***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 To investigate the relationship between the expressions of KAI1 , nm23 , ETS-1 , vascular endothelial growth factor ( VEGF ) and microvascular density ( MVD ) and lymph node metastasis and prognosis in nasopharyngeal carcinoma ( NPC ) . METHODS The Envision immunohistochemical method was used to detect the expressions of KAI1 , nm23 , ETS-1 and VEGF in 50 cases of non-keratinizing carcinoma ( NKC ) with cervical lymph node metastasis , 30 cases of NKC without cervical lymph node metastasis at the primary diagnoses and 30 cases of non-tumor nasopharyngeal tissues ( NP ) . The microvascular density was counted by immunostaining with CD34 . RESULTS ( 1 ) The expression rates of KAI1 and nm23 protein in NKC with cervical lymph node metastasis group and without cervical lymph node metastasis group and NP group increased successively , the difference being significant ( P < 0.05 ) ; The expression rates of ETS-1 and VEGF protein in NKC with cervical lymph node metastasis group and without cervical lymph node metastasis group and NP group increased successively , the difference being significant ( P < 0.05 ) . ( 2 ) In 80 NKC cases , the MVD was respectively lower in KAI1 and nm23 protein positive groups than those in the negative groups ( P < 0.05 ) ; the MVD was respectively higher in ETS-1 and VEGF protein positive groups than those in the negative groups ( P < 0.05 ) . ( 3 ) There was significant difference between the MVD , the number of NKC without cervical lymph node metastasis cases in the single expression of KAI1 or nm23 protein and in common expression of KAI1 and nm23 protein ( P < 0.05 ) , in the same as between the single expression of ETS-1 or VEGF protein and in common expressions of ETS-1 and VEGF protein ( P < 0.05 ) . ( 4 ) There was positive correlation between the expressions of KAI1 and nm23 protein ( P < 0.01 ) , as well as between the expressions of ETS-1 and VEGF protein ( P < 0.01 ) . ( 5 ) the 5-year survival rates of the patients correlated with cervical lymph node metastasis and the expressions of KAI1 , nm23 , ETS-1 and VEGF proteins in NKC ( P < 0.05 ) . CONCLUSIONS The expressions of KAI1 , nm23 , ETS-1 and VEGF proteins were highly related to MVD in NPC , cervical lymph node metastasis and prognosis . They might be considered to be reference indicator for evaluating the cervical lymph node metastasis and prognosis of NPC BACKGROUND Current practice of adding concurrent-adjuvant chemotherapy to radiotherapy ( CRT ) for treating advanced nasopharyngeal carcinoma is based on the Intergroup-0099 Study published in 1998 . However , the outcome for the radiotherapy-alone ( RT ) group in that trial was substantially poorer than those in other trials , and there were no data on late toxicities . Verification of the long-term therapeutic index of this regimen is needed . METHODS Patients with nonkeratinizing nasopharyngeal carcinoma staged T1 - 4N2 - 3M0 were r and omly assigned to RT ( 176 patients ) or to CRT ( 172 patients ) using cisplatin ( 100 mg/m(2 ) ) every 3 weeks for three cycles in concurrence with radiotherapy , followed by cisplatin ( 80 mg/m(2 ) ) plus fluorouracil ( 1000 mg per m(2 ) per day for 4 days ) every 4 weeks for three cycles . Primary endpoints included overall failure-free rate ( FFR ) ( the time to first failure at any site ) and progression-free survival . Secondary endpoints included overall survival , locoregional FFR , distant FFR , and acute and late toxicity rates . All statistical tests were two-sided . RESULTS The two treatment groups were well balanced in all patient characteristics , tumor factors , and radiotherapy parameters . Adding chemotherapy statistically significantly improved the 5-year FFR ( CRT vs RT : 67 % vs 55 % ; P = .014 ) and 5-year progression-free survival ( CRT vs RT : 62 % vs 53 % ; P = .035 ) . Cumulative incidence of acute toxicity increased with chemotherapy by 30 % ( CRT vs RT : 83 % vs 53 % ; P < .001 ) , but the 5-year late toxicity rate did not increase statistically significantly ( CRT vs RT : 30 % vs 24 % ; P = .30 ) . Deaths because of disease progression were reduced statistically significantly by 14 % ( CRT vs RT : 38 % vs 24 % ; P = .008 ) , but 5-year overall survival was similar ( CRT vs RT : 68 % vs 64 % ; P = .22 ; hazard ratio of CRT = 0.81 ,  
    Output:
    
Conclusion : The low expression of nm23-H1 is associated with poorer prognosis in patients with NPC , suggesting that it is a prognostic factor and potential biomarker for survival in NPC