***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: To analyze the clinical characteristics and prognostic factors in patients with glioma in an academic institute in China . From October 2004 to August 2010 , total 1,285 patients were diagnosed as glioma at the Glioma Center of Beijing Tiantan Hospital . Clinical and molecular pathology features and survival rates were analyzed . The median overall survival ( OS ) times were 78.1 , 37.6 and 14.4 months for low- grade glioma ( WHO grade II ) , anaplastic glioma ( WHO grade III ) and glioblastoma ( WHO grade IV ) , respectively . In patients with low- grade glioma , age , preoperative Karnofsky performance scale ( KPS ) , pathological type , radiotherapy , O6-methylguanine-DNA methyltransferase ( MGMT ) expression and Ki-67 expression , were significantly associated with OS in multivariate analyses ; and preoperative KPS and radiotherapy were significantly associated with progression-free survival ( PFS ) . For anaplastic gliomas , age , preoperative KPS , pathological type , extent of resection , radiotherapy , p53 expression and phosphatase and tensin homolog ( PTEN ) expression were associated with OS . For glioblastomas , age , preoperative KPS , pathology type , extent of resection , radiotherapy and chemotherapy were associated with OS ; and age , gender , preoperative KPS , extent of resection , radiotherapy and chemotherapy were associated with PFS . This is the largest survey for glioma management in China to date . We found significant differences in age , presenting symptoms and the expression of p53 , MGMT , PTEN , and Ki-67 among patients with different types of glioma . Age , preoperative KPS , tumor grade s ,  radiotherapy , chemotherapy and Ki-67 expression were significantly associated with clinical prognosis Abstract . The purpose of this study was to determine whether a relationship existed between MIB-1 labeling index ( LI ) percentages and survival in patients with grade II astrocytomas . From archival paraffin-embedded surgical specimens of 50 patients of the University of Michigan Medical Center with World Health Organization grade II astrocytomas , 22 patients had a Ki-67 LI of less than or equal to 2.0 ; and 28 patients had a MIB-1 LI of more than 2.0 . Over a median follow-up interval of 10 years , ranging up to 16 years , 23 % ( n = 5 ) died of tumor in the first group while 82 % ( n = 23 ) died in the second group , a distinct difference in survival between these groups . Univariate analysis showed that a high MIB-1 predicted shorter survival ( p < 0.0001 ) , and that increased age was associated with shorter survival ( p = 0.007 ) . Gender , tumor location and radiotherapy had no significant association with survival . When adjusting for these ( excluding tumor location ) in the Cox proportional hazards model simultaneously , MIB-1 and age were independently prognostic . The hazard ratios were 1.301 per 1 % MIB-1 LI ( p = 0.0001 ) , and 1.045 per year of age ( p = 0.0028 ) . From other studies , we know that histopathologic grade and age predict survival for glioma patients . However , even within grade II astrocytomas there is still a wide heterogeneity in how long a patient survives . We conclude that among grade II astrocytomas older patients and , independently , patients with higher MIB-1 labeling index have shorter survival Aims and background Glioblastoma multiforme is the most common and most malignant primary brain tumor in adults . The current st and ard of care for glioblastoma is surgical resection to the extent feasible , followed by adjuvant radiotherapy plus temozolomide , given concomitantly with and after radiotherapy . This report is a prospect i ve observational study of 43 cases treated in the Department of Radiotherapy , University of Rome La Sapienza , Italy . We examine the relationship between pathologic features and objective response rate in adult patients treated with concomitant radiation plus temozolomide  to identify clinical , neuroradiologic , pathologic , and molecular factors with prognostic significance . Methods Forty-three consecutive patients ( 24 males and 19 females ) , ages 15 - 77 years ( median , 57 ) with newly diagnosed glioblastoma multiforme , were included in this trial between 2002 and 2004 at our department . All patients were treated with surgery ( complete resection in 81 % , incomplete in 19 % ) followed by concurrent temozolomide ( 75 mg/m2/day ) and radiotherapy ( median tumor dose , 60 Gy ) , followed by temozolomide , 200 mg/m2/day for 5 consecutive days every 28 days . Neurologic evaluations were performed monthly and cranial magnetic resonance bimonthly . We analyzed age , clinical manifestations at diagnosis , seizures , Karnofsky performance score , tumor location , extent of resection , proliferation index ( Ki-67 expression ) , p53 , platelet-derived growth factor and epidermal growth factor receptor immunohistochemical expression as prognostic factors in the patients . The Kaplan-Meier statistical method and logrank test were used to assess correlation with survival . Results Fourteen patients ( 32 % ) manifested clinical and neuroradiographic evidence of tumor progression within 6 months of surgery . In contrast , 5 patients ( 12 % ) showed no disease progression for 18 months from the beginning of treatment . Median overall survival was 19 months . Multivariate analysis revealed that an age of 60 years or older ( P < 0.03 ) , a postoperative performance score ≤70 ( P = 0.04 ) , the nontotal tumor resection ( P = 0.03 ) , tumor size > 4 cm ( P = 0.01 ) and proliferation index overexpression ( P = 0.001 ) were associated with the worst prognosis . p53 , PDGF and EGFR overexpression were not significant prognostic factors associated with survival . Conclusions The results suggest that analysis of prognostic markers in glioblastoma multiforme is complex . In addition to previously recognized prognostic variables such as age and Karnofsky performance score , tumor size , total resection and proliferation index overexpression were identified as predictors of survival in a series of patients with glioblastoma multiforme AIMS To evaluate the prognostic value and clinical utility of Ki67 tumour cell proliferation index in anaplastic oligodendroglial tumours ( AOT ) . METHODS AND RESULTS We performed anti-Ki67 immunostaining ( MIB-1 antibody ) of formalin-fixed and paraffin-embedded tumour tissue specimens of 128 patients with newly diagnosed AOT that were treated in a r and omized Phase III trial .  Ki67 index was assessed by three independent observers and was correlated to clinical , histopathological and molecular features ( including 1p/19q co-deletion , epithelial growth factor receptor gene ( EGFR ) amplification , isocitrate dehydrogenase ( IDH1 ) mutations , O6-methylguanine-DNA methyltransferase gene ( MGMT ) promoter methylation , and patient survival times . Intra- and inter-observer agreement of Ki67 index assessment was excellent . Univariable analysis ( n = 79 ) showed that patients with a low Ki67 index had significantly more favourable progression-free survival ( PFS ) ( P-value = 0.004 , log-rank test ) and overall survival ( OS ) ( P-value = 0.003 , log-rank test ) than patients with a high Ki67 index , respectively . On multivariable analysis ( n = 43 ) , Ki67 index showed no independent association with PFS or OS . CONCLUSIONS In AOT the Ki67 index has a strong prognostic impact on univariable analysis , but no independent influence on multivariable analysis . However , further prospect i ve studies including larger numbers of cases and st and ardized evaluation of Ki67 index in conjunction with other relevant prognostic parameters are needed to draw definitive conclusions Abstract Histopathological , immunohistochemical and clinical parameters were correlated with survival in 89 cases of oligodendroglioma ( 65 patients with grade II and 24 patients with grade III of the WHO classification ) .  Median survival time and 5-year survival rate were 3.5 years and 76 % for patients with oligodendroglioma grade II and 0.875 years and 23 % for patients with oligodendroglioma grade III . The tumor biopsy specimens were immunohistochemically analyzed for Ki 67 ( MIB-1 ) , vimentin , glial fibrillary acidic protein ( GFAP ) , neuron-specific enolase ( NSE ) and synaptophysin . MIB-1 nuclear labeling index ranged from 0.0 % to 33.4 % ; vimentin-immunoreactive tumor cells were found in 25 cases . MIB-1 nuclear labeling index and vimentin immunoreaction showed a significant statistical correlation to the 5-year survival rate of the patients . Tumors with vimentin expression ( n = 25 ) and / or high MIB-1 labeling index ( n = 26 ) had a poorer prognosis than tumors lacking vimentin expression ( n = 57 ) and /or displaying a low MIB-1 labeling index ( n = 56 ) . The expression of immunoreactivity for GFAP ( n = 53 ) , NSE ( n = 23 ) and synaptophysin ( n = 15 ) appeared to be of no prognostic relevance . Patients with gross total tumor resection ( n = 47 ) had a median survival time and 5-year survival rate of 3.3 years and 84 % compared to 1.2 years and 42 % for patients with subtotal resection ( n = 41 ) . The comparison between patients who underwent surgery alone ( n = 53 ) and those who had surgery plus postoperative radiation therapy showed no significant survival benefit from postoperative radiation therapy . In conclusion , tumor grade , MIB-1 labeling index , expression of vimentin and the extent of surgery are shown to be of prognostic relevance for patients with oligodendroglioma A quantitative systematic review , or meta- analysis , uses statistical methods to combine the results of multiple studies . Meta-analyses have been done for systematic review s of therapeutic trials , diagnostic test evaluations , and epidemiologic studies . Although the statistical methods involved may at first appear to be mathematically complex , their purpose is simple : They are trying to answer four basic questions . Are the results of the different studies similar ? To the extent that they are similar , what is the best overall estimate ? How precise and robust is this estimate ? Finally , can dissimilarities be explained ? This article provides some guidance in underst and ing the key technical aspects of the quantitative approach to these questions . We have avoided using equations and statistical notations ; interested readers will find implementations of the described methods in the listed references . We focus here on the quantitative synthesis of reports of r and omized , controlled , therapeutic trials because far more meta-analyses on therapeutic studies than on other types of studies have been published . For practical reasons , we present a stepwise description of the tasks that are performed when statistical methods are used to combine data . These tasks are 1 ) deciding whether to combine data and defining what to combine , 2 ) evaluating the statistical heterogeneity of the data , 3 ) estimating a common effect , 4 ) exploring and explaining heterogeneity , 5 ) assessing the potential for bias , and 6 ) presenting the results . Deciding Whether To Combine Data and Defining What To Combine By the time one performs a quantitative synthesis , certain decisions should already have been made about the formulation of the question and the selection of included studies . These topics were discussed in two previous articles in this series [ 1 , 2 ] . Statistical tests can not compensate for lack of common sense , clinical acumen , and biological plausibility in the design of the protocol of a meta- analysis . Thus , a reader of a systematic review should always address these issues before evaluating the statistical methods that have been used and the results that have been generated . Combining poor- quality data , overly biased data , or data that do not make sense can easily produce unreliable results . The data to be combined in a meta- analysis are usually either binary or continuous . Binary data involve a yes/no categorization ( for example , death or survival ) . Continuous data take a range of values ( for example , change in diastolic blood pressure after antihypertensive treatment , measured in mm Hg ) . When one is comparing groups of patients , binary data can be summarized by using several measures of treatment effect that were discussed earlier in this series [ 3 ] . These measures include the risk ratio ; the odds ratio ; the risk difference ; and , when study duration is important , the incidence rate . Another useful clinical measure , the number needed to treat ( NNT ) , is derived from the inverse of the risk difference [ 3 ] . Treatment effect measures , such as the risk ratio and the odds ratio , provide an estimate of the relative efficacy of an intervention , whereas the risk difference describes the intervention 's absolute benefit . The various measures of treatment effect offer complementary information , and all should be examined [ 4 ] . Continuous data can be summarized by the raw mean difference between the treatment and control groups when the treatment effect is measured on the same scale ( for example , diastolic blood pressure in mm Hg ) , by the st and ardized mean difference when different scales are used to measure the same treatment effect ( for example , different pain scales being combined ) , or by the correlation coefficients between two continuous variables [ 5 ] . The st and ardized mean difference , also called the effect size , is obtained by dividing the difference between the mean in the treatment group and the mean in the control group by the SD in the control group . Evaluating the 
    Output:
    
In conclusion , the current meta- analysis revealed that Ki-67 expression might be a predicative factor for poor prognosis of glioma patients , emphasizing its importance as a predictor