Currently Viewing:
Supplements New Approaches to Measuring Value in Oncology Therapy
Dynamic Cost-Effectiveness of Oncology Drugs
Yang Lu, PhD; John R. Penrod, PhD; Neeraj Sood, PhD; Saarah Woodby, BA; and Tomas Philipson, PhD
Currently Reading
Value of Survival Gains in Chronic Myeloid Leukemia
Wesley Yin, PhD; John R. Penrod, PhD; J. Ross Maclean, MD; Darius N. Lakdawalla, PhD; and Tomas Philipson, PhD
Appendix B -- Value of Survival Gains in Chronic Myeloid Leukemia
The Option Value of Innovative Treatments in the Context of Chronic Myeloid Leukemia
Yuri Sanchez, PhD; John R. Penrod, PhD; Xiaoli Lily Qiu, PhD; John Romley, PhD; Julia Thornton Snider, PhD; and Tomas Philipson, PhD
Coverage and Use of Cancer Therapies in the Treatment of Chronic Myeloid Leukemia
Theodore Darkow, PharmD; J. Ross Maclean, MD; Geoffrey F. Joyce, PhD; Dana Goldman, PhD; and Darius N. Lakdawalla, PhD
eAppendix -- New Approaches to Measuring Value in Oncology Therapy
Participating Faculty: New Approaches to Measuring Value in Oncology Therapy

Value of Survival Gains in Chronic Myeloid Leukemia

Wesley Yin, PhD; John R. Penrod, PhD; J. Ross Maclean, MD; Darius N. Lakdawalla, PhD; and Tomas Philipson, PhD
Although clinical trial data have quantified patient survival gains associated with tyrosine kinase inhibitors in chronic myeloid leukemia, the overall value of these benefits is unknown.
Table 1 shows the patient characteristics of all CML patients in the SEER registry and the SEER CML sample. Incident cohorts of CML patients diagnosed in 2000 or later were included in survival-gain estimations associated with the introduction of first-line imatinib treatment. Restricting the data to SEER CML registrants for whom key demographic controls were reported generated a final analytical sample of 5,523 patients. Those in the CML subsample were demographically similar to patients from the full SEER CML sample, with the exception of 2 variables; namely, survival time (which was expected given the greater probability of survival among CML patients diagnosed at later dates) and Hispanic race (which likely resulted from a broader definition of “Hispanic” in more recently diagnosed patients).

Survival Gains: First- Line Therapy

Table 2 shows the results from the multivariate Cox proportional hazard analysis of survival impact following the 2001 introduction of first-line TKI therapy. The independent variable of interest is the post-TKI variable, which takes the value of 1 in 2001 and thereafter. The coefficient of this variable can be interpreted as the HR corresponding to the introduction of imatinib. Table 2 also depicts the most flexible form of the secular effects of time trend and time since diagnosis; year-of-diagnosis indicators and quadratic trend for month-of-diagnosis were included as controls for the secular trend in survival. As shown, the post-TKI variable was associated with an HR of 0.833 (P <.01). The implied TOT survival ratio of 1.307 can be interpreted as imatinib causing an immediate ~30% increase in the probability of CML survival at 90 months. This effect can be seen in the Figure, which shows the estimated pre-TKI and post-TKI survival curves for the treated patients. The survival ratio is equivalent to the vertical distance between curves at 90 months. Alternatively, the HR can be characterized by the median survival length (the life expectancy of a 50th percentile CML patient; ie, the horizontal distance between the curves). The HR of 0.833 corresponds to an estimated increase in median survival from 90 to 210 months.

As previously discussed, the effect of imatinib was estimated from the sustained shift in the survival curve that occurred in 2001, the year of the drug’s introduction. As a sensitivity analysis, we evaluated whether shifts were observable in the survival curve at other years, as a large, sustained shift in survival occurring in any other year might imply that the estimated survival effect at 2001 was driven by factors unrelated to imatinib. To evaluate this, the survival analysis was repeated using a post-year variable for each year between 1998 and 2005. Reported P values for each estimated HR of the post-year variable are available in Appendix B. The only statistically significant coefficient corresponded to the post-2001 (ie, post-TKI) variable.

Survival Gains: Second-Line Therapy

OS rates reported in first-line imatinib studies13,26 were averaged, with response rates weighted by study sample size. This was then compared with OS rates in second-line dasatinib therapy.20 As shown in Table 3, the relative effectiveness of dasatinib in second-line therapy, as compared with imatinib in first-line therapy, was 91%. Under the assumption that the differences in clinical versus community survival rates would be the same for dasatinib and imatinib, we applied this 91% to the survival rate ratio of imatinib estimated in the SEER-based proportional hazard analysis.

Value and Costs

Table 4a shows the cost of treatment, the value of survival gained through treatment, and the value of gains for patients treated with imatinib as a first-line response to CML. Estimated annual and lifetime costs are reported in the first line of Table 4a. The annual value of TKI-related survival gains (column 1) is equivalent to the increase in annual income necessary to make a CML patient indifferent to the pre- and post-treatment survival curves, which is also equivalent to the patient’s willingness to pay for treatment. Column 2 shows the present lifetime value of survival gains per individual treated with imatinib, column 3 illustrates the lifetime value of TKI treatment across all newly diagnosed US CML patients over a 1-year period, and column 4 shows the lifetime value of TKI treatment for all present and future US CM L patient cohorts. Note that the fraction of total value recouped by drug manufacturers is lower in column 4 than in columns 1 through 3. This reflects the assumption that the cost to future CML cohorts of treatment after patent expiration is negligible relative to prices under patent. Columns 1 to 4 in Table 4b show corresponding values for dasatinib in second-line therapy.

These results indicate that patients place an annual value of $110,600 on first-line TKI treatment relative to annual costs (under patent) of $30,500. This implies that, for all patients in present and future CML cohorts, the present social value of first-line TKI therapy is $88 billion. The present value of these costs, accounting for future patent expirations, was estimated to be $8.24 billion. Hence, approximately 91% of the social value of TKIs in first-line therapy is retained by patients, while 9% is recouped by drug companies. Likewise, dasatinib used as second-line CML therapy creates $55 billion in social value, of which patients retain roughly 90%, while 10% is recouped by drug companies.

Discussion

This study evaluated the social value of CML survival gains achieved by treatment with TKIs. This analysis attributes the discrete 2001 HR drop in CML deaths observable in SEER data to the effect of imatinib treatment; this finding was robust to flexible controls for secular time trends in the survival analysis.

The study applied a novel model to assess the social benefit associated with improved CML patient longevity following the introduction of the TKI drug class. Based on this analysis, the TKI drug class in first- and second-line CML therapy has created over $143 billion in present discounted social value. Approximately 90% of this value will be derived from survival gains to be retained by patients and society, while ~10% will be recouped by drug companies. This proportional allocation corresponds with prior research using a similar model, which found that, between 1988 and 2006, 3% to 12% of the value of overall survival gains from cancer treatments was appropriated by drug companies.21 These estimates also suggest that, at current price levels, the vast majority of value created by TKI therapy in CML is appropriated as aggregate benefit to consumers; in other words, patients, not drug companies, are the primary beneficiaries of TKI therapy in CML.

An understanding of the social value of TKI treatment in CML has implications for therapeutic reimbursement and pricing, as well as for healthcare professionals’ awareness of how CML treatment costs contextualize to overall social benefit. Payers succeed in a competitive marketplace when they provide value to patients. From this perspective, the sizable lifetime value of TKI therapy to CML patients (relative to the cost of therapy) provides ample justification for facilitating patients’ access to TKI therapy. While the extant literature calls into question the cost-effectiveness of some seemingly expensive new cancer therapies, the results of this study (based upon comprehensive economic-impact evaluation) underscore the importance of taking into account the social value of such therapies and the attendant lifetime benefits accruable to patients (and not just the contemporaneous cost) in making payer and policy decisions. For instance, it is important to weigh the social value of therapies against costs in making assessments about the impact of managed care on the quality of healthcare delivery.

It is worth noting that the current study’s survival improvement estimates are somewhat smaller than those reported in clinical trials of TKIs. This study estimated a 90-month TOT survival rate of 65% after the introduction of imatinib, which is substantially lower than the 90-month survival rate reported in clinical trials.12,17,27 This may be due to inadequate dosing or poorer monitoring/adherence in community settings relative to clinical trial settings, particularly in the years immediately following the introduction of imatinib. These survival estimates suggest the potential value of addressing real-world obstacles to TKI efficacy, such as poor adherence.

In terms of study limitations, the value of survival gains and costs in second-line therapy identified by this study were confined to clinical trial and cost data for dasatinib, which was the first molecule to receive approval for a second-line CML indication. The additional benefit of a subsequently approved second-line TKI molecule (nilotinib) was not evaluated in this study. As a result, the current figures are conservative to the extent that they omit possible benefits that could accrue from having another second-line agent available. Moreover, the estimated value due to the availability of these second-generation TKI agents is conservative, because the empirical analysis did not capture the incremental benefits that these agents would provide in first-line use. Both dasatinib and nilotinib have demonstrated superiority to imatinib in first-line clinical trials, and received FDA approval for this use in 2010.14-16,28

In addition, the current study’s estimate of value is derived solely from survival gains. To the extent that treatment leads to other benefits, such as reduced caregiver burden or reductions in medical expenditures due to improved health, the fraction of total value retained by patients and society is likely to be underestimated.

Author affiliations: Leonard D. Schaeffer Center for Health Policy and Economics, School of Pharmacy, and Sol Price School of Public Policy, University of Southern California, Los Angeles, CA (DNL); Bristol-Myers Squibb, Plainsboro, NJ (JRM, JRP); Harris Graduate School of Public Policy, University of Chicago, Chicago, IL (TP); Department of Economics, Boston University, Boston, MA (WY).

Funding source: This supplement was supported by Bristol-Myers Squibb. Author disclosures: Dr Maclean and Dr Penrod report employment with and stock ownership in Bristol-Myers Squibb. Dr Lakdawalla and Dr Philipson report consultancy with Bristol-Myers Squibb and partnership in Precision Health Economics. Dr Yin reports consultancy with Precision Health Economics.

Authorship information: Concept and design (DNL, JRM, JRP, TP, WY); acquisition of data (DNL, TP); analysis and interpretation of data (DNL, JRM, JRP, TP, WY); drafting of the manuscript (DNL, JRM, JRP, TP, WY); critical revision of the manuscript for important intellectual content (DNL, JRM, JRP, TP, WY); statistical analysis (WY); obtaining funding (JRM, JRP); and supervision (JRM, WY).

Address correspondence to: Darius N. Lakdawalla, PhD, Leonard D. Schaeffer Center for Health Policy and Economics, University of Southern California, 3335 S Figueroa St, Unit A, Los Angeles, CA 90089-7273. E-mail: dlakdawa@healthpolicy.usc.edu.
  1. Friedman DS,  O’Colmain BJ, Munoz B, et  al.  Prevalence of age-related macular degeneration in the  United States.  Arch Ophthalmol. 2004;122(4):564-572.
  2. Pulte D, Gondos A, Brenner H, et  al.  Ongoing improvement in outcomes for  patients diagnosed as having non-Hodgkin lymphoma from the  1990s to the  early 21st century. Arch Intern Med. 2008;168(5):469-476.
  3. Espey DK, Wu XC, Swan J, et  al.  Annual report to the  nation on  the  status of cancer, 1975-2004, featuring cancer in American Indians and  Alaska natives. Cancer. 2007;110(10):2119-2152.
  4. Breen N, Wagener DK, Brown ML, Davis WW, Ballard-Barbash R. Progress in cancer screening over a decade: results of cancer screening from the  1987, 1992, and  1998 National Health Interview Surveys.  J Nat Cancer Inst.  2001;93(22):1704-1713.
  5. Faguet GB.  The  War on  Cancer: An Anatomy of Failure, A Blueprint for  the Future. New York,  NY: Springer; 2005.
  6. Epstein SS. Cancer-Gate: How to  Win the Losing Cancer War. Amityville, NY: Baywood Publishing Company; 2005.
  7. Shih YC, Halpern MT. Economic evaluations of medical care interventions for  cancer patients: how, why, and  what does it mean?  CA Cancer J Clin.  2008;58(4):231-244.
  8. Hillner  BE, Smith TJ.  Do the  large benefits justify the  large costs of breast cancer trastuzumab? J Clin Oncol. 2007;25(6):611-613.
  9. Kolata G, Pollack A. Costly cancer drug offers hope, but  also a dilemma. The  New York  Times. July 6, 2008.
  10. Berenson A. Cancer drugs offer hope, but  at a huge expense. The  New York  Times. July 12,  2005.
  11. Sun E, Jena AB,  Lakdawalla D, Carolina R, Philipson TJ,  Goldman DP. The  contributions of improved therapy and  earlier detection to cancer survival gains, 1988-2000. Forum for  Health Economics  & Policy. 2010;13(2):1.
  12. O’Brien SG, Guilhot F, Larson RA, et  al.  Imatinib compared with  interferon and  low-dose cytarabine for  newly diagnosed chronic-phase chronic myeloid leukemia. N Engl J Med. 2003; 348(11):994-1004.
  13. Druker  BJ, Guilhot F, O’Brien SG, et  al.  Five-year follow-up of patients receiving imatinib for  chronic myeloid leukemia. N Engl J Med. 2006;355(23):2408-2417.
  14. Cortes JE, Jones D, O’Brien S, et  al.  Results of dasatinib therapy in patients with  early chronic-phase chronic myeloid leukemia. J Clin Oncol. 2010;28(3):398-404.
  15. Kantarjian H, Shah NP, Hochhaus A, et  al.  Dasatinib versus imatinib in newly diagnosed chronic-phase chronic myeloid leukemia. N Engl J Med. 2010;362(24):2260-2270.
  16. Saglio G, Kim DW, Issaragrisil S, et  al.  Nilotinib versus  ima- tinib  for  newly diagnosed chronic myeloid leukemia. N Engl J Med. 2010;362(24):2251-2259.
  17. Talpaz M, Shah NP, Kantarjian H, et  al.  Dasatinib in imatinib- resistant Philadelphia chromosome-positive  leukemias. N Engl J Med. 2006;354(24):2531-2541.
  18. Kantarjian HM, Talpaz M, O’Brien S, et  al.  Survival benefit with  imatinib mesylate versus interferon-alpha-based regimens in newly diagnosed chronic-phase chronic myelogenous leuk mia. Blood. 2006;108(6):1835-1840.
  19. Shah NP, Kantarjian HM, Kim DW, et  al.  Intermittent target inhibition with  dasatinib 100  mg  once daily preserves efficacy and improves tolerability in imatinib-resistant and -intolerant chronic-phase chronic myeloid leukemia. J Clin Oncol. 2008; 26(19):3204-3212.
  20. Shah NP, Cortes JE, Schiffer CA, et  al.  Five-year follow-up of patients with  imatinib-resistant or -intolerant chronic-phase chronic myeloid leukemia (CML-CP) receiving dasatinib. J Clin Oncol. 2011;29.
  21. Lakdawalla DN, Sun EC, Jena AB,  Reyes CM, Goldman DP, Philipson TJ.  An economic evaluation of the  war  on  cancer. J Health Econ. 2010;29(3):333-346.
  22. Becker GS, Philipson TJ,  Soares R. The  quantity and  quality of life  and  the  evolution of world inequality. American Economic Review. 2005;95(1):277-291.
  23. Goldman DP, Jena AB,  Lakdawalla DN, Malin  JL, Malkin  JD,  Sun E. The  value of specialty oncology drugs. Health Serv Res. 2010;45(1):115-132.
  24. Becker G, Murphy K, Philipson T. The  value of life  near its end  and  terminal care. NBER  Working Paper No.13333.2007.
  25. Quintas-Cardama A, Kantarjian HM, Cortes JE. Mechanisms of primary and  secondary resistance to imatinib in chronic myeloid leukemia. Cancer Control. 2009;16(2):122-131.
  26. de  Lavallade H, Apperley JF, Khorashad JS,  et  al.  Imatinib for newly diagnosed patients with  chronic myeloid leukemia: inci- dence of sustained responses in an  intention-to-treat analysis.  J Clin Oncol. 2008;26(20):3358-3363.
  27. Roy  L, Guilhot J, Krahnke T, et  al.  Survival advantage from imatinib compared with  the  combination interferon-alpha plus cytarabine in chronic-phase chronic myelogenous  leukemia: historical comparison between two  phase 3 trials. Blood. 2006; 108(5):1478-1484.
  28. Taylor M, Lewis L, Hirji I, Davis C. Using short-term response rates to predict long-term survival with  dasatinib in chronic myeloid leukemia. Proceedings of the  12th  Annual European School of Hematology Conference – International Conference Chronic Myeloid Leukemia: Biology and  Therapy (ESH-iCMLf); September  24-26, 2010; Washington, DC.
PDF
 
Copyright AJMC 2006-2020 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
x
Welcome the the new and improved AJMC.com, the premier managed market network. Tell us about yourself so that we can serve you better.
Sign Up