***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: In the evaluation of a diagnostic imaging test for the diagnosis of a particular illness in a particular category of patients , the test should be construed as leading to a test result in the sense of a set of descriptive readings from the image(s ) , not interpretation of these ; and in the evaluation of the test , therefore , the first challenge is the translation of each test result ( set of readings ) into the corresponding probability that the illness is present . This interpretive translation should not be subjective , nor should it be based on an objective algorithm founded on clinical judgments . Instead , a suitable diagnostic probability function ( of the elements in the test result ) should be derived empirically by logistic regression analysis of suitable data . We illustrate this alternative outlook by re analysis of the data from the Prospect i ve Investigation of Pulmonary Embolism Diagnosis The performance of a predictive model is overestimated when simply determined on the sample of subjects that was used to construct the model . Several internal validation methods are available that aim to provide a more accurate estimate of model performance in new subjects . We evaluated several variants of split- sample , cross-validation and bootstrapping methods with a logistic regression model that included eight predictors for  30-day mortality after an acute myocardial infa rct ion . R and om sample s with a size between n = 572 and n = 9165 were drawn from a large data set ( GUSTO-I ; n = 40,830 ; 2851 deaths ) to reflect modeling in data sets with between 5 and 80 events per variable . Independent performance was determined on the remaining subjects . Performance measures included discriminative ability , calibration and overall accuracy . We found that split- sample analyses gave overly pessimistic estimates of performance , with large variability . Cross-validation on 10 % of the sample had low bias and low variability , but was not suitable for all performance measures . Internal validity could best be estimated with bootstrapping , which provided stable estimates with low bias . We conclude that split- sample validation is inefficient , and recommend bootstrapping for estimation of internal validity of a predictive logistic regression model Abstract Objective : To assess the extent to which different forms of summarising diagnostic test information influence general practitioners ' ability to estimate disease probabilities . Design : Controlled question naire study . Setting : Three Swiss conferences in continuous medical education . Participants : 263 general practitioners . Intervention : Question naire with multiple choice questions about terms of test accuracy and a clinical vignette with the results of a diagnostic test described in three different ways ( test result only , test result plus test sensitivity and specificity , test result plus the positive likelihood ratio presented in plain language ) . Main outcome measures : Doctors ' knowledge and application of terms of test accuracy and estimation of disease probability in the clinical vignette . Results : The correct definitions for sensitivity and predictive value were chosen by 76 % and 61 % of the doctors respectively , but only 22 % chose the correct answer for the post-test probability of a positive screening test . In the clinical vignette doctors given the test result only overestimated its diagnostic value ( median attributed likelihood ratio (aLR)=9.0 , against 2.54 reported in the literature ) . Providing the scan 's sensitivity and specificity reduced the overestimation ( median aLR=6.0 ) but to a lesser extent than simple wording of the likelihood ratio ( median aLR=3.0 ) . Conclusion : Most general practitioners recognised the correct definitions for sensitivity and positive predictive value but did not apply them correctly . Conveying test accuracy information in simple , non-technical language improved their ability to estimate disease probabilities accurately . What is already known on this topic Many doctors confuse the sensitivity of clinical tests and their positive predictive value Doctors tend to overestimate information derived from such tests and underestimate information from a patient 's clinical history Most primary research on diagnostic accuracy is reported using sensitivity and specificity or likelihood ratios What this study adds In a cohort of experienced Swiss general practitioners most were unable to interpret correctly numerical information on the diagnostic accuracy of a screening test When presented with a positive result alone they grossly overestimated its value Adding information on the test 's sensitivity and specificity moderated these overestimates , and expressing the same numerical information as a positive likelihood ratio in simple , non-technical language brought the estimates still closer to their true Each year 1.5 million patients are admitted to coronary-care units ( CCUs ) for suspected acute ischemic heart disease ; for half of these , the diagnosis is ultimately " ruled out . " In this study , conducted in the emergency rooms of six New Engl and hospitals ranging in type from urban teaching centers to rural nonteaching hospitals , we sought to develop a diagnostic aid to help emergency room physicians reduce the number of their CCU admissions of patients without acute cardiac ischemia . From data on 2801 patients , we developed a predictive instrument for use in a h and -held programmable calculator , which requires only 20 seconds to compute a patient 's probability of having acute cardiac ischemia . In a prospect i ve trial that included 2320 patients in the six hospitals , physicians ' diagnostic specificity for acute ischemia increased when the probability value determined by the instrument was made available to them . Rates of false-positive diagnosis decreased without any increase in rates of false-negative diagnosis . Among study patients with a final diagnosis of " not acute ischemia , " the number of CCU admissions decreased 30 per cent , without any increase in missed diagnoses of ischemia . The proportion of CCU admissions that represented patients without acute ischemia dropped from 44 to 33 per cent . Widespread use of this predictive instrument could reduce the number of CCU admissions in this country by more than 250,000 per year OBJECTIVE To determine the accuracy of ultrasound scan in the diagnosis of  endometrial hyperplasia and cancer in postmenopausal bleeding . DESIGN A prospect i ve diagnostic accuracy study ( 1996 - 97 ) . SETTING Minimal access surgical training centers in two large teaching hospitals . METHODS Ultrasound scan and outpatient endometrial sampling were performed on 96 patients with postmenopausal bleeding . Patients unable to have these outpatient procedures had a formal inpatient hysteroscopy and curettage .  Test performance characteristics were computed for ultrasound scan comparing its estimate of endometrial thickness with histologic diagnosis that served as a ' gold ' st and ard . OUTCOME MEASURES Accuracy of the ultrasonic endometrial thickness  was estimated using sensitivity , specificity and predictive values for binary data . For multilevel data , the diagnostic accuracy was computed using likelihood ratios ( LRs ) . An LR < decreased the probability that endometrial hyperplasia/cancer was present , whereas an LR > 1 increased the probability that such lesion was present . RESULTS Using endometrial thickness > or = 4 mm , the sensitivity of ultrasound to detect the endometrial malignancy was 92.9 % , the specificity was 500 % , and the positive and negative predictive values were 24.1 % and 97.6 % respectively . Analysis using likelihood ratio ( LR ) revealed that LR was 0.14 for endometrial thickness > or = 4.0 mm , 0.94 for endometrial thickness 4.1 - 9.0 mm , and 3.3 for endometrial thickness > 9.0 mm . CONCLUSION In women with postmenopausal bleeding , malignancy can probably be safely excluded if sonographic endometrial thickness is < or = 4.0 mm . However , the probability of endometrial hyperplasia/cancer is not particularly altered by the knowledge that endometrial thickness on scan is > 4.0 mm BACKGROUND Systematic review s that " compare " the accuracy of 2 or more tests often include different sets of studies for each test . PURPOSE To investigate the availability of direct comparative studies of test accuracy and to assess whether summary estimates of accuracy differ between meta-analyses of noncomparative and comparative studies . DATA SOURCES Systematic review s in any language from the Data base of Abstract s of Review s of Effects and the Cochrane Data base of Systematic Review s from 1994 to October 2012 . STUDY SELECTION 1 of 2 assessors selected review s that evaluated at least 2 tests and identified meta-analyses that included both noncomparative studies and comparative studies . DATA EXTRACTION 1 of 3 assessors extracted data about review and study characteristics and test performance . DATA SYNTHESIS 248 review s compared test accuracy ; of the 6915 studies , 2113 ( 31 % ) were comparative . Thirty-six review s ( with 52 meta-analyses ) had adequate studies to compare results of noncomparative and comparative studies by using a hierarchical summary receiver-operating characteristic meta-regression model for each test comparison . In 10 meta-analyses , noncomparative studies ranked tests in the opposite order of comparative studies . A total of 25 meta-analyses showed more than a 2-fold discrepancy in the relative diagnostic odds ratio between noncomparative and comparative studies . Differences in accuracy estimates between noncomparative and comparative studies were greater than expected by chance ( P < 0.001 ) . LIMITATION A paucity of comparative studies limited exploration of direction in bias . CONCLUSION Evidence derived from noncomparative studies often differs from that derived from comparative studies . Robustly design ed studies in which all patients receive all tests or are r and omly assigned to receive one or other of the tests should be more routinely undertaken and are preferred for evidence to guide test selection . PRIMARY FUNDING SOURCE National Institute for Health Research ( United Kingdom ) 
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Most primary accuracy studies lack statistical power to do this , particularly because of the small absolute number of disease events per test included in the diagnostic work .
Synthesis using their raw data can overcome this problem , but meta-analysts will have limited success if there are difficulties in obtaining the large majority of valid studies , without ' missing ' data on the tests relevant in clinical decision-making .