Research Methodology for Rare Diseases Rare Disease Group 14:00 3 rd October 2012 Richard Lilford

Basic mechanisms of disease Incidence and prevalence over time and place Prognosis Diagnosis Research Methodology X X X X Treatment

What Do We Want When We Evaluate? Effects of Treatment Precision Accuracy+

What Does Precision Depend On? (In Frequentist Paradigm) Risk of false positive / negative trial results (α + β) Absolute difference (Δ) in event rates (binary outcome)

Sample Size Calculation – Examples Delta based on 25% improvement; alpha = 0.05; beta = 0.1 Control Event Rate (%) Sample Size (total – nearest 100) 401, , , ,000

Implications for Sample Size for Evaluations of Treatments for Rare Diseases (‘Optimistic’ 25% reduction in an event with 40% probability in the control group (α = 0.05, β = 0.1) Prevalence (per 1,000) Example (approximate) Total Population 50% ‘recruitment’ 10Rheumatoid arthritis / schizophrenia 100,000200,000 1Multiple Sclerosis1,000,0002,000, Cystic Fibrosis (Europeans)2,000,0004,000, Huntington’s Disease10,000,00020,000, Wilson’s Disease50,000,000100,000,000

Rare Diseases: You Are Not Alone! Diagnostic tests Sub-groups (personalised medicine) Rare variants of common diseases

Diagnostic / Screening Tests Population Prevalence: Test Positive + Disease Positive Treatment effect Prior ProbabilityPosterior ProbabilityContingent Probability Initial Sample Test Positive Test Positive + Disease Treatment Effect Risk Attributable Risk

Example: Diagnostic Test Suppose a disease has a prevalence of 10%, We want to detect an improvement in sensitivity of 10%. Death rate 50% if detected late, and 25% if detected early. Disease Present (%) Detected Early Detected Late DeathsDifference New Test Old Test

Rare Diseases: You Are Not Alone! Diagnostic tests Sub-groups (personalised medicine) Rare variants of common diseases

Genetic analysis can identify those patients who will benefit from a given drug Giaccone G, et al. J Clin Oncol. 2004;22: Mok T, et al. N Engl J Med 2009;361: Gefitinib no more effective than placebo in non-stratified population Gefitinib more effective than standard treatment if EGFR+ Gefitinib less effective than standard treatment if EGFR-

Rare Diseases: You Are Not Alone! Diagnostic tests Sub-groups (personalised medicine) Rare variants of common diseases

Panoramic Meta-Analysis Hemming et al. Stat Med. 2012; 31(3): Bowater et al. Ann Surg. 2009; 249: Adjuvant Chemotherapy Bowater et al. Ann Surg Oncol. 2012; 19(11):

What to do in Cases of Rare Diseases? Non-terminal events: 1.Cross over studies 2.n = 1 trials Terminal events: 1.Adaptive designs (Chow & Chang. Orphanet J Rare Dis 2008; 3: 11) 2.α = β > 0.05 (Lilford & Johnson. NEJM 1990; 322: 780-1) 3.Bayesian methods

Factors Influencing Belief 1.THE DATA – Size of effect observed Precision Accuracy 2.‘PRIOR’ BELIEF

Posterior odds (of disease) = prior odds X L R Posterior odds (of null hypothesis) = prior odds X L R Prob test +ve given disease Prob test +ve given no disease Prob data given alternative hypothesis Prob data given null

Clinical trials and rare diseases: a way out of a conundrum. Lilford RJ, Thornton JG, Braunholtz D. BMJ 1995; 311: Rare diseases and the assessment of intervention: What sorts of clinical trials can we use? Wilcken B. J Inherit Metab Dis 2001; 24(2): Strategy for randomised clinical trials in rare cancers. Tan S-B, et al. BMJ 2003; 327:47. Evidence-based medicine for rare diseases: Implications for data interpretation and clinical trial design. Behera M, et al. Cancer Control 2007; 14(2): Clinical research for rare disease: Opportunities, challenges, and solutions. Griggs RC, et al. Mol Genet Metab 2009; 96(1): A framework for applying unfamiliar trial designs in studies of rare diseases. Gupta S, et al. J Clin Epidemiol 2011; 64(10): Trials in rare diseases: The need to think differently. Billingham L, et al. Trials 2011; 12(s1): a107.

Current Conception of Clinical Trials Clinical trials and rare diseases: a way out of a conundrum. Lilford RJ, Thornton JG, Braunholtz D. BMJ 1995; 311:

Interaction Between Prior Beliefs, Surrogate Outcomes, and Mortality Data from a Bayesian Viewpoint.

Are Underpowered Trials Unethical? Edwards et al. Lancet. 1997; 350: