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• Obviously the choice of delta has a big impact on sample size required to provide robust evidence of efficacy. Let’s consider some examples. On the x-axis, we have assumed success rates FOR BOTH ARMS On the y-axis we have the sample size necessary to provide the burden of proof that a desired level of similarity is met with high confidence So when the underlying success rate if 80% for both AC and new -- we would need about 100 pts per arm with a delta of 15, 250 per arm for a delta of 10 and 1000 per arm for a delta of 10% Note that sample size requirements go down as the success rate approaches 100% and increase as the success rate approaches 50%.
• Obviously the choice of delta has a big impact on sample size required to provide robust evidence of efficacy. Let’s consider some examples. On the x-axis, we have assumed success rates FOR BOTH ARMS On the y-axis we have the sample size necessary to provide the burden of proof that a desired level of similarity is met with high confidence So when the underlying success rate if 80% for both AC and new -- we would need about 100 pts per arm with a delta of 15, 250 per arm for a delta of 10 and 1000 per arm for a delta of 10% Note that sample size requirements go down as the success rate approaches 100% and increase as the success rate approaches 50%.
• ### Transcript

• 1. Issues in Selection of Deltas in Non-Inferiority Trials : Acute Bacterial Meningitis and Hospital-Acquired Pneumonia John H. Powers, M.D. Medical Officer Division of Special Pathogen and Immunologic Drug Products Center for Drug Evaluation and Research U.S. Food and Drug Administration
• 2. Introduction
• Clinical perspective on delta
• definition of delta and components
• impact of deltas in clinical setting
• Delta 1 issues in acute bacterial meningitis and HAP
• data from pre-antibiotic and antibiotic eras
• confounders in determining efficacy of control regimens
• Delta 2 issues with acute bacterial meningitis and HAP
• consequences of less effective therapy
• practical issues in selecting delta
• 3. Clinical Trials
• Purpose of clinical trials
• Distinguish effects of drug from other influences
• spontaneous change in course of disease
• placebo effect
• biased observations
• difficult for clinicians to make judgments on drug efficacy/safety outside of setting of clinical trial
• high spontaneous resolution rate in less serious diseases
• confounding factors for lack of patient improvement in serious diseases
• lack of direct comparison of safety of two drugs in similar patient population
• 4. Non-Inferiority Trials
• Non-inferiority trials attempt to prove test drug is not inferior to control drug by some margin
• cannot statistically prove two drugs are identical in efficacy
• need some way to estimate the variability around the difference between two treatments
• Non-inferiority margin (delta) = maximum degree of inferiority of test drug compared to control drug that trial will attempt to exclude statistically
• specified prior to initiation of trial
• 5. Non-Inferiority Margins
• After completion of trial:
• 1) calculate difference in point estimates of efficacy
• of test agent minus control agent
• 2) calculate 95% confidence interval around difference in point estimates
• gives some idea of variability around the estimate in the differences
• 3) compare lower bound of 95% CI to pre-specified non-inferiority margin
-20% +20% -8% -15%
• 6. Components of Delta
• Delta 1
• conservative estimate of advantage of active control over placebo
• data-based
• Delta 2
• largest clinically acceptable difference between active control and experimental drug
• judgement based on consequences to patients of treatment failure
• overall delta for clinical trial smaller of the two values
• if delta 1 is large, overall delta set by delta 2
• 7. Components of Delta - Delta 1
• Historically-based data
• Do we really know what we think we know?
• lack of data from pre-antibiotic era
• change in resistance patterns and epidemiology of organisms
• differing response rates in sub- populations
• changes in practice of medicine
• problems with defining patients with bacterial infection vs. non-bacterial/non-infectious causes
• different definitions of success and failure in current trials compared to previous mortality-based trials
• 8. Components of Delta - Delta 2
• Judgement based “acceptable loss” relative to current therapy
• ideal situation
• smaller delta for more severe disease
• less loss relative to current therapy given potential for greater overall morbidity/mortality
• larger delta for less severe disease
• greater loss relative to current therapy may not translate into as great a consequence for patients
• BUT we don’t live in an ideal world
• practicalities of performing clinical trials
• 9. Components of Delta - various diseases
• Acute bacterial meningitis
•  1 = magnitude of advantage over placebo well-known AND large
•  2 = decision on “acceptable loss”
• Hospital-acquired pneumonia
•  1 = magnitude of advantage over placebo not as clear
•  2 = decision on “acceptable loss”
• Acute exacerbations of chronic bronchitis
•  1 = advantage over placebo unclear (and small?)
•  2 = decision on acceptable loss not as critical
• 10. Components of Delta Meningitis and HAP
• Delta 1 - important questions
• Q1: What is the magnitude of benefit of any antibiotic therapy over placebo?
• Q2: Is the benefit of antimicrobial therapy in current trials measured in the same way as in the original trials showing benefit?
• Q3: Is the magnitude of benefit of therapy over placebo large enough that it should not affect the selection of the overall delta for a trial?
• 11. Components of Delta Meningitis and HAP
• Delta 2
• Q: What is an “acceptable loss” of efficacy compared to accepted therapy in a serious disease ?
• Scientific considerations
• consequences of treatment failure in various patient subsets with meningitis or HAP
• Practical considerations
• effect of changes in delta on sample size as efficacy rate changes
• 12. Historical Data - Meningitis
• Acute bacterial meningitis highly lethal in pre-antibiotic era
• meningococcal disease most common and occurred in previously healthy young people
• overall mortality 70-90% without specific therapy
• mortality decreased to 30% with introduction of antimeningococcal serum
• Flexner S. J Exp Med 1913;17:553-76
• sulfanilamide treatment reduced mortality to 10% (9/11 patients survived in original series)
• Schwenker F et al. JAMA 1937;108:1407-8
• 13. Historical Data - Meningitis
• Problems with historical data
• different endpoints in current trials
• developmental, neurologic, audiologic sequelae as well as mortality
• different epidemiology
• pneumococcal meningitis most common now in U.S.
• different populations
• proportionately more older adults with meningitis since introduction of HIB vaccine
• Schuchat A et al. N Engl J Med 1997;337:970-6.
• 14. Historical Data - HAP
• Clinical entity of HAP not described in pre-antibiotic era
• only 2 spontaneous cures out of 151 cases in military recruits in S. aureus outbreaks in 1918
• few reports of gram-negative pneumonias
• How certain is diagnosis in these case reports?
• No way to compare antibiotic therapy to placebo
• 15.
• Celis R. Chest 93;318-24.1988
• 30.5% (33/108) all-cause mortality with “appropriate” antibiotics
• 91.6% (11/12) all-cause mortality with“inappropriate” antibiotics
• Alvarez-Lerma et al. Intensive Care Med 1996;22:387-94.
• 16.2% (36 /146)attributable mortality with “appropriate” antibiotics
• all-cause mortality 34.9% (51/146)
• 24.7% ( 46/284) attributable mortality with “inappropriate” antibiotics
• all-cause mortality 32.4% (92/284)
Historical Data - HAP
• 16. Historical Data - HAP
• Problems with historical data
• Difficulty in clinical diagnosis of HAP
• patients in study who do not have disease
• Change in nosocomial organisms over time
• changes in resistance patterns
• Different outcomes in various patient populations
• mechanically ventilated pts. Vs. others
• Death attributable to pneumonia vs. all-cause mortality
• Clinical endpoints other than mortality in current trials
• 17. Components of Delta Meningitis
• Delta 1 - important questions
• Q1: What is the magnitude of benefit of any antibiotic therapy over placebo?
• Appears as large as 60%-80% mortality benefit but magnitude of benefit on clinical parameters not as clear
• Q2: Is the benefit of antimicrobial therapy in current trials measured in the same way as in the original trials showing benefit?
• Yes and No
• Q3: Is the magnitude of benefit of therapy over placebo large enough that it should not affect the selection of the overall delta for a trial?
• Yes
• 18. Components of Delta HAP
• Delta 1 - important questions
• Q1: What is the magnitude of benefit of any antibiotic therapy over placebo?
• May be anywhere from 8.5%-60% depending on how and in whom it is measured. Unclear benefit on clinical parameters
• Q2: Is the benefit of antimicrobial therapy in current trials measured in the same way as in the original trials showing benefit?
• Yes and No
• Q3: Is the magnitude of benefit of therapy over placebo large enough that it should not affect the selection of the overall delta for a trial?
• Point for committee discussion
• 19. Components of Delta Meningitis and HAP
• Delta 2
• Q: What is an “acceptable loss” of efficacy compared to accepted therapy in a serious disease ?
• Scientific considerations
• consequences of treatment failure in various patient subsets with HAP
• Practical considerations
• effect of changes in delta on sample size as efficacy rate changes
• 20. Consequences of Failure
• Meningitis
• clear mortality benefit of antibiotic therapy
• morbidity is developmental, neurological and audiological sequelae
• what is magnitude of benefit of antibiotics?
• HAP
• mortality
• magnitude of benefit varies depending on how and in whom it is measured
• morbidity
• increased costs and hospital stay
• effect on rate of clinical resolution?
• 21. Practical Issues
• Effect of success rate and delta selection on sample size
• Selection of a smaller delta in more severe diseases with relatively lower success rates would increase sample size
• Is larger sample size practical given:
• 1) epidemiology of the disease
• 2) limitations of inclusion and exclusion criteria
• 3) inability to continue on randomized therapy in studies of severe disease
• 22. Clinical Trial Implications: Sample size per arm to achieve 80% power 
• 23. Epidemiology of Meningitis* *Based on 248 cases in 1995 from Schuchat et al. N Engl J Med. 1997;337:970-6.
• 24. Epidemiology of Meningitis
• Case fatality rates and incidence vary by organism
• H. influenzae lower case fatality rates than S. disease caused by S. pneumoniae
• S. pneumoniae now more common overall
• mortality rates in future trials may be higher than those in past given shift in epidemiology
• Number of cases in U.S. declining since introduction of HIB vaccine
• estimated 12,920 cases in 1986
• estimated 5,755 cases in 1995
• Schuchat et al. N Engl J Med 1997;337:970-76.
• 25. Epidemiology of HAP
• Actual incidence of HAP unclear (not a reportable illness)
• NNIS data estimates 250,000 cases/year in U.S.
• uses clinical definition of HAP
• estimated 1% of all patients entering hospital develop pneumonia
• 15-18% of all hospital acquired infections
• 2nd most common after UTI
• most common infection in ICU setting
• ICARE report. Am J Infect Control 1999;27:279-84.
• 26. Epidemiology
• Estimated U.S. cases per year (1994)
• acute otitis media 26,000,000
• acute sinusitis 23,000,000
• tonsillitis/pharyngitis 21,000,00
• pneumonia (community) 4,000,000
• hospital-acquired pneumonia 250,000
• acute bacterial meningitis <10,000
• acute bacterial endocarditis 10,000
• 27. Recent Trials
• Practical Points
• success rates in HAP trials in 50% - 70% range
• much larger sample size with smaller delta
• recent approvals with 20% delta based on 1992 guidance in all recent HAP trials
• theoretically a new drug could be as much as 20% less effective than comparator
• almost half of patients do not complete trial
• must take into account when planning sample size
• 28. Clinical Trial Implications: Sample size per arm to achieve 80% power 
• 29. Components of Delta Meningitis and HAP
• Delta 2
• Q: What is an “acceptable loss” of efficacy compared to accepted therapy in a serious disease ?
• serious nature of meningitis and HAP would seem to call for selection of smaller deltas
• smaller deltas would result in larger sample size of clinical trials - is this practical?
• balance with risk of accepting drugs which may be 20% less effective than currently approved therapy
• could be success rate of 40% for new drug for HAP
• 30. The Balance
• Risk to patients of accepting larger deltas, especially in more severe disease
• versus
• Realities of performing clinical trials