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BMC Health Services Research
Published in: BMC Health Services Research 1/2017

Open Access 01-12-2017 | Research article

Effectiveness of triple therapy with direct-acting antivirals for hepatitis C genotype 1 infection: application of propensity score matching in a national HCV treatment registry

Authors: Emma Gray, David J. Pasta, Suzanne Norris, Aisling O’Leary, on behalf of the Irish Hepatitis C Outcomes and Research Network (ICORN)

Published in: BMC Health Services Research | Issue 1/2017

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Abstract

Background

Observational studies are used to measure the effectiveness of an intervention in non-experimental, real world scenarios at the population level and are recognised as an important component of the evidence pyramid. Such data can be accrued through prospective cohort studies and a patient registry is a proven method for this type of study. The national hepatitis C (HCV) registry was established in Ireland in 2012 with the aim of monitoring the clinical and economic outcomes from new, high cost regimens for the treatment of HCV infection. A sustained virological response (SVR) 24 weeks following completion of therapy with interferon-containing regimens is considered a cure. Non-randomisation in these studies can result in confounding or selection bias. Propensity score (PS) matching is one of a number of statistical tools that can be used to mitigate the effects of confounding in observational studies.

Methods

We analysed the data of 309 patients who underwent triple therapy treatment with telaprevir (TPV) in combination with pegylated-interferon and ribavirin (PR) or boceprevir (BOC)/PR between June 2012 and December 2014. The decision to initiate treatment and the selection of the treatment regimen was at the discretion of the physician. To adjust for confounding, three approaches to propensity score matching were assessed Adjusted sustained-virological response rates (SVR), odds ratios, p-values and 95% confidence intervals were calculated from the three PS matched dataset.

Results

Prior to matching, the unadjusted sustained virological response rates 24 weeks after treatment complete (SVR24) were 74% (n = 158/215) and 61% (n = 57/94) for telaprevir/PR and boceprevir/PR, respectively. After matching, adjusted SVR24 rates were between 73–74% and 60–61% for telaprevir/PR and boceprevir/PR, respectively.

Conclusion

Efficacy rates were comparable with those reported in pivotal clinical trials and real world studies. After adjusting for confounding, we conclude that there was no difference in treatment effect after PS matching. The small sample size limits the conclusions that can be made about the effect of PS matching. Propensity score adjustment remains a tool that can be applied to future analysis, however, we suggest, where possible, using a larger sample size in order to reduce the uncertainty around the outcomes.
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Literature
1.
Ades AE, Sculpher M, Sutton A, Abrams K, Cooper N, Welton N, et al. Bayesian methods for evidence synthesis in cost-effectiveness analysis. Pharmacoeconomics. 2006;24(1):1–19.CrossRefPubMed
2.
Dreyer NA, Tunis SR, Berger M, Ollendorf D, Mattox P, Gliklich R. Why observational studies should be among the tools used in comparative effectiveness research. Health Aff (Millwood). 2010;29(10):1818–25.CrossRef
3.
Berger ML, Dreyer N, Anderson F, Towse A, Sedrakyan A, Normand SL. Prospective observational studies to assess comparative effectiveness: the ISPOR good research practices task force report. Value Health. 2012;15(2):217–30.CrossRefPubMed
4.
Silverman SL. From randomized controlled trials to observational studies. Am J Med. 2009;122(2):114–20.CrossRefPubMed
5.
Rawlins M. De testimonio: on the evidence for decisions about the use of therapeutic interventions. Lancet. 2008;372(9656):2152–61.CrossRefPubMed
6.
Ligthelm RJ, Borzi V, Gumprecht J, Kawamori R, Wenying Y, Valensi P. Importance of observational studies in clinical practice. Clin Ther. 2007;29 Spec No:1284–92.CrossRefPubMed
7.
Dowd R, Recker RR, Heaney RP. Study subjects and ordinary patients. Osteoporos Int. 2000;11(6):533–6.CrossRefPubMed
8.
Heiat A, Gross CP, Krumholz HM. Representation of the elderly, women, and minorities in heart failure clinical trials. Arch Intern Med. 2002;162(15):1682–8.CrossRefPubMed
9.
Marko NF, Weil RJ. The role of observational investigations in comparative effectiveness research. Value Health. 2010;13(8):989–97.CrossRefPubMed
10.
van Vollenhoven RF, Severens JL. Observational studies: a valuable source for data on the true value of RA therapies. Clin Rheumatol. 2011;30 Suppl 1:S19–24.CrossRefPubMed
11.
Garrison LP, Neumann PJ, Erickson P, Marshall D, Mullins CD. Using real-world data for coverage and payment decisions: the ISPOR real-world data task force report. Value Health. 2007;10(5):326–35.CrossRefPubMed
12.
Kennedy L, Craig AM. Global registries for measuring pharmacoeconomic and quality-of-life outcomes: focus on design and data collection, analysis and interpretation. Pharmacoeconomics. 2004;22(9):551–68.CrossRefPubMed
13.
14.
15.
16.
17.
Greenfield S, Platt R. Can observational studies approximate RCTs? Value Health. 2012;15(2):215–6.CrossRefPubMed
18.
Boyko EJ. Observational research--opportunities and limitations. J Diabet Complications. 2013;27(6):642–8.CrossRef
19.
Lindor RA, Lindor KD. The value of observational research in liver diseases. Hepatology. 2011;53(1):1–3.CrossRefPubMed
20.
Chang TI, Winkelmayer WC. Comparative effectiveness research: what is it and why do we need it in nephrology? Nephrol Dial Transplant. 2012;27(6):2156–61.CrossRefPubMed
21.
22.
Quartey G, Feudjo-Tepie M, Wang J, Kim J. Opportunities for minimization of confounding in observational research. Pharm Stat. 2011;10(6):539–47.CrossRefPubMed
23.
Wunsch H, Linde-Zwirble WT, Angus DC. Methods to adjust for bias and confounding in critical care health services research involving observational data. J Crit Care. 2006;21(1):1–7.CrossRefPubMed
24.
Austin PC. The relative ability of different propensity score methods to balance measured covariates between treated and untreated subjects in observational studies. Med Decis Making. 2009;29(6):661–77.CrossRefPubMed
25.
Austin PC. The performance of different propensity-score methods for estimating differences in proportions (risk differences or absolute risk reductions) in observational studies. Stat Med. 2010;29(20):2137–48.CrossRefPubMedPubMedCentral
26.
Austin PC. A critical appraisal of propensity-score matching in the medical literature between 1996 and 2003. Stat Med. 2008;27(12):2037–49.CrossRefPubMed
27.
Austin PC. Propensity-score matching in the cardiovascular surgery literature from 2004 to 2006: a systematic review and suggestions for improvement. J Thorac Cardiovasc Surg. 2007;134(5):1128–35.CrossRefPubMed
28.
Ghany MG, Strader DB, Thomas DL, Seeff LB. Diagnosis, management, and treatment of hepatitis C: an update. Hepatology. 2009;49(4):1335–74.CrossRefPubMed
29.
Pol S, Vallet-Pichard A, Corouge M, Mallet VO. Hepatitis C: epidemiology, diagnosis, natural history and therapy. Contrib Nephrol. 2012;176:1–9.CrossRefPubMed
30.
Thornton L, Murphy N, Jones L, Connell J, Dooley S, Gavin S, et al. Determination of the burden of hepatitis C virus infection in Ireland. Epidemiol Infect. 2012;140(8):1461–8.CrossRefPubMed
31.
Ghany MG, Nelson DR, Strader DB, Thomas DL, Seeff LB. An update on treatment of genotype 1 chronic hepatitis C virus infection: 2011 practice guideline by the American Association for the Study of Liver Diseases. Hepatology. 2011;54(4):1433–44.CrossRefPubMedPubMedCentral
32.
Petta S, Cabibbo G, Enea M, Macaluso FS, Plaia A, Bruno R, et al. Personalized cost-effectiveness of boceprevir-based triple therapy for untreated patients with genotype 1 chronic hepatitis C. Dig Liver Dis. 2014;46(10):936–42.CrossRefPubMed
33.
Arnaud C, Trepo C, Petit MA. Predictors of the therapeutic response in hepatitis C. A 2013 update. Clin Res Hepatol Gastroenterol. 2014;38(1):12-7.
34.
Beinhardt S, Rutter K, Stattermayer AF, Ferenci P. Revisiting the predictors of a sustained virologic response in the era of direct-acting antiviral therapy for hepatitis C virus. Clin Infect Dis. 2013;56(1):118–22.CrossRefPubMed
35.
36.
Petta S, Craxi A. How to optimize HCV therapy in genotype 1 patients: predictors of response. Liver Int. 2013;33 Suppl 1:23–9.CrossRefPubMed
37.
Poordad F, Bronowicki J, Gordon SC, Zeuzem S, Jacobson IM, Sulkowski MS, et al. Factors that predict response of patients with hepatitis C virus infection to Boceprevir. Gastroenterology. 2012;143(3):608–18. e5.CrossRefPubMed
38.
IBMCorp. IBM SPSS Statistics for Mac. Version 21 ed. Armonk: IBM Corp; 2012.
39.
StataCorp. Stata Statistical Software. Release 14 ed. College Station: StataCorp LP; 2015.
40.
Jacobson IM, McHutchison JG, Dusheiko G, Di Bisceglie AM, Reddy KR, Bzowej NH, et al. Telaprevir for previously untreated chronic hepatitis C virus infection. N Engl J Med. 2011;364(25):2405–16.CrossRefPubMed
41.
Sherman KE, Flamm SL, Afdhal NH, Nelson DR, Sulkowski MS, Everson GT, et al. Response-guided telaprevir combination treatment for hepatitis C virus infection. N Engl J Med. 2011;365(11):1014–24.CrossRefPubMed
42.
Zeuzem S, Andreone P, Pol S, Lawitz E, Diago M, Roberts S, et al. Telaprevir for retreatment of HCV infection. N Engl J Med. 2011;364(25):2417–28.CrossRefPubMed
43.
Bacon BR, Gordon SC, Lawitz E, Marcellin P, Vierling JM, Zeuzem S, et al. Boceprevir for previously treated chronic HCV genotype 1 infection. N Engl J Med. 2011;364(13):1207–17.CrossRefPubMedPubMedCentral
44.
Poordad F, McCone Jr J, Bacon BR, Bruno S, Manns MP, Sulkowski MS, et al. Boceprevir for untreated chronic HCV genotype 1 infection. N Engl J Med. 2011;364(13):1195–206.CrossRefPubMedPubMedCentral
45.
Poordad F, McCone J, Jr., Bacon BR, Bruno S, Manns MP, Sulkowski MS, et al. Boceprevir for untreated chronic HCV genotype 1 infection; Supplemental Appendix. N Engl J Med. 2011;364(13):1-67.
46.
Gordon SC, Muir AJ, Lim JK, Pearlman B, Argo CK, Ramani A, et al. Safety profile of boceprevir and telaprevir in chronic hepatitis C: Real world experience from HCV-TARGET. J Hepatol. 2015;62(2):286–93.CrossRefPubMed
47.
Mauss S, Böker K, Buggisch P, Christensen S, Hofmann WP, Schott E, et al. Real-life experience with first generation HCV protease inhibitor therapy in Germany: the prospective, non-interventional PAN cohort. Z Gastroenterol. 2015;53(7):644–54.CrossRefPubMed
48.
Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivar Behav Res. 2011;46(3):399–424.CrossRef
Metadata
Title
Effectiveness of triple therapy with direct-acting antivirals for hepatitis C genotype 1 infection: application of propensity score matching in a national HCV treatment registry
Authors
Emma Gray
David J. Pasta
Suzanne Norris
Aisling O’Leary
on behalf of the Irish Hepatitis C Outcomes and Research Network (ICORN)
Publication date
01-12-2017
Publisher
BioMed Central
Published in
BMC Health Services Research / Issue 1/2017
Electronic ISSN: 1472-6963
DOI
https://doi.org/10.1186/s12913-017-2188-1

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