***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 For the case of pharyngeal carcinomas , the clinical value as well as the stability of several evaluation methods of MR tomographic perfusion measurement are compared . Eighteen patients suffering from histologically proven squamous cell carcinomas were investigated by MR tomography ( 1.5 T , 0.2 mmol/kg Gd‐DTPA ) prior to and during radiation therapy . Perfusion measurements were performed using a double‐echo FLASH sequence . Parameters describing regional blood flow , blood volume , mean transit time , and interstitial concentration of contrast medium ( CM ) were calculated , applying seven different combinations of correction approaches ( separating the shortening of T1 and T2∗ , arterial input function ( AIF ) , and tumor shunts ) . Their correlations to MR independent tumor physiological parameters were analyzed ( metabolic activity measurements using 18F‐FDG‐PET , polarographical pO2 measurement , tumor volume ) . Significant improvements of the correlation between perfusion‐dependent and other tumor physiological parameters could be achieved by decoupling the shortening of T1 and T2∗ and by applying of the tumor shunt model . Deconvolution from the AIF deteriorated the correlation . Therefore , the elimination of the T1 shortening due to interstitial CM proves to be essential for MR perfusion measurements on contrast medium uptaking lesions . Depending on the measurement conditions ( temporal resolution , signal‐to‐noise ratio ) , the consideration of the AIF can even make the results significantly worse by introducing additional measuring errors . PACS numbers : The role of pretreatment dynamic contrast-enhanced perfusion MR imaging ( DCE-PWI ) and diffusion-weighted MR imaging ( DWI ) in predicting the treatment response of oropharyngeal or hypopharyngeal squamous cell carcinoma ( OHSCC ) to chemoradiation remains unclear . We prospect ively investigated the ability of pharmacokinetic parameters derived from pretreatment DCE-PWI and DWI to predict the local control of OHSCC patients treated with chemoradiation . Between August , 2010 and March , 2012 , patients with untreated OHSCC scheduled for chemoradiation were eligible for this prospect i ve study . DCE-PWI and DWI were performed in addition to conventional MRI . The relationship of local control with the following clinical and imaging variables was analyzed : the hemoglobin level , T-stage , tumor location , gross tumor volume , maximum st and ardized uptake value , metabolic tumor volume and total lesion glycolysis on FDG PET/CT , transfer constant ( K trans ) , volume of blood plasma and volume of extracellular extravascular space on DCE-PWI , and apparent diffusion coefficient on DWI of the primary tumor . The patients were also divided into a local control group and a local failure group , and their clinical and imaging parameters were compared . There were 58 patients ( 29 with oropharynx squamous cell carcinoma [ SCC ] and 29 with hypopharynx SCC ) with successful pretreatment DCE-PWI and DWI available for analysis . After a median follow-up of 18.2 months , 17 ( 29.3 % ) participants had local failure , whereas the remaining 41 patients achieved local control . Univariate analysis revealed that only the K trans value was significantly associated with local control ( P = 0.03 ) . When the local control and local failure groups were compared , significant differences were observed in K trans and the tumor location ( P = 0.01 and P = 0.04 , respectively ) . In the multivariable analysis , only K trans was statistically significant ( P = 0.04 ) . Our results suggest that pretreatment K trans may help predict the local control in OHSCC patients treated with chemoradiation PURPOSE To evaluate whether a pharmacokinetic analysis is useful for monitoring the response of oral cancer to  chemoradiotherapy ( CRT ) . MATERIAL S AND METHODS Twenty-nine patients were included . They underwent dynamic contrast-enhanced magnetic resonance imaging ( DCE-MRI ) before and after CRT . The DCE-MRI data were analyzed using a Tofts and Kermode ( TK ) model . The histological evaluation of the effects of CRT was performed according to Ohboshi and Shimosato 's classification . RESULTS None of the pre-CRT parameters were significantly different between the responders and nonresponders . The post-CRT volume of the extravascular extracellular space ( EES ) per unit volume of tissue ( v(e ) ) of responders ( 0.397 ± 0.080 ) was higher than that of nonresponders ( 0.281 ± 0.076 ) ( P = 0.01 ) . The change of the v(e ) between the pre- and post-CRT of the responders ( 0.154 ± 0.093 ) was larger than that of the nonresponders ( 0.033 ± 0.073 ) ( P = 0.001 ) . Therefore , the increase in the v(e ) strongly suggested a good tumor response to CRT , which reflected an increase of the EES secondary to the destruction of the cancer nest . The changes in the volume transfer constant ( K(trans ) ) were significantly different between the responders and nonresponders ( P = 0.018 ) . CONCLUSION Both the increase of the v(e ) and the elevation of permeability ( K(trans ) ) were indicative of a good tumor response to CRT . The pharmacokinetic analysis had potential for monitoring the histop 
    Output:
    
Perfusion-weighted MRI shows potential in some aspects of diagnosing HNSCC and predicting prognosis .