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The American Journal of Managed Care October 2017
Low-Value Antibiotic Prescribing and Clinical Factors Influencing Patient Satisfaction
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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
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Tristan Cordier, MPH; S. Lane Slabaugh, PharmD; Eric Havens, MA; Jonathan Pena, MS; Gil Haugh, MS; Vipin Gopal, PhD; Andrew Renda, MD; Mona Shah, PhD; and Matthew Zack, MD

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.

Objectives: To develop a model of the option value a therapy provides by enabling patients to live to see subsequent innovations and to apply the model to the case of nivolumab in renal cell carcinoma (RCC) and non–small cell lung cancer (NSCLC).

Study Design: A model of the option value of nivolumab in RCC and NSCLC was developed and estimated.

Methods: Data from the Surveillance, Epidemiology, and End Results (SEER) cancer registry and published clinical trial results were used to estimate survival curves for metastatic cancer patients with RCC, squamous NSCLC, or nonsquamous NSCLC. To estimate the conventional value of nivolumab, survival with the pre-nivolumab standard of care was compared with survival with nivolumab assuming no future innovation. To estimate the option value of nivolumab, long-term survival trends in RCC and squamous and nonsquamous NSCLC were measured in SEER to forecast mortality improvements that nivolumab patients may live to see.

Results: Compared with the previous standard of care, nivolumab extended life expectancy by 6.3 months in RCC, 7.5 months in squamous NSCLC, and 4.5 months in nonsquamous NSCLC, according to conventional methods. Accounting for expected future mortality trends, nivolumab patients are likely to gain an additional 1.2 months in RCC, 0.4 months in squamous NSCLC, and 0.5 months in nonsquamous NSCLC. These option values correspond to 18%, 5%, and 10% of the conventional value of nivolumab, respectively.

Conclusions: Option value is important when valuing therapies like nivolumab that extend life in a rapidly evolving area of care. 

Am J Manag Care. 2017;23(10):e340-e346
Takeaway Points
  • Therapies that enable patients to live to see further innovations in care have option value. 
  • Option value raises the conventionally estimated value of nivolumab to patients with metastatic cancer by 18% in renal cell carcinoma, 5% in squamous non–small cell lung cancer (NSCLC), and 10% in nonsquamous NSCLC. 
  • Option value is particularly important in disease areas where there is rapid innovation. In such areas, payers and providers should consider option value when gauging the value of new therapies.
Cancer is a leading cause of death in the United States,1 with rising prevalence. In 1995, there were 7.1 million individuals in the US who had ever been diagnosed with cancer (2.7% of the population)2; by 2012, there were 13.4 million such individuals (4.3%).3 Although cancer mortality rates are declining,4 prevalence is expected to increase because of population aging,5,6 advances in cardiovascular care, earlier cancer detection, and life-extending treatment.7,8

Increasing cancer prevalence translates to greater demand for oncology care, with implications for payers. Given growing pressures on payers’ budgets and debate over the cost of cancer treatment,9,10 value is an increasingly important consideration in coverage and access decisions. Moreover, the pressures on payers will increase as cancer prevalence rises, further reinforcing the importance of value.5 

As value has grown in importance in assessing cancer care, organizations have offered recommendations on measuring value. For example, the National Comprehensive Cancer Network and the American Society of Clinical Oncology recently published frameworks for considering a therapy’s efficacy and cost to determine its value.11,12 The Institute of Clinical and Economic Review, an independent health technology assessment (HTA) organization, uses cost-effectiveness analysis (CEA) and budget impact analysis to measure therapies’ value,13 an approach common in Europe.14,15 

Traditional methods of CEA measure the value of an innovation by comparing benefits such as survival gains and improved quality of life with costs, assuming no other health technology improvements besides the one in question.16 However, such methods ignore aspects of therapies that matter to patients, like the value of hope, insurance value to healthy individuals, and the increased value people place on life near its end.17-20

Such components of value can be difficult to quantify in HTA because they are subjective valuations based on unobserved patient preferences. However, 1 relevant component of value is rooted in real-world survival data, the “option value” of therapy. Option value is the benefit a therapy provides patients by enabling them to survive to the next innovation. For example, in cancer care, any survival gains today hold additional value because they increase the likelihood that a patient may live to access even more effective treatment in the future. This concept is particularly important in disease areas with traditionally poor outcomes and rapid innovation. 

Although metastatic non–small cell lung cancer (NSCLC) and metastatic renal cell carcinoma (RCC) have had low survival rates,21,22 innovation to treat both cancers is currently rapid. A number of breakthrough targeted therapies and immuno-oncology (IO) therapies, which harness the immune system to fight cancer, are available, such as nivolumab, pembrolizumab, osimertinib, and ceritinib for NSCLC and nivolumab and lenvatinib for RCC.23,24 These therapies are improving 1 or more clinical endpoints, such as survival rates for cancers with traditionally poor survival odds.23,24 Furthermore, the pipelines for both tumors are active.25,26 

Given the proliferation of treatment options and the prospect of future innovation, payers, policymakers, clinicians, and patients require multiple criteria to make care-related decisions.27 A therapy’s option value accounts for the future benefits of a life-extending therapy in addition to its immediate survival effects. With that in mind, we looked at the option value of nivolumab, the first IO therapy given breakthrough status and approved by the FDA for NSCLC and RCC.23,24 NSCLC is histologically divided into squamous and nonsquamous (adenocarcinoma, large cell) tumor types,21 and individuals face different prognosis and treatment options depending on the histology. Squamous NSCLC (about 25%-30% of all lung cancers) is typically smoking-related, whereas nonsquamous NSCLC is the most common type of lung cancer in nonsmokers (although smokers are still at greater risk than nonsmokers).28 We examined squamous and nonsquamous NSCLC separately.


Study Design

We adapted a framework for estimating a therapy’s option value19,20,29,30 to the contexts of metastatic NSCLC and metastatic RCC. In particular, we examined the option value of nivolumab, the first programmed cell death protein-1 (PD-1) inhibitor in both disease states. In order to estimate nivolumab’s option value, a survival curve for patients taking the pre-nivolumab standard of care was needed first. The pre-nivolumab survival curves were modified using mortality hazard ratios (HRs) from clinical trial publications to obtain a nivolumab survival curve in each setting. Forecasting methods were used to project likely future survival improvements patients with either NSCLC or RCC may live to see. The conventional survival gain from nivolumab was obtained by comparing life expectancy with nivolumab, assuming no future innovation, against life expectancy with the pre-nivolumab standard of care. The option value of nivolumab was obtained by comparing life expectancy with nivolumab under 2 scenarios: allowing for likely future survival gains versus assuming no future innovation. Finally, the option value estimates were converted to economic terms. Additional methodological detail is available in the eAppendix (eAppendices available at


Survival trends in metastatic NSCLC and metastatic RCC were estimated using the Surveillance, Epidemiology and End Results (SEER) cancer registry.31 SEER, which tracks cancer incidence and mortality using data reported by registries across the United States, currently covers about 30% of the US population.32 

Long-term all-cause mortality rates were taken from the Human Mortality Database (HMD).33 The HMD contains detailed population and mortality data for 37 countries, and currently provides US life tables for 1933 through 2013.

Survival curves from SEER were modified to reflect nivolumab patients’ survival using mortality HRs from clinical trial publications.34-36 Specifically, in both squamous and nonsquamous NSCLC, nivolumab was compared with docetaxel, and in RCC, nivolumab was compared with everolimus. These comparisons reflect those in the trials noted on the nivolumab FDA label.37 The comparator drugs were assumed to represent the pre-nivolumab standard of care. 


We identified 3 study populations: metastatic squamous NSCLC, metastatic nonsquamous NSCLC, and metastatic RCC. First, we identified patients with NSCLC in SEER by requiring a primary cancer site of “lung or bronchus” or “trachea.” We distinguished squamous from nonsquamous histology types using International Classification of Diseases for Oncology, Third Edition (ICD-O-3) histology codes. For both histology types, we defined metastatic NSCLC as American Joint Committee on Cancer (AJCC) stage IV, IIIb, or III with no surgery. The latter category addressed the fact that not all patients have a substage listed (eg, IIIa vs IIIb), and a lack of surgery suggested the case was inoperable.

To identify the RCC population, we required a primary site of “kidney,” “renal pelvis,” or “ureter,” and identified the RCC histology using ICD-O-3 histology codes. To limit to patients with RCC with metastatic disease, we selected the “distant” stage using “SEER historic stage A.” Although AJCC staging is commonly used in clinical practice for treatment decisions and in clinical trials for eligibility,38 it was not well documented for RCC in SEER before 2004. Because metastatic RCC is a smaller sample than NSCLC, preserving sample size was important. Moreover, in order to track longer-term trends, it was necessary to be able to identify patients before 2004. In general, SEER distant stage approximates AJCC stage IV. Therefore, we identified metastatic RCC using the SEER distant stage. 

Statistical Analyses

We estimated the option value of nivolumab in the 3 populations by taking these 5 steps.

Step 1: estimate pre-nivolumab survival curves. To establish a pre-nivolumab baseline, we estimated survival curves using the SEER data. We identified metastatic squamous and nonsquamous NSCLC and metastatic RCC patients diagnosed between 2001 and 2010. Survival curves for each population were estimated parametrically using a log-normal distribution. Covariates included age at diagnosis, age squared, gender, race, ethnicity, marital status, tumor grade, and a quadratic time trend.

Our survival estimation was limited by the patients’ duration of follow-up in SEER. Although we preferred using patients with a more recent diagnosis due to the pace of innovation in cancer care, this limited the number of years of follow-up available. Rather than project survival for many years beyond the duration of follow-up in the SEER data, we assumed that the minority of patients surviving more than 20 years past diagnosis had the same mortality rates as the general population, using US life tables from the HMD.

Specifically, we calculated mortality rates in the first 20 years after diagnosis using the estimated survival curves from SEER and then appended the HMD mortality rates. This lifetime mortality table was used as an input in the Lee-Carter model described in Step 2. 

Step 2: forecast survival improvements. The SEER survival curves estimated in Step 1 showed a clear trend of improving survival over time in all 3 populations. Based on these trends, we used the Lee-Carter method39,40 to forecast survival improvements for each population. The Lee-Carter method involves modeling age-specific mortality rates as a function of a long-term trend in overall mortality improvements and an age-specific response to the overall trend. This method is widely used as a benchmark for long-term mortality forecasts, including by the US Census Bureau and the Social Security Administration.40 

Step 3: estimate survival with nivolumab. To obtain survival curves for patients taking nivolumab in each population, we began with the pre-nivolumab survival curves estimated in Step 1. Based on the FDA label, which calls for second- or later-line use in both the NSCLC and RCC indications,37 we assumed that nivolumab would be given as a second-line therapy starting 1 year after diagnosis. Following the clinical trial evidence,34-36 we assumed that nivolumab patients would experience diminished mortality risk compared with patients on the prior standard of care. Specifically, we applied the mortality HRs from nivolumab trial publications to the pre-nivolumab survival curves estimated in Step 1. We conservatively assumed that any mortality benefits of nivolumab would disappear 4 years after beginning nivolumab therapy.

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