Guidelines for Reporting of Statistics for Clinical Research in Urology

Abstract

In an effort to improve the quality of statistics in the clinical urology literature, statisticians at European Urology, The Journal of Urology, Urology and BJUI came together to develop a set of guidelines to address common errors of statistical analysis, reporting and interpretation. Authors should "break any of the guidelines if it makes scientific sense to do so" but would need to provide a clear justification. Adoption of the guidelines will in our view not only increase the quality of published papers in our journals but improve statistical knowledge in our field in general.It is widely acknowledged that the quality of statistics in the clinical research literature is poor. This is true for urology just as it is for other medical specialties. In 2005, Scales et al. published a systematic evaluation of the statistics in papers appearing in a single month in one of the four leading urology medical journals: European Urology,

Cerenkov luminescence imaging is an effective preclinical tool for assessing colorectal cancer PD-L1 levels in vivo

“…All data were expressed as means±SD and statistical methods refer to "guidelines for reporting of statistics for clinical research in urology" provided by Assel et al [17].The difference in the uptake of 131 I-PD-L1-Mab was assessed using ANOVA with Student-Newman-Keuls method multiple comparison test. The receiver operating characteristic (ROC) curves were drawn to evaluate the diagnostic e cacy of tumor uptake at different time points on tumors PD-L1 expression, and the areas under the curves (AUCs) at different time points were compared using the U tests.…”

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“…Baseline characteristics across BMI categories and by surgical method were tested using Kruskal–Wallis tests for continuous variables, and the χ 2 ‐test for categorical variables. All analyses adhered to guidelines for the reporting of statistics 10 . GEE logistic regression models were used to test the association between BMI (both categorical and continuous) and each surgical margin: overall, peripheral, apical and bladder neck PSMs.…”

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“…The measures of central tendency and variability used to describe each data set should be clear, as well as and how effects and estimated precision are expressed (e.g., 95% confidence interval). If p values are to be reported, then it should be recognized that those close to but higher than .05 do not indicate a "trend" or an approach to significance, whereas a value equal to 0 is not possible (Assel et al, 2019). Units of measurement should not be used in place of variables when describing data: for example, data should be referred to as energy intake rather than kilojoule (or calorie) intake.…”

“…It should also be clearly expressed whether the hypothesis is of a "superiority" nature, where one treatment/intervention is hypothesized to differ from the control or another intervention, or whether the study is more akin to an "equivalence trial" in which one treatment/ intervention is deemed to be of similar effectiveness to another intervention-but perhaps simpler, less costly or less invasive in some way. In the latter situation, the null hypothesis testing procedure is not appropriate-p > .05 should never be used to infer that there is "no difference" between two or more sample estimates (Assel et al, 2019) nor should p values marginally greater than .05 be interpreted as a "trend. "…”