Critical appraisal tools CONSORT Guidelines Consolidated Standards of Reporting Trials Endorsed by >50% of core medical journals Extensions for different types of trials: Cluster randomised Non-inferiority trials >25 items on checklist
Other appraisal tools Centre for Evidence Based Medicine (Oxford) 2 page document http://www.cebm.net/index.aspx?o=1157 http://www.cebm.net/index.aspx?o=1157 Critical Appraisal Skills Program (CASP) tool Public Health Resource Unit, NHS http://www.sph.nhs.uk/sph-files/rct%20appraisal%20tool.pdf
Cochrane risk of bias tool Were methods for sequence generation reported? Was there adequate allocation concealment? Was there complete outcome data? Was there intention to treat analysis? Was there blinding of participants, investigators, outcomes assessors, data analysts? Was there selective outcome reporting? Other sources of bias? Co-interventions Commercial Yes, No, Unclear
Elements of appraisal 1.Did the study ask a clearly focussed question? 2.Was it an RCT and an appropriate design for the question? 3.Were subjects appropriately allocated to int/cont groups? 4.Were subjects/staff/others blinded to allocation? 5.Were all who entered the trail accounted for at the end? 6.Were all subjects followed up and measured the same way? 7.Did the study have enough subjects to minimise the play of chance? 8.How are the results presented and what is the main result? 9.How precise are these results? 10.Were all impt outcomes considered so the results can be applied?
Randomisation The play of chance Ideally central/independent rather than local Separate preparation of the agents Eg: pharmacy, with numbered/coded bottles Serially numbered, opaque, sealed envelopes Beware: alternation, dates of arrival Note: Permuted blocks Stratification Put yourself in the place of the local PI….
Outcome of effective randomisation Table 1 Assurance that the groups were equivalent at baseline Accounts for both measured and (more importantly) unmeasured confounders
Power Not a part of all appraisal tools Not many treatments have an effect size (RRR) of >30- 40% A clue to study quality Why did they chose it? What evidence supports such a view? Is that consistent with my perception of risk in this population?
Bias Definition: When an estimated measure of frequency or association differs systematically from the true value. Random samples will differ from the true population because of random sampling variability Bigger the sample, more proximate it is to the underlying pop. Selection bias Confounding Measurement bias
Selection bias Not usually so much of an issue in RCTs Except: Through the treatment of missing participants Loss to follow up Other select exclusions (non-compliant, intolerant)
Confounding A situation in which a measure of the effect of exposure on disease is distorted because of the association of the study factor with other factors that influence the outcome. Three criteria: An idependent risk factor for the outcome of interest Not an intervening variable Unevenly distributed in study groups In RCTs should be fixed by adequate randomisation Look to Table 1
Measurement bias Distortion in the measure of frequency or association due to inaccuracy in measurement Minimise in RCTs by: Use of placebo Keep measurements ‘blind’ to intervention Avoid differential treatments to the study groups
Blinding Not always possible Try to blind Participants Clinicians Outcome assessment Colorectal surgery example
Secondary analyses Should not overshadow the primary outcome Greater validity if pre-specified Beware 1/20 chance of statistically significant finding by chance alone More that are done, more likely to make a ‘significant’ finding
FDA: We do not believe that either reported outcome can be accepted for the following reasons: Assignment of patients often inaccurate and failed to conform to criteria set forth at the outset Errors in assignment nearly all favoured the conclusion that sulfinpyrazone decreased sudden death Mortality classification system had no clear logic Reported effect upon overall mortality heavily dependent upon after-the-fact exclusion from the analysis of certain patients The exclusions virtually all favoured sulfinpyrazone
Change in the primary outcome? Press release: “During this long trial, the proportion of patients who stopped taking their allocated treatment was about one third, but this was not generally due to side-effects and was the same for both real and dummy treatments. If taken without interruption, however, ezetimibe plus simvastatin could have even larger effects than were seen in SHARP, potentially reducing risk by about one quarter.” How will/does it change your treatment?
Power? Blinding? Bias? What about patients over 65?
But is it still an issue? ACT NAC trial from South America 2308 patients, randomisation Blinding of study treatment? HDF Studies CONTRAST & Turkish studies Designed to answer one question but conclude: “treatment with…HDF does not seem to offer a survival benefit…However, subgroup analysis suggested benefit among patients treatment with high convection volumes on all cause mortality” “Composite for death from any cause and non-fatal CV events is not different between post-dilution on-line HDF and high flux HD. HDF treatment with substitution volume over 17.4L provides better CV and overall survival compared to HD”