Références

     

[1] Hernán MA. Methods of Public Health Research - Strengthening Causal Inference from Observational Data. The New England journal of medicine 2021 10.1056/NEJMp2113319 [34596980]

[2] Park K. The use of real-world data in drug repurposing. Transl Clin Pharmacol 2021;29:117–24 10.12793/tcp.2021.29.e18 [34621704]

[3] Hatswell AJ, Baio G, Berlin JA, et al. Regulatory approval of pharmaceuticals without a randomised controlled study: analysis of EMA and FDA approvals 1999-2014. BMJ open 2016;6:e011666 10.1136/bmjopen-2016-011666 [27363818]

[4] Gyawali B, Rome BN, Kesselheim AS. Regulatory and clinical consequences of negative confirmatory trials of accelerated approval cancer drugs: retrospective observational study. BMJ 2021;374:n1959 10.1136/bmj.n1959 [34497044]

[5] Mahase E. FDA allows drugs without proven clinical benefit to languish for years on accelerated pathway. BMJ 2021;374:n1898 10.1136/bmj.n1898 [34326042]

[6] Naci H, Smalley KR, Kesselheim AS. Characteristics of Preapproval and Postapproval Studies for Drugs Granted Accelerated Approval by the US Food and Drug Administration. JAMA 2017;318:626–36 10.1001/jama.2017.9415 [28810023]

[7] Gyawali B, Hey SP, Kesselheim AS. Assessment of the Clinical Benefit of Cancer Drugs Receiving Accelerated Approval. JAMA Internal Medicine 2019;179:906–13 10.1001/jamainternmed.2019.0462 [31135808]

[8] Boyle JM, Hegarty G, Frampton C, et al. Real-world outcomes associated with new cancer medicines approved by the Food and Drug Administration and European Medicines Agency: A retrospective cohort study. Eur J Cancer 2021;155:136–44 10.1016/j.ejca.2021.07.001 [34371443]

[9] Song F, Zang C, Ma X, et al. The use of real-world data/evidence in regulatory submissions. Contemporary Clinical Trials 2021;109:106521 10.1016/j.cct.2021.106521 [34339865]

[10] Soto-Becerra P, Culquichicón C, Hurtado-Roca Y, et al. Real-world effectiveness of hydroxychloroquine, azithromycin, and ivermectin among hospitalized COVID-19 patients: results of a target trial emulation using observational data from a nationwide healthcare system in Peru 2020.

[11] Greenland S, Pearl J, Robins JM. Causal diagrams for epidemiologic research. Epidemiology 1999;10:37–48 ; [9888278]

[12] Sterne JAC, Hernán MA, Reeves BC, et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ 2016;355:i4919 10.1136/bmj.i4919

[13] Schünemann HJ, Cuello C, Akl EA, et al. GRADE Guidelines: 18. How ROBINS-I and other tools to assess risk of bias in non-randomized studies should be used to rate the certainty of a body of evidence. J Clin Epidemiol 2018 10.1016/j.jclinepi.2018.01.012

[14] Hernán MA, Alonso A, Logan R, et al. Observational studies analyzed like randomized experiments: an application to postmenopausal hormone therapy and coronary heart disease. Epidemiology 2008;19:766–79 10.1097/EDE.0b013e3181875e61 [18854702]

[15] Lash TL, VanderWeele TJ, Haneuse S, et al. Modern epidemiology. Philadelphia etc.: Wolters Kluwer 2021 ISBN:1451193289;

[16] Schuemie MJ, Ryan PB, Pratt N, et al. Principles of Large-scale Evidence Generation and Evaluation across a Network of Databases (LEGEND). J Am Med Inform Assoc 2020;27:1331–37 10.1093/jamia/ocaa103 [32909033]

[17] Bruns SB, Ioannidis JPA. p-Curve and p-Hacking in Observational Research. PLoS ONE 2016;11:e0149144 10.1371/journal.pone.0149144 [26886098]

[18] Patel CJ, Burford B, Ioannidis JPA. Assessment of vibration of effects due to model specification can demonstrate the instability of observational associations. Journal of Clinical Epidemiology 2015;68:1046–58 10.1016/j.jclinepi.2015.05.029 [26279400]

[19] Head ML, Holman L, Lanfear R, et al. The extent and consequences of p-hacking in science. PLoS Biology 2015;13:e1002106 10.1371/journal.pbio.1002106 [25768323]

[20] Silberzahn R, Uhlmann EL, Martin DP, et al. Many analysts, one dataset: Making transparent how variations in analytical choices affect results 2017.

[21] Chuard PJC, Vrtílek M, Head ML, et al. Evidence that nonsignificant results are sometimes preferred: Reverse P-hacking or selective reporting? PLoS Biol 2019;17:e3000127 10.1371/journal.pbio.3000127 [30682013]

[22] Michels KB, Rosner BA. Data trawling: to fish or not to fish. The Lancet 1996;348:1152–53 10.1016/S0140-6736(96)05418-9

[23] Data dredging - Wikipedia 2021. Available at: https://en.wikipedia.org/wiki/Data_dredging Accessed August 30, 2021.

[24] Berger ML, Sox H, Willke RJ, et al. Good Practices for Real-World Data Studies of Treatment and/or Comparative Effectiveness: Recommendations from the Joint ISPOR-ISPE Special Task Force on Real-World Evidence in Health Care Decision Making. Value Health 2017;20:1003–08 10.1016/j.jval.2017.08.3019 [28964430]

[25] Orsini LS, Monz B, Mullins CD, et al. Improving transparency to build trust in real-world secondary data studies for hypothesis testing-Why, what, and how: recommendations and a road map from the real-world evidence transparency initiative. Pharmacoepidemiol Drug Saf 2020;29:1504–13 10.1002/pds.5079 [32924243]

[26] Langan SM, Schmidt SA, Wing K, et al. The reporting of studies conducted using observational routinely collected health data statement for pharmacoepidemiology (RECORD-PE). BMJ 2018;363:k3532 10.1136/bmj.k3532 [30429167]

[27] Hernán MA, Sauer BC, Hernández-Díaz S, et al. Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses. Journal of Clinical Epidemiology 2016;79:70–75 10.1016/j.jclinepi.2016.04.014 [27237061]

[28] Rothman KJ, Greenland S. Causation and causal inference in epidemiology. Am J Public Health 2005;95 Suppl 1:S144-50 10.2105/AJPH.2004.059204 [16030331]

[29] Pearl J. An introduction to causal inference. The International Journal of Biostatistics 2010;6:Article 7 10.2202/1557-4679.1203 [20305706]

[30] Hernán MA, Robins JM. Estimating causal effects from epidemiological data. J Epidemiol Community Health 2006;60:578–86 10.1136/jech.2004.029496 [16790829]

[31] Hernán MA. A definition of causal effect for epidemiological research. J Epidemiol Community Health 2004;58:265–71 10.1136/jech.2002.006361 [15026432]

[32] Belas N. P-hacking in Clinical Trials: A Meta-Analytical Approach ;

[33] Hripcsak G, Suchard MA, Shea S, et al. Comparison of Cardiovascular and Safety Outcomes of Chlorthalidone vs Hydrochlorothiazide to Treat Hypertension. JAMA Internal Medicine 2020 10.1001/jamainternmed.2019.7454 [32065600]

[34] Nyström T, Bodegard J, Nathanson D, et al. Second line initiation of insulin compared with DPP-4 inhibitors after metformin monotherapy is associated with increased risk of all-cause mortality, cardiovascular events, and severe hypoglycemia. Diabetes Research and Clinical Practice 2017;123:199–208 10.1016/j.diabres.2016.12.004 [28056431]

[35] Gerstein HC, Bosch J, Dagenais GR, et al. Basal insulin and cardiovascular and other outcomes in dysglycemia. N Engl J Med 2012;367:319–28 10.1056/NEJMoa1203858 [22686416]

[36] Concato J, Shah N, Horwitz RI. Randomized, controlled trials, observational studies, and the hierarchy of research designs. The New England journal of medicine 2000;342:1887–92 10.1056/nejm200006223422507

[37] Ioannidis JP, Haidich AB, Pappa M, et al. Comparison of evidence of treatment effects in randomized and nonrandomized studies. JAMA 2001;286:821–30 ;

[38] Benson K, Hartz AJ. A comparison of observational studies and randomized, controlled trials. New Engl J Med 2000;342:1878–86 10.1056/NEJM200006223422506 [10861324]

[39] Banerjee R, Prasad V. Are Observational, Real-World Studies Suitable to Make Cancer Treatment Recommendations? JAMA Netw Open 2020;3:e2012119 10.1001/jamanetworkopen.2020.12119 [32729916]

[40] Concato J. Observational versus experimental studies: what's the evidence for a hierarchy? NeuroRx the journal of the American Society for Experimental NeuroTherapeutics 2004;1:341–47 10.1602/neurorx.1.3.341

[41] Dahabreh IJ, Kent DM. Can the Learning Health Care System Be Educated With Observational Data? JAMA 2014;312:129–30 10.1001/jama.2014.4364

[42] Gerstein HC, McMurray J, Holman RR. Real-world studies no substitute for RCTs in establishing efficacy. The Lancet 2019;393:210–11 10.1016/s0140-6736(18)32840-x

[43] Kumar A, Guss ZD, Courtney PT, et al. Evaluation of the Use of Cancer Registry Data for Comparative Effectiveness Research. JAMA Netw Open 2020;3:e2011985 10.1001/jamanetworkopen.2020.11985 [32729921]

[44] Naudet F, Maria AS, Falissard B. Antidepressant response in major depressive disorder: a meta-regression comparison of randomized controlled trials and observational studies. PLoS ONE 2011;6:e20811 10.1371/journal.pone.0020811 [21687681]

[45] Oliver S, Bagnall AM, Thomas J, et al. Randomised controlled trials for policy interventions: a review of reviews and meta-regression. Health Technol Assess 2010;14:1-165, iii 10.3310/hta14160 [20338119]

[46] Papanikolaou PN, Christidi GD, Ioannidis JPA. Comparison of evidence on harms of medical interventions in randomized and nonrandomized studies. CMAJ 2006;174:635–41 10.1503/cmaj.050873 [16505459]

[47] Shikata S, Nakayama T, Noguchi Y, et al. Comparison of effects in randomized controlled trials with observational studies in digestive surgery. Ann Surg 2006;244:668–76 10.1097/01.sla.0000225356.04304.bc [17060757]

[48] Golder S, Loke YK, Bland M. Meta-analyses of adverse effects data derived from randomised controlled trials as compared to observational studies: methodological overview. PLOS Medicine 2011;8:e1001026 10.1371/journal.pmed.1001026 [21559325]

[49] Kuss O, Legler T, Börgermann J. Treatments effects from randomized trials and propensity score analyses were similar in similar populations in an example from cardiac surgery. Journal of Clinical Epidemiology 2011;64:1076–84 10.1016/j.jclinepi.2011.01.005 [21482068]

[50] Bhandari M, Tornetta P, Ellis T, et al. Hierarchy of evidence: differences in results between non-randomized studies and randomized trials in patients with femoral neck fractures. Arch Orthop Trauma Surg 2004;124:10–16 10.1007/s00402-003-0559-z [14576955]

[51] Edwards JP, Kelly EJ, Lin Y, et al. Meta-analytic comparison of randomized and nonrandomized studies of breast cancer surgery. Can J Surg 2012;55:155–62 10.1503/cjs.023410 [22449722]

[52] Furlan AD, Tomlinson G, Jadad AAR, et al. Examining heterogeneity in meta-analysis: comparing results of randomized trials and nonrandomized studies of interventions for low back pain. Spine (Phila Pa 1976) 2008;33:339–48 10.1097/BRS.0b013e31816233b5 [18303468]

[53] Müeller D, Sauerland S, Neugebauer EAM, et al. Reported effects in randomized controlled trials were compared with those of nonrandomized trials in cholecystectomy. Journal of Clinical Epidemiology 2010;63:1082–90 10.1016/j.jclinepi.2009.12.009 [20346627]

[54] Tannen RL, Weiner MG, Xie D. Use of primary care electronic medical record database in drug efficacy research on cardiovascular outcomes: comparison of database and randomised controlled trial findings. BMJ 2009;338:b81 10.1136/bmj.b81 [19174434]

[55] Dahabreh IJ, Sheldrick RC, Paulus JK, et al. Do observational studies using propensity score methods agree with randomized trials? A systematic comparison of studies on acute coronary syndromes. Eur. Heart J. 2012;33:1893–901 10.1093/eurheartj/ehs114

[56] Lonjon G, Boutron I, Trinquart L, et al. Comparison of treatment effect estimates from prospective nonrandomized studies with propensity score analysis and randomized controlled trials of surgical procedures. Ann Surg 2014;259:18–25 10.1097/SLA.0000000000000256

[57] Anglemyer A, Horvath HT, Bero L. Healthcare outcomes assessed with observational study designs compared with those assessed in randomized trials. Cochrane Database Syst Rev 2014:MR000034 10.1002/14651858.MR000034.pub2 [24782322]

[58] Califf RM, Hernandez AF, Landray M. Weighing the Benefits and Risks of Proliferating Observational Treatment Assessments: Observational Cacophony, Randomized Harmony. JAMA 2020;324:625–26 10.1001/jama.2020.13319 [32735313]

[59] Rush CJ, Campbell RT, Jhund PS, et al. Association is not causation: treatment effects cannot be estimated from observational data in heart failure. Eur Heart J 2018;39:3417–38 10.1093/eurheartj/ehy407 [30085087]

[60] Soni PD, Hartman HE, Dess RT, et al. Comparison of Population-Based Observational Studies With Randomized Trials in Oncology. JCO 2019;37:1209–16 10.1200/JCO.18.01074 [30897037]

[61] Klassen SA, Senefeld J, Johnson PW, et al. The Effect of Convalescent Plasma Therapy on COVID-19 Patient Mortality: Systematic Review and Meta-analysis. medRxiv 2021 10.1101/2020.07.29.20162917 [33140056]

[62] Janiaud P, Axfors C, Schmitt AM, et al. Association of Convalescent Plasma Treatment With Clinical Outcomes in Patients With COVID-19: A Systematic Review and Meta-analysis. JAMA 2021;325:1185–95 10.1001/jama.2021.2747 [33635310]