***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: Prognosis studies are investigations of future events or the evaluation of associations between risk factors and health outcomes in population s of patients ( 1 ) . The results of such studies improve our underst and ing of the clinical course of a disease and assist clinicians in making informed decisions about how best to manage patients . Prognostic research also informs the design of intervention studies by helping define subgroups of patients who may benefit from a new treatment and by providing necessary information about the natural history of a disorder ( 2 ) . There has recently been a rapid increase in the use of systematic review methods to synthesize the evidence on research questions related to prognosis . It is essential that investigators conducting systematic review s thoroughly appraise the method ologic quality of included studies to be confident that a study 's design , conduct , analysis , and interpretation have adequately reduced the opportunity for bias ( 3 , 4 ) . Caution is warranted , however , because inclusion of method ologically weak studies can threaten the internal validity of a systematic review ( 4 ) . This follows abundant empirical evidence that inadequate attention to biases can cause invalid results and inferences ( 5 - 9 ) . However , there is limited consensus on how to appraise the quality of prognosis studies ( 1 ) . A useful framework to assess bias in such studies follows the basic principles of epidemiologic research ( 10 , 11 ) . We focus on 6 areas of potential bias : study participation , study attrition , prognostic factor measurement , confounding measurement and account , outcome measurement , and analysis . The main objectives of our review of review s are to describe methods used to assess the quality of prognosis studies and to describe how well current practice s assess potential biases . Our secondary objective is to develop recommendations to guide future quality appraisal , both within single studies of prognostic factors and within systematic review s of the evidence . We hope this work facilitates future discussion and research on biases in prognosis studies and systematic review s. Methods Literature Search and Study Selection We identified systematic review s of prognosis studies by search ing MEDLINE ( 1966 to October 2005 ) using the search strategy recommended by McKibbon and colleagues ( 12 ) . This strategy combines broad search terms for systematic review s ( systematic review .mp ; meta- analysis .mp ) and a sensitive search strategy for prognosis studies ( cohort , incidence , mortality , follow-up studies , prognos * , predict * , or course ) . We also search ed the reference lists of included review s and method ologic papers to identify other relevant publications . We restricted our search to English- language publications . One review er conducted the search and selected the studies . Systematic review s , defined as review s of published studies with a comprehensive search and systematic selection , were included if they assessed the method ologic quality of the included studies by using 1 or more explicit criteria . We excluded studies if they were meta-analyses of independent patient data only , if their primary goal was to investigate the effectiveness of an intervention or specific diagnostic or screening tests , or if they included studies that were not done on humans . Data Extraction and Synthesis Individual items included in the quality assessment of the systematic review s were recorded as they were reported in the publication ( that is , the information that would be available to readers and future review ers ) . We review ed journal Web sites and contacted the authors of the systematic review s for additional information when authors made such an offer in their original papers . When review s assessed different study design s by using different sets of quality items , we extracted only those items used to assess cohort studies . We constructed a comprehensive list of distinct items that the review s used to assess the quality of their included studies . The full text of each review was screened . All items used by the review authors to assess the quality of studies were extracted into a computerized spreadsheet by 1 review er . Two experienced review ers , a clinical epidemiologist and an epidemiologist , independently synthesized the quality items extracted from the prognosis review s to determine how well the systematic review s assessed potential biases . We did this in 3 steps : 1 ) identified distinct concepts or domains addressed by the quality items ; 2 ) grouped each extracted quality item into the appropriate domain or domains ; and 3 ) identified the domains necessary to assess potential biases in prognosis studies . We then used this information to assess how well the review s ' quality assessment included items from the domains necessary to assess potential biases . After completing each of the first 3 steps , the review ers met to attempt to reach a consensus . The consensus process involved each review er presenting his or her observations and results , followed by discussion and debate . A third review er was available in cases of persistent disagreement or uncertainty . In the first step , all domains addressed by the quality items were identified . The first review er iteratively and progressively defined the domains as items were extracted from the included review s. The second review er defined domains from a r and om list of all extracted quality items . Limited guidance was provided to the review ers so that their assessment s and definitions of domains would be independent . The review ers agreed on a final set of domains that adequately and completely defined all of the extracted items . In the second step , review ers independently grouped each extracted item into the appropriate domains . Review ers considered each extracted item by asking , What is each particular quality item addressing ? or What are the review 's authors getting at with the particular quality assessment item ? . Items were grouped into the domain or domains that best represented the concepts being addressed . For example , the extracted items at least 80 % of the group originally identified was located for follow-up and follow-up was sufficiently complete or does n't jeopardize validity were each independently classified by both review ers as assessing the domain completeness of follow-up adequate , whereas the extracted item quantification and description of all subjects lost to follow-up was classified as assessing the domain completeness of follow-up described . In the third step , we identified the domains necessary to assess potential biases . Each review er considered the ability of the identified domains to adequately address , at least in part , 1 of the following 6 potential biases : 1 ) study participation , 2 ) study attrition , 3 ) prognostic factor measurement , 4 ) confounding measurement and account , 5 ) outcome measurement , and 6 ) analysis . Domains were considered to adequately address part of the framework if information garnered from that domain would inform the assessment of potential bias . For example , both review ers judged that the identified domain study population represents source population or population of interest assessed potential bias in a prognosis study , whereas the domain research question definition did not , although the latter is an important consideration in assessing the inclusion of studies in a systematic review . Finally , on the basis of our previous ratings , we looked at whether each review included items from the domains necessary to assess the 6 potential biases . We calculated the frequency of systematic review s by assessing each potential bias and the number of review s that adequately assessed bias overall . From this systematic synthesis , we developed recommendations for improving quality appraisal in future systematic review s of prognosis studies . We used Microsoft Access and Excel 2002 ( Microsoft Corp. , Redmond , Washington ) for data management and SAS for Windows , version 9.1 ( SAS Institute , Inc. , Cary , North Carolina ) for descriptive statistics . Role of the Funding Sources The funding sources , the Canadian Institutes of Health Research , the Canadian Chiropractic Research Foundation , the Ontario Chiropractic Association , and the Ontario Ministry of Health and Long Term Care , did not have a role in the collection , analysis , or interpretation of the data or in the decision to su bmi t the manuscript for publication . Results We identified 1384 potentially relevant articles . Figure 1 shows a flow chart of studies that were included and excluded . Figure 2 shows the number of review s identified by year of publication . We excluded 131 systematic review s of prognosis studies that did not seem to include any quality assessment of the included studies ; this represented 44 % of prognosis review s. We included 163 review s of prognosis studies in our analysis ( 13 - 175 ) . The most common topics were cancer ( 15 % ) , musculoskeletal disorders and rheumatology ( 13 % ) , cardiovascular ( 10 % ) , neurology ( 10 % ) , and obstetrics ( 10 % ) . Other review s included a wide range of health and health care topics . Sixty-three percent of the review s investigated the association between a specific prognostic factor and a particular outcome ; the remainder investigated multiple prognostic factors or models . The number of primary studies included in each systematic review ranged from 3 to 167 ( median , 18 [ interquartile range , 12 to 31 ] ) . A complete description of the included review s is available from the authors on request . Figure 1 . Flow diagram of inclusion and exclusion criteria of systematic review s. Figure 2 . Number of systematic review s of prognosis studies identified over time . Quality Items One hundred fifty-three review s provided adequate detail to allow extraction of quality items . Eight hundred eighty-two distinct quality items were extracted from the review s. Most review s developed their own set of quality items , with only a few applying criteria from previous review s. Most quality items BACKGROUND Previous studies showing that tiotropium improves multiple end points in patients with chronic obstructive pulmonary disease ( COPD ) led us to examine the long-term effects of tiotropium therapy . METHODS In this r and omized , double-blind trial , we compared 4 years of therapy with either tiotropium or placebo in patients with COPD who were permitted to use all respiratory medications except inhaled anticholinergic drugs . The patients were at least 40 years of age , with a forced expiratory volume in 1 second ( FEV(1 ) ) of 70 % or less after bronchodilation and a ratio of FEV(1 ) to forced vital capacity ( FVC ) of 70 % or less . Co primary end points were the rate of decline in the mean FEV(1 ) before and after bronchodilation beginning on day 30 . Secondary end points included measures of FVC , changes in response on St. George 's Respiratory Question naire ( SGRQ ) , exacerbations of COPD , and mortality . RESULTS Of a total of 5993 patients ( mean age , 65+/-8 years ) with a mean FEV(1 ) of 1.32+/-0.44 liters after bronchodilation ( 48 % of predicted value ) , we r and omly assigned 2987 to the tiotropium group and 3006 to the placebo group . Mean absolute improvements in FEV(1 ) in the tiotropium group were maintained throughout the trial ( ranging from 87 to 103 ml before bronchodilation and from 47 to 65 ml after bronchodilation ) , as compared with the placebo group ( P<0.001 ) . After day 30 , the differences between the two groups in the rate of decline in the mean FEV(1 ) before and after bronchodilation were not significant . The mean absolute total score on the SGRQ was improved ( lower ) in the tiotropium group , as compared with the placebo group , at each time point throughout the 4-year period ( ranging from 2.3 to 3.3 units , P<0.001 ) . At 4 years and 30 days , tiotropium was associated with a reduction in the risks of exacerbations , related hospitalizations , and respiratory failure . CONCLUSIONS In patients with COPD , therapy with tiotropium was associated with improvements in lung function , quality of life , and exacerbations during a 4-year period but did not significantly reduce the rate of decline in FEV(1 ) . ( Clinical Trials.gov number , NCT00144339 . Background Forced expiratory volume in one second ( FEV1 ) is used to diagnose and establish a prognosis in chronic obstructive pulmonary disease ( COPD ) . Using multi-dimensional scores improves this predictive capacity . Two instruments , the BODE-index ( Body mass index , Obstruction , Dyspnea , Exercise capacity ) and the HADO-score ( Health , Activity , Dyspnea , Obstruction ) , were compared in the prediction of mortality among COPD patients . Methods This is a prospect i ve longitudinal study . During one year ( 2003 to 2004 ) , 543 consecutively COPD patients were recruited in five outpatient clinics and followed for three years . The endpoints were all-causes and respiratory mortality . Results In the multivariate analysis of patients with FEV1 < 50 % , no significant differences were observed in all-cause or respiratory mortality across HADO categories , while significant differences were observed between patients with a lower BODE ( less severe disease ) and those with a higher BODE ( greater severity ) . Among patients with FEV1 ≥ 50 % , statistically significant differences were observed across HADO categories for all-cause and respiratory mortality , while differences were observed across BODE categories only in all-cause mortality . Conclusions HADO-score and BODE-index were good predictors of all-cause and respiratory mortality in the entire cohort . In patients with severe COPD ( FEV1 < 50 % ) the BODE index was a better predictor of mortality whereas in patients with mild or moderate COPD ( FEV1 ≥ 50 % ) , the HADO-score was as good a predictor of respiratory mortality as the BODE-index . These differences suggest that the HADO-score and BODE-index could be used for different patient population s and at different healthcare levels , but can be used complementarily The Global Initiative for Chronic Obstructive Lung Disease ( GOLD ) serves as a guide to treat and manage different severity classes of patients with COPD . It was suggested that the five categories of FEV1 % predicted ( GOLD 0–4 ) , can be applied for selecting different therapeutic approaches . However , validation of these selective properties is very poor . To determine the relevance of the GOLD staging system for estimating the severity of clinical problems , GOLD 2 ( n=70 ) and GOLD 3 ( n=65 ) patients were drawn from a prospect i ve cohort of patients with COPD and evaluated crosssectionally by a newly developed Nijmegen Integral Assessment Framework ( NIAF ) . The NIAF is a detailed assessment of a wide range of aspects of health status ( HS ) . Significant , though small , differences were found in Static Lung Volumes , Exercise Capacity , Subjective Pulmonary Complaints , Subjective Impairment , and Health-Related QoL , besides Airflow of 
    Output:
    
Consistent strong predictors were FEV1 percentage predicted , age and dyspnoea .
Although the prognostic performance of some of the indices has been vali date d , they all lack sufficient evidence for implementation .