***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: The relative accuracy of r and omized control trials ( RCTs ) and historical control trials ( HCTs ) in determining effective therapies has not been compared since there is no external verification of efficacy . We review ed six therapies studied by both methods . Most HCTs concluded therapy was better than control , but few RCTs agreed . We calculated sensitivity and specificity for each type of trial by combining published results with all possible combinations of effectiveness . The sensitivity of  HCTs  was 0.80 to 1.00 ( mean , 0.90 ) and specificity was 0.0 to 0.27 ( mean , 0.11 ) . The sensitivity of RCTs was 0.0 to 0.27 ( mean , 0.12 ) and specificity was 0.67 to 1.00 ( mean , 0.88 ) . Defects of RCTs are more easily corrected than those of HCTs . Readers should consider trial design and the probability of errors when deciding how much credence to give to a clinical trial CONTEXT Medical evidence may be biased over time if completion and publication of r and omized efficacy trials are delayed when results are not statistically significant . OBJECTIVE To evaluate whether the time to completion and the time to publication of r and omized phase 2 and phase 3 trials are affected by the statistical significance of results and to describe the natural history of such trials . DESIGN Prospect i ve cohort of r and omized efficacy trials conducted by 2 trialist groups from 1986 to 1996 . SETTING Multicenter trial groups in human immunodeficiency virus infection sponsored by the National Institutes of Health . PATIENTS A total of 109 efficacy trials ( total enrollment , 43708 patients ) . MAIN OUTCOME MEASURES Time from start of enrollment to completion of follow-up and time from completion of follow-up to peer- review ed publication assessed with survival analysis . RESULTS The median time from start of enrollment to publication was 5.5 years and was substantially longer for negative trials than for results favoring an experimental arm ( 6.5 vs 4.3 years , respectively ; P<.001 ; hazard ratio for time to publication for positive vs negative trials , 3.7 ; 95 % confidence interval [ CI ] , 1.8 - 7.7 ) . This difference was mostly attributable to differences in the time from completion to publication ( median , 3.0 vs 1.7 years for negative vs positive trials ; P<.001 ) . On average , trials with significant results favoring any arm completed follow-up slightly earlier than trials with nonsignificant results ( median , 2.3 vs 2.5 years ; P=.045 ) , but long-protracted trials often had low event rates and failed to reach statistical significance , while trials that were terminated early had significant results . Positive trials were su bmi tted for publication significantly more rapidly after completion than were negative trials ( median , 1.0 vs 1.6 years ; P=.001 ) and were published more rapidly after su bmi ssion ( median , 0.8 vs 1.1 years ; P=.04 ) . CONCLUSION Among r and omized efficacy trials , there is a time lag in the publication of negative findings that occurs mostly after the completion of the trial follow-up Meta-analytic investigations sometimes use assessment s of research quality according to a formal protocol as a tool for improving research synthesis . We asked whether a particular  quality scoring system could have a direct use in adjusting the summary estimates of a treatment difference . In an empirical study of the relation of quality scores to treatment differences in published meta-analyses of 7 groups of controlled r and omized clinical trials comprising 107 primary studies , we found no relation between treatment difference and overall quality score . We also found no relation between quality score and variation in treatment difference . The level of quality scores has increased at a rate of 9 % per decade for three decades , averaging 0.51 on a scale of 0 to 1 for the 1980s , and leaving much room for improvement . Nevertheless , attention to quality of studies by editors , review ers , and authors may be raising both the level of research done and quality of the reports OBJECTIVE To determine whether crossover trials with simple pooling of data over different study periods leads to a different estimate of treatment effect compared with parallel group trials in infertility research using pregnancy as the outcome measure . DESIGN An observational study using nine overviews that included trials with both crossover and parallel group design s. These overviews comprised 17 crossover and 17 parallel group trials . In total , there were 5,291 outcomes including 775 pregnancies . The association between study design and treatment effect estimate was analyzed using multiple logistic regression , controlling for differences in the therapeutic interventions and variations in the method ological quality of the trials . SETTING Infertile patients in an academic research environment . PATIENTS Infertile patients undergoing treatment efficacy evaluation in controlled trials . INTERVENTIONS R and om allocation to a variety of treatments including clomiphene citrate , hCG , IUI , tamoxifen , and bromocriptine . MAIN OUTCOME MEASURE Estimate of bias between study design s , based on the interaction of study design and treatment in the logistic regression model . RESULTS Crossover trials produced a larger average estimate of treatment effect compared with trials with a parallel group design , overestimating the odds ratio by 74 % ( 95 % confidence interval , 2 % to 197 % ) . CONCLUSION The use of a crossover design for evaluating infertility treatments with outcomes that prevent patients from completing later phases of the trial should be avoided because it leads to exaggerated estimates of treatment effect and may result in erroneous inferences and clinical decisions . Furthermore , the type of study design should be taken into account when assessing the method ological quality of therapy trials in infertility To compare the use of  r and omized controls ( RCTs ) and historical controls ( HCTs )  for clinical trials , we search ed the literature for therapies studied by both methods . We found six therapies for which 50 RCTs and 56 HCTs were reported . Forty-four of 56 HCTs  ( 79 percent ) found the therapy better than the control regimen , but only 10 of 50 RCTs ( 20 percent ) agreed . For each therapy , the treated patients in RCTs and HCTs of the same therapy was largely due to differences in outcome for the control groups , with HCT control patients generally doing worse than the RCT control groups . Adjustment of the outcomes of the HCTs for prognostic factors , when possible , did not appreciably change the results . The data suggest that biases in patient selection may irretrievably weight the outcome of HCts in favor of new therapies . RCTs may miss clinical ly important benefits because of inadequate attention to sample size . The predictive value of each might be improved by reconsidering the use of p less than 0.05 as the significance level for all types of clinical trials , and by the use of confidence intervals around estimates of treatment effects BACKGROUND Traditional and largely qualitative review s of evidence are now giving way to much more structured systematic overviews that use a quantitative method to calculate the overall effect of treatment . The latter approach is dependent on the quality of primary studies , which may introduce bias if they are of poor method ologic quality . OBJECTIVE To test the hypothesis that the inclusion of poor- quality trials in meta-analyses would bias the conclusions and produce incorrect estimates of treatment effect . METHODS An overview of r and omized trials of antiestrogen therapy in subfertile men with oligospermia was performed to test the hypothesis . Data sources included online search ing of MEDLINE and Science Citation Index data bases between 1966 and 1994 , scanning the bibliography of known primary studies and review articles , and contacting experts in the field . After independent , blind assessment , nine of 149 originally identified studies met the inclusion criteria and were selected . We assessed study quality independently . Outcome data from each study were pooled and statistically summarized . RESULTS There was a marginal improvement in pregnancy rate with antiestrogen treatment ( odds ratio , 1.6 ; 95 % confidence interval , 0.9 to 2.6 ) . Sensitivity analyses on the basis of method ologic quality demonstrated that poor- quality studies produced a positive effect with treatment , whereas no benefit was observed with high- quality studies . CONCLUSION The results of a meta- analysis are influenced by the quality of the primary studies included . Method ologically , poor studies tend to exaggerate the overall estimate of treatment effect and may lead to incorrect inferences Background : Information on major harms of medical interventions comes primarily from epidemiologic studies performed after licensing and marketing . Comparison with data from large-scale r and omized trials is occasionally feasible . We compared evidence from r and omized trials with that from epidemiologic studies to determine whether they give different estimates of risk for important harms of medical interventions . Methods : We targeted well-defined , specific harms of various medical interventions for which data were already available from large-scale r and omized trials ( > 4000 subjects ) . Nonr and omized studies involving at least 4000 subjects addressing these same harms were retrieved through a search of MEDLINE . We compared the relative risks and absolute risk differences for specific harms in the r and omized and nonr and omized studies . Results : Eligible nonr and omized studies were found for 15 harms for which data were available from r and omized trials addressing the same harms . Comparisons of relative risks between the study types were feasible for 13 of the 15 topics , and of absolute risk differences for 8 topics . The estimated increase in relative risk differed more than 2-fold between the r and omized and nonr and omized studies for 7 ( 54 % ) of the 13 topics ; the estimated increase in absolute risk differed more than 2-fold for 5 ( 62 % ) of the 8 topics . There was no clear predilection for r and omized or nonr and omized studies to estimate greater relative risks , but usually ( 75 % [ 6/8 ] ) the r and omized trials estimated larger absolute excess risks of harm than the nonr and omized studies did . Interpretation : Nonr and omized studies are often conservative in estimating absolute risks of harms . It would be useful to compare and scrutinize the evidence on harms obtained from both r and omized and nonr and omized studies Background There has been increasing concern regarding the potential effects of the commercialization of research . Methods In order to examine the relationships between funding source , trial outcome and reporting quality , recent issues of five peer- review ed , high impact factor , general medical journals were h and - search ed to identify a sample of 100 r and omized controlled trials ( 20 trials/journal ) . Relevant data , including funding source ( industry/not-for-profit/mixed/not reported ) and statistical significance of primary outcome ( favouring new treatment/favouring conventional treatment/neutral/unclear ) , were abstract ed . Quality scores were assigned using the Jadad scale and the adequacy of allocation concealment . Results Sixty-six percent of trials received some industry funding . Trial outcome was not associated with funding source ( p= .461 ) . There was a preponderance of favourable statistical conclusions among published trials with 67 % reporting results that favored a new treatment whereas 6 % favoured the conventional treatment . Quality scores were not associated with funding source or trial outcome . Conclusions It is not known whether the absence of significant associations between funding source , trial outcome and reporting quality reflects a true absence of an association or is an artefact of inadequate statistical power , reliance on voluntary disclosure of funding information , a focus on trials recently published in the top medical journals , or some combination thereof . Continued and exp and ed monitoring of potential conflicts is recommended , particularly in light of new guidelines for disclosure that have been endorsed by the ICMJE The evidence -based research of the effectiveness of homeopathic medicines in common immunologic disorders is review ed . In part 1 , we introduce method ological issues of clinical research in homeopathy , and criteria utilized to evaluate the literature . Then 24 studies ( 12 r and omized and 12 non-r and omized ) on common upper respiratory tract infections and otorhinolaryngologic complaints  are described . In part 2 , the focus will be on allergic diseases and the effectiveness of homeopathy will be globally evaluated and discussed using the criteria of evidence -based medicine We analysed 113 reports published in 1980 in a sample of medical journals to relate features of study design to the magnitude of gains attributed to new therapies over old . Overall we rated 87 per cent of new therapies as improvements over st and ard therapies . The mean gain ( measured by the Mann-Whitney statistic ) was relatively constant across study design s , except for non-r and omized controlled trials with sequential assignment to therapy , which showed a significantly higher likelihood that a patient would do better on the innovation than on st and ard therapy ( p = 0.004 ) . R and omized controlled trials that did not use a double-blind design had a higher likelihood of showing a gain for the innovation than did double-blind trials ( p = 0.02 ) . Any evaluation of an innovation may include both bias and the true efficacy of the new therapy , therefore we may consider making adjustments for the average bias associated with a study design . When interpreting an evaluation of a new therapy , readers should consider the impact of the following average adjustments to the Mann-Whitney statistic : for trials with non-r and om sequential assignment a decrease of 0.15 , for non-double-blind r and omized controlled trials a decrease of 0.11 Background Previous studies have assessed the validity of the observational study design by comparing results of studies using this design to results from r and omized controlled trials . The present study examined design features of observational studies that could have influenced these comparisons . Methods To find at least 4 observational studies that evaluated the same treatment , we review ed meta-analyses comparing observational studies and r and omized controlled trials for the assessment of medical treatments .  Details critical for interpretation of these studies were abstract 
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Some of these differences were due to a poorer prognosis in the control groups in the non-r and omised trials .
Comparisons of adequately and inadequately concealed allocation in r and omised trials of the same intervention provided high quality evidence that concealment can be crucial in achieving similar treatment groups and , therefore , unbiased estimates of treatment effects .
Studies with inadequate concealment tended to overestimate treatment effects .
Comparisons of high and low quality trials of the same intervention have found important differences in estimates of effect , but it is not possible to determine the extent to which these differences can be attributed to r and omisation or concealment of allocation .
Omitting comparisons between r and omised trials and non-r and omised trials using historical controls did not substantially alter the results or conclusions of our review .
On average , non-r and omised trials and r and omised trials with inadequate concealment of allocation tend to result in larger estimates of effect than r and omised trials with adequately concealed allocation .
However , it is not generally possible to predict the magnitude , or even the direction , of possible selection biases and consequent distortions of treatment effects