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The American Journal of Managed Care October 2017
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The Option Value of Innovative Treatments for Non–Small Cell Lung Cancer and Renal Cell Carcinoma
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The Option Value of Innovative Treatments for Non–Small Cell Lung Cancer and Renal Cell Carcinoma

Julia Thornton Snider, PhD; Katharine Batt, MD, MSc; Yanyu Wu, PhD; Mahlet Gizaw Tebeka, MS; and Seth Seabury, PhD
Option value is the benefit a therapy provides patients by enabling them to survive to the next innovation.
Step 4: calculate option value in terms of life expectancy gains. Using the survival curves from Steps 1 and 3 and the survival forecasts from Step 2, we calculated the undiscounted life expectancies of patients in each population for several scenarios. First, we calculated life expectancy under the pre-nivolumab standard of care, assuming no future innovation; call this LEpre-nivo. Second, we calculated life expectancy with nivolumab, assuming no future innovation; call this LEnivo. Finally, we calculated life expectancy with nivolumab allowing for future innovation based on the forecasts from Step 2; call this ELnivo.

We calculated the conventional survival gain with nivolumab by comparing life expectancy with nivolumab to that with the pre-nivolumab standard of care. Specifically:

Conventional survival gain with nivolumab = LEnivo – LEpre-nivo

To calculate the option value of nivolumab, we compared life expectancy with nivolumab assuming no further innovation to expected lifetime with nivolumab allowing for future innovation. Specifically:

Option value of nivolumab = ELnivoLEnivo

Step 5: calculate option value in economic terms. Finally, we expressed the conventional and option values in economic terms by applying an economic value of a life year to the additional life years gained. We selected a mid-range value from the literature of $150,000 per life year41,42 and applied a discount rate of 3% to obtain present discounted values. The per-patient option value was multiplied by the estimated size of each patient population to obtain the total economic values in each population. Population sizes were estimated using several sources.28,43-47 

Sensitivity Analysis

To test the robustness of the study results to the underlying assumptions, several sensitivity analyses were performed. First, we estimated an alternative parametric survival model (log logistic). This tested the sensitivity of the results to our choice of parametric model. Second, we estimated survival exclusively using the parametric model rather than taking HMD mortality rates after 20 years. This tested the effect of our use of the HMD data. Third, we assumed nivolumab would be taken in the first year after diagnosis, rather than the second. This reflected the fact that metastatic cancer can progress rapidly and, therefore, some patients could potentially reach second-line therapy in the first rather than second year from diagnosis. Fourth, we varied the duration post diagnosis that nivolumab would be effective, from 2 to 10 years. This addressed the limited duration of clinical trial data and the accompanying uncertainty about the duration of nivolumab’s effects. Fifth, we estimated nivolumab’s mortality benefits using the confidence intervals of the published mortality HRs in order to address uncertainty about the exact magnitude of nivolumab’s effects of survival. Sixth, we varied the discount rate from 0% to 6%. Seventh, we varied the value of a life year from $50,000 to $250,000.26,27 Last, we varied the stage definition used for the selection of the SEER RCC data, using AJCC stage IV instead of the historic “distant” stage. (We used the historic stage definition in our base case analysis because it was better populated and we wanted to test the sensitivity of our results to this choice.)


Study Populations

The Table presents descriptive statistics on the 3 study populations in SEER. The nonsquamous NSCLC population was the largest, at 210,419 individuals, followed by squamous NSCLC (49,194) and RCC (12,868). The RCC population was younger than the squamous and nonsquamous NSCLC populations, with average ages of 64.5, 69.0, and 68.0 years, respectively. A higher share of patients with nonsquamous NSCLC (44%) was female compared with squamous NSCLC (35%) and RCC (33%). Patients with RCC were more likely to be married (60%) compared with patients with squamous (52%) or nonsquamous (53%) NSCLC. Racial composition was similar, with whites composing over 80% of all 3 groups. Median survival was 8 months in RCC and 7 months in both squamous and nonsquamous NSCLC.

Survival Trends

All 3 populations showed an increasing 1-year survival rate in the 2001 to 2010 SEER data (Figure 1). Projected survival in 2011 to 2060 according to the Lee-Carter method is shown via the dashed lines. Survival improved the most quickly in RCC (0.44% per year), followed by nonsquamous NSCLC (0.39%) and squamous NSCLC (0.27%).

Life Expectancy Estimates and Option Value

Life expectancy for patients taking the pre-nivolumab standard of care was estimated to be 18.2 months in RCC, 11.7 months in nonsquamous NSCLC, and 11.6 months in squamous NSCLC. Ignoring future innovations, patients taking nivolumab were expected to survive 24.5 months with RCC, 16.2 months with nonsquamous NSCLC, and 19.1 months with squamous NSCLC, implying gains of 6.3 months, 4.5 months, and 7.5 months, respectively. These gains are shown in blue in Figure 2 and represent the conventional survival gains from nivolumab.

However, during the time that nivolumab patients’ survival was extended, we allowed for additional innovations to come to market. Incorporating expected innovation, nivolumab extends survival by an additional 1.2 months in RCC, 0.5 months in nonsquamous NSCLC, and 0.4 months in squamous NSCLC. These additional gains due to option value represent 18% of nivolumab’s conventionally estimated survival gain in RCC, 10% in nonsquamous NSCLC, and 5% in squamous NSCLC.

Valuing the per-patient survival gains over the full incident metastatic population with each tumor, we found a conventional economic value from nivolumab of $775 million in RCC and an option value of $105 million (Figure 3). Due to its higher incidence, economic values were larger in NSCLC. The conventional value of nivolumab was $2.6 billion in nonsquamous NSCLC and $2.0 billion in squamous NSCLC, while the option values were $203 million and $73 million, respectively. Although these valuations are based on a mid-range value of a quality-adjusted life year, it should be noted that debate exists about the best way to provide economic valuations of incremental changes in survival, such as those in this study.41,42,48

Sensitivity Analysis

The study results were robust to a variety of specifications. Across the 3 populations, the value of a life year was particularly influential on option value in economic terms. Varying the value from $50,000 to $250,000 changed the option value from $35 to $174 million in RCC, $68 to $339 million in nonsquamous NSCLC, and $24 to $122 million in squamous NSCLC. Varying the discount rate was also influential, with a 0% discount rate leading to the largest option values ($180 million in RCC, $316 million in nonsquamous NSCLC, $118 million in squamous NSCLC) and 6% to the lowest ($67 million in RCC, $141 million in nonsquamous NSCLC, $49 million in squamous NSCLC). The nivolumab mortality HR was particularly influential on option value in life expectancy terms, with values at the lower (higher) end of the confidence intervals producing the highest (lowest) option value (1.42 vs 0.88 months in RCC, 0.56 vs 0.35 in nonsquamous NSCLC, 0.46 vs 0.27 in squamous NSCLC). Assuming a longer duration of benefit from nivolumab and allowing nivolumab therapy to start in the first, rather than second, year after diagnosis also led to greater option value. Results were qualitatively similar regardless of the parametric model used, whether HMD was used, and the stage definition. (Additional detail is available in the eAppendix.)


The study results show that incorporating option value can substantially increase the conventionally calculated value of a therapy. The option value of nivolumab accounts for an additional gain of 1.2 months (18% of conventional survival gain) in metastatic RCC, 0.5 months (10%) in nonsquamous NSCLC, and 0.4 months (5%) in squamous NSCLC. Over the full US incident population, this amounted to an option value of $105 million in metastatic RCC. Given the high incidence of lung cancer, the option value was greater in nonsquamous NSCLC ($203 million) and squamous NSCLC ($73 million). These results show that option value is quantitatively meaningful.

This concept of option value has been introduced in other diseases, such as HIV/AIDS, breast cancer, and chronic myeloid leukemia,20,29,30 where innovation alters survival and therefore the value of life near its end.19 This study adds to the existent literature, showing that option value can be important in various healthcare contexts with rapid innovation, as seen in metastatic RCC and NSCLC.

Although our analysis focused on metastatic RCC and NSCLC, the methodology can be applied in other therapeutic areas. The study results demonstrate the need for payers and providers to be aware of attributes of therapies that patients value that are not reflected in traditional value metrics, like the value of hope, the value of life near its end, and the insurance value of therapy.17-19 Option value is closely related to these concepts, since the option of surviving to see new therapies may give patients hope. Such considerations may be particularly important for patients near the end of life, for example, with a terminal cancer diagnosis. Moreover, option value is especially relevant to patients with metastatic cancer because of rapid innovation in this area. 

This study's results suggest promising directions for future research of relevance to payers, providers, and patients. Option value studies can better inform payers and providers of expected survival gains in areas of rapid innovation, as well as their economic value. Further research is needed to understand the patient perspective on innovative therapies and their value. For example, patients could be surveyed on their perceptions and valuations of option value in different disease states. Such research could help to improve the care of patients being treated for serious illnesses, such as cancer.


This study has limitations. First, SEER is an incidence sample; therefore, we assumed second-line therapy started 1 year after diagnosis. Second, the SEER population could not be made perfectly comparable with the trial population, thereby affecting life expectancy estimates. In particular, because SEER is an incidence sample and does not report therapies used over time, it was not possible to select only those patients who took the second-line therapies with which nivolumab was compared in the trials (docetaxel in NSCLC and everolimus in RCC). Instead, we obtained the nivolumab survival curves by applying the mortality HRs from the trials to the pre-nivolumab survival curves from SEER. Therefore, both the pre-nivolumab and nivolumab survival estimates in our model are based on the SEER population and should be similarly affected by this assumption. As a result, the effect on our option value estimates should be minimal.

Third, the option value calculations are based on forecasted mortality improvements, which are inherently less accurate than historical data. However, this approach allows us to calculate option value for current treatments rather than focusing on purely historical examples. To do so, we used the Lee-Carter method, which is widely used to forecast improvements in mortality, including by the US Census Bureau and Social Security Administration.40

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