Skip to main content

Advertisement

Springer Nature Link
Log in

Simulating Progression-Free and Overall Survival for First-Line Doublet Chemotherapy With or Without Bevacizumab in Metastatic Colorectal Cancer Patients Based on Real-World Registry Data

  • Original Research Article
  • Published:
PharmacoEconomics Aims and scope Submit manuscript

Abstract

Background

Simulation models utilizing real-world data have potential to optimize treatment sequencing strategies for specific patient subpopulations, including when conducting clinical trials is not feasible. We aimed to develop a simulation model to estimate progression-free survival (PFS) and overall survival for first-line doublet chemotherapy with or without bevacizumab for specific subgroups of metastatic colorectal cancer (mCRC) patients based on registry data.

Methods

Data from 867 patients were used to develop two survival models and one logistic regression model that populated a discrete event simulation (DES). Discrimination and calibration were used for internal validation of these models separately and predicted and observed medians and Kaplan–Meier plots were compared for the integrated DES. Bootstrapping was performed to correct for optimism in the internal validation and to generate correlated sets of model parameters for use in a probabilistic analysis to reflect parameter uncertainty.

Results

The survival models showed good calibration based on the regression slopes and modified Hosmer–Lemeshow statistics at 1 and 2 years, but not for short-term predictions at 0.5 years. Modified C-statistics indicated acceptable discrimination. The simulation estimated that median first-line PFS (95% confidence interval) of 219 (25%) patients could be improved from 175 days (156–199) to 269 days (246–294) if treatment would be targeted based on the highest expected PFS.

Conclusions

Extensive internal validation showed that DES accurately estimated the outcomes of treatment combination strategies for specific subpopulations, with outcomes suggesting treatment could be optimized. Although results based on real-world data are informative, they cannot replace randomized trials.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Explore related subjects

Discover the latest articles and news from researchers in related subjects, suggested using machine learning.

Data and code availability statement

All R code, including intermediate and final outcomes, as well as a tool that allows exploration of dummy data similar to the TRACC data and simulations using the DES to be performed, are available online at https://personex.nl/research/mcrc-tracc/. Data from the TRACC registry is not publicly available.

References

  1. Van Cutsem E, Cervantes A, Nordlinger B, Arnold D. Metastatic colorectal cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2014;25(Suppl 3):1–9.

    Google Scholar 

  2. Douillard JY, Cunningham D, Roth AD, Navarro M, James RD, Karasek P, et al. Irinotecan combined with fluorouracil compared with fluorouracil alone as first-line treatment for metastatic colorectal cancer: a multicentre randomised trial. Lancet. 2000;355(9209):1041–7.

    PubMed  CAS  Google Scholar 

  3. Saltz LB, Cox JV, Blanke C, Rosen LS, Fehrenbacher L, Moore MJ, et al. Irinotecan plus fluorouracil and leucovorin for metastatic colorectal cancer. Irinotecan Study Group. N Engl J Med. 2000;343(13):905–14.

    PubMed  CAS  Google Scholar 

  4. de Gramont A, Figer A, Seymour M, Homerin M, Hmissi A, Cassidy J, et al. Leucovorin and fluorouracil with or without oxaliplatin as first-line treatment in advanced colorectal cancer. J Clin Oncol. 2000;18(16):2938–47.

    PubMed  Google Scholar 

  5. Giacchetti S, Perpoint B, Zidani R, Le Bail N, Faggiuolo R, Focan C, et al. Phase III multicenter randomized trial of oxaliplatin added to chronomodulated fluorouracil-leucovorin as first-line treatment of metastatic colorectal cancer. J Clin Oncol. 2000;18(1):136–47.

    PubMed  CAS  Google Scholar 

  6. Kohne CH, van Cutsem E, Wils J, Bokemeyer C, El-Serafi M, Lutz MP, et al. Phase III study of weekly high-dose infusional fluorouracil plus folinic acid with or without irinotecan in patients with metastatic colorectal cancer: European Organisation for Research and Treatment of Cancer Gastrointestinal Group Study 40986. J Clin Oncol. 2005;23(22):4856–65.

    PubMed  Google Scholar 

  7. Hurwitz H, Fehrenbacher L, Novotny W, Cartwright T, Hainsworth J, Heim W, et al. Bevacizumab plus irinotecan, fluorouracil, and leucovorin for metastatic colorectal cancer. N Engl J Med. 2004;350(23):2335–42.

    CAS  Google Scholar 

  8. Cunningham D, Lang I, Marcuello E, Lorusso V, Ocvirk J, Shin DB, et al. Bevacizumab plus capecitabine versus capecitabine alone in elderly patients with previously untreated metastatic colorectal cancer (AVEX): an open-label, randomised phase 3 trial. Lancet Oncol. 2013;14(11):1077–85.

    PubMed  CAS  Google Scholar 

  9. Guan ZZ, Xu JM, Luo RC, Feng FY, Wang LW, Shen L, et al. Efficacy and safety of bevacizumab plus chemotherapy in Chinese patients with metastatic colorectal cancer: a randomized phase III ARTIST trial. Chin J Cancer. 2011;30(10):682–9.

    PubMed  PubMed Central  Google Scholar 

  10. Kabbinavar FF, Schulz J, McCleod M, Patel T, Hamm JT, Hecht JR, et al. Addition of bevacizumab to bolus fluorouracil and leucovorin in first-line metastatic colorectal cancer: results of a randomized phase II trial. J Clin Oncol. 2005;23(16):3697–705.

    PubMed  CAS  Google Scholar 

  11. Tebbutt NC, Wilson K, Gebski VJ, Cummins MM, Zannino D, van Hazel GA, et al. Capecitabine, bevacizumab, and mitomycin in first-line treatment of metastatic colorectal cancer: results of the australasian gastrointestinal trials group randomized phase III MAX study. J Clin Oncol. 2010;28(19):3191–8.

    PubMed  CAS  Google Scholar 

  12. Goldberg RM, Sargent DJ, Morton RF, Fuchs CS, Ramanathan RK, Williamson SK, et al. A randomized controlled trial of fluorouracil plus leucovorin, irinotecan, and oxaliplatin combinations in patients with previously untreated metastatic colorectal cancer. J Clin Oncol. 2004;22(1):23–30.

    PubMed  CAS  Google Scholar 

  13. Tournigand C, Andre T, Achille E, Lledo G, Flesh M, Mery-Mignard D, et al. FOLFIRI followed by FOLFOX6 or the reverse sequence in advanced colorectal cancer: a randomized GERCOR study. J Clin Oncol. 2004;22(2):229–37.

    PubMed  CAS  Google Scholar 

  14. Falcone A, Ricci S, Brunetti I, Pfanner E, Allegrini G, Barbara C, et al. Phase III trial of infusional fluorouracil, leucovorin, oxaliplatin, and irinotecan (FOLFOXIRI) compared with infusional fluorouracil, leucovorin, and irinotecan (FOLFIRI) as first-line treatment for metastatic colorectal cancer: the Gruppo Oncologico Nord Ovest. J Clin Oncol. 2007;25(13):1670–6.

    PubMed  CAS  Google Scholar 

  15. Passardi A, Nanni O, Tassinari D, Turci D, Cavanna L, Fontana A, et al. Effectiveness of bevacizumab added to standard chemotherapy in metastatic colorectal cancer: final results for first-line treatment from the ITACa randomized clinical trial. Ann Oncol. 2015;26(6):1201–7.

    PubMed  CAS  Google Scholar 

  16. Saltz LB, Clarke S, Díaz-Rubio E, Scheithauer W, Figer A, Wong R, et al. Bevacizumab in combination with oxaliplatin-based chemotherapy as first-line therapy in metastatic colorectal cancer: a randomized phase III study. J Clin Oncol. 2008;26(12):2013–9.

    PubMed  CAS  Google Scholar 

  17. Cremolini C, Loupakis F, Antoniotti C, Lupi C, Sensi E, Lonardi S, et al. FOLFOXIRI plus bevacizumab versus FOLFIRI plus bevacizumab as first-line treatment of patients with metastatic colorectal cancer: updated overall survival and molecular subgroup analyses of the open-label, phase 3 TRIBE study. Lancet Oncol. 2015;16(13):1306–15.

    PubMed  CAS  Google Scholar 

  18. Loupakis F, Cremolini C, Masi G, Lonardi S, Zagonel V, Salvatore L, et al. Initial therapy with FOLFOXIRI and bevacizumab for metastatic colorectal cancer. N Engl J Med. 2014;371(17):1609–18.

    PubMed  Google Scholar 

  19. Simkens LHJ, van Tinteren H, May A, ten Tije AJ, Creemers GJM, Loosveld OJL, et al. Maintenance treatment with capecitabine and bevacizumab in metastatic colorectal cancer (CAIRO3): a phase 3 randomised controlled trial of the Dutch Colorectal Cancer Group. Lancet. 2015;385(9980):1843–52.

    PubMed  CAS  Google Scholar 

  20. Loree JM, Kopetz S. Recent developments in the treatment of metastatic colorectal cancer. Ther Adv Med Oncol. 2017;9(8):551–64.

    PubMed  PubMed Central  CAS  Google Scholar 

  21. Temraz S, Mukherji D, Shamseddine A. Sequencing of treatment in metastatic colorectal cancer: where to fit the target. World J Gastroenterol. 2014;20(8):1993–2004.

    PubMed  PubMed Central  CAS  Google Scholar 

  22. Aparicio T, Desrame J, Lecomte T, Mitry E, Belloc J, Etienney I, et al. Oxaliplatin- or irinotecan-based chemotherapy for metastatic colorectal cancer in the elderly. Br J Cancer. 2003;89(8):1439–44.

    PubMed  PubMed Central  CAS  Google Scholar 

  23. Stintzing S, Modest DP, Rossius L, Lerch MM, von Weikersthal LF, Decker T, et al. FOLFIRI plus cetuximab versus FOLFIRI plus bevacizumab for metastatic colorectal cancer (FIRE-3): a post-hoc analysis of tumour dynamics in the final RAS wild-type subgroup of this randomised open-label phase 3 trial. Lancet Oncol. 2016;17(10):1426–34.

    PubMed  CAS  Google Scholar 

  24. Loupakis F, Cremolini C, Salvatore L, Masi G, Sensi E, Schirripa M, et al. FOLFOXIRI plus bevacizumab as first-line treatment in BRAF mutant metastatic colorectal cancer. Eur J Cancer. 2014;50(1):57–63.

    PubMed  CAS  Google Scholar 

  25. Arnold D, Lueza B, Douillard JY, Peeters M, Lenz HJ, Venook A, et al. Prognostic and predictive value of primary tumour side in patients with RAS wild-type metastatic colorectal cancer treated with chemotherapy and EGFR directed antibodies in six randomized trials. Ann Oncol. 2017;28(8):1713–29.

    PubMed  PubMed Central  CAS  Google Scholar 

  26. Giordano SH. Comparative effectiveness research in cancer with observational data. American Society of Clinical Oncology Educational Book. 2015;35:e330–5.

    Google Scholar 

  27. Hershman DL, Wright JD. Comparative effectiveness research in oncology methodology: observational data. J Clin Oncol. 2012;30(34):4215–22.

    PubMed  Google Scholar 

  28. McLean J, Rho YS, Kuruba G, Mamo A, Gilabert M, Kavan T, et al. Clinical practice patterns in chemotherapeutic treatment regimens for metastatic colorectal cancer. Clin Colorectal Cancer. 2016;15(2):135–40.

    PubMed  Google Scholar 

  29. Teng C-LJ, Wang C-Y, Chen Y-H, Lin C-H, Hwang W-L. Optimal sequence of irinotecan and oxaliplatin-based regimens in metastatic colorectal cancer: a population-based observational study. PLoS One. 2015;10(8):e0135673.

    PubMed  PubMed Central  Google Scholar 

  30. Clarke S, Burge M, Cordwell C, Gibbs P, Reece W, Tebbutt N. An Australian translational study to evaluate the prognostic role of inflammatory markers in patients with metastatic ColorEctal caNcer Treated with bevacizumab (Avastin) [ASCENT]. BMC Cancer. 2013;13:120.

    PubMed  PubMed Central  CAS  Google Scholar 

  31. Field K, Wong H-L, Shapiro J, Kosmider S, Tie J, Bae S, et al. Developing a national database for metastatic colorectal cancer management: perspectives and challenges. Intern Med J. 2013;43(11):1224–31.

    PubMed  CAS  Google Scholar 

  32. Semira C, Wong H-L, Field K, Lee M, Lee B, Nott L, et al. Chemotherapy and biologic use in the routine management of metastatic colorectal cancer in Australia: is clinical practice following the evidence? Intern Med J. 2019;49(4):446–54.

    PubMed  Google Scholar 

  33. Wong H-L, Lee B, Field K, Lomax A, Tacey M, Shapiro J, et al. Impact of primary tumor site on bevacizumab efficacy in metastatic colorectal cancer. Clin Colorectal Cancer. 2016;15(2):e9–15.

    PubMed  Google Scholar 

  34. Lee B, Wong H-L, Tacey M, Tie J, Wong R, Lee M, et al. The impact of bevacizumab in metastatic colorectal cancer with an intact primary tumor: results from a large prospective cohort study. Asia Pac J Clin Oncol. 2017;13(4):314–21.

    PubMed  Google Scholar 

  35. Rajagopalan H, Bardelli A, Lengauer C, Kinzler KW, Vogelstein B, Velculescu VE. Tumorigenesis: RAF/RAS oncogenes and mismatch-repair status. Nature. 2002;418(6901):934.

    PubMed  CAS  Google Scholar 

  36. Van Buuren S, Brand JPL, Groothuis-Oudshoorn CGM, Rubin DB. Fully conditional specification in multivariate imputation. J Stat Comput Simul. 2006;76(12):1049–64.

    Google Scholar 

  37. Van Buuren S, Groothuis-Oudshoorn K. mice: multivariate imputation by chained equations in R. J Stat Softw. 2011;45(3):1–67.

    Google Scholar 

  38. Wood AM, White IR, Royston P. How should variable selection be performed with multiply imputed data? Stat Med. 2008;27(17):3227–46.

    PubMed  Google Scholar 

  39. Rubin DB, Schenker N. Multiple imputation for interval estimation from simple random samples with ignorable nonresponse. J Am Stat Assoc. 1986;81(394):366–74.

    Google Scholar 

  40. Degeling K, Koffijberg H, Franken MD, Koopman M, IJzerman MJ. Comparing strategies for modeling competing risks in discrete-event simulations: a simulation study and illustration in colorectal cancer. Med Decis Making. 2019;39(1):57–73.

    PubMed  Google Scholar 

  41. Degeling K, IJzerman MJ, Koopman M, Koffijberg H. Accounting for parameter uncertainty in the definition of parametric distributions used to describe individual patient variation in health economic models. BMC Med Res Methodol. 2017;17(1):170.

    PubMed  PubMed Central  Google Scholar 

  42. Rahman MS, Ambler G, Choodari-Oskooei B, Omar RZ. Review and evaluation of performance measures for survival prediction models in external validation settings. BMC Med Res Methodol. 2017;17(1):60.

    PubMed  PubMed Central  Google Scholar 

  43. Uno H, Cai T, Pencina MJ, D’Agostino RB, Wei LJ. On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data. Stat Med. 2011;30(10):1105–17.

    PubMed  PubMed Central  Google Scholar 

  44. Harrell FE Jr, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15(4):361–87.

    PubMed  Google Scholar 

  45. Van Houwelingen HC. Validation, calibration, revision and combination of prognostic survival models. Stat Med. 2000;19(24):3401–15.

    PubMed  Google Scholar 

  46. Demler OV, Paynter NP, Cook NR. Tests of calibration and goodness-of-fit in the survival setting. Stat Med. 2015;34(10):1659–80.

    PubMed  PubMed Central  Google Scholar 

  47. D’Agostino RB, Nam B-H. Evaluation of the performance of survival analysis models: discrimination and calibration measures. Advances in survival analysis; 2003. p. 1–25.

  48. Miller ME, Langefeld CD, Tierney WM, Hui SL, McDonald CJ. Validation of probabilistic predictions. Med Decis Making. 1993;13(1):49–57.

    PubMed  CAS  Google Scholar 

  49. Arkes HR, Dawson NV, Speroff T, Harrell FE Jr, Alzola C, Phillips R, et al. The covariance decomposition of the probability score and its use in evaluating prognostic estimates. SUPPORT Investigators. Med Decis Making. 1995;15(2):120–31.

    PubMed  CAS  Google Scholar 

  50. Steyerberg EW, Harrell FE Jr, Borsboom GJJM, Eijkemans MJC, Vergouwe Y, Habbema JDF. Internal validation of predictive models: Efficiency of some procedures for logistic regression analysis. J Clin Epidemiol. 2001;54(8):774–81.

    PubMed  CAS  Google Scholar 

  51. R Core Team. R: a language and environment for statistical computing. Version 3.5.2 [software]. https://www.r-project.org/.

  52. Goldstein DA, Chen Q, Ayer T, Chan KKW, Virik K, Hammerman A, et al. Bevacizumab for metastatic colorectal cancer: a global cost-effectiveness analysis. Oncologist. 2017;22(6):694–9.

    PubMed  PubMed Central  CAS  Google Scholar 

  53. Parikh RC, Du XL, Robert MO, Lairson DR. Cost-effectiveness of treatment sequences of chemotherapies and targeted biologics for elderly metastatic colorectal cancer patients. J Manag Care Spec Pharm. 2017;23(1):64–73.

    PubMed  Google Scholar 

  54. Toumazis I, Kurt M, Toumazi A, Karacosta LG, Kwon C. Comparative effectiveness of up to three lines of chemotherapy treatment plans for metastatic colorectal cancer. MDM Policy Pract. 2017;2(2):2381468317729650.

    PubMed  PubMed Central  Google Scholar 

  55. Westwood M, van Asselt T, Ramaekers B, Whiting P, Joore M, Armstrong N, et al. KRAS mutation testing of tumours in adults with metastatic colorectal cancer: a systematic review and cost-effectiveness analysis. Health Technol Assess. 2014;18(62).

  56. Degeling K, Vu M, Koffijberg H, Wong HL, Koopman M, Gibbs P, IJzerman MJ. Health economic models for metastatic colorectal cancer: a methodological review. PharmacoEconomics. 2020;38:683–713.

    PubMed  Google Scholar 

Download references

Author information

Author notes

  1. Peter Gibbs and Maarten IJzerman contributed equally.

Authors and Affiliations

  1. Health Technology and Services Research Department, Faculty of Behavioural, Management and Social Sciences, Technical Medical Centre, University of Twente, Enschede, The Netherlands

    Koen Degeling, Hendrik Koffijberg & Maarten IJzerman

  2. Cancer Health Services Research, School of Population and Global Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, VIC, Australia

    Koen Degeling & Maarten IJzerman

  3. Personalised Oncology Division, Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia

    Hui-Li Wong, Azim Jalali, Rachel Wong, Belinda Lee, Jeanne Tie & Peter Gibbs

  4. Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia

    Hui-Li Wong, Belinda Lee, Jeanne Tie & Maarten IJzerman

  5. Department of Medical Oncology, Cabrini Health, Melbourne, VIC, Australia

    Jeremy Shapiro

  6. Department of Medical Oncology, Western Health, Melbourne, VIC, Australia

    Suzanne Kosmider, Jeanne Tie & Peter Gibbs

  7. Department of Medical Oncology, Eastern Health, Melbourne, VIC, Australia

    Rachel Wong

  8. Eastern Health Clinical School, Monash University, Box Hill, VIC, Australia

    Rachel Wong

  9. Department of Medical Oncology, Northern Health, Melbourne, VIC, Australia

    Belinda Lee

  10. Department of Medical Oncology, Royal Brisbane and Women’s Hospital, Brisbane, QLD, Australia

    Matthew Burge

  11. Department of Medical Oncology, The Canberra Hospital, Canberra, ACT, Australia

    Desmond Yip

  12. Department of Medical Oncology, Royal Hobart Hospital, Hobart, TAS, Australia

    Louise Nott

  13. Department of Medical Oncology, Fiona Stanley Hospital, Perth, WA, Australia

    Adnan Khattak

  14. Department of Medical Oncology, Campbelltown Hospital, Campbelltown, NSW, Australia

    Stephanie Lim

  15. Department of Medical Oncology, Gold Coast University Hospital, Gold Coast, QLD, Australia

    Susan Caird

Authors
  1. Koen Degeling
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Hui-Li Wong
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Hendrik Koffijberg
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Azim Jalali
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Jeremy Shapiro
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Suzanne Kosmider
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Rachel Wong
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Belinda Lee
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Matthew Burge
    View author publications

    You can also search for this author inPubMed Google Scholar

  10. Jeanne Tie
    View author publications

    You can also search for this author inPubMed Google Scholar

  11. Desmond Yip
    View author publications

    You can also search for this author inPubMed Google Scholar

  12. Louise Nott
    View author publications

    You can also search for this author inPubMed Google Scholar

  13. Adnan Khattak
    View author publications

    You can also search for this author inPubMed Google Scholar

  14. Stephanie Lim
    View author publications

    You can also search for this author inPubMed Google Scholar

  15. Susan Caird
    View author publications

    You can also search for this author inPubMed Google Scholar

  16. Peter Gibbs
    View author publications

    You can also search for this author inPubMed Google Scholar

  17. Maarten IJzerman
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

KD, HLW, HK, PG, and MIJ contributed to the study conception and design. KD analyzed the data in close collaboration with HLW and under supervision of PG and MIJ. KD developed the simulation under supervision of HK and MIJ. All authors contributed to the interpretation and discussion of the results. The first draft of the manuscript was prepared by KD and HLW, and critically reviewed by all other authors. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Koen Degeling.

Ethics declarations

Funding

This research was partly funded by the Netherlands Organisation for Health Research and Development (ZonMW) as part of the Translational Research Program (project number: 446001006). Roche Products Pty Limited (Australia) provided financial assistance for the development, installation and maintenance of the TRACC database. BioGrid Australia manages the TRACC database and provided data access and support.

Conflict of interest

MB has served on an advisory board to Roche, the manufacturer of bevacizumab. The authors declare that there is no conflict of interest regarding the publication of this article.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 461 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Degeling, K., Wong, HL., Koffijberg, H. et al. Simulating Progression-Free and Overall Survival for First-Line Doublet Chemotherapy With or Without Bevacizumab in Metastatic Colorectal Cancer Patients Based on Real-World Registry Data. PharmacoEconomics 38, 1263–1275 (2020). https://doi.org/10.1007/s40273-020-00951-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40273-020-00951-1

Profiles

  1. Jeanne Tie View author profile
  2. Desmond Yip View author profile
  3. Maarten IJzerman View author profile