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Abstract

The objective of all confirmatory Phase II and Phase III behavioral trials is to estimate the likelihood that the intervention(s) under study will improve a future health outcome. This future health outcome is the primary outcome for the trial. It is a decision that is made early in the design phase and drives many subsequent design decisions. This chapter focuses on considerations that guide the selection of a primary outcome, ways to avoid biased assessment, and the balance between multiple secondary outcomes and the risk of unintended consequences from them. Simplicity, objectivity, pre-specification, and clinical relevance are characteristics of outcome assessment in confirmatory behavioral trials. Exploration of moderators, mediators, and mechanisms are more appropriate for earlier stages of behavioral treatment development.

“Truth is ever to be found in simplicity, and not in the multiplicity and confusion of things.”

Isaac Newton

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References

  1. Kolodziej M, Klein I, Reisman L (2013) A new value proposition. Nat Med 19:1365. https://doi.org/10.1038/nm1113-1365

  2. Temple RJ (1995) A regulatory authority’s opinion about surrogate endpoints. In: Nimmo W, Tucker G (eds) Clinical measurement in drug evaluation. Wiley, New York

    Google Scholar 

  3. Department of Health and Human Services, Food and Drug Administration (1992) New drug, antibiotic, and biological drug product regulations: accelerated approval. Fed Regist 57:13234–13242

    Google Scholar 

  4. D’Agostino RB (2000) Debate: the slippery slope of surrogate outcomes. Curr Control Trials Cardiovas Med 1:76–78

    Google Scholar 

  5. Svensson S, Menkes DB, Lexchin J (2013) Surrogate outcomes in clinical trials: a cautionary tale. JAMA Intern Med 173:611–612

    Article  PubMed  Google Scholar 

  6. Ciani O, Buyse M, Garside R, Pavey T, Stein K, Sterne JAC, Taylor RS (2013) Comparison of treatment effect sizes associated with surrogate and final patient relevant outcomes in randomised controlled trials: meta-epidemiological study. BMJ 346. https://doi.org/10.1136/bmj.f457

  7. Wieland LS, Berman BM, Altman DG, Barth J, Bouter LM, D’Adamo CR, Linde K, Moher D, Mullins CD, Treweek S, Tunis S, van der Windt DA, Zwarenstein M, Witt C (2017) Rating of included trials on the efficacy-effectiveness spectrum: development of a new tool for systematic reviews. J Clin Epidemiol 84:95–104

    Article  PubMed  PubMed Central  Google Scholar 

  8. Freemantle N (2001) Interpreting the results of secondary end points and subgroup analyses in clinical trials: should we lock the crazy aunt in the attic? BMJ 322:989–991

    Article  PubMed  PubMed Central  Google Scholar 

  9. Sheehan B (2012) Assessment scales in dementia. Ther Adv Neurol Disord 5:349–358

    Article  PubMed  PubMed Central  Google Scholar 

  10. Gracely E (2008) So, why do I have to correct for multiple comparisons? Concepts and commentary on Turk et al. Pain 139:481–482

    Article  PubMed  Google Scholar 

  11. Ioannidis JPA (2005) Why most published research findings are false. PLoS Med 2:e124. https://doi.org/10.1371/journal.pmed.0020124

  12. U.S. Department of Health and Human Services (2017) Multiple endpoints in clinical trials. Draft guidance for industry; 4353–4354 [2017-00695]. https://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/ucm536750

  13. U.S. Department of Health and Human Services (2009) Patient-reported outcome measures: use in medical product development to support labeling claims. Guidance for Industry, December. https://www.fda.gov/ucm/groups/fdagov-public/@fdagov-drugs-gen/documents/document/ucm193282

  14. Stone AA, Shiffman S, Schwartz JE, Broderick JE, Hufford MR (2002) Patient non-compliance with paper diaries. BMJ 324:1193–1194

    Article  PubMed  PubMed Central  Google Scholar 

  15. Bolt DM, Lu Y, Kim JS (2014) Measurement and control of response styles using anchoring vignettes: a model-based approach. Psychol Methods 19:528–541

    Article  PubMed  Google Scholar 

  16. Stirratt M, Dunbar-Jacob J, Crane HM, Simoni JM, Czajkowski S, Hilliard ME, Aikens JE, Hunter CM, Velligan DI, Huntley H, Ogedegbe G, Rand CS, Schron E, Nilsen WJ (2015) Self-report measures of medication adherence behavior: recommendations on optimal use. Transl Behav Med 5:470–482

    Article  PubMed  PubMed Central  Google Scholar 

  17. Wood L, Egger M, Gluud LL, Schulz KF, Jüni P, Altman DG, Gluud C, Martin RM, Wood AJ, Sterne JA (2008) Empirical evidence of bias in treatment effect estimates in controlled trials with different interventions and outcomes: meta-epidemiological study. BMJ 336:601–605

    Article  PubMed  PubMed Central  Google Scholar 

  18. U.S. Department of Health and Human Services, Medicare Evidence Development and Coverage Advisory Committee (2016) Treatment resistant depression. https://www.cms.gov/Regulations-and-Guidance/Guidance/FACA/downloads/id71c

  19. Jones DA, West RR (1996) Psychological rehabilitation after myocardial infarction: multicentre randomised controlled trial. BMJ 313:1517–1521

    Article  PubMed  PubMed Central  Google Scholar 

  20. Landsberger HA (1958) Hawthorne revisited. Management and the worker, its critics, and developments in human relations in industry. Cornell University, Ithaca

    Google Scholar 

  21. McCambridge J, Kalaitzaki E, White IR, Khadjesari Z, Murray E, Linke S, Thompson SG, Godfrey C, Wallace P (2011) Impact of length or relevance of questionnaires on attrition in online trials: randomized controlled trial. J Med Internet Res 13:e96. https://doi.org/10.2196/jmir.1733

  22. Donovan DM, Bogenschutz MP, Perl H, Forcehimes A, Adinoff B, Mandler R, Oden N, Walker R (2012) Study design to examine the potential role of assessment reactivity in the Screening, Motivational Assessment, Referral, and Treatment in Emergency Departments (SMART-ED) protocol. Addict Sci Clin Pract 7:16. https://doi.org/10.1186/1940-0640-7-16

  23. Bogenschutz MP, Donovan DM, Mandler RN, Perl HI, Forcehimes AA, Crandall C, Lindblad R, Oden NL, Sharma G, Metsch L, Lyons MS, McCormack R, Macias-Konstantopoulos W, Douaihy A (2014) Brief intervention for patients with problematic drug use presenting in emergency departments: a randomized clinical trial. JAMA Intern Med 174:1736–1745

    Article  PubMed  PubMed Central  Google Scholar 

  24. McCambridge J, Butor-Bhavsar K, Witton J, Elbourne D (2011) Can research assessments themselves cause bias in behaviour change trials? A systematic review of evidence from solomon 4-group studies. PLoS One 6:e25223. https://doi.org/10.1371/journal.pone.0025223

  25. Friedman LM, Furberg CD, DeMets D, Reboussin DM, Granger CB (2015) Fundamentals of clinical trials, 5th edn. Springer, Cham

    Google Scholar 

  26. Turk DC, Dworkin RH, Allen RR, Bellamy N, Brandenburg N, Carr DB, Cleeland C, Dionne R, Farrar JT, Galer BS, Hewitt DJ, Jadad AR, Katz NP, Kramer LD, Manning DC, McCormick CG, McDermott MP, McGrath P, Quessy S, Rappaport BA, Robinson JP, Royal MA, Simon L, Stauffer JW, Stein W, Tollett J, Witter J (2003) Core outcome domains for chronic pain clinical trials: IMMPACT recommendations. Pain 106:337–345

    Article  PubMed  Google Scholar 

  27. Mehta P, Claydon L, Hendrick P, Winser S, Baxter GD (2015) Outcome measures in randomized-controlled trials of neuropathic pain conditions: a systematic review of systematic reviews and recommendations for practice. Clin J Pain 2015:169–176

    Article  Google Scholar 

  28. Zarin DA, Tse T, Williams RJ, Carr S (2016) Trial reporting in ClinicalTrials.gov: the final rule. N Engl J Med 375:1998–2004

    Article  PubMed  PubMed Central  Google Scholar 

  29. Mahaffey KW, Harrington RA, Akkerhuis M, Kleiman NS, Berdan LG, Crenshaw BS, Tardiff BE, Granger CB, DeJong I, Bhapkar M, Widimsky P, Corbalon R, Lee KL, Deckers JW, Simoons ML, Topol EJ, Califf RM, for the PURSUIT Investigators (2001) Systematic adjudication of myocardial infarction end-points in an international clinical trial. Curr Control Trials Cardiovasc Med 2:180–186

    Article  PubMed  PubMed Central  Google Scholar 

  30. Chan AW, Tetzlaff JM, Altman DG, Laupacis A, Gøtzsche PC, Krleža-Jerić K, Hróbjartsson A, Mann H, Dickersin K, Berlin J, Doré C, Parulekar W, Summerskill W, Groves T, Schulz K, Sox H, Rockhold FW, Rennie D, Moher D (2013) SPIRIT 2013 statement: defining standard protocol items for clinical trials. Ann Intern Med 158:200–207

    Article  PubMed  PubMed Central  Google Scholar 

  31. Burke LE, Kennedy DL, Miskala PH, Papadopoulos EJ, Trentacosti AM (2008) The use of patient-reported outcome measures in the evaluation of medical products for regulatory approval. Clin Pharmacol Ther 84:281–283

    Article  PubMed  Google Scholar 

  32. Riley WT, Pilkonis P, Cella D (2011) Application of the National Institutes of Health Patient-Reported Outcome Measurement Information System (PROMIS) to mental health research. J Ment Health Policy Econ 14:201–208

    Google Scholar 

  33. Look AHEAD Research Group, Wing RR, Bolin P, Brancati FL, Bray GA, Clark JM, Coday M, Crow RS, Curtis JM, Egan CM, Espeland MA, Evans M, Foreyt JP, Ghazarian S, Gregg EW, Harrison B, Hazuda HP, Hill JO, Horton ES, Hubbard VS, Jakicic JM, Jeffery RW, Johnson KC, Kahn SE, Kitabchi AE, Knowler WC, Lewis CE, Maschak-Carey BJ, Montez MG, Murillo A, Nathan DM, Patricio J, Peters A, Pi-Sunyer X, Pownall H, Reboussin D, Regensteiner JG, Rickman AD, Ryan DH, Safford M, Wadden TA, Wagenknecht LE, West DS, Williamson DF, Yanovski SZ (2013) Cardiovascular effects of intensive lifestyle intervention in type 2 diabetes. N Engl J Med 369:145–154

    Article  Google Scholar 

  34. Tomlinson G, Detsky AS (2010) Composite end points in randomized trials: there is no free lunch. JAMA 303:267–268

    Article  PubMed  Google Scholar 

  35. The ACCORD Study Group, Gerstein HC, Miller ME, Genuth S, Ismail-Beigi F, Buse JB, Goff DC Jr, Probstfield JL, Cushman WC, Ginsberg HN, Bigger JT, Grimm RH Jr, Byington RP, Rosenberg YD, Friedewald WT (2011) Long-term effects of intensive glucose lowering on cardiovascular outcomes. N Engl J Med 364:818–828

    Article  PubMed Central  Google Scholar 

  36. Brindle PM, McConnachie A, Upton MN, Hart CL, Davey Smith G, Watt GC (2005) The accuracy of the Framingham risk-score in different socioeconomic groups: a prospective study. Br J Gen Pract 55:838–845

    PubMed  PubMed Central  Google Scholar 

  37. Cohen J (1988) Statistical power analysis for the behavioral sciences, 2nd edn. Lawrence Erlbaum Assoc, Mahwah

    Google Scholar 

  38. Aberegg SK, Richards DR, O’Brien JM (2010) Delta inflation: a bias in the design of randomized controlled trials in critical care medicine. Crit Care 14:R77. https://doi.org/10.1186/cc8990

  39. Jaeschke R, Singer J, Guyatt GH (1989) Measurement of health status: ascertaining the minimal clinically important difference. Control Clin Trials 10:407–415

    Article  PubMed  Google Scholar 

  40. Powell LH, Appelhans BM, Ventrelle J, Karavolos K, March ML, Ong JC, Fitzpatrick SL, Normand P, Dawar R, Kazlauskaite R (2018) Development of a lifestyle intervention for the metabolic syndrome: discovery through proof-of-concept. Health Psych 37:929–939

    Article  Google Scholar 

  41. De Geest S, Sabate E (2003) Adherence to long-term therapies: evidence for action. Europ J Cardiovasc Nursing 2:323. https://doi.org/10.1016/S1474-5151(03)00091-4

  42. Esposito K, Marfella R, Ciotola M, Di Palo C, Giugliano F, Giugliano G, D’Armiento M, D’Andrea F, Giugliano D (2004) Effect of a Mediterranean-style diet on endothelial dysfunction and markers of vascular inflammation in the metabolic syndrome: a randomized trial. JAMA 292:1440–1446

    Google Scholar 

  43. Colman E (2012) Food and Drug Administration’s obesity drug guidance document: a short history. Circulation 125:2156–2164

    Article  PubMed  Google Scholar 

  44. Wen L, Badgett R, Cornell J (2005) Number needed to treat: a descriptor for weighing therapeutic options. Am J Health Syst Pharm 62:2031–2036

    Article  PubMed  Google Scholar 

  45. Stang A, Poole C, Bender R (2010) Common problems related to the use of number needed to treat. J Clin Epidemiol 63:820–825

    Article  PubMed  Google Scholar 

  46. McAlister FA (2008) The “number needed to treat” turns 20--and continues to be used and misused. CMAJ 179:549–553

    Article  PubMed  PubMed Central  Google Scholar 

  47. Fairman KA, Davis LE, Kruse CR, Sclar DA (2017) Financial impact of direct-acting oral anticoagulants in medicaid: budgetary assessment based on number needed to treat. Appl Health Econ Health Policy 15:203–214

    Article  PubMed  Google Scholar 

  48. Revicki D, Hays RD, Cella D, Sloan J (2008) Recommended methods for determining responsiveness and minimally important differences for patient-reported outcomes. J Clin Epidemiol 61:102–109

    Article  PubMed  Google Scholar 

  49. Copay AG, Subach BR, Glassman SD, Polly DW Jr, Schuler TC (2007) Understanding the minimum clinically important difference: a review of concepts and methods. Spine J 7:541–546

    Article  PubMed  Google Scholar 

  50. Gatchel RJ, Mayer TG, Choi Y, Chou R (2013) Validation of a consensus-based minimal clinically important difference (MCID) threshold using an objective functional external anchor. Spine J 13:889–893

    Article  PubMed  Google Scholar 

  51. Black N, Murphy M, Lamping D, McKee M, Sanderson C, Askham J, Marteau T (1999) Consensus development methods: a review of best practice in creating clinical guidelines. J Health Serv Res Policy 4:236–248

    Article  PubMed  Google Scholar 

  52. Karow A, Naber D, Lambert M, Moritz S, the EGOFORS Initiative (2012) Remission as perceived by people with schizophrenia, family members, and psychiatrists. Eur Psychiatry 27:426–431

    Article  PubMed  Google Scholar 

  53. Button KS, Kounali D, Thomas L, Wiles NJ, Peters TJ, Welton NJ, Ades AE, Lewis G (2015) Minimal clinically important difference on the Beck Depression Inventory-II according to the patient’s perspective. Psychol Med 45:3269–3279

    Google Scholar 

  54. Duru G, Fantino B (2008) The clinical relevance of changes in the Montgomery-Asberg Depression Rating Scale using the minimum clinically important difference approach. Curr Med Res Opin 24:1329–1335

    Article  PubMed  Google Scholar 

  55. Berkman LF, Blumenthal J, Burg M, Carney RM, Catellier D, Cowan MJ, Czajkowski SM, DeBusk R, Hosking J, Jaffe A, Kaufmann PG, Mitchell P, Norman J, Powell LH, Raczynski JM, Schneiderman N, the Enhancing Recovery in Coronary Heart Disease Patients Investigators (ENRICHD) (2003) Effects of treating depression and low perceived social support on clinical events after myocardial infarction: the Enhancing Recovery in Coronary Heart Disease Patients (ENRICHD) Randomized Trial. JAMA 289:3106–3116

    Google Scholar 

  56. Hermes EDA, Sokoloff DM, Stroup TS, Rosenheck RA (2012) Minimum clinically important difference in the Positive and Negative Syndrome Scale with data from the CATIE schizophrenia trial. J Clin Psychiatry 73:526–532

    Google Scholar 

  57. Wright A, Hannon J, Hegedus EJ, Kavchak AE (2012) Clinimetrics corner: a closer look at the minimal clinically important difference (MCID). J Man Manip Ther 20:160–166

    Article  PubMed  PubMed Central  Google Scholar 

  58. Kraemer HC, Wilson T, Fairburn CG, Agras WS (2002) Mediators and moderators of treatment effects in randomized clinical trials. Arch Gen Psychiatry 59:877–883

    Article  PubMed  Google Scholar 

  59. Hinshaw SP (2007) Moderators and mediators of treatment outcome for youth with ADHD: understanding for whom and how interventions work. J Pediatr Psychol 32:664–675

    Article  PubMed  Google Scholar 

  60. Kaufmann PG (2009) Psychosocial interventions in breast cancer: to light a candle. Cancer 115:5617–5619

    Article  PubMed  Google Scholar 

  61. ENRICHD (2011) Enhancing Recovery in Coronary Heart Disease Patients (ENRICHD) protocol, Version 7.0. https://biolincc.nhlbi.nih.gov/studies/enrichd/

  62. Popper KR (1959) The logic of scientific discovery. Basic Books, New York

    Google Scholar 

  63. Shadish WR, Cook TD, Campbell DT (2002) Experimental and quasi-experimental designs for generalized causal inference. Houghton Mifflin, Boston

    Google Scholar 

  64. Kazdin A (2007) Mediators and mechanisms of change in psychotherapy research. Ann Rev Clin Psychol 3:1–27

    Google Scholar 

  65. Hinshaw SP, Arnold LE for the MTA Cooperative Group (2015) ADHD, multimodal treatment, and longitudinal outcome: evidence, paradox, and challenge. Wiley Interdiscip Rev Cog Sci 6:39–52

    Google Scholar 

  66. MTA Cooperative Group (2004) National Institute of Mental Health Multimodal Treatment Study of ADHD follow-up: 24-month outcomes of treatment strategies for attention-deficit/hyperactivity disorder. Pediatrics 113:754–761

    Google Scholar 

  67. Jensen PS, Arnold LE, Swanson JM, Vitiello B, Abikoff HB, Greenhill LL, Hechtman L, Hinshaw SP, Pelham WE, Wells KC, Conners CK, Elliott GR, Epstein JN, Hoza B, March JS, Molina BSG, Newcorn JH, Severe JB, Wigal T, Gibbons RD, Hur K (2007) 3-year follow-up of the NIMH MTA study. J Am Acad Child Adolesc Psychiatry 46:989–1002

    Google Scholar 

  68. Molina BSG, Hinshaw SP, Swanson JM, Arnold LE, Vitiello B, Jensen PS, Epstein JN, Hoza B, Hechtman L, Abikoff HB, Elliott GR, Greenhill LL, Newcorn JH, Wells KC, Wigal T, Gibbons RD, Hur K, Houck PR, MTA Cooperative Group (2009) The MTA at 8 years: prospective follow-up of children treated for combined-type ADHD in a multisite study. J Am Acad Child Adolesc Psychiatry 48:484–500

    Google Scholar 

  69. Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, Nathan DM, Diabetes Prevention Program Research Group (2002) Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 346:393–403

    Google Scholar 

  70. Look AHEAD clinical trial protocol, 7th revision (2009). https://www.div12.org/wp-content/uploads/2015/04/Look-AHEAD-Protocol

  71. Brancati FL, Evans M, Furberg CD, Geller N, Haffner S, Kahn SE, Kaufmann PG, Lewis CE, Nathan DM, Pitt B, Safford MM, Look AHEAD Study Group (2012) Midcourse correction to a clinical trial when the event rate is underestimated: the Look AHEAD (Action for Health in Diabetes) Study. Clin Trials 9:113–124

    Article  PubMed  PubMed Central  Google Scholar 

  72. Barrett-Connor E (2013) Looking back on the look AHEAD trial. https://www.acc.org/latest-in-cardiology/articles/2014/07/18/18/22/looking-back-on-the-look-ahead-trial

  73. Shelleby EC, Kolko DJ (2015) Predictors, moderators, and treatment parameters of community and clinic-based treatment for child disruptive behavior disorders. J Child Fam Stud 24:734–748

    Article  PubMed  Google Scholar 

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Powell, L.H., Kaufmann, P.G., Freedland, K.E. (2021). Outcomes. In: Behavioral Clinical Trials for Chronic Diseases. Springer, Cham. https://doi.org/10.1007/978-3-030-39330-4_9

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