Skip to main content Accessibility help
×
Hostname: page-component-76fb5796d-zzh7m Total loading time: 0 Render date: 2024-04-26T17:52:44.288Z Has data issue: false hasContentIssue false

Chapter 2 - Understanding Evidence

from Part I - Foundations

Published online by Cambridge University Press:  15 December 2020

Jeffrey L. Saver
Affiliation:
David Geffen School of Medicine, University of Ca
Graeme J. Hankey
Affiliation:
University of Western Australia, Perth
Get access

Summary

Almost all efficacious stroke treatments confer moderate-to-large benefits, but not staggeringly huge benefits. However, moderate treatment effects can be clinically very worthwhile for the patient. To detect moderate-large treatment benefits, trials must avoid bias and random error. Studies with weak designs (personal experience, observational studies with historical controls, and observational studies with concurrent, non-randomized controls) will not sufficiently control bias and random error to enable reliable discrimination of a true moderate-to-large benefit from false positives and false negatives. Randomized clinical trials are required. 'Ingredients' for a good trial – Proper randomization and concealment of allocation (i.e. clinician cannot have foreknowledge of next treatment allocation)/Outcome evaluation blind to the allocated treatment/Analysis by allocated treatment (including all randomized patients: intention-to-treat)/Large numbers of major outcomes and correspondingly narrow CIs/Conclusion based on pre-specified primary hypothesis and outcome/Chief emphasis on findings in overall study population. Advantages of systematic reviews (over traditional unsystematic, narrative reviews) – Use explicit, well-developed methods to reduce bias/Summarize large amounts of data explicitly/Provide all available data/Increase statistical power and precision/Look for consistencies/inconsistencies/Improve generalizability. Cochrane Reviews – Generally higher quality than other systematic reviews/Periodically updated/Available over internet/Abstracts available free of charge/Full reviews available free of charge in over 100 low- and middle-income countries

Type
Chapter
Information
Stroke Prevention and Treatment
An Evidence-based Approach
, pp. 10 - 34
Publisher: Cambridge University Press
Print publication year: 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

AAMC-AAU Advisory Committee on Financial Conflicts of Interest in Human Subjects Research. (2008). Protecting patients, preserving integrity, advancing health: accelerating the implementation of COI policies in human subjects research. www.aamc.org/download/482216/data/protectingpatients.pdf. Accessed March 2019.Google Scholar
Adeoye, O, Hornung, R, Khatri, P, Kleindorfer, D. (2011). Recombinant tissue-type plasminogen activator use for ischemic stroke in the United States: a doubling of treatment rates over the course of 5 years. Stroke, 42, 1952–5.Google Scholar
Ali, M, Bath, P, Brady, M, Davis, S, Diener, HC, Donnan, G, et al.; VISTA Steering Committees. (2012). Development, expansion, and use of a stroke clinical trials resource for novel exploratory analyses. Int J Stroke, 7, 133–8.Google Scholar
Ashcroft, R. (2000). Giving medicine a fair trial: trials should not second guess what patients want. BMJ, 320, 1686.Google Scholar
Bassler, D, Briel, M, Montori, VM, Lane, M, Glasziou, P, Zhou, Q, et al.; STOPIT-2 Study Group. (2010). Stopping randomized trials early for benefit and estimation of treatment effects: systematic review and meta-regression analysis. JAMA, 303: 1180–7.Google Scholar
Bath, PM, Lees, KR, Schellinger, PD, Altman, H, Bland, M, Hogg, C, et al.; European Stroke Organisation Outcomes Working Group. (2012). Statistical analysis of the primary outcome in acute stroke trials. Stroke, 43, 1171–8.Google Scholar
Bekelman, JE, Li, Y, Gross, CP. (2003). Scope and impact of financial conflicts of interest in biomedical research: a systematic review. JAMA, 289, 454–65.Google Scholar
Blanco, D, Biggane, AM, Cobo, E; MiRoR Network. (2018). Are CONSORT checklists submitted by authors adequately reflecting what information is actually reported in published papers? Trials, 19, 80. doi:10.1186/s13063-018-2475-0.Google Scholar
Borenstein, M, Hedges, LV, Higgins, JP, Rothstein, HR. (2010). A basic introduction to fixed-effect and random-effects models for meta-analysis. Res Synth Methods, 1, 97111.Google Scholar
Broderick, JP, Palesch, YY, Demchuk, AM, Yeatts, SD, Khatri, P, Hill, MD, et al.; Interventional Management of Stroke (IMS) III Investigators. (2013). Endovascular therapy after intravenous t-PA versus t-PA alone for stroke. N Engl J Med, 368, 893903.Google Scholar
Broglio, K. (2018). Randomization in clinical trials: permuted blocks and stratification. JAMA, 319, 2223–4.Google Scholar
Chalmers, I. (2004). Well informed uncertainties about the effects of treatments. BMJ, 328, 475–6.CrossRefGoogle ScholarPubMed
Chan, AW. (2012). Out of sight but not out of mind: how to search for unpublished clinical trial evidence. BMJ, 344, d8013. doi:10.1136/bmj.d8013.Google Scholar
Clarke, M, Williamson, PR. (2016). Core outcome sets and systematic reviews. Syst Rev, 5, 11. doi:10.1186/s13643-016-0188-6.Google Scholar
Collins, R, MacMahon, S. (2001). Reliable assessment of the effects of treatment on mortality and major morbidity I: clinical trials. Lancet, 357, 373–80.Google Scholar
Counsell, CE, Clarke, MJ, Slattery, J, Sandercock, PA. (1994). The miracle of DICE therapy for acute stroke: fact or fictional product of subgroup analysis? BMJ, 309, 1677–81.Google Scholar
Coutinho, J, de Bruijn, SF, Deveber, G, Stam, J. (2011). Anticoagulation for cerebral venous sinus thrombosis. Cochrane Database Syst Rev, 8, CD002005. doi:10.1002/14651858.CD002005.pub2.Google Scholar
Cranston, JS, Kaplan, BD, Saver, JL. (2017). Minimal clinically important difference for safe and simple novel acute ischemic stroke therapies. Stroke, 48, 2946–51.Google Scholar
Dahabreh, IJ, Hayward, R, Kent, DM. (2016). Using group data to treat individuals: understanding heterogeneous treatment effects in the age of precision medicine and patient-centred evidence. Int J Epidemiol, 45, 2184–93.Google Scholar
DAMOCLES Study Group, NHS Health Technology Assessment Programme. (2005). A proposed charter for clinical trial data monitoring committees: helping them to do their job well . Lancet, 365, 711–22.Google Scholar
Dekkers, OM, von Elm, E, Algra, A, Romijn, JA, Vandenbroucke, JP. (2010). How to assess the external validity of therapeutic trials: a conceptual approach. Int J Epidemiol, 39, 8994.Google Scholar
DeMets, DL, Cook, T. (2019). Challenges of non-intention-to-treat analyses. JAMA, 321, 145–6.Google Scholar
Djulbegovic, B, Guyatt, GH. (2017). Progress in evidence-based medicine: a quarter century on. Lancet 390, 415–23.Google Scholar
Donnan, GA, Davis, SM, Kaste, M; International Trial Subcommittee of the International Stroke Liaison Committee, American Stroke Association. (2003). Stroke. Recommendations for the relationship between sponsors and investigators in the design and conduct of clinical stroke trials. Stroke, 34, 1041–5.Google Scholar
Doust, J, Del Mar, C. (2004). Why do doctors use treatments that do not work? BMJ, 328, 474–5.Google Scholar
ECST Trialists. (1998). Randomised trial of endarterectomy for recently symptomatic carotid stenosis: final results of the MRC European Carotid Surgery Trial (ECST). Lancet, 351, 1379–87.Google Scholar
Emanuel, EJ, Wendler, D, Grady, C. (2000). What makes clinical research ethical? JAMA, 283, 2701–11.Google Scholar
Emberson, J, Lees, KR, Lyden, P, Blackwell, L, Albers, G, Bluhmki, E, et al.; Stroke Thrombolysis Trialists’ Collaborative Group. (2014). Effect of treatment delay, age, and stroke severity on the effects of intravenous thrombolysis with alteplase for acute ischaemic stroke: a meta-analysis of individual patient data from randomised trials. Lancet, 384, 1929–35.Google Scholar
Falk Delgado, A, Falk Delgado, A. (2017). The association of funding source on effect size in randomized controlled trials: 2013–2015 – a cross-sectional survey and meta-analysis. Trials, 18, 125. doi:10.1186/s13063-017-1872-0.Google Scholar
Flather, M, Delahunty, N, Collinson, J. (2006). Generalizing results of randomized trials to clinical practice: reliability and cautions. Clin Trials, 3, 508–12.Google Scholar
Fleming, TR, Powers, JH. (2012). Biomarkers and surrogate endpoints in clinical trials. Stat Med, 31, 2973–84.CrossRefGoogle ScholarPubMed
George, BP, Pieters, TA, Zammit, CG, Kelly, AG, Sheth, KN, Bhalla, T. (2019). Trends in interhospital transfers and mechanical thrombectomy for United States acute ischemic stroke inpatients. J Stroke Cerebrovasc Dis, 28, 980–7. doi:10.1016/j.jstrokecerebrovasdis.2018.12.018. [Epub ahead of print]Google Scholar
Gopal, AD, Wallach, JD, Aminawung, JA, Gonsalves, G, Dal-Ré, R, Miller, JE, et al. (2018). Adherence to the International Committee of Medical Journal Editors’ (ICMJE) prospective registration policy and implications for outcome integrity: a cross-sectional analysis of trials published in high-impact specialty society journals. Trials, 19, 448. doi:10.1186/s13063-018-2825-y.Google Scholar
Guyatt, G, Oxman, AD, Akl, EA, Kunz, R, Vist, G, Brozek, J, et al. (2011). GRADE guidelines: 1. Introduction-GRADE evidence profiles and summary of findings tables. J Clin Epidemiol, 64, 383–94.Google Scholar
Halperin, JL, Levine, GN, Al-Khatib, SM, Birtcher, KK, Bozkurt, B, Brindis, RG, et al. (2016). Further evolution of the ACC/AHA Clinical Practice Guideline Recommendation Classification System: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation, 133, 1426–8.Google Scholar
Harman, NL, Conroy, EJ, Lewis, SC, Murray, G, Norrie, J, Sydes, MR, et al. (2015). Exploring the role and function of trial steering committees: results of an expert panel meeting. Trials, 16, 597. doi:10.1186/s13063-015-1125-z.Google Scholar
Higgins, JPT, Green, S, eds. (2011). Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [updated March 2011]. The Cochrane Collaboration. Available from www.handbook.cochrane.org.Google Scholar
Higgins, JPT, Savović, J, Page, MJ, Sterne, JAC, on behalf of the ROB2 Development Group. (2018). Revised Cochrane risk-of-bias tool for randomized trials (RoB 2). www.riskofbias.info/welcome/rob-2–0-tool/current-version-of-rob-2 . Accessed March 2019.Google Scholar
Higgins, JPT, Thompson, SG, Deeks, JJ, Altman, DG. (2003). Measuring inconsistency in meta-analyses. BMJ, 327, 557–60.Google Scholar
Hill, MD. (2018). How to review a clinical research paper. Stroke, 49, e204e206.Google Scholar
Hobbs, BP, Carlin, BP, Sargent, DJ. (2013). Adaptive adjustment of the randomization ratio using historical control data. Clin Trials, 10, 430–40.Google Scholar
Hoffrage, U, Lindsey, S, Hertwig, R, Gigerenzer, G. (2000). Medicine: communicating statistical information. Science, 290, 2261–2.Google Scholar
Hopewell, S, Loudon, K, Clarke, MJ, Oxman, AD, Dickersin, K. (2009). Publication bias in clinical trials due to statistical significance or direction of trial results. Cochrane Database Syst Rev, 1, MR000006. doi:10.1002/14651858.MR000006.pub3.Google Scholar
International Committee of Medical Journal Editors. (2018). Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly Work in Medical Journals. www.icmje.org/icmje-recommendations.pdf. Accessed March 2019.Google Scholar
International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use. (2016). Guideline for Good Clinical Practice E6 (R2). www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Efficacy/E6/E6_R2__Step_4_2016_1109.pdf. Accessed March 2019.Google Scholar
IST-3 Collaborative Group, Sandercock, P, Wardlaw, JM, Lindley, RI, Dennis, M, Cohen, G, Murray, G, et al. (2012). The benefits and harms of intravenous thrombolysis with recombinant tissue plasminogen activator within 6 h of acute ischaemic stroke (the third international stroke trial [IST-3]): a randomised controlled trial. Lancet, 379, 2352–63.Google Scholar
Ioannidis, JP. (2005). Why most published research findings are false. PLoS Med, 2, e124.CrossRefGoogle ScholarPubMed
Johnston, KC, Bruno, A, Paulis, Q, Hall, CE, Barrett, KM, Barsan, W, et al. (2019). Intensive versus standard treatment of hyperglycemia in acute ischemic stroke: a randomized controlled trial. JAMA, 322, 326–35.CrossRefGoogle Scholar
Johnston, SC, Rootenberg, JD, Katrak, S, Smith, WS, Elkins, JS. (2006). Effect of a US National Institutes of Health programme of clinical trials on public health and costs. Lancet, 367, 1319–27.Google Scholar
Jones, AP, Riley, RD, Williamson, PR, Whitehead, A. (2009). Meta-analysis of individual patient data versus aggregate data from longitudinal clinical trials. Clin Trials, 6, 1627.Google Scholar
Kaplan, RM, Chambers, DA, Glasgow, RE. (2014). Big data and large sample size: a cautionary note on the potential for bias. Clin Transl Sci, 7, 342–6.Google Scholar
Kirkham, JJ, Altman, DG, Chan, AW, Gamble, C, Dwan, KM, Williamson, PR. (2018). Outcome reporting bias in trials: a methodological approach for assessment and adjustment in systematic reviews. BMJ, 362, k3802. doi:10.1136/bmj.k3802.Google Scholar
Laika, J. (2008). Time to weed the (EBM-) pyramids?! https://laikaspoetnik.wordpress.com/2008/09/26/time-to-weed-the-ebm-pyramids/. Accessed March 2019.Google Scholar
Laine, C, Horton, R, DeAngelis, CD, Drazen, JM, Frizelle, FA, Godlee, F, et al. (2007). Clinical trial registration: looking back and moving ahead. JAMA, 298, 93–4.CrossRefGoogle ScholarPubMed
Laupacis, A, Sackett, DL, Roberts, RS. (1988). An assessment of clinically useful measures of the consequences of treatment. N Engl J Med, 318, 1728–33.Google Scholar
Lees, KR, Hankey, GJ, Hacke, W. (2003). Design of future acute-stroke treatment trials. Lancet Neurol, 2, 5461.Google Scholar
Lees, KR, Zivin, JA, Ashwood, T, Davalos, A, Davis, SM, Diener, HC, Grotta, J, Lyden, P, Shuaib, A, Hårdemark, HG, Wasiewski, WW; Stroke-Acute Ischemic NXY Treatment (SAINT I) Trial Investigators. (2006). NXY-059 for acute ischemic stroke. N Engl J Med 354: 588600.Google Scholar
Lewis, SC, Warlow, CP. (2004). How to spot bias and other potential problems in randomised controlled trials. J Neurol Neurosurg Psychiatry, 75(2), 181–7.Google Scholar
Liberati, A, Altman, DG, Tetzlaff, J, Mulrow, C, Gøtzsche, PC, Ioannidis, JP, et al. (2009). The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med, 6, e1000100. doi:10.1371/journal.pmed.1000100.Google Scholar
Lichtman, JH, Jones, MR, Leifheit, EC, Sheffet, AJ, Howard, G, Lal, BK, et al. (2017). Carotid endarterectomy and carotid artery stenting in the US Medicare population, 1999–2014. JAMA, 318, 1035–46.Google Scholar
Liebeskind, DS, Kidwell, CS, Sayre, JW, Saver, JL. (2006). Evidence of publication bias in reporting acute stroke clinical trials. Neurology, 67, 973–9.Google Scholar
Lo, B, Field, MJ; Institute of Medicine Committee on Conflict of Interest in Medical Research, Education, and Practice. (2009). Conflict of Interest in Medical Research, Education, and Practice. Washington, DC: National Academies Press.Google Scholar
Lundh, A, Lexchin, J, Mintzes, B, Schroll, JB, Bero, L5. (2017). Industry sponsorship and research outcome. Cochrane Database Syst Rev, 2, MR000033. doi:10.1002/14651858.MR000033.pub3.Google Scholar
Lyden, PD, Meyer, BC, Hemmen, TM, Rapp, KS. (2010). An ethical hierarchy for decision making during medical emergencies. Ann Neurol, 67, 434–40.Google Scholar
Mauri, L, D’Agostino, RB Sr. (201). Challenges in the design and interpretation of noninferiority trials. N Engl J Med, 377, 1357–67.Google Scholar
McAlister, FA, van Diepen, S, Padwal, RS, Johnson, JA, Majumdar, SR. (2007). How evidence-based are the recommendations in evidence-based guidelines? PLoS Med, 4, e250.Google Scholar
Mead, G, Hackett, ML, Lundström, E, Murray, V, Hankey, GJ, Dennis, M. (2015). The FOCUS, AFFINITY and EFFECTS trials studying the effect(s) of fluoxetine in patients with a recent stroke: a study protocol for three multicentre randomised controlled trials. Trials, 16, 369. doi:10.1186/s13063-015-0864-1.Google Scholar
Molyneux, AJ, Kerr, RS, Yu, LM, Clarke, M, Sneade, M, Yarnold, JA, et al.; International Subarachnoid Aneurysm Trial (ISAT) Collaborative Group. (2005). International subarachnoid aneurysm trial (ISAT) of neurosurgical clipping versus endovascular coiling in 2143 patients with ruptured intracranial aneurysms: a randomised comparison of effects on survival, dependency, seizures, rebleeding, subgroups, and aneurysm occlusion. Lancet, 366, 809–17.Google Scholar
Munroe, R. (2011). Significant. https://xkcd.com/882/. Accessed March 2019.Google Scholar
Murad, MH, Montori, VM, Ioannidis, JP, Jaeschke, R, Devereaux, PJ, Prasad, K, (2014). How to read a systematic review and meta-analysis and apply the results to patient care: users’ guides to the medical literature. JAMA, 312, 171–9.Google Scholar
NICE: National Institute for Health and Care Excellence. (2014). Developing NICE guidelines: the manual. www.nice.org.uk/media/default/about/what-we-do/our-programmes/developing-nice-guidelines-the-manual.pdf. Accessed March 2019.Google Scholar
NINDS (National Institute of Neurological Disorders and Stroke) rt-PA Stroke Study Group. (1995). Tissue plasminogen activator for acute ischemic stroke. N Engl J Med, 333, 1581–7.Google Scholar
Norton, EC, Dowd, BE, Maciejewski, ML. (2018). Odds ratios – current best practice and use. JAMA, 320, 84–5.Google Scholar
Pocock, SJ, Stone, GW. (2016a). The primary outcome fails – what next? N Engl J Med, 375, 861–70.Google Scholar
Pocock, SJ, Stone, GW. (2016b). The primary outcome is positive – is that good enough? N Engl J Med, 375, 971–9.Google Scholar
Pollock, A, Berge, E. (2018). How to do a systematic review. Int J Stroke, 13, 138–56.CrossRefGoogle Scholar
Powers, WJ, Clarke, WR, Grubb, RL Jr, Videen, TO, Adams, HP Jr, Derdeyn, CP; COSS Investigators. (2011). Extracranial-intracranial bypass surgery for stroke prevention in hemodynamic cerebral ischemia: the Carotid Occlusion Surgery Study randomized trial. JAMA, 306, 1983–92.Google Scholar
Ranganathan, P, Pramesh, CS, Aggarwal, R. (2016). Common pitfalls in statistical analysis: Absolute risk reduction, relative risk reduction, and number needed to treat. Perspect Clin Res, 7, 51–3.Google Scholar
Rasmussen, K, Bero, L, Redberg, R, Gøtzsche, PC, Lundh, A. (2018). Collaboration between academics and industry in clinical trials: cross sectional study of publications and survey of lead academic authors. BMJ, 363, k3654. doi:10.1136/bmj.k3654.CrossRefGoogle ScholarPubMed
Ridker, PM, Torres, J. (2006). Reported outcomes in major cardiovascular clinical trials funded by for-profit and not-for-profit organizations: 2000–2005. JAMA, 295, 2270–4.CrossRefGoogle ScholarPubMed
Riley, RD, Lambert, PC, Abo-Zaid, G. (2010). Meta-analysis of individual participant data: rationale, conduct, and reporting. BMJ, 340, c221.Google Scholar
Rothwell, PM. (2005). External validity of randomised controlled trials: ‘to whom do the results of this trial apply?Lancet, 365, 8293.Google Scholar
Rothwell, PM, Mehta, Z, Howard, SC, Gutnikov, SA, Warlow, CP. (2005). Treating individuals 3: from subgroups to individuals: general principles and the example of carotid endarterectomy. Lancet, 365, 256–65.Google Scholar
Rush, CJ, Campbell, RT, Jhund, PS, Petrie, MC, McMurray, JJV. (2018). Association is not causation: treatment effects cannot be estimated from observational data in heart failure. Eur Heart J, 39, 3417–38.CrossRefGoogle Scholar
Sackett, DL. (2000). Why randomized controlled trials fail but needn’t. 1. Failure to gain ‘coal-face’ commitment and to use the uncertainty principle. Can Med Assoc J, 162, 1311–14.Google Scholar
Sackett, DL, Deeks, JJ, Altman, DG. (1996). Down with odds ratios! Evid Based Med, 1, 164–6.Google Scholar
Sanders, GD, Maciejewski, ML, Basu, A. (2019). Overview of cost-effectiveness analysis. JAMA, 321, 1400–1. doi:10.1001/jama.2019.1265.Google Scholar
Sarpong, EM, Zuvekas, SH. (2014). Changes in Statin Therapy among Adults (Age ≥ 18) by Selected Characteristics, United States, 2000–2001 to 2010–2011. Statistical Brief #459. November. Rockville, MD: Agency for Healthcare Research and Quality. www.meps.ahrq.gov/mepsweb/data_files/publications/st459/stat459.shtml.Google Scholar
Saver, JL. (2011). Optimal end points for acute stroke therapy trials: best ways to measure treatment effects of drugs and devices. Stroke, 42, 2356–62.Google Scholar
Saver, JL, Gornbein, J. (2009). Treatment effects for which shift or binary analyses are advantageous in acute stroke trials. Neurology, 72, 1310–15.Google Scholar
Saver, JL, Lewis, RJ. (2019). Number needed to treat: conveying the likelihood of a therapeutic effect. JAMA, 321, 798–9. doi:10.1001/jama.2018.21971.Google Scholar
Savovic, J, Turner, RM, Mawdsley, D, Jones, HE, Beynon, R, Higgins, JPT, et al. (2018). Association between risk-of-bias assessments and results of randomized trials in Cochrane Reviews: the ROBES Meta-Epidemiologic Study. Am J Epidemiol, 187, 1113–22.Google Scholar
Schulz, KF, Altman, DG, Moher, D, for the CONSORT Group. (2010). CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials. PLoS Med, 7, e1000251.CrossRefGoogle ScholarPubMed
Schumacher, RC, Nguyen, OK, Desphande, K, Makam, AN. (2019). Evidence-based medicine and the American Thoracic Society Clinical Practice Guidelines. JAMA Intern Med, 179, 584–6. doi:10.1001/jamainternmed.2018.7461. [Epub ahead of print]Google Scholar
Sedgwick, P. (2015). Meta-analysis: what is heterogeneity? BMJ, 16, h1435. doi:10.1136/bmj.h1435.Google Scholar
Senn, SJ, Lewis, RJ. (2019). Treatment effects in multicenter randomized clinical trials. JAMA, 321, 1211–12. doi:10.1001/jama.2019.1480.Google Scholar
Serghiou, S, Goodman, SN. (2019). Random-effects meta-analysis: summarizing evidence with caveats. JAMA, 321, 301–2.Google Scholar
Shaneyfelt, T. (2016). Pyramids are guides not rules: the evolution of the evidence pyramid. Evid Based Med, 21, 121–2.Google Scholar
Shaw, GB. (1911). The Doctor’s Dilemma. London: Constable and Company.Google Scholar
Sheth, SA, Saver, JL, Starkman, S, Grunberg, ID, Guzy, J, Ali, LK, et al. (2016). Enrollment bias: frequency and impact on patient selection in endovascular stroke trials. J Neurointerv Surg, 8, 353–9.Google Scholar
Shuaib, A, Lees, KR, Lyden, P, Grotta, J, Davalos, A, Davis, SM, et al.; SAINT II Trial Investigators. (2007). NXY-059 for the treatment of acute ischemic stroke. N Engl J Med, 357, 562–71.Google Scholar
Stead, WW. (2017). The complex and multifaceted aspects of conflicts of interest. JAMA, 317, 1765–7.Google Scholar
Stewart, LA, Clarke, M, Rovers, M, Riley, RD, Simmonds, M, Stewart, G, et al.; PRISMA-IPD Development Group. (2015). Preferred reporting items for systematic review and meta-analyses of individual participant data: the PRISMA-IPD statement. JAMA, 313, 1657–65.Google Scholar
Straus, SE, Glasziou, P, Richardson, WS, Haynes, RB. (2019). Evidence-Based Medicine: How to Practice and Teach EBM, 5th ed. Edinburgh: Elsevier Limited.Google Scholar
Sullivan, GM, Feinn, R. (2012). Using effect size – or why the p value is not enough. J Grad Med Educ, 4, 279–82.Google Scholar
Sun, X, Briel, M, Walter, SD, Guyatt, GH. (2010). Is a subgroup effect believable? Updating criteria to evaluate the credibility of subgroup analyses. BMJ, 340, c117.Google Scholar
Taichman, DB, Sahni, P, Pinborg, A, Peiperl, L, Laine, C, James, A, et al. (2017). Data sharing statements for clinical trials: a requirement of the International Committee of Medical Journal Editors. JAMA, 317, 2491–2.Google Scholar
Tudur Smith, C, Marcucci, M, Nolan, SJ, Iorio, A, Sudell, M, Riley, R, et al. (2016). Individual participant data meta-analyses compared with meta-analyses based on aggregate data. Cochrane Database Syst Rev, 9, MR000007. doi:10.1002/14651858.MR000007.pub3.Google Scholar
van Gijn, J. (2005). From randomised trials to rational practice. Cerebrovasc Dis, 19, 6976.Google Scholar
Vyas, A, Saver, J. (2016). The ‘uncertainty principle’ as an entry criterion in stroke clinical trials: bias towards null findings. Neurology, 86 (16 Supplement), P2.382.Google Scholar
Wallach, JD, Sullivan, PG, Trepanowski, JF, Sainani, KL, Steyerberg, EW, Ioannidis, JP. (2017). Evaluation of evidence of statistical support and corroboration of subgroup claims in randomized clinical trials. JAMA Intern Med, 177, 554–60.Google Scholar
Wallis, CJD, Detsky, AS, Fan, E. (2018). Establishing the effectiveness of procedural interventions: the limited role of randomized trials. JAMA, 320, 2421-2. doi:10.1001/jama.2018.16329.Google Scholar
Warlow, C. (2004). The Willis Lecture 2003: evaluating treatments for stroke patients too slowly: time to get out of second gear. Stroke, 35, 2211–19.Google Scholar
WHO Commission on Macroeconomics and Health & World Health Organization. (2001). Macroeconomics and Health: Investing in Health for Economic Development. Geneva: World Health Organization. www.who.int/iris/handle/10665/42463.Google Scholar
Zarin, DA, Tse, T, Williams, RJ, Carr, S. (2016). Trial reporting in ClinicalTrials.gov – the final rule. N Engl J Med, 375, 19982004.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×