Research Techniques Made Simple: Interpreting Measures of Association in Clinical Research

Abstract

To bring evidence-based improvements in medicine and health care delivery to clinical practice, health care providers must know how to interpret clinical research findings and critically evaluate the strength of evidence. This requires an understanding of differences in clinical study designs and the various statistical methods used to identify associations. We aim to provide a foundation for understanding the common measures of association used in epidemiologic studies to quantify relationships between exposures and outcomes, including relative risks, odds ratios, and hazard ratios. We also provide a framework for critically assessing clinical research findings and highlight specific methodologic concerns.

Multilocus sequence typing (MLST) analysis reveals many novel genotypes and a high level of genetic diversity in Candida tropicalis isolates from Italy and Africa

“…Moreover, in addition to these data bias issues, which have a significant impact on the real amount of genetic diversity in the global C. tropicalis population, 25 it should also be stressed that there is a remarkable lack of essential metadata, especially those from antifungal susceptibility testing. As per February 2022, a MIC value for fluconazole was present for only 39% (529/1351) of the isolates deposited, making MLST data underpowered to detect significant associations 25,59 . In this regard, the MLST genotypes (DSTs 225, 376, 506 and 546) of the large Chinese FNS clonal complex (CC2), recently described by Wang et al, 2020 31 in Wuhan, were grouped by our goeBURST analysis with six fluconazole‐susceptible Italian isolates indicating that all the genetic diversity (not only genotypes with MIC data) 31 should be considered to assess potential relationships between MLST genotypes and other variables, for example geographic locations.…”

“…As per February 2022, a MIC value for fluconazole was present for only 39% (529/1351) of the isolates deposited, making MLST data underpowered to detect significant associations. 25,59 In this regard, the MLST genotypes (DSTs 225, 376, 506 and 546) of the large Chinese FNS clonal complex (CC2), The global genetic structure of the C. tropicalis population has not yet been fully elucidated as its complexity grows rapidly as the number of different types of isolates (clinical or environmental) increases. 15,37,60 Our MLST data confirm this trend, as 14% of MLST alleles and over 70% of DSTs detected here were novel (Table 1).…”

“…As per February 2022, a MIC value for fluconazole was present for only 39% (529/1351) of the isolates deposited, making MLST data underpowered to detect significant associations. 25 , 59 In this regard, the MLST genotypes (DSTs 225, 376, 506 and 546) of the large Chinese FNS clonal complex (CC2), recently described by Wang et al, 2020 31 in Wuhan, were grouped by our goeBURST analysis with six fluconazole‐susceptible Italian isolates indicating that all the genetic diversity (not only genotypes with MIC data) 31 should be considered to assess potential relationships between MLST genotypes and other variables, for example geographic locations. Furthermore, based on our data, the use of clonal complexes in association analyses may not be exhaustive as the results obtained by analysing global MIC values and MLST genotypes showed a positive correlation of some DSTs with non‐susceptibility to caspofungin (DST 1176 and 1186) or posaconazole (DST 1179), a feature that was not detected by statistical analysis employing CCs.…”

The role of depression in the prediction of a “late” remission in first-episode psychosis: An analysis of the OPTiMiSE study

“…Both estimates can be interpreted as the strength of the association between a particular predictor and the outcome. OR and HR values >1 indicate that the predictor increases the likelihood of the occurrence of the outcome, while values <1 indicate that it decreases the likelihood of the occurrence of the outcome (Roberts et al, 2019).…”

Association of Psoriasis With Incident Venous Thromboembolism and Peripheral Vascular Disease

“…As psoriasis shares similar inflammatory pathomechanisms with VTE and PVD, previous meta-analyses in 2013 and 2014 discussed the potential associations of psoriasis with VTE and PVD . Nevertheless, the number of included studies in these meta-analyses was relatively small, with a resultant lack of statistical power to draw solid conclusions . Moreover, the pooled results in these meta-analyses were mainly based on cross-sectional studies, which failed to prove a temporal association .…”