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Thus cheap 100mg metoprolol with mastercard blood pressure kits for sale, the number of patients actu- One procedure that used to be in widespread ally starting the protocol treatment allocated may use was discount metoprolol 100 mg blood pressure normal reading, once the protocol treatment and follow- be less than the number randomised to receive up were complete quality 12.5mg metoprolol blood pressure 50 30, and all the trial-specific it buy metoprolol on line amex pulse pressure therapy. This review would, for example, for analysis whatever occurs, even in situations check that the patient eligibility criteria were where a patient after consent is randomised to satisfied and that there had been no important (say) A but then refuses and even insists on protocol deviations while on treatment. The effect of such patients following this review, then found to be a patient is to dilute the estimate of the true dif- ineligible or protocol violators would then, in ference between A and B. However, if such a principle, be set aside and excluded from the patient was analysed as if allocated to treatment trial results. In the meantime the tal and these include the statistical significance patient is randomised and treatment commenced test, confidence intervals and analysis adjusted but once the report is returned the patient is for confounding (usually prognostic) variables. The form of these techniques will depend on the above review process would automatically the design and especially the type of endpoint exclude this patient, whereas Freedman and variable under consideration. In are examined in this way as to which treatment is a survival time context, the difference between which. As a consequence, this process would tend treatments may, under certain conditions, be sum- to exclude more patients on the more aggressive marised by use of the hazard ratio (HR) and treatment. This type of exclusion sis is done by group rather than on an individual was widespread practice, the consequences of subject basis. The TESTS OF HYPOTHESES AND CONFIDENCE latter policy insisting that the progress of all the INTERVALS randomised patients be reported. In general, the application of ITThis con- If the data are continuous and can be summarised servative in the sense that it will tend to by the corresponding mean values in each of the dilute between-treatment differences. Piaggio and 64 two treatment groups A and B,thenasimple Pinol have pointed out that for equivalence tri- comparison is made using the difference d = als ITT will not be conservative but will tend to xA − xB and the test of the null hypothesis is favour the equivalence hypothesis. Many of these are described in assumption that the null hypothesis of equal GENERAL ISSUES 35 means is true, an approximately standard normal scientific conferences. There are many types of distribution from which the corresponding p- graphics that can be used but careful thought value can be obtained. However, as has been pointed out it is very Graphs used for exploratory data analysis may important to report the observed difference d include histograms, scatter plots, etc. When presenting the results of clinical 100(1 − α)%CIisgivenby trials, the comparative nature of trials should be kept in mind and graphics produced that help in d − z1−α/2SE(d) to d + z1−α/2SE(d) (2. In trials using time as an endpoint measure where z is obtained from tables of the the Kaplan–Meier survival curves provide an ele- 1−α/2 gant summary (Figure 2. Such a CI provides a sense of the precision NUMBER NEEDED TO TREAT (NNT) with which the observed difference between the two treatments is provided by the data. In broad Although many summary measures, for example terms, the width of the interval is determined by a difference in response rates or the hazard the number of subjects recruited, the larger the ratio, are utilised in clinical trials a measure number the narrower the corresponding CI. In unique to this context is the number needed general, the 95% CI will exclude the null value to treat. This is one very convenient way of (zero in this instance) if the corresponding p- assessing the treatment benefit from trials with a value <0. From the result of a randomised Although d provides a simple summary of trial comparing a new treatment with a standard the between-treatment group differences it is treatment, the NNThis the number of patients important to verify if this remains unchanged who need to be treated with the new treatment when taking full account of baseline character- rather than the standard (control) treatment in istics: sometimes termed confounding variables order for one additional patient to benefit. This is often achieved by using can be obtained for any trial that has reported regression techniques to adjust the observed dif- a binary outcome. The NNThis calculated as the reciprocal of In most circumstances, there will be some chance the difference between treatments where this is of imbalances in the values of the variables that expressed as a difference of two proportions may arise following randomisation. The adjust- (say) pT and pC for test and control treatments ment may affect the value of d itself as well as under study. Thus NNT = 1/(pT − pC) and a the associated standard error, SE(d), and hence large treatment effect thus leads to a small NNT. Such adjustments for important covari- A therapy that will lead to one life saved for ates affecting prognosis may result in the esti- every 10 patients treated is clearly better than a mate d being reduced, essentially unchanged or competing treatment that saves one life for every increased – which of these occurs will depend on 50 treated. A confidence interval for the NNThis obtained GRAPHS by taking reciprocals of the values defining the confidence interval for the treatment difference Graphical presentation of data is invaluable to itself. However, as Altman7 has pointed out there communicate results in published journal arti- are some difficulties if the treatment effect that cles or in presentations or posters presented at is not statistically significant and the confidence 36 TEXTBOOK OF CLINICAL TRIALS 1. Kaplan–Meier estimates of survival in patients with inoperable hepatocellular carcinoma by double-blind treatment group interval includes the null value of 0 (see also the comparison has an associated two-sided test size comments by Hutton68). For these studies the p-value, calculated from the data for the the NNThis not a single number, but varies primary endpoint of the trial, must fall to be according to time since the start of treatment. In this case the null hypothesis of no difference between groups MULTIPLE COMPARISONS is then rejected. In fact for k (assumed independent) outcome measures the false positive tive these issues are reviewed by Proschan and Waclawiw. Clearly, the false positive rate increases as the number of comparisons made increases. SUBGROUP ANALYSIS In order to retain the false positive rate as In designing a RCT, sample size is usually deter- 100α% the Bonferroni correction is often sug- mined by considering a clinically worthwhile gested. This implies only declaring differences as effect which will be estimated from the trial data statistically significant at the 100α% level if the by a comparison of all patients randomised to one observed p-value <α/k. Equiv- that the precision with which this effect size is alently, and preferably, multiply the observed p- estimatedmaybeimprovedbyastratifiedanal- value by k and declare this significant if less ysis adjusted for baseline prognostic variables than α. However, if treat- One approach that has been used to overcome this ments are compared within these strata (thereby difficulty is to quote 99% CIs rather than 95% CIs ignoring information on patients not in that stra- whenever more than a single outcome is regarded tum) it is clear that the patient numbers must be as primary. Thus any such Study Group70 report 21 distinct endpoints, comparisons will usually lack sufficient statistical ranging from fatal myocardial infarction to death power and hence may be unreliable. In some cir- between taking no account of the multiplicity cumstances, one of these subgroup comparisons and retaining 0. For example, Green22 highlights group analysis can appear to favour one treatment this problem with respect to trials of a facto- in one subgroup and the other in the other sub- rial design. This may then lead to a false conclusion 38 TEXTBOOK OF CLINICAL TRIALS that the new treatment works for one group but COMPETING RISKS not for the other. If a subgroup analysis is planned for at the design stage, adjustment for this should In some situations, a patient may fail following be built into the sample size considerations. If relapse is the outcome of interest Although the standard of reporting of randomised in the clinical trial, then usually it is the first event controlled trials has improved in many medi- that is of primary importance to the clinician. There are also many situations in 1A monoclonal therapy was thought to be most which inappropriate and substandard analyses are effective against individually dispersed cells and conducted. Particular examples include statisti- less effective against local satellite tumour nod- cal significance tests of pre-randomisation (base- 78 ules or cell aggregates. Since the 17-1A anti- line) variables, often describing demographic and body should be most effective in preventing or patient eligibility criteria in the different treat- delaying distant metastases after surgery, distant ment groups, despite the allocation to groups metastasis as a first event was thus a key endpoint having been made by randomisation so that any 75 in this trial. In the analysis of competing patterns of failure, the Kaplan–Meier method and the associated OTHER MISUSED APPROACHES logrank test are frequently used to estimate TO ANALYSIS the comparative rates of, for example, local recurrence and distant metastasis in patients Anderson76 catalogues some commonly misused receiving alternative treatments for their cancer in approaches used in the analysis of clinical trials.

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They follow a specific formula (see IMRAD structure) and a particular style discount metoprolol 50mg with mastercard pulse pressure 12. They earn their authors valuable credits buy 50mg metoprolol hypertension medscape, which they use for climbing up the career ladder or amassing more funds for their department buy metoprolol 100 mg lowest price arrhythmia 16 year old. Certainly it can be seen as any other transaction that requires researching a market purchase metoprolol on line heart attack vol 1 pt 14, making a product and then selling it in that market. Meeting the following points should increase the chances of your article being accepted for publication. Often the starting point for a paper is the request to put a mass of data into some kind of order. Then set the brief, the 118 SCIENTIFIC PAPERS first part of which involves formulating a one-sentence message for your work. There seems to be a feeling that a paper that starts out suitable only for a minor specialist journal can somehow be improved by detailed criticism (see Icarus fallacy) so that finally it will be accepted by a major international journal. You can and should decide, before setting out to write, which journal will be most suitable (see marketing). This will save time, increase your chances of getting accepted, and make the writing itself much easier (see evidence-based writing). The hard part of writing is not putting in information but deciding what to leave out. I therefore recommend some kind of brain storming (see branching) that will encourage you to select information that supports the message you have chosen. Many writers spend long and unhappy hours at a word processor, inching forward painfully. Take your plan, find a quiet spot for 15 minutes or so, and start (see free writing), doing one section at a time. Never interrupt your flow – whether it be to go back and fiddle with the sentence you have just written, check a matter of detail with your records, or copy down the precise details of a key reference. Now you can start to work on the details, but be careful not to neglect macro-editing. Polish up the presentation of your figures and tables, and write the addi- tional items you will need – the title, the abstract, the references and the covering letter. If you have done your work well you will have a product that will meet the needs of your target journal. Yet many feel that they should now subject the draft to a barrage of detailed criticism, most of which will concern minor matters. It will be a great help at this stage if you have already agreed the market and message with your co-authors. Keep your nerve: your job is to keep the article on track for publication (see negotiating changes). The fact that you can write a scien- tific paper shows that you can write a scientific paper. It does not predict your performance as a doctor or your worth as a human being. BOOKLIST: scientific papers • Winning the publications game (2nd edition), by Tim Albert, Abingdon: Radcliffe Medical Press, 2000. Five hundred tips for success from an author who comes from the UK (as opposed to US) tradition of science writing. It is written from the US perspective and has some interesting data about what reviewers think. A broad sweep through many aspects of planning, publishing and presenting research. Includes some useful chapters on the changes brought by electronic publishing. Short articles Do not assume that they take less time than long articles. Shuffling data around One of the main preoccupations of those writing scientific papers. Slander A defamation which is spoken (as opposed to libel, which is written). Spacing after a full stop Many who trained as typists on mechanical typewriters were instructed to leave two spaces after the full stop. Word processors are more flexible when it comes to spacing, and now the convention is to have one space only. One of the problems is that English spelling has few rules, and those that do exist have exceptions. Computerized spelling checks do help, and there is no excuse for not switching them on. However, they tell us only that we have a properly spelt word, and do not tell us if we have a good word in the wrong place. One of the best ways of improving your spelling is to read clear English. You need to be familiar with the shape of words, because alarm bells will start to ring when you see an aberration. You then need a good dictionary, and the energy and self discipline to use it. Get them right and you are already doing better than others: accom- modation, corollary, diarrhoea, inoculate, occurred, ophthalmology, publicly, resuscitate, separate, unnecessary. All writers on style, however, seem to agree that this rule is based on Latin grammar and was misguided from the start. If you want to split an infinitive and it sounds right, most modern authorities say, then go ahead and split it. If anyone complains, pass them a reference book and challenge them to find support for their position. Statisticians Most scientific journals now take statistics very seriously, with professional statisticians advising them at the highest level. We need to take this into account when writing for journals and involve a statistician at an early stage. Establish before you start 122 STATISTICIANS whether you will have enough numbers from which to draw any meaningful conclusions. Unfortunately much modern science writing has become a succession of statistics that only the statistician and his mate understand. Use statistics to support the message, not to drown it (see leaf shuffling). Structure It is easy to get so caught up in the meaning of a piece of writing that we take for granted the way the writing has been constructed – in other words the structure. Variables are likely to include: how long will the piece of writing be (length)? Should the message be at the start, or buried at the end (inverted triangle)? The structure to use is the one that your target audience likes and knows (see evidence-based writing).

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