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: 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 Objective Cancer is one of the most common diagnoses in elderly patients . Of all types of abdominal cancer , colorectal cancer ( CRC ) is undoubtedly the most frequent . Median age at diagnosis is approximately 70 years old worldwide . Due to the multiple comorbidities affecting elderly people , frailty evaluation is very important in order to avoid over- or under-treatment . This pilot study was design ed to investigate the variables capable of predicting the long-term risk of mortality and living situation after surgery for CRC . Methods Patients with 70 years old and older undergoing elective surgery for CRC were prospect ively enrolled in the study . The patients were preoperatively screened using 11 internationally-vali date d-frailty- assessment tests . The endpoints of the study were long-term mortality and living situation . The data were analyzed using univariate Cox proportional-hazard regression analysis to verify the predictive value of score indices in order to identify possible risk factors . Results Forty-six patients were studied . The median follow-up time after surgery was 4.6 years ( range , 2.9 - 5.7 years ) and no patients were lost to follow-up . The overall mortality rate was 39 % . Four of the patients who survived ( 4/28 , 14 % ) lost their functional autonomy . The preoperative impaired Timed Up and Go ( TUG ) , Eastern Cooperative Group Performance Status ( ECOG PS ) , Instrumental Activities of Daily Living ( IADLs ) , Vulnerable Elders Survey ( VES-13 ) scoring systems were significantly associated with increased long term mortality risk . Conclusion Simplified frailty-assessing tools should be routinely used in elderly cancer patients before treatment in order to stratify patient risk . The TUG , ECOG-PS , IADLs and VES-13 scoring systems are potentially able to predict long-term mortality and disability . Additional studies will be needed to confirm the preliminary data in order to improve management strategies for oncogeriatric surgical patients BACKGROUND Screening tools are used in geriatric oncology to determine who should receive a Comprehensive Geriatric Assessment ( CGA ) . However , in this prospect i ve study , we evaluated the association between geriatric screening results , measured with the G8 and Groningen Frailty Indicator ( GFI ) , and severe treatment toxicity . METHODS Patients over 65 years with various types and stages of cancer were screened with the G8 and the GFI prior to the start of treatment . The association between geriatric screening results and Serious Adverse Events ( SAE ) after the first cycle of (radio)chemotherapy were studied with bivariate analysis ( normal versus abnormal screening test ) and logistic regression analysis . RESULTS From 170 screened patients , 85 patients were eligible for this study . The median age was 76 years ( range : 66 - 88 years ) . The treatment intent was curative in 46 % and palliative in 54 % . A SAE occurred in 15 patients ( 18 % ) of which three result ed in death . There was no significant association between the G8 , as a dichotomous predictor ( p = 0.376 ) or as a continuous predictor ( p = 0.298 ) , and risk of a SAE . We also found no significant association for the GFI analysed as a dichotomous predictor ( cut-off ≥4 : p = 0.384 ; cut-off ≥3 : p = 0.773 ) , nor as a continuous predictor ( p = 0.734 ) . All associations remained insignificant when adjusted for treatment type and comorbidity . CONCLUSION The G8 and the GFI can be used to select patients for CGA , but they do not seem to be predictive for short-term severe treatment toxicity Chemotherapy is associated with toxicity in elderly patients with potentially curable malignancies , posing the dilemma of whether to intensify therapy , thereby improving the cure rate , or de-escalate therapy , thereby reducing toxicity , with consequent risks for under- or overtreatment . Adequate tools to define doses and combinations have not been identified for lymphoma patients . We conducted a prospect i ve trial aim ed to evaluate the feasibility and efficacy of chemotherapy modulated according to a modified comprehensive geriatric assessment ( CGA ) in elderly ( aged ≥70 years ) patients with diffuse large B-cell lymphoma ( DLBCL ) . In June 2000 to March 2006 , 100 patients were stratified using a CGA into three groups ( fit , unfit , and frail ) , and they received a rituximab plus cyclophosphamide , doxorubicin , vincristine , and prednisone modulated in dose and drugs according to comorbidities and activities of daily living ( ADL ) and instrumental ADL scores . Treatment was associated with a complete response rate of 81 % and mild toxicity : grade 4 neutropenia in 14 % , anemia in 1 % , and neurological and cardiac toxicity in 2 % of patients . At a median follow-up of 64 months , 51 patients were alive , with 5-year disease-free , overall , and cause-specific survival rates of 80 % , 60 % , and 74 % , respectively . Chemoimmunotherapy adjustments based on a CGA are associated with manageable toxicity and excellent outcomes in elderly patients with DL 
    Output:
    
agent
All eight domains were predictive for at least one of the investigated outcomes but the results were quite variable across studies .
Physical function and nutritional status were the domains most often associated with mortality and systemic treatment-related outcomes , and the domain physical function was most often associated with postoperative complications .
Overall , this review demonstrates that the GA should minimally consist of physical function and nutritional status , when the aim is to predict patients -related outcomes of older patients with cancer , although the results are quite heterogeneous .
***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 Objective Cancer is one of the most common diagnoses in elderly patients . Of all types of abdominal cancer , colorectal cancer ( CRC ) is undoubtedly the most frequent . Median age at diagnosis is approximately 70 years old worldwide . Due to the multiple comorbidities affecting elderly people , frailty evaluation is very important in order to avoid over- or under-treatment . This pilot study was design ed to investigate the variables capable of predicting the long-term risk of mortality and living situation after surgery for CRC . Methods Patients with 70 years old and older undergoing elective surgery for CRC were prospect ively enrolled in the study . The patients were preoperatively screened using 11 internationally-vali date d-frailty- assessment tests . The endpoints of the study were long-term mortality and living situation . The data were analyzed using univariate Cox proportional-hazard regression analysis to verify the predictive value of score indices in order to identify possible risk factors . Results Forty-six patients were studied . The median follow-up time after surgery was 4.6 years ( range , 2.9 - 5.7 years ) and no patients were lost to follow-up . The overall mortality rate was 39 % . Four of the patients who survived ( 4/28 , 14 % ) lost their functional autonomy . The preoperative impaired Timed Up and Go ( TUG ) , Eastern Cooperative Group Performance Status ( ECOG PS ) , Instrumental Activities of Daily Living ( IADLs ) , Vulnerable Elders Survey ( VES-13 ) scoring systems were significantly associated with increased long term mortality risk . Conclusion Simplified frailty-assessing tools should be routinely used in elderly cancer patients before treatment in order to stratify patient risk . The TUG , ECOG-PS , IADLs and VES-13 scoring systems are potentially able to predict long-term mortality and disability . Additional studies will be needed to confirm the preliminary data in order to improve management strategies for oncogeriatric surgical patients BACKGROUND Screening tools are used in geriatric oncology to determine who should receive a Comprehensive Geriatric Assessment ( CGA ) . However , in this prospect i ve study , we evaluated the association between geriatric screening results , measured with the G8 and Groningen Frailty Indicator ( GFI ) , and severe treatment toxicity . METHODS Patients over 65 years with various types and stages of cancer were screened with the G8 and the GFI prior to the start of treatment . The association between geriatric screening results and Serious Adverse Events ( SAE ) after the first cycle of (radio)chemotherapy were studied with bivariate analysis ( normal versus abnormal screening test ) and logistic regression analysis . RESULTS From 170 screened patients , 85 patients were eligible for this study . The median age was 76 years ( range : 66 - 88 years ) . The treatment intent was curative in 46 % and palliative in 54 % . A SAE occurred in 15 patients ( 18 % ) of which three result ed in death . There was no significant association between the G8 , as a dichotomous predictor ( p = 0.376 ) or as a continuous predictor ( p = 0.298 ) , and risk of a SAE . We also found no significant association for the GFI analysed as a dichotomous predictor ( cut-off ≥4 : p = 0.384 ; cut-off ≥3 : p = 0.773 ) , nor as a continuous predictor ( p = 0.734 ) . All associations remained insignificant when adjusted for treatment type and comorbidity . CONCLUSION The G8 and the GFI can be used to select patients for CGA , but they do not seem to be predictive for short-term severe treatment toxicity Chemotherapy is associated with toxicity in elderly patients with potentially curable malignancies , posing the dilemma of whether to intensify therapy , thereby improving the cure rate , or de-escalate therapy , thereby reducing toxicity , with consequent risks for under- or overtreatment . Adequate tools to define doses and combinations have not been identified for lymphoma patients . We conducted a prospect i ve trial aim ed to evaluate the feasibility and efficacy of chemotherapy modulated according to a modified comprehensive geriatric assessment ( CGA ) in elderly ( aged ≥70 years ) patients with diffuse large B-cell lymphoma ( DLBCL ) . In June 2000 to March 2006 , 100 patients were stratified using a CGA into three groups ( fit , unfit , and frail ) , and they received a rituximab plus cyclophosphamide , doxorubicin , vincristine , and prednisone modulated in dose and drugs according to comorbidities and activities of daily living ( ADL ) and instrumental ADL scores . Treatment was associated with a complete response rate of 81 % and mild toxicity : grade 4 neutropenia in 14 % , anemia in 1 % , and neurological and cardiac toxicity in 2 % of patients . At a median follow-up of 64 months , 51 patients were alive , with 5-year disease-free , overall , and cause-specific survival rates of 80 % , 60 % , and 74 % , respectively . Chemoimmunotherapy adjustments based on a CGA are associated with manageable toxicity and excellent outcomes in elderly patients with DL 
    Output:
    