort consists of 9076 patients treated by open radical prostatectomy at one of four US academic institutions 1987 - 2003. The primary analyses focused on 7765 patients without neoadjuvant therapy. The most well-known finding is that of a surgical "learning curve", with rates of prostate cancer cure strongly dependent on surgeon experience. In this "data note", we provide the raw data set, as well as well-annotated programming code for the main analyses. Data include markers of cancer severity (stage, grade and prostate-specific antigen level), cancer outcome, and surgeon variables such as training and experience

Osteoarticular Infection in Three Young Thoroughbred Horses Caused by a Novel Gram Negative Cocco-Bacillus

© 2020 Bernard J. Hudson et al. We describe three cases of osteoarticular infection (OAI) in young thoroughbred horses in which the causative organism was identified by MALDI-TOF as Kingella species. The pattern of OAI resembled that reported with Kingella infection in humans. Analysis by 16S rRNA PCR enabled construction of a phylogenetic tree that placed the isolates closer to Simonsiella and Alysiella species, rather than Kingella species. Average nucleotide identity (ANI) comparison between the new isolate and Kingella kingae and Alysiella crassa however revealed low probability that the new isolate belonged to either of these species. This preliminary analysis suggests the organism isolated is a previously unrecognised species

Traffic-related pollution and asthma prevalence in children. Quantification of associations with nitrogen dioxide.

Ambient nitrogen dioxide is a widely available measure of traffic-related air pollution and is inconsistently associated with the prevalence of asthma symptoms in children. The use of this relationship to evaluate the health impact of policies affecting traffic management and traffic emissions is limited by the lack of a concentration-response function based on systematic review and meta-analysis of relevant studies. Using systematic methods, we identified papers containing quantitative estimates for nitrogen dioxide and the 12 month period prevalence of asthma symptoms in children in which the exposure contrast was within-community and dominated by traffic pollution. One estimate was selected from each study according to an a priori algorithm. Odds ratios were standardised to 10 μg/m(3) and summary estimates were obtained using random- and fixed-effects estimates. Eighteen studies were identified. Concentrations of nitrogen dioxide were estimated for the home address (12) and/or school (8) using a range of methods; land use regression (6), study monitors (6), dispersion modelling (4) and interpolation (2). Fourteen studies showed positive associations but only two associations were statistically significant at the 5 % level. There was moderate heterogeneity (I(2) = 32.8 %) and the random-effects estimate for the odds ratio was 1.06 (95 % CI 1.00 to 1.11). There was no evidence of small study bias. Individual studies tended to have only weak positive associations between nitrogen dioxide and asthma prevalence but the summary estimate bordered on statistical significance at the 5 % level. Although small, the potential impact on asthma prevalence could be considerable because of the high level of baseline prevalence in many cities. Whether the association is causal or indicates the effects of a correlated pollutant or other confounders, the estimate obtained by the meta-analysis would be appropriate for estimating impacts of traffic pollution on asthma prevalence

Statistical methods to correct for verification bias in diagnostic studies are inadequate when there are few false negatives: a simulation study

<p>Abstract</p> <p>Background</p> <p>A common feature of diagnostic research is that results for a diagnostic gold standard are available primarily for patients who are positive for the test under investigation. Data from such studies are subject to what has been termed "verification bias". We evaluated statistical methods for verification bias correction when there are few false negatives.</p> <p>Methods</p> <p>A simulation study was conducted of a screening study subject to verification bias. We compared estimates of the area-under-the-curve (AUC) corrected for verification bias varying both the rate and mechanism of verification.</p> <p>Results</p> <p>In a single simulated data set, varying false negatives from 0 to 4 led to verification bias corrected AUCs ranging from 0.550 to 0.852. Excess variation associated with low numbers of false negatives was confirmed in simulation studies and by analyses of published studies that incorporated verification bias correction. The 2.5^th– 97.5^thcentile range constituted as much as 60% of the possible range of AUCs for some simulations.</p> <p>Conclusion</p> <p>Screening programs are designed such that there are few false negatives. Standard statistical methods for verification bias correction are inadequate in this circumstance.</p

Determinants of abstract acceptance for the Digestive Diseases Week – a cross sectional study

BACKGROUND: The Digestive Diseases Week (DDW) is the major meeting for presentation of research in gastroenterology. The acceptance of an abstract for presentation at this meeting is the most important determinant of subsequent full publication. We wished to examine the determinants of abstract acceptance for this meeting. METHODS: A cross-sectional study was performed, based on abstracts submitted to the DDW. All 17,205 abstracts submitted from 1992 to 1995 were reviewed for acceptance, country of origin and research type (controlled clinical trials (CCT), other clinical research (OCR), basic science (BSS)). A random sub-sample (n = 1,000) was further evaluated for formal abstract quality, statistical significance of study results and sample size. RESULTS: 326 CCT, 455 OCR and 219 BSS abstracts were evaluated in detail. Abstracts from N/W Europe (OR 0.4, 95% CI 0.3–0.6), S/E Europe (OR 0.4, 95% CI 0.2–0.6) and non-Western countries (OR 0.3, 95% CI 0.2–0.5) were less likely to be accepted than North-American contributions when controlling for research type. In addition, the OR for the acceptance for studies with negative results as compared to those with positive results was 0.4 (95% CI 0.3–0.7). A high abstract quality score was also weakly associated with acceptance rates (OR 1.4, 95% CI 1.0–2.0). CONCLUSIONS: North-American contributions and reports with statistically positive results have higher acceptance rates at the AGA. Formal abstract quality was also predictive for acceptance

Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers

<p>Abstract</p> <p>Background</p> <p>Decision curve analysis is a novel method for evaluating diagnostic tests, prediction models and molecular markers. It combines the mathematical simplicity of accuracy measures, such as sensitivity and specificity, with the clinical applicability of decision analytic approaches. Most critically, decision curve analysis can be applied directly to a data set, and does not require the sort of external data on costs, benefits and preferences typically required by traditional decision analytic techniques.</p> <p>Methods</p> <p>In this paper we present several extensions to decision curve analysis including correction for overfit, confidence intervals, application to censored data (including competing risk) and calculation of decision curves directly from predicted probabilities. All of these extensions are based on straightforward methods that have previously been described in the literature for application to analogous statistical techniques.</p> <p>Results</p> <p>Simulation studies showed that repeated 10-fold crossvalidation provided the best method for correcting a decision curve for overfit. The method for applying decision curves to censored data had little bias and coverage was excellent; for competing risk, decision curves were appropriately affected by the incidence of the competing risk and the association between the competing risk and the predictor of interest. Calculation of decision curves directly from predicted probabilities led to a smoothing of the decision curve.</p> <p>Conclusion</p> <p>Decision curve analysis can be easily extended to many of the applications common to performance measures for prediction models. Software to implement decision curve analysis is provided.</p

Abdominal functional electrical stimulation to improve respiratory function after spinal cord injury: a systematic review and meta-analysis

Objectives: Abdominal functional electrical stimulation (abdominal FES) is the application of a train of electrical pulses to the abdominal muscles, causing them to contract. Abdominal FES has been used as a neuroprosthesis to acutely augment respiratory function and as a rehabilitation tool to achieve a chronic increase in respiratory function after abdominal FES training, primarily focusing on patients with spinal cord injury (SCI). This study aimed to review the evidence surrounding the use of abdominal FES to improve respiratory function in both an acute and chronic manner after SCI. Settings: A systematic search was performed on PubMed, with studies included if they applied abdominal FES to improve respiratory function in patients with SCI. Methods: Fourteen studies met the inclusion criteria (10 acute and 4 chronic). Low participant numbers and heterogeneity across studies reduced the power of the meta-analysis. Despite this, abdominal FES was found to cause a significant acute improvement in cough peak flow, whereas forced exhaled volume in 1 s approached significance. A significant chronic increase in unassisted vital capacity, forced vital capacity and peak expiratory flow was found after abdominal FES training compared with baseline. Conclusions: This systematic review suggests that abdominal FES is an effective technique for improving respiratory function in both an acute and chronic manner after SCI. However, further randomised controlled trials, with larger participant numbers and standardised protocols, are needed to fully establish the clinical efficacy of this technique