human
***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: STUDY DESIGN Prospect i ve inception cohort study . OBJECTIVE To develop a prognostic model that predicts time receiving  workers ' compensation benefits for low back pain cl aim ants . SUMMARY OF BACKGROUND DATA As the cost and difficulty of managing low back pain escalate , any predictor of outcome is advantageous . METHODS To obtain the outcome and predictor variables , patient data from two separate data bases were linked : a clinical data base and an administrative ( Ontario workers ' compensation ) data base . Cl aim ants injured between January 1 and December 31 , 1994 , were included and observed for 1 year from the date of accident . The outcome variable was cumulative number of calendar days receiving benefits . RESULTS Multivariable Cox proportional hazards regression ( forward stepwise ) showed eight significant predictors ; five were associated with increased time receiving benefits compared with their reference groups : 1 ) working in the construction industry , 2 ) older age , 3 ) lag time from injury to treatment , 4 )  pain referred into the leg  , and 5 ) three or more positive Waddell nonorganic signs . Three predictors were associated with reduced time receiving benefits : 1 ) higher values of question naire score , 2 ) intermittent pain , and 3 ) a previous episode of back pain . A predictive score was calculated to categorize cl aim ants as at high or low risk for chronicity . When an arbitrary cutoff point was set at the 75th percentile of predictive score , negative predictive value was 94 % . CONCLUSION This research identified eight factors for time receiving workers ' compensation benefits among cl aim ants with low back pain . This model discriminates between high- and low-risk cl aim ants . Few low-risk cl aim ants continued to receive benefits for more than 3 months 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 Study Design . A prospect i ve clinical trial was conducted that involved six groups of patients with chronic low back pain selected from a large cohort ( N = 816 ) . Objectives . To correlate pretreatment baseline variables with outcome parameters after treatment in a functional restoration program or in control programs , to identify possible factors predictive of the need for functional restoration . Summary of Background Data . Since the functional restoration program was first described , research has focused on identifying patients who will or will not benefit from such a program . The value of previous studies is limited , however , because predictive factors from a control group were not " subtracted . " Methods . Eight hundred sixteen patients with chronic low back disability were included . All had a structured medical examination , including various physical tests before participation in either a functional restoration program ( n = 621 ) or shorter " control " outpatient programs ( n = 144 ) . A smaller group of the cohort ( n = 51 ) had no treatment and served as a pure control group . Six groups were selected from the cohort : Three underwent an identical functional restoration program and three underwent different outpatient control programs . Several baseline demographic , physical , and socioeconomic variables were correlated to 1‐year outcome parameters . Results . Age , days of sick leave , connection to the work force , and back pain intensity , were significantly correlated to success 1 year after entry into the study in all groups , no matter what kind of treatment was administered . Back muscle endurance , sports activity , activity of daily living scores , and vibrations were of importance in some outcome parameters for success after functional restoration . Smoking was positively correlated to disability pension . Days of sick leave and , in functional restoration , ability to work were the only factors that were correlative with statistics for people who withdrew . Conclusions . Different factors can be identified as predictive of outcome in a functional restoration program , but most of these factors were also shown to predict success for shorter control outpatient programs or of no treatment Many manual therapists assess and treat spinal stiffness of people with low back pain . The objectives of this study were to investigate : ( i ) whether spinal stiffness changes after treatment ; ( ii ) the relationship between pre-treatment spinal stiffness and change in stiffness with treatment ; ( iii ) the relationship between spinal stiffness , pain , disability and global perceived effect of treatment ; ( iv ) whether spinal stiffness predicts outcome of treatment or response to treatment in chronic low back pain patients . One hundred and ninety-one subjects with chronic low back pain were r and omly allocated to groups that received either spinal manipulative therapy , motor control exercise , or a general exercise program . Spinal stiffness  was assessed before and after intervention . All three groups showed a significant decrease in stiffness following treatment ( p<0.001 ) . No difference between groups was observed . There was a significant negative correlation between pre-treatment stiffness and change in stiffness ( r=-0.61 ; p<0.001 ) . There was a significant but weak correlation ( r=0.18 ; p=0.02 ) between change in stiffness and change in global perceived effect of treatment , and a significant but weak correlation between change in stiffness and change in function for subjects in the spinal manipulative therapy group ( r=-0.28 ; p=0.02 ) . No significant association was observed between initial stiffness score and any of the final outcome measures following treatment . Initial stiffness did not predict response to any treatment . In conclusion , spinal stiffness decreases over the course of an episode of treatment , more so in those with the stiffest spines , but the decrease is not dependent on treatment and is not generally related to outcome Study Design Two-hundred-forty-three patients with chronic low back pain were studied in a prospect i ve comparative survey to determine whether the “ central ization phenomenon ” was associated with outcome after an interdisciplinary work-hardning program . Objective The hypothesis was that patients who demonstrated 
    Output:
    
agent
Conclusions For most clinical tests in LBP there is not consistent evidence for an association with outcome .
Central ization and non-organic signs are exceptions from that .
***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: STUDY DESIGN Prospect i ve inception cohort study . OBJECTIVE To develop a prognostic model that predicts time receiving  workers ' compensation benefits for low back pain cl aim ants . SUMMARY OF BACKGROUND DATA As the cost and difficulty of managing low back pain escalate , any predictor of outcome is advantageous . METHODS To obtain the outcome and predictor variables , patient data from two separate data bases were linked : a clinical data base and an administrative ( Ontario workers ' compensation ) data base . Cl aim ants injured between January 1 and December 31 , 1994 , were included and observed for 1 year from the date of accident . The outcome variable was cumulative number of calendar days receiving benefits . RESULTS Multivariable Cox proportional hazards regression ( forward stepwise ) showed eight significant predictors ; five were associated with increased time receiving benefits compared with their reference groups : 1 ) working in the construction industry , 2 ) older age , 3 ) lag time from injury to treatment , 4 )  pain referred into the leg  , and 5 ) three or more positive Waddell nonorganic signs . Three predictors were associated with reduced time receiving benefits : 1 ) higher values of question naire score , 2 ) intermittent pain , and 3 ) a previous episode of back pain . A predictive score was calculated to categorize cl aim ants as at high or low risk for chronicity . When an arbitrary cutoff point was set at the 75th percentile of predictive score , negative predictive value was 94 % . CONCLUSION This research identified eight factors for time receiving workers ' compensation benefits among cl aim ants with low back pain . This model discriminates between high- and low-risk cl aim ants . Few low-risk cl aim ants continued to receive benefits for more than 3 months 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 Study Design . A prospect i ve clinical trial was conducted that involved six groups of patients with chronic low back pain selected from a large cohort ( N = 816 ) . Objectives . To correlate pretreatment baseline variables with outcome parameters after treatment in a functional restoration program or in control programs , to identify possible factors predictive of the need for functional restoration . Summary of Background Data . Since the functional restoration program was first described , research has focused on identifying patients who will or will not benefit from such a program . The value of previous studies is limited , however , because predictive factors from a control group were not " subtracted . " Methods . Eight hundred sixteen patients with chronic low back disability were included . All had a structured medical examination , including various physical tests before participation in either a functional restoration program ( n = 621 ) or shorter " control " outpatient programs ( n = 144 ) . A smaller group of the cohort ( n = 51 ) had no treatment and served as a pure control group . Six groups were selected from the cohort : Three underwent an identical functional restoration program and three underwent different outpatient control programs . Several baseline demographic , physical , and socioeconomic variables were correlated to 1‐year outcome parameters . Results . Age , days of sick leave , connection to the work force , and back pain intensity , were significantly correlated to success 1 year after entry into the study in all groups , no matter what kind of treatment was administered . Back muscle endurance , sports activity , activity of daily living scores , and vibrations were of importance in some outcome parameters for success after functional restoration . Smoking was positively correlated to disability pension . Days of sick leave and , in functional restoration , ability to work were the only factors that were correlative with statistics for people who withdrew . Conclusions . Different factors can be identified as predictive of outcome in a functional restoration program , but most of these factors were also shown to predict success for shorter control outpatient programs or of no treatment Many manual therapists assess and treat spinal stiffness of people with low back pain . The objectives of this study were to investigate : ( i ) whether spinal stiffness changes after treatment ; ( ii ) the relationship between pre-treatment spinal stiffness and change in stiffness with treatment ; ( iii ) the relationship between spinal stiffness , pain , disability and global perceived effect of treatment ; ( iv ) whether spinal stiffness predicts outcome of treatment or response to treatment in chronic low back pain patients . One hundred and ninety-one subjects with chronic low back pain were r and omly allocated to groups that received either spinal manipulative therapy , motor control exercise , or a general exercise program . Spinal stiffness  was assessed before and after intervention . All three groups showed a significant decrease in stiffness following treatment ( p<0.001 ) . No difference between groups was observed . There was a significant negative correlation between pre-treatment stiffness and change in stiffness ( r=-0.61 ; p<0.001 ) . There was a significant but weak correlation ( r=0.18 ; p=0.02 ) between change in stiffness and change in global perceived effect of treatment , and a significant but weak correlation between change in stiffness and change in function for subjects in the spinal manipulative therapy group ( r=-0.28 ; p=0.02 ) . No significant association was observed between initial stiffness score and any of the final outcome measures following treatment . Initial stiffness did not predict response to any treatment . In conclusion , spinal stiffness decreases over the course of an episode of treatment , more so in those with the stiffest spines , but the decrease is not dependent on treatment and is not generally related to outcome Study Design Two-hundred-forty-three patients with chronic low back pain were studied in a prospect i ve comparative survey to determine whether the “ central ization phenomenon ” was associated with outcome after an interdisciplinary work-hardning program . Objective The hypothesis was that patients who demonstrated 
    Output:
    