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Cited by 52Statistical Methods in Clinical TrialsSepsis Diagnosis and TreatmentVitamin C and Antioxidants Research

Arguing for Adaptive Clinical Trials in Sepsis

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Talisa, Victor B., Yende, Sachin, Seymour, Christopher W., Angus, Derek C.·2018·Frontiers in Immunology
DOI 10.3389/fimmu.2018.01502PMC PMC6031704
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Abstract

Sepsis is life-threatening organ dysfunction due to dysregulated response to infection. Patients with sepsis exhibit wide heterogeneity stemming from genetic, molecular, and clinical factors as well as differences in pathogens, creating challenges for the development of effective treatments. Several gaps in knowledge also contribute: (i) biomarkers that identify patients likely to benefit from specific treatments are unknown; (ii) therapeutic dose and duration is often poorly understood; and (iii) short-term mortality, a common outcome measure, is frequently criticized for being insensitive. To date, the majority of sepsis trials use traditional design features, and have largely failed to identify new treatments with incremental benefit over standard of care. Traditional trials are also frequently conducted as part of a drug evaluation process that is segmented into several phases, each requiring separate trials, with a long time delay from inception through design and execution to incorporation of results into clinical practice. By contrast, adaptive clinical trial designs facilitate the evaluation of several candidate treatments simultaneously, learn from emergent discoveries during the course of the trial, and can be structured efficiently to lead to more timely conclusions compared to traditional trial designs. Adoption of new treatments in clinical practice can be accelerated if these trials are incorporated in electronic health records as part of a learning health system. In this review, we discuss challenges in the evaluation of treatments for sepsis, and explore potential benefits and weaknesses of recent advances in adaptive trial methodologies to address these challenges.

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  • Early clinical recognition of sepsis can be challenging due to disease complexity and heterogeneity of the septic population.

    “Early clinical recognition of sepsis can be challenging.”

    From Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy (2020) · cites this paper as [10]

    The Introduction and “Sepsis Is Extremely Heterogeneous” section describe patient heterogeneity as a challenge for developing treatments and conducting trials, not for early clinical recognition. Searches for early recognition and diagnosis found no passage addressing whether clinicians have difficulty recognizing sepsis early. (LLM, conf=0.75)

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References 47 · Cited by 52

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Authors
Talisa, V. B., Yende, S., Seymour, C. W., & Angus, D. C.
Affiliations
University of Pittsburgh (US)
ORCID
Venue
Frontiers in Immunology
Publisher
Frontiers Media SA
Published
2018-06-28
Volume
9
Pages
1502-1502
ISSN
1664-3224 (ISSN-L)
DOI
10.3389/fimmu.2018.01502
PMC
PMC6031704
OpenAlex
W2809406588
Cited by
52
References
47
Citations by year
2026: 4 · 2025: 6 · 2024: 4 · 2023: 7 · 2022: 5 · 2021: 7 · 2020: 10 · 2019: 6 · 2018: 3
FWCI
0.90
Type
journal article
Language
en
Open access
Licence
Locations
  • Frontiers in Immunology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
National Institute of General Medical Sciences (R35GM119519)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Health Sciences › Medicine › Epidemiology › Sepsis Diagnosis and Treatment
  • Health Sciences › Nursing › Nutrition and Dietetics › Vitamin C and Antioxidants Research
Keywords
sepsis, adaptive trial design, patient heterogeneity, biomarkers, learning health systems, electronic health records, trial design limitations, drug development

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