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Improving Study Conduct and Data Quality in Clinical Trials of Chronic Pain Treatments: IMMPACT Recommendations

Published:December 13, 2019DOI:https://doi.org/10.1016/j.jpain.2019.12.003

      Highlights

      • Optimizing clinical trial conduct and data quality is essential for drug development.
      • Expert consensus recommendations to improve data quality discussed.
      • Key elements include: site selection and training, participant selection and training.
      • Key elements include: treatment adherence, data collection, and study monitoring.

      Abstract

      The estimated probability of progressing from phase 3 analgesic clinical trials to regulatory approval is approximately 57%, suggesting that a considerable number of treatments with phase 2 trial results deemed sufficiently successful to progress to phase 3 do not yield positive phase 3 results. Deficiencies in the quality of clinical trial conduct could account for some of this failure. An Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials meeting was convened to identify potential areas for improvement in trial conduct in order to improve assay sensitivity (ie, ability of trials to detect a true treatment effect). We present recommendations based on presentations and discussions at the meeting, literature reviews, and iterative revisions of this article. The recommendations relate to the following areas: 1) study design (ie, to promote feasibility), 2) site selection and staff training, 3) participant selection and training, 4) treatment adherence, 5) data collection, and 6) data and study monitoring. Implementation of these recommendations may improve the quality of clinical trial data and thus the validity and assay sensitivity of clinical trials. Future research regarding the effects of these strategies will help identify the most efficient use of resources for conducting high quality clinical trials.

      Perspective

      Every effort should be made to optimize the quality of clinical trial data. This manuscript discusses considerations to improve conduct of pain clinical trials based on research in multiple medical fields and the expert consensus of pain researchers and stakeholders from academia, regulatory agencies, and industry.

      Key Words

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      References

        • Andersen JR
        • Byrjalsen I
        • Bihlet A
        • Kalakou F
        • Hoeck HC
        • Hansen G
        • Hansen HB
        • Karsdal MA
        • Riis BJ
        Impact of source data verification on data quality in clinical trials: An empirical post hoc analysis of three phase 3 randomized clinical trials.
        Br J Clin Pharmacol. 2015; 79: 660-668
        • Apseloff G
        • Swayne JK
        • Gerber N
        Medical histories may be unreliable in screening volunteers for clinical trials.
        Clin Pharmacol Ther. 1996; 60: 353-356
        • Bakobaki JM
        • Rauchenberger M
        • Joffe N
        • Mccormack S
        • Stenning S
        • Meredith S
        The potential for central monitoring techniques to replace on-site monitoring: Findings from an international multi-centre clinical trial.
        Clin Trials. 2012; 9: 257-264
        • Blaschke TF
        • Osterberg L
        • Vrijens B
        • Urquhart J
        Adherence to medications: Insights arising from studies on the unreliable link between prescribed and actual drug dosing histories.
        Annu Rev Pharmacol Toxicol. 2012; 52: 275-301
        • Breckenridge A
        • Aronson JK
        • Blaschke TF
        • Hartman D
        • Peck CC
        • Vrijens B
        Poor medication adherence in clinical trials: Consequences and solutions.
        Nat Rev Drug Discov. 2017; 16: 149-150
        • Brosteanu O
        • Schwarz G
        • Houben P
        • Paulus U
        • Strenge-Hesse A
        • Zettelmeyer U
        • Schneider A
        • Hasenclever D
        Risk-adapted monitoring is not inferior to extensive on-site monitoring: Results of the ADAMON cluster-randomised study.
        Clin Trials. 2017; 14: 584-596
        • Bryant C
        • Lewis P
        • Bennell KL
        • Ahamed Y
        • Crough D
        • Jull GA
        • Kenardy J
        • Nicholas MK
        • Keefe FJ
        Can physical therapists deliver a pain coping skills program? An Examination of training processes and outcomes.
        Phys Ther. 2014; 94: 1443-1454
        • Bushnell DM
        • Martin ML
        • Scanlon M
        • Chen T
        • Chau D
        • Viswanathan HN
        Equivalence and measurement properties of an electronic version of the Psoriasis Symptom Inventory.
        Qual Life Res. 2014; 23: 897-906
      1. Cai X, Gewandter JS, He H, Turk DC, Dworkin RH, McDermott MP: Estimands and missing data in clinical trials of chronic pain treatments: Advances in design and analysis. Pain 2020. Available at: https://journals.lww.com/pain/Abstract/9000/Estimands_and_missing_data_in_clinical_trials_of.98392.aspx. Accessed June 3, 2020

        • Carpenter JR
        • Roger JH
        • Kenward MG
        Analysis of longitudinal trials with protocol deviation: A framework for relevant, accessible assumptions, and inference via multiple imputation.
        J Biopharm Stat. 2013; 23: 1352-1371
      2. Code of Federal Regulations Title 21, part 11. Available at: https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRSearch.cfm?CFRPart=11. Accessed October 23, 2019

      3. Code of Federal Regulations Title 21, part 312.50. Available at: https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRSearch.cfm?fr=312.50. Accessed October 23, 2019

      4. CTSdatabase. Available at: http://ctsdatabase.com/. Accessed June 3, 2020

        • Curran PG
        Methods for the detection of carelessly invalid responses in survey data.
        J Exp Soc Psychol. 2016; 66: 4-19
        • De Geest S
        • Zullig LL
        • Dunbar-Jacob J
        • Helmy R
        • Hughes DA
        • Wilson IB
        • Vrijens B
        ESPACOMP Medication Adherence Reporting Guideline (EMERGE).
        Ann Intern Med. 2018; 169: 30-35
        • Desmet L
        • Venet D
        • Doffagne E
        • Timmermans C
        • Burzykowski T
        • Legrand C
        • Buyse M
        Linear mixed-effects models for central statistical monitoring of multicenter clinical trials.
        Stat Med. 2014; 33: 5265-5279
        • Devine EG
        • Peebles KR
        • Martini V
        Strategies to exclude subjects who conceal and fabricate information when enrolling in clinical trials.
        Contemp Clin Trials Commun. 2017; 5: 67-71
        • Devine EG
        • Waters ME
        • Putnam M
        • Surprise C
        • O'malley K
        • Richambault C
        • Fishman RL
        • Knapp CM
        • Patterson EH
        • Sarid-Segal O
        • Streeter C
        • Colanari L
        • Ciraulo DA
        Concealment and fabrication by experienced research subjects.
        Clin Trials. 2013; 10: 935-948
      5. DUPCHECK: Available at: https://www.dupcheck.org/. Accessed June 3, 2020

        • Dworkin RH
        • Turk DC
        • Peirce-Sandner S
        • Baron R
        • Bellamy N
        • Burke LB
        • Chappell A
        • Chartier K
        • Cleeland CS
        • Costello A
        • Cowan P
        • Dimitrova R
        • Ellenberg S
        • Farrar JT
        • French JA
        • Gilron I
        • Hertz S
        • Jadad AR
        • Jay GW
        • Kalliomaki J
        • Katz NP
        • Kerns RD
        • Manning DC
        • Mcdermott MP
        • Mcgrath PJ
        • Narayana A
        • Porter L
        • Quessy S
        • Rappaport BA
        • Rauschkolb C
        • Reeve BB
        • Rhodes T
        • Sampaio C
        • Simpson DM
        • Stauffer JW
        • Stucki G
        • Tobias J
        • White RE
        • Witter J
        Research design considerations for confirmatory chronic pain clinical trials: IMMPACT recommendations.
        Pain. 2010; 149: 177-193
        • Dworkin RH
        • Turk DC
        • Peirce-Sandner S
        • Burke LB
        • Farrar JT
        • Gilron I
        • Jensen MP
        • Katz NP
        • Raja SN
        • Rappaport BA
        • Rowbotham MC
        • Backonja MM
        • Baron R
        • Bellamy N
        • Bhagwagar Z
        • Costello A
        • Cowan P
        • Fang WC
        • Hertz S
        • Jay GW
        • Junor R
        • Kerns RD
        • Kerwin R
        • Kopecky EA
        • Lissin D
        • Malamut R
        • Markman JD
        • Mcdermott MP
        • Munera C
        • Porter L
        • Rauschkolb C
        • Rice AS
        • Sampaio C
        • Skljarevski V
        • Sommerville K
        • Stacey BR
        • Steigerwald I
        • Tobias J
        • Trentacosti AM
        • Wasan AD
        • Wells GA
        • Williams J
        • Witter J
        • Ziegler D
        Considerations for improving assay sensitivity in chronic pain clinical trials: IMMPACT recommendations.
        Pain. 2012; 153: 1148-1158
        • Edwards P
        • Shakur H
        • Barnetson L
        • Prieto D
        • Evans S
        • Roberts I
        Central and statistical data monitoring in the clinical randomisation of an antifibrinolytic in significant haemorrhage (CRASH-2) trial.
        Clinical Trials. 2014; 11: 336-343
        • Eisenstein EL
        • Collins R
        • Cracknell BS
        • Podesta O
        • Reid ED
        • Sandercock P
        • Shakhov Y
        • Terrin ML
        • Sellers MA
        • Califf RM
        • Granger CB
        • Diaz R
        Sensible approaches for reducing clinical trial costs.
        Clin Trials. 2008; 5: 75-84
      6. European Medicines Agency: Reflection paper on risk based quality management in clinical trials. 2013. Available at:http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2013/11/WC500155491.pdf. Accessed April 10, 2019

      7. European Medicines Agency, Committee for Human Medicinal Products: ICH E9 (R1) addendum on estimands and sensitivity analysis in clinical trials to the guideline on statistical principles for clinical trials. 2017. Available at:https://www.ema.europa.eu/documents/scientific-guideline/draft-ich-e9-r1-addendum-estimands-sensitivity-analysis-clinical-trials-guideline-statistical_en.pdf. Accessed April 10, 2019

        • Farrar JT
        • Troxel AB
        • Haynes K
        • Gilron I
        • Kerns RD
        • Katz NP
        • Rappaport BA
        • Rowbotham MC
        • Tierney AM
        • Turk DC
        • Dworkin RH
        Effect of variability in the 7-day baseline pain diary on the assay sensitivity of neuropathic pain randomized clinical trials: An ACTTION study.
        Pain. 2014; 155: 1622-1631
        • Fischer K
        • Goetghebeur E
        Structural mean effects of noncompliance: Estimating interaction with baseline prognosis and selection effects.
        J Am Stat Assoc. 2004; 99: 918-928
        • George SL
        • Buyse M
        Data fraud in clinical trials.
        Clin Investig (Lond). 2015; 5: 161-173
        • Getz K
        Improving protocol design feasibility to drive drug development economics and performance.
        Int J Environ Res Public Health. 2014; 11: 5069-5080
        • Gewandter JS
        • Dworkin RH
        • Turk DC
        • Mcdermott MP
        • Baron R
        • Gastonguay MR
        • Gilron I
        • Katz NP
        • Mehta C
        • Raja SN
        • Senn S
        • Taylor C
        • Cowan P
        • Desjardins P
        • Dimitrova R
        • Dionne R
        • Farrar JT
        • Hewitt DJ
        • Iyengar S
        • Jay GW
        • Kalso E
        • Kerns RD
        • Leff R
        • Leong M
        • Petersen KL
        • Ravina BM
        • Rauschkolb C
        • Rice AS
        • Rowbotham MC
        • Sampaio C
        • Sindrup SH
        • Stauffer JW
        • Steigerwald I
        • Stewart J
        • Tobias J
        • Treede RD
        • Wallace M
        • White RE
        Research designs for proof-of-concept chronic pain clinical trials: IMMPACT recommendations.
        Pain. 2014; 155: 1683-1695
        • Gewandter JS
        • Mcdermott MP
        • Mbowe O
        • Edwards RR
        • Katz NP
        • Turk DC
        • Dworkin RH
        Navigating trials of personalized pain treatments: We're going to need a bigger boat.
        Pain. 2019; 160: 1235-1239
        • Harris RE
        • Williams DA
        • Mclean SA
        • Sen A
        • Hufford M
        • Gendreau RM
        • Gracely RH
        • Clauw DJ
        Characterization and consequences of pain variability in individuals with fibromyalgia.
        Arthritis Rheum. 2005; 52: 3670-3674
        • Harrison T
        • Miyahara S
        • Lee A
        • Evans S
        • Bastow B
        • Simpson D
        • Gilron I
        • Dworkin R
        • Darr ES
        • Wieclaw L
        • Clifford DB
        • the ACTG A5252 Team
        Experience and challenges presented by a multicenter crossover study of combination analgesic therapy for the treatment of painful HIV-associated polyneuropathies.
        Pain Med. 2013; 14: 1039-1047
        • Hay M
        • Thomas DW
        • Craighead JL
        • Economides C
        • Rosenthal J
        Clinical development success rates for investigational drugs.
        Nat Biotechnol. 2014; 32: 40-51
        • Kardas P
        • Lewek P
        • Matyjaszczyk M
        Determinants of patient adherence: A review of systematic reviews.
        Front Pharmacol. 2013; 4: 91
        • Kirkwood AA
        • Cox T
        • Hackshaw A
        Application of methods for central statistical monitoring in clinical trials.
        Clin Trials. 2013; 10: 783-806
        • Kobak KA
        • Kane JM
        • Thase ME
        • Nierenberg AA
        Why do clinical trials fail? The problem of measurement error in clinical trials: Time to test new paradigms?.
        J Clin Psychopharmacol. 2007; 27: 1-5
        • Korieth K
        The high cost and questionable impact of 100% SDV.
        Center Watch Monthly. 2011; 19: 15-17
        • Kube T
        • Rief W
        Are placebo and drug-specific effects additive? Questioning basic assumptions of double-blinded randomized clinical trials and presenting novel study designs.
        Drug Discov Today. 2017; 22: 729-735
        • Liu KS
        • Snavely DB
        • Ball WA
        • Lines CR
        • Reines SA
        • Potter WZ
        Is bigger better for depression trials?.
        J Psychiatr Res. 2008; 42: 622-630
        • Manninen V
        • Elo MO
        • Frick MH
        • Haapa K
        • Heinonen OP
        • Heinsalmi P
        • Helo P
        • Huttunen JK
        • Kaitaniemi P
        • Koskinen P
        • Mäenpää H
        • Mälkönen M
        • Mänttäri M
        • Norola S
        • Pasternack A
        • Pikkarainen J
        • Romo M
        • Sjöblom T
        • Nikkilä EA
        Lipid alterations and decline in the incidence of coronary heart disease in the Helsinki Heart Study.
        JAMA. 1988; 260: 641-651
        • Marrazzo JM
        • Ramjee G
        • Richardson BA
        • Gomez K
        • Mgodi N
        • Nair G
        • Palanee T
        • Nakabiito C
        • Van Der Straten A
        • Noguchi L
        • Hendrix CW
        • Dai JY
        • Ganesh S
        • Mkhize B
        • Taljaard M
        • Parikh UM
        • Piper J
        • Masse B
        • Grossman C
        • Rooney J
        • Schwartz JL
        • Watts H
        • Marzinke MA
        • Hillier SL
        • Mcgowan IM
        • Chirenje ZM
        • Team VS
        Tenofovir-based preexposure prophylaxis for HIV infection among African women.
        N Engl J Med. 2015; 372: 509-518
        • Mundt JC
        • Greist JH
        • Jefferson JW
        • Katzelnick DJ
        • Debrota DJ
        • Chappell PB
        • Modell JG
        Is it easier to find what you are looking for if you think you know what it looks like?.
        J Clin Psychopharmacol. 2007; 27: 121-125
        • O'kelly M
        Using statistical techniques to detect fraud: A test case.
        Pharmaceutical Statistics. 2004; 3: 237-246
        • Olsen R
        • Bihlet AR
        • Kalakou F
        • Andersen JR
        The impact of clinical trial monitoring approaches on data integrity and cost-a review of current literature.
        Euro J Clin Pharm. 2016; 72: 399-412
        • Pocock SJ
        • Abdalla M
        The hope and the hazards of using compliance data in randomized controlled trials.
        Stat Med. 1998; 17: 303-317
        • Pogue JM
        • Devereaux PJ
        • Thorlund K
        • Yusuf S
        Central statistical monitoring: Detecting fraud in clinical trials.
        Clinical Trials. 2013; 10: 225-235
        • Sertkaya A
        • Wong HH
        • Jessup A
        • Beleche T
        Key cost drivers of pharmaceutical clinical trials in the United States.
        Clin Trials. 2016; 13: 117-126
        • Shiovitz TM
        • Bain EE
        • Mccann DJ
        • Skolnick P
        • Laughren T
        • Hanina A
        • Burch D
        Mitigating the effects of nonadherence in clinical trials.
        J Clin Pharmacol. 2016; 56: 1151-1164
        • Shiovitz TM
        • Wilcox CS
        • Gevorgyan L
        • Shawkat A
        CNS sites cooperate to detect duplicate subjects with a clinical trial subject registry.
        Innov Clin Neurosci. 2013; 10: 17-21
        • Simpson DM
        • Rice AS
        • Emir B
        • Landen J
        • Semel D
        • Chew ML
        • Sporn J
        A randomized, double-blind, placebo-controlled trial and open-label extension study to evaluate the efficacy and safety of pregabalin in the treatment of neuropathic pain associated with human immunodeficiency virus neuropathy.
        Pain. 2014; 155: 1943-1954
        • Skonnord T
        • Steen F
        • Skjeie H
        • Fetveit A
        • Brekke M
        • Klovning A
        Survey Email Scheduling and Monitoring in eRCTs (SESAMe): A digital tool to improve data collection in randomized controlled clinical trials.
        J Med Internet Res. 2016; 18: e311
        • Smith SM
        • Amtmann D
        • Askew RL
        • Gewandter JS
        • Hunsinger M
        • Jensen MP
        • Mcdermott MP
        • Patel KV
        • Williams M
        • Bacci ED
        • Burke LB
        • Chambers CT
        • Cooper SA
        • Cowan P
        • Desjardins P
        • Etropolski M
        • Farrar JT
        • Gilron I
        • Huang IZ
        • Katz M
        • Kerns RD
        • Kopecky EA
        • Rappaport BA
        • Resnick M
        • Strand V
        • Vanhove GF
        • Veasley C
        • Versavel M
        • Wasan AD
        • Turk DC
        • Dworkin RH
        Pain intensity rating training: Results from an exploratory study of the ACTTION PROTECCT system.
        Pain. 2016; 157: 1056-1064
        • Tantsyura V
        • Grimes I
        • Mitchel J
        • Fendt K
        • Sirichenko S
        • Waters J
        • Crowe J
        • Tardiff B
        Risk-based source data verification approaches: Pros and cons.
        Regul Aff. 2010; 44: 745-756
        • Taylor RN
        • Mcentegart DJ
        • Stillman EC
        Statistical techniques to detect fraud and other data irregularities in clinical questionnaire data.
        Drug Inf Jour. 2002; 36: 115-125
        • The Lipid Research Clinics Coronary Primary Prevention Trial results. II
        The relationship of reduction in incidence of coronary heart disease to cholesterol lowering.
        JAMA. 1984; 251: 365-374
        • Treister R
        • Honigman L
        • Lawal OD
        • Lanier RK
        • Katz NP
        A deeper look at pain variability and its relationship with the placebo response: results from a randomized, double-blind, placebo-controlled clinical trial of naproxen in osteoarthritis of the knee.
        Pain. 2019; 160: 1522-1528
        • Treister R
        • Lawal OD
        • Shecter JD
        • Khurana N
        • Bothmer J
        • Field M
        • Harte SE
        • Kruger GH
        • Katz NP
        Accurate pain reporting training diminishes the placebo response: Results from a randomised, double-blind, crossover trial.
        PLoS One. 2018; 13e0197844
        • Tudur Smith C
        • Stocken DD
        • Dunn J
        • Cox T
        • Ghaneh P
        • Cunningham D
        • Neoptolemos JP
        The value of source data verification in a cancer clinical trial.
        PLoS One. 2012; 7: e51623
      8. U.S. Health and Human Services, Food and Drug Administration: Guidance for industry: Oversight of clinical investigations – A risk-based approach to monitoring. 2013. Available at: https://www.fda.gov/downloads/Drugs/Guidances/UCM269919.pdf. Accessed April 10, 2019

      9. U.S. Health and Human Services, Food and Drug Administration: Guidance for industry: Electronic source data in clinical investigations. 2013. Available at:https://www.fda.gov/downloads/drugs/guidances/ucm328691.pdf. Accessed April 10, 2019

        • Valgimigli M
        • Garcia Garcia H
        • Vrijens B
        • Vranckx P
        • Mcfadden EP
        • Costa F
        • Pieper K
        • Vock DM
        • Zhang M
        • Van Es GA
        • Tricoci P
        • Baber U
        • Steg G
        • Montalescot G
        • Angiolillo DJ
        • Serruys PW
        • Farb A
        • Windecker S
        • Kastrati A
        • Colombo A
        • Feres F
        • Juni P
        • Stone GW
        • Bhatt DL
        • Mehran R
        • Tijssen JGP
        Standardized classification and framework for reporting, interpreting, and analysing medication non-adherence in cardiovascular clinical trials: A consensus report from the Non-adherence Academic Research Consortium (NARC).
        Eur Heart J. 2018; 00: 1-16
        • Venet D
        • Doffagne E
        • Burzykowski T
        • Beckers F
        • Tellier Y
        • Genevois-Marlin E
        • Becker U
        • Bee V
        • Wilson V
        • Legrand C
        • Buyse M
        A statistical approach to central monitoring of data quality in clinical trials.
        Clin Trials. 2012; 9: 705-713
      10. Verified Clinical Trials. Available at: http://www.verifiedclinicaltrials.com/

        • Vrijens B
        • Urquhart J
        Methods for measuring, enhancing, and accounting for medication adherence in clinical trials.
        Clin Pharmacol Ther. 2014; 95: 617-626
        • Vrijens B
        • Urquhart J
        • White D
        Electronically monitored dosing histories can be used to develop a medication-taking habit and manage patient adherence.
        Expert Rev Clin Pharmacol. 2014; 7: 633-644
        • Wise RA
        • Bartlett SJ
        • Brown ED
        • Castro M
        • Cohen R
        • Holbrook JT
        • Irvin CG
        • Rand CS
        • Sockrider MM
        • Sugar EA
        • American Lung Association Asthma Clinical Research C
        Randomized trial of the effect of drug presentation on asthma outcomes: The American Lung Association Asthma Clinical Research Centers.
        J Allergy Clin Immunol. 2009; 124 (436-44, 444e1-8)