Novel Trial Design in Sepsis

  • Christopher W. Seymour
  • Derek C. Angus


  • Large, randomized clinical trials in sepsis have found few successful therapeutics in the past decade.

  • Traditional randomized trials of novel therapies, both in sepsis and in other fields, typically test a single drug or intervention in a single, and often narrowly defined, patient population, randomizing patients evenly to intervention versus control.

  • Newer designs in other fields have incorporated features to improve efficiency, such as the testing of multiple agents with a common control arm, the testing of a single agent within different patient subgroups, or the testing of agents within patients with different diseases but common mechanisms of action. Other features include randomization schemes that adapt over time, typically using Bayesian inference rules, to preferentially assign better performing agents within different subgroups.

  • These designs may be ideal to test new precision interventions in sepsis phenotypes, although rapid patient phenotyping will be required to enable more sophisticated randomization schemes.

  • Electronic health records found in many large healthcare systems are well-positioned to help deploy adaptive trials with point-of-care efficiency.


Disease heterogeneity Phenotype Response-adaptive randomization Enrichment Adaptive trial Platform trial Basket trial Umbrella trial Embedded 


  1. 1.
    Czura CJ. “Merinoff symposium 2010: sepsis”—speaking with one voice. Mol Med. 2011;17(1–2):2–3.PubMedPubMedCentralGoogle Scholar
  2. 2.
    Kellum JA, Kong L, Fink MP, Weissfeld LA, Yealy DM, Pinsky MR, et al. Understanding the inflammatory cytokine response in pneumonia and sepsis: results of the Genetic and Inflammatory Markers of Sepsis (GenIMS) Study. Arch Intern Med. 2007;167(15):1655–63.CrossRefGoogle Scholar
  3. 3.
    Huang DT, Angus DC, Barnato A, Gunn SR, Kellum JA, Stapleton DK, et al. Harmonizing international trials of early goal-directed resuscitation for severe sepsis and septic shock: methodology of ProCESS, ARISE, and ProMISe. Intensive Care Med. 2013;39(10):1760–75.CrossRefGoogle Scholar
  4. 4.
    Angus DC, van der Poll T. Severe sepsis and septic shock. N Engl J Med. 2013;369(21):2063.PubMedGoogle Scholar
  5. 5.
    Boomer JS, To K, Chang KC, Takasu O, Osborne DF, Walton AH, et al. Immunosuppression in patients who die of sepsis and multiple organ failure. JAMA. 2011;306(23):2594–605.CrossRefGoogle Scholar
  6. 6.
    Medzhitov R, Schneider DS, Soares MP. Disease tolerance as a defense strategy. Science. 2012;335(6071):936–41.CrossRefGoogle Scholar
  7. 7.
    Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The third international consensus definitions for sepsis and septic shock (sepsis-3). JAMA. 2016;315(8):801–10.CrossRefGoogle Scholar
  8. 8.
    Seymour CW, Liu VX, Iwashyna TJ, Brunkhorst FM, Rea TD, Scherag A, et al. Assessment of clinical criteria for sepsis: for the third international consensus definitions for sepsis and septic shock (sepsis-3). JAMA. 2016;315(8):762–74.CrossRefGoogle Scholar
  9. 9.
    Christiansen CF, Christensen S, Johansen MB, Larsen KM, Tonnesen E, Sorensen HT. The impact of pre-admission morbidity level on 3-year mortality after intensive care: a Danish cohort study. Acta Anaesthesiol Scand. 2011;55(8):962–70.PubMedGoogle Scholar
  10. 10.
    Clermont G, Bartels J, Kumar R, Constantine G, Vodovotz Y, Chow C. In silico design of clinical trials: a method coming of age. Crit Care Med. 2004;32(10):2061–70.CrossRefGoogle Scholar
  11. 11.
    Sprung CL, Annane D, Keh D, Moreno R, Singer M, Freivogel K, et al. Hydrocortisone therapy for patients with septic shock. N Engl J Med. 2008;358(2):111–24.CrossRefGoogle Scholar
  12. 12.
    Seymour CW, Gomez H, Chang CH, Clermont G, Kellum JA, Kennedy J, et al. Precision medicine for all? Challenges and opportunities for a precision medicine approach to critical illness. Crit Care. 2017;21(1):257.CrossRefGoogle Scholar
  13. 13.
    Wong HR, Sweeney TE, Hart KW, Khatri P, Lindsell CJ. Pediatric sepsis endotypes among adults with sepsis. Crit Care Med. 2017;45:e1289–91.CrossRefGoogle Scholar
  14. 14.
    Scicluna BP, van Vught LA, Zwinderman AH, Wiewel MA, Davenport EE, Burnham KL, et al. Classification of patients with sepsis according to blood genomic endotype: a prospective cohort study. Lancet Respir Med. 2017;5(10):816–26.CrossRefGoogle Scholar
  15. 15.
    Iwashyna TJ, Burke JF, Sussman JB, Prescott HC, Hayward RA, Angus DC. Implications of heterogeneity of treatment effect for reporting and analysis of randomized trials in critical care. Am J Respir Crit Care Med. 2015;192(9):1045–51.CrossRefGoogle Scholar
  16. 16.
    Bos LD, Schouten LR, van Vught LA, Wiewel MA, Ong DSY, Cremer O, et al. Identification and validation of distinct biological phenotypes in patients with acute respiratory distress syndrome by cluster analysis. Thorax. 2017;72(10):876–83.CrossRefGoogle Scholar
  17. 17.
    Famous KR, Delucchi K, Ware LB, Kangelaris KN, Liu KD, Thompson BT, et al. Acute respiratory distress syndrome subphenotypes respond differently to randomized fluid management strategy. Am J Respir Crit Care Med. 2017;195(3):331–8.PubMedPubMedCentralGoogle Scholar
  18. 18.
    Rhee C, Dantes R, Epstein L, Murphy DJ, Seymour CW, Iwashyna TJ, et al. Incidence and Trends of Sepsis in US Hospitals Using Clinical vs Claims Data, 2009-2014. JAMA. 2017;318:1241–9.CrossRefGoogle Scholar
  19. 19.
    Cohen J, Vincent JL, Adhikari NK, Machado FR, Angus DC, Calandra T, et al. Sepsis: a roadmap for future research. Lancet Infect Dis. 2015;15(5):581–614.CrossRefGoogle Scholar
  20. 20.
    Mebazaa A, Laterre PF, Russell JA, Bergmann A, Gattinoni L, Gayat E, et al. Designing phase 3 sepsis trials: application of learned experiences from critical care trials in acute heart failure. J Intensive Care. 2016;4:24.CrossRefGoogle Scholar
  21. 21.
    Opal SM, Laterre PF, Francois B, LaRosa SP, Angus DC, Mira JP, et al. Effect of eritoran, an antagonist of MD2-TLR4, on mortality in patients with severe sepsis: the ACCESS randomized trial. JAMA. 2013;309(11):1154–62.CrossRefGoogle Scholar
  22. 22.
    Opal SM, Fisher CJ Jr, Dhainaut JF, Vincent JL, Brase R, Lowry SF, et al. Confirmatory interleukin-1 receptor antagonist trial in severe sepsis: a phase III, randomized, double-blind, placebo-controlled, multicenter trial. The Interleukin-1 Receptor Antagonist Sepsis Investigator Group. Crit Care Med. 1997;25(7):1115–24.CrossRefGoogle Scholar
  23. 23.
    Carcillo JA, Halstead ES, Hall MW, Nguyen TC, Reeder R, Aneja R, et al. Three hypothetical inflammation pathobiology phenotypes and pediatric sepsis-induced multiple organ failure outcome. Pediatr Crit Care Med. 2017;18(6):513–23.CrossRefGoogle Scholar
  24. 24.
    Shakoory B, Carcillo JA, Chatham WW, Amdur RL, Zhao H, Dinarello CA, et al. Interleukin-1 receptor blockade is associated with reduced mortality in sepsis patients with features of macrophage activation syndrome: reanalysis of a prior phase III trial. Crit Care Med. 2016;44(2):275–81.CrossRefGoogle Scholar
  25. 25.
    The PRISM Investigators. Early, goal-directed therapy for septic shock—a patient-level meta-analysis. N Engl J Med. 2017;376:2223–34.CrossRefGoogle Scholar
  26. 26.
    Rhodes A, Evans LE, Alhazzani W, Levy MM, Antonelli M, Ferrer R, et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock: 2016. Intensive Care Med. 2017;43(3):304–77.CrossRefGoogle Scholar
  27. 27.
    Lewis RJ. The pragmatic clinical trial in a learning health care system. Clin Trials. 2016;13(5):484–92.CrossRefGoogle Scholar
  28. 28.
    Berry SM, Connor JT, Lewis RJ. The platform trial: an efficient strategy for evaluating multiple treatments. JAMA. 2015;313(16):1619–20.CrossRefGoogle Scholar
  29. 29.
    Meurer WJ, Lewis RJ, Berry DA. Adaptive clinical trials: a partial remedy for the therapeutic misconception? JAMA. 2012;307(22):2377–8.CrossRefGoogle Scholar
  30. 30.
    Huang X, Ning J, Li Y, Estey E, Issa JP, Berry DA. Using short-term response information to facilitate adaptive randomization for survival clinical trials. Stat Med. 2009;28(12):1680–9.CrossRefGoogle Scholar
  31. 31.
    Bartlett RH, Roloff DW, Cornell RG, Andrews AF, Dillon PW, Zwischenberger JB. Extracorporeal circulation in neonatal respiratory failure: a prospective randomized study. Pediatrics. 1985;76(4):479–87.PubMedGoogle Scholar
  32. 32.
    UK Collaborative ECMO Trail Group. UK collaborative randomised trial of neonatal extracorporeal membrane oxygenation. Lancet. 1996;348(9020):75–82.CrossRefGoogle Scholar
  33. 33.
    Administration FaD. Enrichment strategies for clinical trials to support approval of human drugs and biological products. Available at: https://www.fdagov/downloads/drugs/guidancecomplianceregulatoryinformation/guidances/ucm332181pdf. 2012.
  34. 34.
    Panacek EA, Marshall JC, Albertson TE, Johnson DH, Johnson S, MacArthur RD, et al. Efficacy and safety of the monoclonal anti-tumor necrosis factor antibody F(ab′)2 fragment afelimomab in patients with severe sepsis and elevated interleukin-6 levels. Crit Care Med. 2004;32(11):2173–82.CrossRefGoogle Scholar
  35. 35.
    Group CTS. Effects of enalapril on mortality in severe congestive heart failure. Results of the Cooperative North Scandinavian Enalapril Survival Study (CONSENSUS). N Engl J Med. 1987;316(23):1429–35.CrossRefGoogle Scholar
  36. 36.
    Chapman PB, Hauschild A, Robert C, Haanen JB, Ascierto P, Larkin J, et al. Improved survival with vemurafenib in melanoma with BRAF V600E mutation. N Engl J Med. 2011;364(26):2507–16.CrossRefGoogle Scholar
  37. 37.
    Berry SM, Petzold EA, Dull P, Thielman NM, Cunningham CK, Corey GR, et al. A response adaptive randomization platform trial for efficient evaluation of Ebola virus treatments: a model for pandemic response. Clin Trials. 2016;13(1):22–30.CrossRefGoogle Scholar
  38. 38.
    Berry DA. Adaptive clinical trials in oncology. Nat Rev Clin Oncol. 2012;9(4):199–207.CrossRefGoogle Scholar
  39. 39.
    Woodcock J, LaVange LM. Master protocols to study multiple therapies, multiple diseases, or both. N Engl J Med. 2017;377(1):62–70.CrossRefGoogle Scholar
  40. 40.
    Kim ES, Herbst RS, Wistuba II, Lee JJ, Blumenschein GR Jr, Tsao A, et al. The BATTLE trial: personalizing therapy for lung cancer. Cancer Discov. 2011;1(1):44–53.CrossRefGoogle Scholar
  41. 41.
    Heinrich MC, Joensuu H, Demetri GD, Corless CL, Apperley J, Fletcher JA, et al. Phase II, open-label study evaluating the activity of imatinib in treating life-threatening malignancies known to be associated with imatinib-sensitive tyrosine kinases. Clin Cancer Res. 2008;14(9):2717–25.CrossRefGoogle Scholar
  42. 42.
  43. 43.
    Angus DC. Fusing randomized trials with big data: the key to self-learning health care systems? JAMA. 2015;314(8):767–8.CrossRefGoogle Scholar
  44. 44.
    Randomized embedded multifactorial adaptive platform trial in community acquired pneumonia. Available from:

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Critical Care Medicine, The Clinical Research, Investigation, and Systems Modeling of Acute Illness (CRISMA) CenterUniversity of Pittsburgh School of MedicinePittsburghUSA

Personalised recommendations