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      The role of RAS oncogene in survival of patients with lung cancer: a systematic review of the literature with meta-analysis

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          The proto-oncogene RAS, coding for a 21 kDa protein (p21), is mutated in 20% of lung cancer. However, the literature remains controversial on its prognostic significance for survival in lung cancer. We performed a systematic review of the literature with meta-analysis to assess its possible prognostic value on survival. Published studies on lung cancer assessing prognostic value of RAS mutation or p21 overexpression on survival were identified by an electronic search. After a methodological assessment, we estimated individual hazard ratios (HR) estimating RAS protein alteration or RAS mutation effect on survival and combined them using meta-analytic methods. In total, 53 studies were found eligible, with 10 concerning the same cohorts of patients. Among the 43 remaining studies, the revelation method was immunohistochemistry (IHC) in nine and polymerase chain reaction (PCR) in 34. Results in terms of survival were significantly pejorative, significantly favourable, not significant and not conclusive in 9, 1, 31, 2, respectively. In total, 29 studies were evaluable for meta-analysis but we aggregated only the 28 dealing with non-small-cell lung cancer (NSCLC) and not the only one dealing with small-cell-lung cancer (SCLC). The quality scores were not statistically significantly different between studies with or without significant results in terms of survival, allowing us to perform a quantitative aggregation. The combined HR was 1.35 (95% CI: 1.16–1.56), showing a worse survival for NSCLC with KRAS2 mutations or p21 overexpression and, particularly, in adenocarcinomas (ADC) (HR 1.59; 95% CI 1.26–2.02) and in studies using PCR (HR 1.40; 95% CI 1.18–1.65) but not in studies using IHC (HR 1.08; 95% CI 0.86–1.34). RAS appears to be a pejorative prognostic factor in terms of survival in NSCLC globally, in ADC and when it is studied by PCR.

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          Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints.

          Meta-analyses aim to provide a full and comprehensive summary of related studies which have addressed a similar question. When the studies involve time to event (survival-type) data the most appropriate statistics to use are the log hazard ratio and its variance. However, these are not always explicitly presented for each study. In this paper a number of methods of extracting estimates of these statistics in a variety of situations are presented. Use of these methods should improve the efficiency and reliability of meta-analyses of the published literature with survival-type endpoints.
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            Beta blockade during and after myocardial infarction: an overview of the randomized trials.

             S Yusuf,  R. Peto,  J. Lewis (2015)
            Long-term beta blockade for perhaps a year or so following discharge after an MI is now of proven value, and for many such patients mortality reductions of about 25% can be achieved. No important differences are clearly apparent among the benefits of different beta blockers, although some are more convenient than others (or have slightly fewer side effects), and it appears that those with appreciable intrinsic sympathomimetic activity may confer less benefit. If monitored, the side effects of long-term therapy are not a major problem, as when they occur they are easily reversible by changing the beta blocker or by discontinuation of treatment. By contrast, although very early IV short-term beta blockade can definitely limit infarct size, more reliable information about the effects of such treatment on mortality will not be available until a large trial (ISIS) reports later this year, with data on some thousands of patients entered within less than 4 hours of the onset of pain. Our aim has been not only to review the 65-odd randomized beta blocker trials but also to demonstrate that when many randomized trials have all applied one general approach to treatment, it is often not appropriate to base inference on individual trial results. Although there will usually be important differences from one trial to another (in eligibility, treatment, end-point assessment, and so on), physicians who wish to decide whether to adopt a particular treatment policy should try to make their decision in the light of an overview of all these related randomized trials and not just a few particular trial results. Although most trials are too small to be individually reliable, this defect of size may be rectified by an overview of many trials, as long as appropriate statistical methods are used. Fortunately, robust statistical methods exist--based on direct, unweighted summation of one O-E value from each trial--that are simple for physicians to use and understand yet provide full statistical sensitivity. These methods allow combination of information from different trials while avoiding the unjustified direct comparison of patients in one trial with patients in another. (Moreover, they can be extended of such data that there is no real need for the introduction of any more complex statistical methods that might be more difficult for physicians to trust.) Their robustness, sensitivity, and avoidance of unnecessary complexity make these particular methods an important tool in trial overviews.
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              Role of p53 as a prognostic factor for survival in lung cancer: a systematic review of the literature with a meta-analysis.

              The role of p53, as a prognostic factor for survival in lung cancer, is controversial and the purpose of the present systematic review of the literature is to determine this effect. Published studies were identified with the objective to aggregate the available survival results after a methodological assessment using a scale specifically designed by the European Lung Cancer Working Party (ELCWP). To be eligible, a study had to deal with p53 assessment in lung cancer (primary site) only, and to provide a survival comparison according to the p53 status. Among the 74 eligible papers, 30 identified p53 abnormalities as a univariate statistically significant poor prognostic factor and 56 provided sufficient data to allow survival results aggregation. There was no significant difference between the trials that either showed or did not show a prognostic effect of p53 according to the methodological score or to the laboratory technique used. The studies were categorized by histology, disease stage, treatment and laboratory technique. Combined hazard ratios suggested that an abnormal p53 status had an unfavourable impact on survival: in any stage nonsmall cell lung cancer (NSCLC) the mean (95% confidence interval) was 1.44 (1.20-1.72) (number of studies included in the subgroup was 11), 1.50 (1.32-1.70) in stages I-II NSCLC (n=19), 1.68 (1.23-2.29) in stages I-IIIB NSCLC (n=5), 1.68 (1.30-2.18) in stages III-IV NSCLC (n=9), 1.48 (1.29-1.70) in surgically resected NSCLC (n=20), 1.37 (1.02-1.85) in squamous cell carcinoma (n=9), 2.24 (1.70-2.95) in adenocarcinoma (n=9), 1.57 (1.28-1.91) for a positive immunohistochemistry with antibody 1801 (n=8), 1.25 (1.09-1.43) for a positive immunohistochemistry with antibody DO-7 (n=16), and 1.65 (1.35-2.00) for an abnormal molecular biology test (n=13). Data were insufficient to determine the prognostic value of p53 in small cell lung cancer. In each subgroup of nonsmall cell lung cancer, p53 abnormal status was shown to be associated with a poorer survival prognosis.

                Author and article information

                Br J Cancer
                British Journal of Cancer
                Nature Publishing Group
                14 December 2004
                14 January 2005
                17 January 2005
                : 92
                : 1
                : 131-139
                [1 ]Department of Intensive Care and Thoracic Oncology, Institut Jules Bordet, Centre des Tumeurs de l'Université Libre de Bruxelles, Belgium
                [2 ]Data Centre, Institut Jules Bordet, Centre des Tumeurs de l'Université Libre de Bruxelles, Belgium
                [3 ]Department of Nuclear Medicine, Institut Jules Bordet, Centre des Tumeurs de l'Université Libre de Bruxelles, Belgium
                [4 ]Department of Pathology, Institut Jules Bordet, Centre des Tumeurs de l'Université Libre de Bruxelles, Belgium
                [5 ]Department of Surgery, Institut Jules Bordet, Centre des Tumeurs de l'Université Libre de Bruxelles, Belgium
                [6 ]Chest Department, CHU Calmette, Lille, France
                [7 ]FNRS (Fonds National de la Recherche Scientifique), Belgium
                Author notes
                [* ]Author for correspondence: celine.mascaux@ 123456bordet.be
                Copyright 2005, Cancer Research UK
                Molecular Diagnostics

                Oncology & Radiotherapy

                systematic review, p21, survival, lung cancer, ras, prognostic factor, meta-analysis


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