Bio‐creep in non‐inferiority clinical trials

Everson-Stewart, Siobhan; Emerson, Scott S.

doi:10.1002/sim.4053

Cited by 54 publications

(42 citation statements)

References 17 publications

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“…Everson-Stewart and Emerson (2010) assessed bio-creep by evaluating the rate of approving therapies that are no better than, or worse than, placebo, i.e. “ineffective” or “harmful” treatments (Everson-Stewart & Emerson 2010).…”

Section: Introductionmentioning

confidence: 99%

A Simulation Study Evaluating Bio-Creep Risk in Serial Noninferiority Clinical Trials for Preservation of Effect

Odem‐Davis

Fleming

2015

Statistics in Biopharmaceutical Research

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In non-inferiority trials, acceptable efficacy of an experimental treatment is established by ruling out some defined level of reduced effect relative to an effective active control standard. Serial use of non-inferiority trials may lead to newly approved therapies that provide meaningfully reduced levels of benefit; this phenomenon is called bio-creep. Simulations were designed to facilitate understanding of bio-creep risk when approval of an experimental treatment with efficacy less than some proportion of the effect of the active control treatment would constitute harm, such as when new antibiotics that are meaningfully less effective than the most effective current antibiotic would be used for treatment of Community-Acquired Bacterial Pneumonia. In this setting, risk of approval of insufficiently effective therapies may be great, even when the standard treatment effect satisfies constancy across trials. Modifiable factors contributing to this manifestation of bio-creep included the active control selection method, the non-inferiority margin, and bias in the active control effect estimate. Therefore, when non-inferiority testing is performed, the best available treatment should be used as the standard, and margins should be based on the estimated effect of this control, accounting for the variability and for likely sources of bias in this estimate, and addressing the importance of preservation of some portion of the standard’s effect.

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Section: Introductionmentioning

confidence: 99%

A Simulation Study Evaluating Bio-Creep Risk in Serial Noninferiority Clinical Trials for Preservation of Effect

Odem‐Davis

Fleming

2015

Statistics in Biopharmaceutical Research

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“…With respect to study implications and future trials, the metaanalysis results were robust in regard to analysis models and indicative of little interstudy heterogeneity (41). The primary efficacy endpoint in cUTI clinical trials has historically been the microbiological response at the follow-up visit, typically 5 to 9 days after the last treatment dose in the microbiological ITT population, which consists of all assigned subjects with microbiologically evaluable uropathogens at the baseline visit (13,14).…”

Section: Discussionmentioning

confidence: 88%

“…Application of this metric for the estimation of treatment effect would result in higher and more consistent estimates for doripenem (49.2%), levofloxacin (47.2%), and imipenem-cilastatin (48.7%). Debate exists in the literature for use of other alternative methods to estimate the antimicrobial treatment effect (41). The systematic review identified historical clinical trials of treatment effect as a proxy of placebo treatment effect.…”

Section: Discussionmentioning

confidence: 99%

Systematic Review and Meta-Analysis of Antimicrobial Treatment Effect Estimation in Complicated Urinary Tract Infection

Singh

Mitrani-Gold

et al. 2013

Antimicrob Agents Chemother

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bNoninferiority trial design and analyses are commonly used to establish the effectiveness of a new antimicrobial drug for treatment of serious infections such as complicated urinary tract infection (cUTI). A systematic review and meta-analysis were conducted to estimate the treatment effects of three potential active comparator drugs for the design of a noninferiority trial. The systematic review identified no placebo trials of cUTI, four clinical trials of cUTI with uncomplicated urinary tract infection as a proxy for placebo, and nine trials with reports of treatment effect estimates for doripenem, levofloxacin, or imipenem-cilastatin. In the meta-analysis, the primary efficacy endpoint of interest was the microbiological eradication rate at the test-of-cure visit in the microbiological intent-to-treat population. The estimated eradication rates and corresponding 95% confidence intervals (CI) were 31.8% (26.5% to 37.2%) for placebo, 81% (77.7% to 84.2%) for doripenem, 79% (75.9% to 82.2%) for levofloxacin, and 80.5% (71.9% to 89.1%) for imipenem-cilastatin. The treatment effect estimates were 40.5% for doripenem, 38.7% for levofloxacin, 34.7% for imipenem-cilastatin, and 40.8% overall. These treatment effect estimates can be used to inform the design and analysis of future noninferiority trials in cUTI study populations. Complicated urinary tract infections (cUTI) occur in persons with structural or functional abnormalities of the urinary tract and in hospitalized patients with significant medical or surgical comorbidities (1, 2). These infections are a major cause of hospital admission, morbidity, mortality, and excess health care costs (3-6). National and international treatment guidance for urinary tract infections includes recommendations for targeted and empirical treatment of the major causative pathogens, including Escherichia coli, Klebsiella pneumoniae, and non-Enterobacteriaceae organisms such as Pseudomonas aeruginosa (7-9).Of notable concern for the clinical care of patients with cUTI and other serious infections is effective antimicrobial treatment amid the emergence and spread of drug-resistant pathogens (10, 11). To demonstrate efficacy of a new or test antimicrobial agent for the treatment of adult subjects with cUTI, randomized parallel-group noninferiority phase 3 trials have traditionally been used to meet regulatory requirements for approval of the test drug (12). An active-comparator, noninferiority study design is generally used in cUTI trials given the ethical implications of placebo treatment (13,14). In order to conduct a noninferiority trial, an estimate of the treatment effect of the planned antimicrobial comparator must be obtained from historical data (12). Once an estimate of the treatment effect of the antimicrobial comparator is determined, the largest clinically acceptable difference of the test drug compared to the comparator must be decided. This decision is critical to the design, analysis, and interpretation of a noninferiority trial.We conducted a systematic review and me...

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“…''Being no worse than 5% worse than the effect of the active control'' also could be interpreted as trying to maintain at least 95% of the effect of the active control. However, there is a risk of so-called ''biocreep'' [16,18] (Fig. 3), which refers to the problem of having a new treatment B that is no worse than 5% of the current standard of care treatment A, and then comparing an even newer treatment C again by 5% with treatment B, and then treatment D with treatment C, and so on.…”

Section: Reason Explanationmentioning

confidence: 99%

Rationale for and Methods of Superiority, Noninferiority, or Equivalence Designs in Orthopaedic, Controlled Trials

Vavken

2011

Clinical Orthopaedics &Amp; Related Research

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Background To provide value-based healthcare in orthopaedics, controlled trials are needed to assess the comparative effectiveness of treatments. Typically comparative trials are based on superiority testing using statistical tests that produce a p value. However, as orthopaedic treatments continue to improve, superiority becomes more difficult to show and, perhaps, less important as margins of improvement shrink to clinically irrelevant levels. Alternative methods to compare groups in controlled trials are noninferiority and equivalence. It is important to equip the reader of the orthopaedic literature with the knowledge to understand and critically evaluate the methods and findings of trials attempting to establish superiority, noninferiority, and equivalence. Questions/purposes I will discuss supplemental and alternative methods to superiority for assessment of the outcome of controlled trials in the context of diminishing returns on new therapies over old ones. Methods The three methods-superiority, noninferiority, and equivalence-are presented and compared, with a discussion of implied pitfalls and problems.

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Bio‐creep in non‐inferiority clinical trials

Cited by 54 publications

References 17 publications

A Simulation Study Evaluating Bio-Creep Risk in Serial Noninferiority Clinical Trials for Preservation of Effect

A Simulation Study Evaluating Bio-Creep Risk in Serial Noninferiority Clinical Trials for Preservation of Effect

Systematic Review and Meta-Analysis of Antimicrobial Treatment Effect Estimation in Complicated Urinary Tract Infection

Rationale for and Methods of Superiority, Noninferiority, or Equivalence Designs in Orthopaedic, Controlled Trials

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