The likelihood ratio and its graphical representation

Diagnostic tests are important clinical tools. Bayes’ theorem and Bayesian approach are important methods for interpreting test results. The Bayesian factor, the so-called likelihood ratio, has not always been well-understood. In this article, we try to discuss the likelihood ratio and its value for a specific test result, a positive or negative test result, and a range of test results, along with their graphical representations

On determining the sensitivity and specificity of a new diagnostic test through comparing its results against a non-gold-standard test

Diagnostic tests are important clinical tools. To assess the sensitivity and specificity of a new test, its results should be compared against a gold standard. However, the gold-standard test is not always available. Herein, I show that we can compare the new test against a well-established diagnostic test (not a gold-standard test, but with known sensitivity and specificity) and compute the sensitivity and specificity of the new test if we would have compared it against the gold-standard test. The technique presented is useful for situations where the gold standard is not readily available

What’s in a name, anyway?

We have used names, particularly surnames, to identify people who are related. However, this has been done in various ways in different societies. While in many western countries we use a given (first) name and a surname (family name) to identify a person, in Arab countries, there are in fact no surnames; people use their given name followed by their father’s given name. For example, while my name in a western system is “Farrokh Habibzadeh” (Farrokh is my first name and Habibzadeh is my family name), my name in Arabic documents, say in a visa, would be “Farrokh Naser” (Naser is my father’s first name). Chinese use another style. They usually use their surname followed by their given name. Then, my name in a Chinese system would be “Habibzadeh Farrokh

The apparent prevalence, the true prevalence

Serologic tests are important for conducting seroepidemiologic and prevalence studies. However, the tests used are typically imperfect and produce false-positive and false-negative results. This is why the seropositive rate (apparent prevalence) does not typically reflect the true prevalence of the disease or condition of interest. Herein, we discuss the way the true prevalence could be derived from the apparent prevalence and test sensitivity and specificity. A computer simulation based on the Monte-Carlo algorithm was also used to further examine a situation where the measured test sensitivity and specificity are also uncertain. We then complete our review with a real example. The apparent prevalence observed in many prevalence studies published in medical literature is a biased estimation and cannot be interpreted correctly unless we correct the value

Are Shorter Article Titles More Attractive for Citations? Crosssectional Study of 22 Scientific Journals

Aim To investigate the correlation between the length of the title of a scientific article and the number of citations it receives, in view of the common editorial call for shorter titles. Methods Title and the number of citations to all articles published in 2005 in 22 arbitrarily chosen English-language journals (n = 9031) were retrieved from citation database Scopus. The 2008 journal impact factors of these 22 journals were also retrieved from Thomson Reuters’ Journal Citation Report (JCR). Assuming the article title length as the independent variable, and the number of citations to the article as the dependent variable, a linear regression model was applied. Results The slope of the regression line for some journals (n = 6, when titles were measured in characters but 7 when titles were measured in words) was negative – none was significantly different from 0. The overall slope for all journals was 0.140 (when titles were measured in characters) and 0.778 (when titles were measured in words), which is significantly different from 0 (P < 0.001 , t test). Overall, articles with longer titles received more citations – Spearman ρ = 0.266 – when titles were measured in characters, and ρ = 0.244 when titles were measured in words (P < 0.001). This association was found for 7 of 8 journals with impact factor >10 and for 2 out of 14 journals with impact factor <10 (P < 0.001, Fisher exact test). Conclusion Longer titles seem to be associated with higher citation rates. This association is more pronounced for journals with high impact factors. Editors who insist on brief and concise titles should perhaps update the guidelines for authors of their journals and have more flexibility regarding the length of the title

MY LIFE AS AN EDITOR AND CONSULTANT OF MEDICAL JOURNALS

MY LIFE AS AN EDITOR AND CONSULTANT OF MEDICAL JOURNAL