Skip to main content

Advertisement

SpringerLink
Log in

Modernizing adverse events analysis in oncology clinical trials using alternative approaches: rationale and design of the MOTIVATE trial

  • Review
  • Published:
Investigational New Drugs Aims and scope Submit manuscript

Summary

In oncology clinical research, the analysis and reporting of adverse events is of major interest. A consistent depiction of the safety profile of a new treatment is as crucial in establishing how to use it as its antitumor activity. The advent of new therapeutics has led to major changes in the management of patients and targeted therapies or immune checkpoint inhibitors are administered continuously for months or even years. However, the classical methods of adverse events analysis are no longer adequate to properly assess their safety profile. Indeed, the worst grade method and time-to-event analysis cannot capture the duration or the evolution of adverse events induced by extended treatment durations. Many authors have highlighted this issue and argue that the analysis of safety data from clinical trials should be modernized by considering the dimension of time and the recurrent nature of adverse events. This paper aims to illustrate the limitations of current methods and discusses the value of alternative approaches such as the prevalence function, Q-TWiST, the ToxT and the recurrent event approaches. The rationale and design of the MOTIVATE trial, which aims to model the evolution of toxicities over time using the prevalence function in patients treated by immunotherapy, is also presented (ClinicalTrials.gov Identifier: NCT03447483; Date of registration: 27 February 2018).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

Data Availability

Not applicable.

References

  1. Ioannidis JPA, Evans SJW, Gøtzsche PC, O’Neill RT, Altman DG, Schulz K, Moher D (2004) CONSORT group, better reporting of harms in randomized trials: an extension of the CONSORT statement. Ann Intern Med 141:781–788. https://doi.org/10.7326/0003-4819-141-10-200411160-00009

    Article  PubMed  Google Scholar 

  2. Péron J, Maillet D, Gan HK, Chen EX, You B (2013) Adherence to CONSORT adverse event reporting guidelines in randomized clinical trials evaluating systemic cancer therapy: a systematic review. J Clin Oncol Off J Am Soc Clin Oncol 31:3957–3963. https://doi.org/10.1200/JCO.2013.49.3981

    Article  Google Scholar 

  3. Sivendran S, Latif A, McBride RB, Stensland KD, Wisnivesky J, Haines L, Oh WK, Galsky MD (2014) Adverse event reporting in cancer clinical trial publications. J Clin Oncol Off J Am Soc Clin Oncol 32:83–89. https://doi.org/10.1200/JCO.2013.52.2219

    Article  Google Scholar 

  4. Basch E (2010) The missing voice of patients in drug-safety reporting. N Engl J Med 362:865–869. https://doi.org/10.1056/NEJMp0911494

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. E. Basch, B.B. Reeve, S.A. Mitchell, S.B. Clauser, L.M. Minasian, A.C. Dueck, T.R. Mendoza, J. Hay, T.M. Atkinson, A.P. Abernethy, D.W. Bruner, C.S. Cleeland, J.A. Sloan, R. Chilukuri, P. Baumgartner, A. Denicoff, D. St Germain, A.M. O’Mara, A. Chen, J. Kelaghan, A.V. Bennett, L. Sit, L. Rogak, A. Barz, D.B. Paul, D. Schrag, Development of the National Cancer Institute’s patient-reported outcomes version of the common terminology criteria for adverse events (PRO-CTCAE). J Natl Cancer Inst. 106 (2014). https://doi.org/10.1093/jnci/dju244

  6. Maillet D, Blay JY, You B, Rachdi A, Gan HK, Péron J (2016) The reporting of adverse events in oncology phase III trials: a comparison of the current status versus the expectations of the EORTC members. Ann Oncol Off J Eur Soc Med Oncol 27:192–198. https://doi.org/10.1093/annonc/mdv485

    Article  CAS  Google Scholar 

  7. G. Thanarajasingam, J.M. Hubbard, J.A. Sloan, A. Grothey, The imperative for a new approach to toxicity analysis in oncology clinical trials. J Natl Cancer Inst. 107 (2015). https://doi.org/10.1093/jnci/djv216

  8. Kieser M (2016) Statistical methods for the analysis of adverse event data. Pharm Stat 15:290–291. https://doi.org/10.1002/pst.1759

    Article  PubMed  Google Scholar 

  9. Cabarrou B, Boher JM, Bogart E, Tresch-Bruneel E, Penel N, Ravaud A, Escudier B, Mahier Ait-Oukhatar C, Delord JP, Roché H, Filleron T (2016) How to report toxicity associated with targeted therapies? Ann Oncol Off J Eur Soc Med Oncol 27:1633–1638. https://doi.org/10.1093/annonc/mdw218

    Article  CAS  Google Scholar 

  10. Pepe MS, Longton G, Thornquist M (1991) A qualifier Q for the survival function to describe the prevalence of a transient condition. Stat Med 10:413–421. https://doi.org/10.1002/sim.4780100313

    Article  CAS  PubMed  Google Scholar 

  11. Kaplan EL, Meier P (1958) Nonparametric estimation from incomplete observations. J Am Stat Assoc 53:457–481

    Article  Google Scholar 

  12. R.L. Prentice, J.D. Kalbfleisch, A.V. Peterson Jr, N. Flournoy, V.T. Farewell, N.E. Breslow, The analysis of failure times in the presence of competing risks, Biometrics. (1978) 541–554

  13. Weber JS, Kähler KC, Hauschild A (2012) Management of immune-related adverse events and kinetics of response with ipilimumab. J Clin Oncol Off J Am Soc Clin Oncol 30:2691–2697. https://doi.org/10.1200/JCO.2012.41.6750

    Article  CAS  Google Scholar 

  14. H. Borghaei, L. Paz-Ares, L. Horn, D.R. Spigel, M. Steins, N.E. Ready, L.Q. Chow, E.E. Vokes, E. Felip, E. Holgado, F. Barlesi, M. Kohlhäufl, O. Arrieta, M.A. Burgio, J. Fayette, H. Lena, E. Poddubskaya, D.E. Gerber, S.N. Gettinger, C.M. Rudin, N. Rizvi, L. Crinò, G.R. Blumenschein, S.J. Antonia, C. Dorange, C.T. Harbison, F. Graf Finckenstein, J.R. Brahmer, Nivolumab versus docetaxel in advanced nonsquamous non-small-cell lung cancer. N Engl J Med. 373 (2015) 1627–1639. https://doi.org/10.1056/NEJMoa1507643

  15. Lancar R, Kramar A, Haie-Meder C (1995) Non-parametric methods for analysing recurrent complications of varying severity. Stat Med 14:2701–2712. https://doi.org/10.1002/sim.4780142409

    Article  CAS  PubMed  Google Scholar 

  16. Pepe MS, Fleming TR (1989) Weighted Kaplan-Meier statistics: a class of distance tests for censored survival data. Biometrics. 45:497–507

    Article  CAS  Google Scholar 

  17. Longué M, Cabarrou B, Wallet J, Brodowicz T, Roché H, Boher JM, Delord JP, Penel N, Filleron T (2018) The importance of jointly analyzing treatment administration and toxicity associated with targeted therapies: a case study of regorafenib in soft tissue sarcoma patients. Ann Oncol Off J Eur Soc Med Oncol 29:1588–1593. https://doi.org/10.1093/annonc/mdy168

    Article  Google Scholar 

  18. Cabarrou B, Jouin A, Boher JM, Kramar A, Filleron T (2015) Assessment of health status over time by prevalence and weighted prevalence functions: Interface in R. Comput Methods Prog Biomed 118:298–308. https://doi.org/10.1016/j.cmpb.2014.12.006

    Article  CAS  Google Scholar 

  19. Champiat S, Lambotte O, Barreau E, Belkhir R, Berdelou A, Carbonnel F, Cauquil C, Chanson P, Collins M, Durrbach A, Ederhy S, Feuillet S, François H, Lazarovici J, Le Pavec J, De Martin E, Mateus C, Michot J-M, Samuel D, Soria J-C, Robert C, Eggermont A, Marabelle A (2016) Management of immune checkpoint blockade dysimmune toxicities: a collaborative position paper. Ann Oncol Off J Eur Soc Med Oncol 27:559–574. https://doi.org/10.1093/annonc/mdv623

    Article  CAS  Google Scholar 

  20. S.L. Topalian, F.S. Hodi, J.R. Brahmer, S.N. Gettinger, D.C. Smith, D.F. McDermott, J.D. Powderly, R.D. Carvajal, J.A. Sosman, M.B. Atkins, P.D. Leming, D.R. Spigel, S.J. Antonia, L. Horn, C.G. Drake, D.M. Pardoll, L. Chen, W.H. Sharfman, R.A. Anders, J.M. Taube, T.L. McMiller, H. Xu, A.J. Korman, M. Jure-Kunkel, S. Agrawal, D. McDonald, G.D. Kollia, A. Gupta, J.M. Wigginton, M. Sznol, Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N Engl J Med. 366 (2012) 2443–2454. https://doi.org/10.1056/NEJMoa1200690

  21. Brahmer JR, Tykodi SS, Chow LQM, Hwu W-J, Topalian SL, Hwu P, Drake CG, Camacho LH, Kauh J, Odunsi K, Pitot HC, Hamid O, Bhatia S, Martins R, Eaton K, Chen S, Salay TM, Alaparthy S, Grosso JF, Korman AJ, Parker SM, Agrawal S, Goldberg SM, Pardoll DM, Gupta A, Wigginton JM (2012) Safety and activity of anti-PD-L1 antibody in patients with advanced cancer. N Engl J Med 366:2455–2465. https://doi.org/10.1056/NEJMoa1200694

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Weber JS, Hodi FS, Wolchok JD, Topalian SL, Schadendorf D, Larkin J, Sznol M, Long GV, Li H, Waxman IM, Jiang J, Robert C (2017) Safety profile of Nivolumab Monotherapy: a pooled analysis of patients with advanced melanoma. J Clin Oncol Off J Am Soc Clin Oncol 35:785–792. https://doi.org/10.1200/JCO.2015.66.1389

    Article  CAS  Google Scholar 

  23. Chen TW, Razak AR, Bedard PL, Siu LL, Hansen AR (2015) A systematic review of immune-related adverse event reporting in clinical trials of immune checkpoint inhibitors. Ann Oncol Off J Eur Soc Med Oncol 26:1824–1829. https://doi.org/10.1093/annonc/mdv182

    Article  CAS  Google Scholar 

  24. Arnaud-Coffin P, Maillet D, Gan HK, Stelmes J-J, You B, Dalle S, Péron J (2019) A systematic review of adverse events in randomized trials assessing immune checkpoint inhibitors. Int J Cancer 145:639–648. https://doi.org/10.1002/ijc.32132

    Article  CAS  PubMed  Google Scholar 

  25. Hengelbrock J, Gillhaus J, Kloss S, Leverkus F (2016) Safety data from randomized controlled trials: applying models for recurrent events. Pharm Stat 15:315–323. https://doi.org/10.1002/pst.1757

    Article  PubMed  Google Scholar 

  26. Gray RJ (1988) A class of K-sample tests for comparing the cumulative incidence of a competing risk. Ann Stat 16:1141–1154

    Article  Google Scholar 

  27. Fine JP, Gray RJ (1999) A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc 94:496–509

    Article  Google Scholar 

  28. Goldhirsch A, Gelber RD, Simes RJ, Glasziou P, Coates AS (1989) Costs and benefits of adjuvant therapy in breast cancer: a quality-adjusted survival analysis. J Clin Oncol Off J Am Soc Clin Oncol 7:36–44. https://doi.org/10.1200/JCO.1989.7.1.36

    Article  CAS  Google Scholar 

  29. Beaumont JL, Salsman JM, Diaz J, Deen KC, McCann L, Powles T, Hackshaw MD, Motzer RJ, Cella D (2016) Quality-adjusted time without symptoms or toxicity analysis of pazopanib versus sunitinib in patients with renal cell carcinoma. Cancer. 122:1108–1115. https://doi.org/10.1002/cncr.29888

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. McDermott DF, Shah R, Gupte-Singh K, Sabater J, Luo L, Botteman M, Rao S, Regan MM, Atkins M (2019) Quality-adjusted survival of nivolumab plus ipilimumab or nivolumab alone versus ipilimumab alone among treatment-naive patients with advanced melanoma: a quality-adjusted time without symptoms or toxicity (Q-TWiST) analysis. Qual Life Res Int J Qual Life Asp Treat Care Rehab 28:109–119. https://doi.org/10.1007/s11136-018-1984-3

    Article  Google Scholar 

  31. Cocks K, Contente M, Simpson S, DeRosa M, Taylor FC, Shaw JW (2019) A Q-TWiST analysis comparing Nivolumab and therapy of Investigator’s choice in patients with recurrent/metastatic platinum-refractory squamous cell carcinoma of the head and neck. PharmacoEconomics. 37:1041–1047. https://doi.org/10.1007/s40273-019-00798-1

    Article  PubMed  PubMed Central  Google Scholar 

  32. Huang M, Pietanza MC, Samkari A, Pellissier J, Burke T, Chandwani S, Kong F, Pickard AS (2019) Q-TWiST analysis to assess benefit-risk of Pembrolizumab in patients with PD-L1-positive advanced or metastatic non-small cell lung Cancer. PharmacoEconomics. 37:105–116. https://doi.org/10.1007/s40273-018-0752-0

    Article  PubMed  Google Scholar 

  33. Bogart E, Jouin A, Béhal H, Duhamel A, Filleron T, Kramar A (2016) Analysis of survival adjusted for quality of life using the Q-TWiST function: Interface in R. Comput Methods Prog Biomed 125:79–87. https://doi.org/10.1016/j.cmpb.2015.11.005

    Article  Google Scholar 

  34. Thanarajasingam G, Atherton PJ, Novotny PJ, Loprinzi CL, Sloan JA, Grothey A (2016) Longitudinal adverse event assessment in oncology clinical trials: the toxicity over time (ToxT) analysis of Alliance trials NCCTG N9741 and 979254. Lancet Oncol 17:663–670. https://doi.org/10.1016/S1470-2045(16)00038-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Loprinzi CL, Kugler JW, Sloan JA, Mailliard JA, LaVasseur BI, Barton DL, Novotny PJ, Dakhil SR, Rodger K, Rummans TA, Christensen BJ (2000) Venlafaxine in management of hot flashes in survivors of breast cancer: a randomised controlled trial. Lancet Lond Engl 356:2059–2063. https://doi.org/10.1016/S0140-6736(00)03403-6

    Article  CAS  Google Scholar 

  36. Goldberg RM, Sargent DJ, Morton RF, Fuchs CS, Ramanathan RK, Williamson SK, Findlay BP, Pitot HC, Alberts SR (2004) A randomized controlled trial of fluorouracil plus leucovorin, irinotecan, and oxaliplatin combinations in patients with previously untreated metastatic colorectal cancer. J Clin Oncol Off J Am Soc Clin Oncol 22:23–30. https://doi.org/10.1200/JCO.2004.09.046

    Article  CAS  Google Scholar 

  37. Gong Q, Tong B, Strasak A, Fang L (2014) Analysis of safety data in clinical trials using a recurrent event approach. Pharm Stat 13:136–144. https://doi.org/10.1002/pst.1611

    Article  PubMed  Google Scholar 

  38. Andersen PK, Gill RD (1982) Cox’s regression model for counting processes: a large sample study. Ann Stat 10:1100–1120. https://doi.org/10.1214/aos/1176345976

    Article  Google Scholar 

  39. Prentice RL, Williams BJ, Peterson AV (1981) On the regression analysis of multivariate failure time data. Biometrika. 68:373–379. https://doi.org/10.2307/2335582

    Article  Google Scholar 

  40. Ghosh D, Lin DY (2000) Nonparametric analysis of recurrent events and death. Biometrics. 56:554–562

    Article  CAS  Google Scholar 

  41. Masters GA, Krilov L, Bailey HH, Brose MS, Burstein H, Diller LR, Dizon DS, Fine HA, Kalemkerian GP, Moasser M, Neuss MN, O’Day SJ, Odenike O, Ryan CJ, Schilsky RL, Schwartz GK, Venook AP, Wong SL, Patel JD (2015) Clinical cancer advances 2015: annual report on progress against cancer from the American Society of Clinical Oncology. J Clin Oncol Off J Am Soc Clin Oncol 33:786–809. https://doi.org/10.1200/JCO.2014.59.9746

    Article  Google Scholar 

Download references

Acknowledgments

The authors wish to thank the Direction of Clinical Research and Innovation staff at the Institut Claudius Regaud, IUCT-O.

Manuscript type

Clinical trial methodologies.

Code availability

Not applicable.

Funding

The MOTIVATE trial (Scientific coordinator: T Filleron; ClinicalTrials.gov Identifier: NCT03447483) is conducted with the support of Bristol-Myers Squibb Foundation for Research in Immuno-Oncology.

Author information

Authors and Affiliations

  1. Department of Biostatistics, Institut Claudius Regaud - IUCT-O, 1 avenue Irène Joliot-Curie, 31059, Toulouse Cedex 9, France

    Bastien Cabarrou & Thomas Filleron

  2. Department of Medical Oncology, Institut Claudius Regaud - IUCT-O, Toulouse, France

    Carlos Gomez-Roca & Jean-Pierre Delord

  3. Department of Medical Oncology, Institut du Cancer de Montpellier (ICM), Montpellier, France

    Marie Viala

  4. Department of Pneumology, CHU Toulouse Larrey, Toulouse, France

    Audrey Rabeau

  5. Department of Medical Oncology, CH Castres, Castres, France

    Rodolphe Paulon

  6. Department of Drug Development and Innovation (D3i), Institut Curie, Paris, Saint-Cloud, France

    Delphine Loirat

  7. Department of Medical Oncology, CH Albi, Albi, France

    Nadia Munsch

  8. French National Platform Quality of Life and Cancer, Toulouse, France

    Thomas Filleron

Authors
  1. Bastien Cabarrou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Carlos Gomez-Roca
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marie Viala
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Audrey Rabeau
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rodolphe Paulon
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Delphine Loirat
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Nadia Munsch
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jean-Pierre Delord
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Thomas Filleron
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Bastien Cabarrou, Thomas Filleron, Carlos Gomez-Roca and Jean-Pierre Delord contributed to the conception and design. The first draft of the manuscript was written by Bastien Cabarrou and Thomas Filleron and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Thomas Filleron.

Ethics declarations

Conflict of interest

Bastien Cabarrou declares that he has no conflict of interest. Carlos Gomez-Roca declares Institutional Research Funding, Honoraria and Travel grant by BMS. Marie Viala declares that she has no conflict of interest. Audrey Rabeau declares that she has no conflict of interest. Rodolphe Paulon declares that he has no conflict of interest. Delphine Loirat declares Honoraria and Travel grant by BMS, MSD and Roche. Nadia Munsch declares that she has no conflict of interest. Jean-Pierre Delord declares Institutional Research Funding by Genentech, BMS and MSD Oncology and has a consulting or advisory role for Novartis, Roche/Genentech, BMS and MSD Oncology. Thomas Filleron declares that he has no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

For this type of study, formal consent is not required.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cabarrou, B., Gomez-Roca, C., Viala, M. et al. Modernizing adverse events analysis in oncology clinical trials using alternative approaches: rationale and design of the MOTIVATE trial. Invest New Drugs 38, 1879–1887 (2020). https://doi.org/10.1007/s10637-020-00938-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10637-020-00938-x

Keywords

Search

Navigation