clinical decision - making should be founded on the highest level of evidence available . according to current hierarchies , randomized control trials ( rcts ) govern the top echelon due to the lowest possible influence of bias . as such , well - executed rcts are the gold standard for clinicians assessing therapeutic effectiveness and treatment options . borawski et al . , performed the first formal evaluation of the levels of evidence in urological literature . independent reviewers familiar with the level of evidence concept rated 600 studies using a standardized evaluation form adapted from the center of evidence based medicine . the studies were randomly selected from four major urology journals ( the journal of urology , european urology , bju international , and urology ) in the periods 2000 and 2005 . overall , 60.3% of studies addressed questions of therapy / prevention , 11.5% addressed etiology / harm , 11.3% addressed prognosis , and 9.2% addressed diagnosis . articles centered mainly on adult populations ( 86% ) with oncology as the topic of choice ( 38.8% ) . disturbingly , the levels of evidence provided by these studies were low : 5.3% level i , 10.3% level ii , 9.8% level iii , and 74.5% level iv . from 2000 to 2005 , the authors conclude by suggesting that the majority of studies in urological literature can not adequately guide clinical decision - making as a result of such low level of evidence . several barriers to providing the highest level of evidence among surgical subspecialties have been previously identified , such as lack of surgeon patient equipoise about certain therapies , difficulty of standardizing quality of a given surgical procedure , and limited funding mechanisms . however , another looming possibility exists : is there paucity in statistical sense among urologists ? in line with low levels of evidence , findings at scientific meetings do not see the light of full - text publication in many cases . failure to publish is problematic for two main reasons : 1 ) clinicians looking to apply research findings lack the necessary detail in abstracts to critically appraise a given study for validity and impact ; 2 ) it is wasteful of resources , unethical , and can lead to unnecessary replication of studies . smith et al . , reviewed clinical research abstracts accepted for publication at 2002 and 2003 aua meetings . literature search follow - up of published articles was performed in 2005 . out of 1683 abstracts , the majority of abstracts from north america ( 62.5% ) , reported single institution efforts ( 68.2% ) mainly in the domain of therapy / prevention ( 51.6% ) . forty - four percent of these abstracts were published with a median follow - up of 27.8 months and 54.2% indicated formal statistical hypothesis testing . kaplan - meier analysis showed less time to publication of abstracts that had statistical testing ( 912 ) compared to those that did not ( 771 ) ( log - rank p = 0.009 ) . univariate analyses identified statistical hypothesis testing with time for publication along with other predictors as significant factors contributing to the difference in publication rates . this was confirmed in multivariable analysis , as reporting to statistical testing remained predictive ( hr 1.2 , 95% ci 1.11.4 ) . the authors highlighted how 61% of studies are affected by nonpublication of research findings two years after presentation at the aua meeting due to a lack of statistics . increasingly , statistical methodology has transitioned from the realm of statistical journals to medical research . with the advent and plethora of available statistical software , not using statistics is one weakness , but making errors in statistical testing and reporting of results can compromise the health of research animals , human subjects , and ultimate recipients of therapies . in research literature , scales and colleagues performed a systematic assessment of statistical usage in urology literature . using a single issue ( august 2004 ) of four leading urology journals ( journal of urology , british journal of urology , urology , and european urology ) , two independent raters with formal statistics training reviewed the articles using a standardized evaluation form developed with an experienced biostatistician . out of 97 articles that met eligibility criteria , cohort design comprised the majority of studies ( 44% ) . of the 12.4% of studies that were randomized trials , 42% detailed clinically significant differences , 50% detailed power calculations , and 30% described method of randomization . descriptive statistics were widely reported ( 94% ) and articles mainly included simple statistical comparisons of two groups ( 77% ) . distressingly , 71% of studies with statistical comparisons had at least one statistical error , including incorrect test ( 28% ) , faulty use of a parametric test ( 22% ) , and failure to adjust for multiple comparisons ( 65% ) . in addition , overfitting a regression model was a common problem ( 39% ) in the 29% of studies that applied multivariable analysis . such flawed application of statistics can potentially increase the likelihood of type i error and should be identified as a potential threat to validity of conclusions . statistics is paramount to success for the urologist as a researcher and as a clinician in urology . the remainder of this review will focus on probing the underlying problem of statistical use among clinicians and offer solutions that can be applied to rectify this situation . to exercise evidence - based medicine ( ebm ) , physicians need access to full - fledged research reports to critically evaluate study analysis and interpretation . however , surveys dating back to the 1980s identified physicians who had a poor grasp of statistical tests and interpretation of statistical results due to a lack of formal training in biostatistics.[1012 ] this problem is even more explosive today in light of increased complexity of statistical methods used in the literature . in response , graduate medical educators have increased training in biostatistics throughout the expanse of medical education . medical schools have incorporated statistics courses and accreditation council for graduate medical education ( agcme ) guidelines since residency competency stipulates that residents must have a solid basic foundation in statistical methodology as it pertains to scientific research . while residency programs address this issue through ebm curricula and journal clubs,[1517 ] a few , if any , programs focus on selection and interpretation of statistical results . to broadly assess residents ' knowledge and skills in ebm , windish et al . , conducted a seminal multiprogram assessment of 11 internal medicine residency programs in connecticut . by first reviewing research articles in six leading general medical journals between january and march 2005 on the basis of statistical methods used , the researchers developed a survey instrument of questions focused on identifying and interpreting results in the most frequently occurring statistical tests . questions were multiple - choice , centered on a clinical vignette , and required no calculations . attitudes and confidence questions were adapted from surveys on the assessment resource tools for improving statistical thinking website , rated on a 5-point likert scale . this instrument was validated and reformulated by pilot testing the questions on 5 internal medicine faculty with advanced training in biostatistics and 12 primary care internal medicine residents . in terms of respondent characteristics , out of 277 residents , 48% were female , 60.8% aged 2630 years with no advanced degrees ( 85.1% ) , and a modest distribution of years since medical school ( 35.0% < 1 year , 26.8% 13 years , 30.1% 410 years ) . of the foreign medical graduates in the population , 38.6% completed their medical school training outside the u.s . , 68.8% had previous coursework in biostatistics [ 69.5% of which were during medical school ( 15.9% college , 3.2% residency ) ] . over 50% had previous training in epidemiology and ebm , and regularly read medical journals . interestingly , the number of residents who could correctly identify and interpret statistical results was low . approximately 25.6% could correctly identify chi - squared analysis , 13.0% could correctly identify cox proportional hazard regression , 11.9% could interpret a 95% ci and statistical significance , and only 10.5% could interpret kaplan - meier analysis results . using a forward stepwise regression model , advanced degrees , successive years since medical school , and prior biostatistics training were all factors found to be independently associated with knowledge scores . in terms of attitudes and confidence , 95% of residents agreed that knowledge of statistics is essential to being an intelligent reader of literature and 77% indicated they would like to learn more statistics . while over 58% of residents reported using statistics in forming opinions or making clinical decisions , 75% indicated they did not fully understand the statistics reported in literature . only 38% of residents felt confident assessing the appropriateness of statistical testing used and respondents with a higher confidence level in statistical knowledge fared better on the knowledge questions . while their report was confined to internal medicine residents , high internal consistency , good discriminative validity , and similarity in results among different residency programs lend credibility to the illustrated problem . a comprehensive review of biostatistics teaching indicates that 90% of medical schools taught biostatistics in preclinical years only with varying breadth and depth of education . another pressing issue is that senior residents performed worse than junior residents , indicating a time correlation . most likely , loss of knowledge over time , coupled with lack of adequate reinforcement could lead to loss of statistical competency . if clinicians can not evaluate appropriate statistical tests and accurately interpret results , risks could be carried over to incorrect clinical decision - making . west and colleagues performed a similar study in 2005 on 301 medical students , internal medicine residents and faculty , about their attitudes toward biostatistics in medicine . according to their findings , 48.3% of those surveyed felt biostatistics is a difficult subject , 87.3% felt that understanding biostatistics would help their careers , and 17.6% felt their training in biostatistics was adequate for their needs . furthermore , 23.3% of respondents could evaluate appropriateness of statistical methods used in a study , 88% felt knowledge of statistics is necessary for evaluating medical literature , and 48.5% felt that biostatistics is a necessary skill for clinicians not involved in research . in essence , the survey strongly indicated that clinicians were uncomfortable with biostatistics and even more dissatisfied with this cognizance . it is unclear why physicians are queasy regarding statistics even though they use statistics in their daily routine . perhaps the finding that 20% of respondents felt their biostatistics coursework was taught effectively calls into question as to how clinicians are being educated about statistics in healthcare fields traditional teaching methods in schools employ a stepwise approach entailing formulae , data , and spoon - fed instructions . bordering on a moral quandary is the question of whether expectations for the average urologist are too high . would the urologist who is not a researcher be better suited to appraise practice guidelines , derived by experts with the necessary statistical knowledge , rather than interpret statistics ? urology is a highly competitive field that is constantly evolving and as such , expectations will continue to be shattered and stacked higher . the current consensus will most likely rest on the urologist having a strong statistical repertoire because research is an increasingly integral component of residency and fellowship programs , because guidelines can change given new information , and because treatment accountability ultimately rests with the physician 's ability to evaluate evidence and make decisions . most of the studies examining the use of statistics and knowledge of clinicians have thus far been centered in the u.s . in urology , only major journals have been examined leaving other international journals indexed in medline , such as brazilian journal of urology and indian journal of urology out of the loop . it is vital to assess how these journals and how urology practitioners in these regions fare in comparison to the current data through future investigations of this nature . although errors in statistics and a lack of comprehensive understanding in methodology are common in the literature , modifications to current mindsets can still be made in the best interests of the patient . curran - everett and benos have proposed guidelines for reporting statistics in journals published by the american physiological society . a set of 10 guidelines , ranging from advice to consult a biostatistician to interpretation based on confidence intervals and p - values , address reporting of statistics in the materials and methods , results , and discussion sections of a manuscript . a cursory look at additional references cited in the manuscript provides additional resources for urologists interested in looking at the framework of statistics and presentation issues . in addition , a commentary aimed at the publication of these guidelines by murray clayton provides an excellent critique of when to use the guidelines . clayton argues that the algorithmic approach of guidelines may not always serve the practitioner or peer - reviewer well as situational cues dictate statistical testing and interpretation . as such the word is still out as to whether these guidelines truly represent the best practices in statistics . focusing on urology , scales and colleagues have produced two publications that can serve as a starting point of quick statistical reference . first , they provided a series of non - technical explanations of basic statistical concepts encountered in urological literature . in terms of results , they discuss various outcome measures , how to summarize continuous data , how to summarize non - normal continuous and ordinal data , how to summarize unordered categorical data , how to interpret cis , how to interpret rrs , the difference between odds , or , and rr , how to interpret a km curve , and how to interpret multivariable analyses . in addition , the authors provide examples of common statistical flaws involving type i and ii errors , sample size calculations , multiple comparisons , and confounding variables to increase awareness of study limitations in light of statistical restrictions . by providing a statistical roadmap , the authors provide advice on choosing appropriate statistical tests as a brief introductory roundup for the practicing urologist . scales and colleagues also provided a complementary companion primer on evidence - based clinical practice ( ebcp ) for urologists using examples from the literature . principles of ebcp are discussed followed by a step - by - step approach to implementing ebcp . sources of evidence are discussed along with methods to evaluate a study for therapeutic effectiveness . with appendices that summarize levels of evidence , electronic databases of primary evidence , and web addresses of online ebcp centers , this primer can provide urologists with the tools and questions that can aid in accumulating evidence and clinical decision - making . faculty who are implementing biostatistics curricula can access these teaching resources . without a doubt , teaching of statistics to medical students , residents , and fellows can be improved . rather than sparse statistical exchanges during journal clubs , medical education should be expanded to make biostatistics less daunting and more meaningful to urologists in practice . more time should be allotted to biostatistics education in medical school in a clinical problem - based learning format . rather than a one - shot infusion of statistics through an isolated course or a seminar , reinforced and integrated ideally , medical students will have exposure to statistics throughout their training . in residency , this can be complemented by recurring seminars from available biostatisticians or visiting faculty from nearby universities . these can be in the form of a retreat with a distribution of problem - sets at the end . small - group work can be encouraged for a gathering and review of solutions a week later . yet another option is online - educational courses offered by a variety of universities . for instance , harvard university extension school offers a semester - long course on introductory graduate biostatistics . students can view streamed video lectures , post questions on an online discussion board , ask questions from professors and teaching assistants and receive feedback on homework and examinations as if they were partaking in a live course . while mailing outside the u.s . for graded assignments poses a time - lag problem , courses such as these provide an alternative if the means of quality education and expertise are lacking in the area . such courses provide the welcome opportunity of immersing oneself in statistical software and learning the realities behind a particular formula . ultimately , broader facilitation should be imparted at the departmental level to enable urologists to better answer research questions . considering a hectic schedule of surgeries in the or and clinic presence , accessibility of literature for review , adequate data management infrastructure , availability of statistics know - how , and project supervision by faculty are the key factors that can dissuade even the most curious physician . urology training programs need to be more trainee - centered to imbibe a statistical way of thinking to work around the areas of uncertainty . statistical software that can transform raw data from a database into meaningful results using a core set of statistical tests should be freely available for use . softwares such as stata , spss , sas , sigmaplot , r , jmp , and comprehensive meta analysis , to name a few , understandably require institutional licenses . although these licenses are expensive , the investment is worthwhile because residents and fellows will get hands - on exposure to working with numbers . if such expenses are prohibitive , regional collaborations are encouraged to allow such software packages to be transitive in distribution . departmental oversight of this nature can help ensure competency in fields of data management , statistical formula application , critical analysis , and study interpretation . competencies should be expanded in medical school and residency to mandate a certain level of proficiency in order to progress from one training year to the next . in conjunction with better education of urologists , attitudes toward , and use of statistics medicine is evolving at a rapid pace with publications increasing to the rate that journals have a backlog of articles that see print six months after acceptance . at this pace , urologists need to be less intimidated by biostatistics . as important as the stethoscope , statistical sense is crucial to evaluate research findings and examining patient research . if not just for clinical decision - making , at least the physicians have a mechanism of expressing to patients why they are making a particular decision . the current problem of a low level of statistical evidence in urology literature coupled with a significant lag between abstract presentation and a full - text publication represent a lack of understanding of , and comfort with , statistics . this is reflected in errors in statistical usage that can be corrected by increased awareness of the problem and readiness to act by improving medical education of statistics .
understanding statistical terminology and the ability to appraise clinical research findings and statistical tests are critical to the practice of evidence - based medicine . 
 urologists require statistics in their toolbox of skills in order to successfully sift through increasingly complex studies and realize the drawbacks of statistical tests . 
 currently , the level of evidence in urology literature is low and the majority of research abstracts published for the american urological association ( aua ) meetings lag behind for full - text publication because of a lack of statistical reporting . 
 underlying these issues is a distinct deficiency in solid comprehension of statistics in the literature and a discomfort with the application of statistics for clinical decision - making . 
 this review examines the plight of statistics in urology and investigates the reason behind the white - coat aversion to biostatistics . 
 resources such as evidence - based medicine websites , primers in statistics , and guidelines for statistical reporting exist for quick reference by urologists . 
 ultimately , educators should take charge of monitoring statistical knowledge among trainees by bolstering competency requirements and creating sustained opportunities for statistics and methodology exposure .