Presentation on theme: "Inclusion and Exclusion Criteria (Defining the Study Population) General considerations Run-in periods (enrichment) Regression toward the mean."— Presentation transcript:
Inclusion and Exclusion Criteria (Defining the Study Population) General considerations Run-in periods (enrichment) Regression toward the mean
Some Issues in Selecting Patients for Clinical Trials Broad or narrow criteria Recruitment and patient logs Nature of clinical sites (patient to research or research to patients)
Relationship of Study Sample to Study Population and Population at Large Population at Large Population without Condition Population with Condition With Condition but Ineligible Study Population Eligible but not Enrolled Study Sample Source: Friedman, Furberg and DeMets. Definition of Condition Entry Criteria Enrollment
Internal and External Validity Internal validity – can you attribute the differences among treatment groups to the treatments studied –Randomization –Blinding –Sample size –Random and systematic errors minimized External validity – can you generalize the results to patients outside the trial (the same or larger target population); to whom to the results apply? –Inclusion criteria –Characteristics of those randomized –Setting of trial –Outcomes assessed and duration of follow-up
The Study Population is Defined by Inclusion and Exclusion Criteria Eligibility Criteria: – Should be defined in advance – No exceptions should be made unless a priori stated –Characterize population (e.g., labeling indication for a new drug/device) Impact of results (assessment by others) Replication of study
Considerations in Developing Eligibility Criteria 1.Enroll patients who have potential to benefit from intervention 2.Enroll patients for whom there is a high probability of detecting results of intervention 3.Do not enroll patients to whom intervention is potentially harmful 4.Do not enroll patients at high risk of conditions which preclude ascertainment of endpoints 5.Do not enroll patients who cannot comply with protocol Friedman, Furberg, DeMets: Fundamentals of Clinical Trials, Chapter 4
Selection of Patients for a Trial Drug clearly indicated based on current knowledge Exclude Drug effect unknown: –But likely to be beneficial to certain patients Include* –And outcome uncertain in certain patients ? Include –But theoretical possibility of harm or little hope ?? Include* of benefit Special exclusions (competing risk, poor Exclude compliance, inability to ascertain endpoint) Drug contraindicated based on current knowledge Exclude Yusuf et al., Stat Med, 9:73-86, *Include such patients with explicit prior statement of a subgroup hypothesis
Advantages and Disadvantages of Opposing Selection Strategies Highly restrictive selection criteria Advantages –Provides more precise comparison of the test and control treatments –Results of the trial less likely to be affected by population variability Disadvantages –Increases the cost and time required for patient recruitment –Limits the generalizability of the study findings Minimally restrictive selection criteria Advantages –Makes patient recruitment easier –Provides base for wider generalization of findings Disadvantages –May obscure treatment effects because of variability in composition of study population –Results of the trial may be confusing, especially if an observed effect appears to be associated with a subgroup of patients in the study and the subgroup is too small to yield a reliable treatment comparison Meinert C., Clinical Trials. Design, Conduct and Analysis.
Usually Favor Minimal Restrictions for Large Outcome Trials A priori, often not clear who will do best Rare that there are large subgroup differences of a qualitative nature Faster answer to question With few restrictions, risk stratification after the trial is completed can be performed (more information to formulate treatment guidelines; cannot assess consistency of results in a subgroup if they were excluded)
Does it Work? “Practical Clinical Trials: Increasing the Value of Clinical Research for Decision Making in Clinical and Health Policy” Treatments that mimic use in practice Diverse patient population; minimal exclusions Many clinical sites; heterogeneous practice settings Multiple, easily ascertained, clinically relevant endpoints Tunis SR et al, JAMA Center for Medicare and Medicaid Services and Agency for Healthcare Research and Quality
Explanatory and Pragmatic Trials Explanatory (“laboratory” conditions) –Strict selection criteria aimed at creating a homogenous patient population Pragmatic (“normal” conditions) –Heterogeneous patient population, one where might expect more non-adherence Schwartz & Lellouch J Chronic Dis 1967)
Recruitment Considerations Always more difficult than anticipated (need a backup plan to the backup plan) Easier with broad eligibility criteria (e.g., large simple trials) Yield not 100% –Eligibility criteria (age, prior history, prior treatment, etc.) –Exclusion criteria –Physician refusal –Patient refusal MRFIT screened 361,662 men to identify 12,866 Must closely monitor to ensure target is met
Patient Logs Should You Count Those Not Included? Possible Advantages May provide insights on how to improve slow enrollment May allow more reasonable recommendations concerning findings – generalizability Allows an assessment of how many eligible patients are being enrolled Disadvantages Time-consuming Often uncertain where the counting starts Issue of generalizability usually cannot be addressed with logs alone
Randomized Trial of Extracranial-Intracranial Arterial Bypass Patients Undergoing Randomization versus Patients Operated on Outside of the Trial in 57 of 71 Participating Centers United States30/ Europe15/ Japan12/ Canada5*9484? TOTAL Location No. of Centers Surveyed/Total Randomized to Medical Treatment Randomized to Surgery Operated on Outside the Trial no. of patients *These centers were not surveyed; randomization was assumed to have been complete. Sundt, TM. N Eng J Med 316:814-16, 1987.
MRFIT Recruitment 22 centers (specially funded to carry out the study) Sources of 12,866 participants (no. centers using source) –Census tract listings (door-to-door) (3) –Industry/government (15) –HMOs (2) –Union lists (10) –Churches (7) –Shopping centers (10) –Civic clubs (8) –Other (14)
ESPRIT HIV – IL clinical sites 25 countries 4,150 patients ELITE II CHF – Losartan 288 sites 45 countries 3,152 patients Some trials require many sites and different types of sites
Advantages of Multi-Center Trials SAMPLE SIZE! Faster enrollment and therefore faster answer to the research question External validity (generalizability) – diversity of patients – convenience to patients – diversity of clinical sites Credibility (each site is a replicate) More clinicians involved in research
Run-in Periods Def. A period before randomization in which patients are given a treatment (active or placebo) to establish eligibility. Run-ins involve compromises between internal and external validity and are often considered for reasons of efficiency. Pablo-Mendez A, JAMA 1998
Rationale for Run-In Periods 1.Expected compliance is low; 2.Substantial behavior change is required (SNaP); 3.Contact with participants is infrequent (Physician’s Health Study); 4.Possibility of side effects to experimental treatment; 5.A large number of “placebo responders” are expected (e.g., pain study); 6.It is necessary to assure disease status is stable (or washout); 7.Efficacy of treatment on intermediate response variables is required, thereby enhancing clinical applicability (CAST). May be active or placebo; generally considered when:
ITT and Run-Ins If the primary interest (primary estimand) is the difference in outcome between treatment and control groups among patients who can tolerate the treatment, it is better to use a run-in period and ITT analysis than to try and estimate this estimand using only the patients who tolerated the treatment after randomization.
Run-In Periods in Trials - Examples To enhance clinical applicability (CAST) To screen for placebo response (pindolol + fluoxetine versus placebo + fluoxetine for depression) To assess tolerability of active treatment (carvedilol for the treatment of heart failure) To screen for non-adherence (Physician’s Health Study used carotene placebo and open-label aspirin during run- in) All have the potential to increase power or reduce sample size requirements
Potential Problems with Run-In Periods Carryover effects Blinding jeopardized Interpretation of results have to be qualified Strategy for enrichment wrong Leber PD and Davis CS, Cont Clin Trials 1998
Enrichment Designs Enrichment designs refers to studies that aim to increase power by choosing patients that are more likely to show benefit than a broader population (personalized medicine). –In heart failure and hypertension – initial studies were in more advance patients –Active run-in periods (e.g. CAST) or randomized withdrawal studies –Biomarkers and genetic traits that predict response (e.g., expression of HER-2 in tumors in women with metastatic breast cancer) Temple R, Commun Statist Theory Meth, 1994
An Example of Enrichment That Backfired Tacrine for the treatment of Alzheimer’s disease (N Engl J Med 1992;327: ) –Patients first randomized to 2 doses of tacrine (10 or 20 mg four times a day) or placebo (titration or enrichment phase) for 6 weeks (crossover). –Following 2 week placebo washout period, responders in first phase randomized to their best dose or placebo for 6 weeks (parallel group). –This was followed by an active treatment phase (uncontrolled). Concerns: Carryover effects, withdrawal effects, maintenance of blind, and generalizability See also Leber and Davis, Cont Clin Trials, 1998 and Encyclopedia of Biopharmaceutical Statistics
Factors Influencing Efficiency of Targeted Therapy (Enrichment) Design Heterogeneity of effect across subgroups (e.g., test positive patients expected to do much better than test-negative patients) Prevalence of factor describing responder group Sensitivity and specificity of test to define the responders There is often uncertainty. Thus, may first have to determine efficacy of treatment in both test-positive and test negative patients. Maitournam and Simon, Stat Med 2005
Summary In most trials eligibility requirements are too restrictive (an opinion) Arguments concerning logs versus no logs arise because of restrictions Trial entry procedures are simplified with broad inclusion criteria Study design teams should carefully consider reasons for exclusion Exemptions should not be granted We need to determine way of efficiently involving more clinicians in the community in research There are advantages and disadvantages to run-ins and enrichment designs. The latter are being actively pursued as part of a “personalized medicine” research agenda.