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Smarts: Part I

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Smarts: Part I SMARTs: Part I Eric B. Laber Department of Statistics, North Carolina State University April 2019 SAMSI Warm up part I: quiz! I Discuss with your stat buddy: I What is a clinical trial? What's the best way to quantify the shame you should feel if you don't know? I What is a power calculation? I What are common complicating statistical issues associated with clinical trials? I True or false I Sequential Hierarchically Assigned Randomization Trials are the gold standard design for estimation and evaluation of treatment regimes. I Susan Murphy, who authored several seminal papers on sequential clinical trial design, is affectionately known as `Smurphy' to her friends and colleagues. I The legend of Santa Clause may be partially based on Siberian Shamans consuming psychedelic mushrooms with reindeer. 1 / 64 Warm up: quiz! I Discuss with your stat buddy: I What is a clinical trial? What's the best way to quantify the shame you should feel if you don't know? I What is a power calculation? I What are common complicating statistical issues associated with clinical trials? I True or false I Sequential Hierarchically Assigned Randomization Trials are the gold standard design for estimation and evaluation of treatment regimes. I Susan Murphy, who authored several seminal papers on sequential clinical trial design, is affectionately known as `Smurphy' to her friends and colleagues. I The legend of Santa Clause may be partially based on Siberian Shamans consuming psychedelic mushrooms with reindeer.1 1https://www.npr.org/2010/12/24/132260025/did-shrooms-send-santa- and-his-reindeer-flying Starting easy Instead of having \answers" on a math test, they should just call them \impressions," and if you got a different \impression," so what, can't we all be brothers? { Pythagoras 2 / 64 Precision medicine I \The right treatment for the right patient at the right time." {Mantra of precision medicine advocates I Widely recognized that best clinical care requires treatment decisions tailored to individual patient characteristics I Improve patient outcomes, reduce cost and patient burden 3 / 64 Precision medicine background I Patient heterogeneity I Demographic I Physiological I Medical history/comorbidities I Genetic/genomic factors I Environment I ::: I Clinicians tailor therapy to individual patient characteristics I Evolution of health status I Patient individual preference I Local availability I Cost I ::: 4 / 64 Precision medicine background cont'd I Clinical decision making I Synthesis of available information I Expert judgment I Treatment guidelines I Precision medicine I Data-driven, aka evidence-based I Seeks to inform not dictate decision making 5 / 64 Treatment regimes I Formalize clinical decision making via sequence decision rules I One rule per stage of clinical intervention I Maps current patient info to recommended treatment I Optimal regime maximizes the mean of some cumulative clinical outcome if applied to population of interest 6 / 64 Ex. Treatment regime: mHealth for PTSD in cancer patients (PI S. Smith) First stage decision rule If distress ≥ 3 then: Cancer Distress Coach (CDC) Else if PTSD symptom score ≥ 20 then: CDC Else: usual care Second stage decision rule If responder then: continue first stage treatment Else if using CDC and PSTD change ≥ 3 then: add mCoaching Else if using CDC and distress ≥ 4 then: add FaceTime CBT Else FaceTime CBT only 7 / 64 Key ingredients I Critical decision points I Opportunities to change course of treatment I Fixed in calendar time or outcome driven I Patient characteristics I Up-to-date history I Personal preferences I Treatment options I Depend on time and patient history I May also depend on cost, resource availability, etc. 8 / 64 Data sources I Observational studies I Cohort study, e.g., Framingham I EHR data I Randomized clinical trials I K-arm randomized trial I Sequential Multiple Assignment Randomized Trials I Micro-randomized trials 9 / 64 Data sources I Observational studies I Cohort study, e.g., Framingham I EHR data I Randomized clinical trials I K-arm randomized trial I Sequential Multiple Assignment Randomized Trials I Micro-randomized trials 10 / 64 SMARTs I Sequential Multiple Assignment Randomized Trials (SMARTs) I Gold standard randomized trial design for evaluating treatment sequences (seminal paper: Murphy 2005 SIM) I Basic idea: randomize treatment assignment at critical decision points where there is equipoise I Motivation for SMARTs I Avoid causal issues assoc with observational longitudinal data I Efficiently compare partial and full treatment sequences I Estimate optimal treatment regimes I Better mimic clinical practice 10 / 64 Ex. SMART: mHealth for PTSD Continue Distress coach Yes Treatment AA Add mCoaching Treatment A Distress Coach Response? No Treatment AB Facetime CBT R Continue R Follow-up only Yes Treatment BA DC + mCoaching Treatment B Standard Care Response? No Treatment BB Facetime CBT R 11 / 64 Ex. SMART: mHealth for PTSD cont'd I Additional trial details I Response status assessed at 4 weeks I Response criterion PTSD symptoms exceed threshold I Primary outcome: PTSD symptoms 12 / 64 Ex. SMART: ADHD (PI: Pelham) Yes Treatment AA Treatment A Augment with MEDS Low Intensity BMOD Response? Treatment AB No Intensify BMOD R R Yes Treatment BA Treatment B Augment with BMOD Low Intensity MEDS Response? Treatment BB No Intensify MEDS R 13 / 64 Ex. SMART: ADHD (PI: Pelham) Cont'd I Additional trial details I Response status assessed each month I Response criterion teacher reported classroom performance I Primary outcomes: parent and teacher reported outcomes, academic assessments, rule violations 14 / 64 Ex. SMART: Zika (PI: S. Becker-Dreps) No change Continue Yes Treatment Passive messaging + Response? Insecticide + Condoms Intensify Add active messaging No Augment R In-home visits R Active control Insecticide + Condoms 15 / 64 Ex. SMART: Zika cont'd I Additional trial details I Response status assessed at first trimester clinic visit I Response criterion: patient-reported compliance I Primary outcome: Zika infection at full term 16 / 64 Ongoing: Trial design for children with epilepsy Treatment 1 Treatment 1 Continue Continue Yes No Response? R Treatment 0 Treatment 1 Treatment 3 Run-in period E+ADR+IAF E+ADR+IAF+PS No High adherence? R Yes Treatment 2 No further treatment E+ADR 17 / 64 Ongoing: Trial design for children with epilepsy I Multiple outcomes I Adherence at 8, 14, and 20 months I Seizures in months 8-14 I QOL in month 14 I Healthcare utilization months 8-20 18 / 64 Randomization I Three embedded regimes I A: E+ADR+IAF and add PS if non-response I B: E+ADR+IAF and continue if non-response I C: E+ADR and continue until end of study I Block-permuted design among embedded treatment regimes I Balance within strata (base adherence x age x severity) Strata Block 1 Block 2 Block 3 ··· Block J 1 ACB CBA ACB ··· CBA 2 ABC CBA BCA ··· CBA 3 BAC BAC CAB ··· ABC . 8 ABC ACB CAB ··· CBA 19 / 64 We shall see that these concerns are mostly unfounded. Common concerns with SMARTs I Many design choices ) unwieldy I Splitting data ) loss of power I Involves subgroup analyses ) complicated inference 20 / 64 Common concerns with SMARTs I Many design choices ) unwieldy I Splitting data ) loss of power I Involves subgroup analyses ) complicated inference We shall see that these concerns are mostly unfounded. 20 / 64 Warm-up part II: toy study I Prompt: researchers considering a two-stage SMART to evaluate two candidate first-stage treatments and two salvage therapies for non-responders. Responders will all receive the same maintenance therapy. I Sketch a SMART assuming I First stage txts: (i) new active txt and (ii) std care I Non-responders: (i) salvage 1 and (ii) salvage 2 I Responders: maintenance I Add'l details I Response assessed at four weeks I Justified by clinical application of std of care 21 / 64 Warm-up part II: toy study cont'd Treatment 2 Maintenance Yes Treatment 3 Salvage 1 Treatment 0 New Active Treatment Response? No Treatment 4 Salvage 2 R R Treatment 2 Maintenance Yes Treatment 3 Salvage 1 Treatment 1 Standard of Care Response? No Treatment 4 Salvage 2 R 22 / 64 A slight line or fold in time 23 / 64 Warm-up part II: toy study cont'd I Suppose that the optimal duration of the new treatment is unknown and deemed of primary interest I Want to compare waiting 4 and 8 weeks before assessing response under the new treatment I All other aspects are the same I Draw your design! 24 / 64 Thoughts? Feelings? Don't forget. I care about you. Warm-up part II: toy study cont'd Treatment 3 Maintenance Yes Treatment 0 Treatment 4 New Active Treat- Salvage 1 ment Assess Resp. Response? Treatment 5 4WK No Salvage 2 R Treatment 3 Maintenance Yes Treatment 1 Treatment 4 New Active Treat- Salvage 1 R ment Assess Resp. Response? Treatment 5 8WK No Salvage 2 R Treatment 3 Maintenance Yes Treatment 4 Treatment 2 Salvage 1 Standard of Care Response? Assess Resp. 4WK Treatment 5 No Salvage 2 R 25 / 64 Warm-up part II: toy study cont'd Treatment 3 Maintenance Yes Treatment 0 Treatment 4 New Active Treat- Salvage 1 ment Assess Resp. Response? Treatment 5 4WK No Salvage 2 R Treatment 3 Maintenance Yes Treatment 1 Treatment 4 New Active Treat- Salvage 1 R ment Assess Resp. Response? Treatment 5 8WK No Salvage 2 R Treatment 3 Maintenance Yes Treatment 4 Treatment 2 Salvage 1 Standard of Care Response? Assess Resp. 4WK Treatment 5 No Salvage 2 R Thoughts? Feelings? Don't forget. I care about you. 25 / 64 Warm-up part II: toy study cont'd I Suppose that the researchers determine that the evaluation of salvage therapies under the standard of care arm is of less interest than the comparison of response rates across the new treatment at 4 and 8 weeks and standard of care at 4 weeks.
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