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Dynamic Cost-Effectiveness of Oncology Drugs
Yang Lu, PhD; John R. Penrod, PhD; Neeraj Sood, PhD; Saarah Woodby, BA; and Tomas Philipson, PhD
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 A -- Value of Survival Gains in Chronic Myeloid Leukemia
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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
eAppendix -- New Approaches to Measuring Value in Oncology Therapy
Participating Faculty: New Approaches to Measuring Value in Oncology Therapy

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
The second part of the statistical analysis forecasted improvements in CML and other-cause survival from 2000 to 2055 by applying the Lee-Carter method to the year-specific (2000-2008) SEER survival curves. This method involved modeling age-specific mortality rates in terms of a long-term trend in overall mortality and an age-specific response to the overall trend.21,22 Furthermore, sensitivity analyses tested the robustness of our results to alternative survival forecasts. The eAppendix describes the Lee-Carter method in detail and presents sensitivity analyses where the option value of innovative CML treatments is recalculated using the lower and upper bounds of the survival forecasts’ 95% confidence intervals.

We calculated the option value of innovative TKI treatments relative to the survival profile of a CML patient with the average age in the sample (62 years) diagnosed in 2000. Finally, we used an economic model based on previous work by Becker et al18 and Philipson et al2 to express option value in monetary terms. This economic model is described in the eAppendix.

Results

The option value of innovative TKI therapies, accounting for medical progress in CML and background mortality, is shown in Table 2. These gains were quantified in the context of 3 possible scenarios. The first scenario (column 1) represents the survival gain and option value derived from first-line therapy for patients who have not developed resistance to treatment, relative to patients in the control group. This option value arises from future reductions in all-cause mortality, future advances in first-line treatment of CML, and future availability of second-line therapies if first-line treatment fails. The second scenario (column 2) represents the survival gain and option value of second-line therapy for patients in whom first-line treatment fails, as compared with patients in the control group. This option value is generated by future reductions in all-cause mortality, advances in second-line treatment of CML, and future availability of third-line therapy if second-line treatment fails. Calculating the weighted average of columns 1 and 2 reveals the third scenario (column 3) as the expected survival gain and option value for a recently diagnosed hypothetical CML patient with access to second-line therapies if first-line treatment fails.

Per the results in Table 2, there is almost negligible option value among CML patients from medical progress against background mortality (ie, 0.02-0.04 life-years) even though TKIs provide non-negligible survival benefits against other diseases (ie, 0.82-1.99 life-years). The option value of firstline treatment with imatinib as a bridge to further innovation in CML treatment alone (and not other diseases) accounts for 96% of the total option value.

First-line treatment provides an estimated total life expectancy gain of 9.54 life-years in CML patients who do not experience treatment failure, as compared with the control group (Table 2, column 1). In addition, future medical progress in CML treatment and background mortality provides patients who have not developed resistance to first-line treatment an option value of 0.78 life-years, or 8.2% of the total life-expectancy gain. Conversely, second-line treatments provide an estimated total life-expectancy gain of 6.82 life-years in CML patients who have experienced first-line treatment failure (Table 2, column 2). For these patients, the option value of second-line treatment from future medical progress against CML and background mortality is 0.71 lifeyears, or 10.4% of the total life-expectancy gain. On average, the option value of innovative TKI treatments for a recently diagnosed CML patient is 0.76 life-years, or 8.7% of the 8.73 expected life-year gain from first- and second-line treatments (Table 2, column 3).

Expressing all life-year gains as a private monetary valuation,2,18 the option value of first-line treatment is worth approximately $66,000. For patients who develop resistance to first-line treatment, the option value of second-line treatment is worth nearly $57,000. Newly diagnosed patients have an average (or expected) option value of 0.76 life-years, worth approximately $63,000.

Discussion

For this study we developed an analytical framework for incorporating option value into the standard calculation of the value of a health innovation, and applied this framework to the case of innovative CML therapies. While economic theory suggests the presence of option value in the context of medical treatment, this source of value has been ignored in the literature on health technology assessment. This study is among the first applications of option value to the assessment of pharmaceutical innovation, and the first to measure option value prospectively.

Our findings show that, in the context of CML, the option value of innovative TKI therapies is equivalent to 9% of their average survival gain. Thus, ignoring the option value of these treatments underestimates their effectiveness by approximately 9%. In monetary terms, an option value of $63,000 is a sizable benefit, especially when compared with the annual costs of TKI therapies, which range from $30,000 to $70,000.23 Although a thorough cost-effectiveness analysis of these therapies would require an assessment of the costs incurred in the additional years of life extension, our findings suggest that the option value may fall within the range of costs for the first year of TKI treatment.

An intrinsic limitation of our study is that option value estimates depend on forecasts of future improvements in CML and other-cause survival. Although forecasts are inherently uncertain and not definitive, ours were based on highquality and representative data on historical survival gains. A sensitivity analysis addressed this issue by recalculating option value at the lower and upper bounds of the survival forecasts’ 95% confidence intervals; this sensitivity analysis is shown in the eAppendix. Proceeding from the least to the most optimistic forecast scenario, the average option value of a newly diagnosed patient increased from 0.36 life-years (with a net worth of $34,000) to 1.16 life-years (with a net worth of $92,000).

Given the limited time-span of our sample (2000-2008), we assumed survival past 7 years from diagnosis declined at the same rate as in the general population, based on the HMD. Although this assumption forces survival curves in the treatment and control groups to decay at the same rate, it is conservative to the extent that the control group’s survival curve may actually decay at a faster rate than those of the treatment groups. Nevertheless, we performed an even more conservative sensitivity test by limiting the analysis to 7 years post-diagnosis. Only 30% of survival gains and 20% of the estimated option value accrued in the first 7 years after diagnosis. In this more conservative scenario the option value as a percentage of the survival gains from TKI treatments was reduced from 9% to 7%, given the limited time frame for the benefits from future medical breakthroughs to accrue.

Because option value captures the benefits from surviving long enough to take advantage of the next medical breakthrough, it is determined exclusively by the effectiveness of present and future treatments. In this regard, the greater option value of first-line treatment relative to second-line TKIs can be attributed largely to the substantial survival benefits of second-generation therapies. Several therapeutic approaches for a cure for CML are under evaluation,24-27 suggesting that actual innovation in second- and later-line CML treatment may develop faster than forecasted. In such a scenario, future research may provide a larger benefit from first- and second-line treatment than estimated here.

Given the available survival data for CML patients, this study, by necessity, focused on imatinib as the only first-line TKI treatment; however, both dasatinib and nilotinib have been found to offer better cytogenetic response than imatinib in recently completed trials,8,12,13,17 which points to greater survival gains.28 Although our study did not directly quantify the option value of using second-generation TKIs in firstline treatment, based on the survival improvements relative to first-generation treatment that have been recently documented in the literature,8,12,13,17 we could expect larger option value from the newer TKIs if given as first-line therapy.

While the primary analysis used SEER data over the period 2000 to 2008, 2 sensitivity analyses reported in the eAppendix were used to determine whether CML-specific survival improved at an uncharacteristic rate over this period. Including patients diagnosed with CML as early as 1995 in the Cox proportional hazards regression provided quantitatively similar results and, subsequently, estimating option value at the lower and upper bounds of the survival forecasts’ 95% confidence intervals also yielded similar results.

We also assessed the sensitivity of our option value estimates by varying the probability of first-line treatment failure over a wider spectrum than previously suggested.20 Estimates were not overly sensitive to this key parameter, as the average option value for a recently diagnosed CML patient from future innovations in CML treatment ranged from 0.62 lifeyears (with a failure probability of 0.05) to 0.82 life-years (with a failure probability of 0.50) (see eAppendix).

While our analysis is tailored to the specific context of innovative TKI treatments for CML, our methodology also can be applied to other diseases. The feasibility of this method will naturally be favored in those areas for which comprehensive survival data are available (as is the case with SEER data in oncology). Although it is still possible to measure option value in disease areas for which survival data are scant but sufficient to identify treatment efficacy and posttreatment survival, such analyses will inevitably be subject to greater uncertainty.

Conclusion

Recent innovations in the treatment of CML have increased patient survival not only by improving the management of the disease, but also by allowing patients to live long enough to experience more effective future treatments. For a recently diagnosed CML patient, the option value of innovative therapies in terms of future medical innovations in CML and other diseases amounts to 0.76 life-years. This option value is equivalent to 9% of the average survival gains from existing treatments and is worth approximately $63,000. Future innovations in CML treatment jointly account for 96% of this benefit.

Our study demonstrates to researchers and payers that, by ignoring option value, the traditional methods of health technology assessment undervalue life-extending healthcare innovations, particularly those in areas of medicine in which rapid innovation is producing substantial survival gains. We provided methods for incorporating option value into standard health-technology assessment, and identified the scenarios for which this methodology could be applied in the future. It is worth noting that ongoing medical progress against a particular disease guarantees that the option value of available treatments will always be positive.

 
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