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Understanding Price Growth in the Market for Targeted Oncology Therapies
Jesse Sussell, PhD; Jacqueline Vanderpuye-Orgle, PhD; Diana Vania, MSc; Hans-Peter Goertz, MPH; and Darius Lakdawalla, PhD
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Understanding Price Growth in the Market for Targeted Oncology Therapies

Jesse Sussell, PhD; Jacqueline Vanderpuye-Orgle, PhD; Diana Vania, MSc; Hans-Peter Goertz, MPH; and Darius Lakdawalla, PhD
The prices of targeted oncology therapies have grown substantially, but revenues have not. This is due in part to large declines in per-drug patient counts.

The rising cost of novel oncology therapies has been a source of great controversy in recent years.11-13 Our analysis confirms that prices of oncology drugs are indeed rising rapidly. We show that the number of patients taking each drug has dropped substantially over the same period of time. As a result, revenues have fallen at every point in the distribution, after accounting for life cycle growth in revenues over years since launch. This suggests that price growth is unlikely to have resulted from greater pricing power, at least within this market segment. Profit-maximizing firms with more pricing power would never willingly make decisions that lead to lower revenues for each drug launched. One exception to this point might occur if costs of drug discovery or production have fallen significantly. Although the extant academic literature on the costs of drug discovery remains controversial, all of it points to rising costs.14 We know of no academic publications on trends in the costs of oncology drug production; more research is called for in this area.


This study has several important limitations. The IQVIA NSP data set, which provided much of the source data for this study, contained “restrictions” (partially missing values) for some therapies in some years; we recoded these as missing. This step will not affect the results of the study, as long as the circumstance of missing data is not correlated with our outcomes of interest. Also, our measure of the cost of individual therapies contains only the component of total cost that returns to pharmaceutical manufacturers; it does not incorporate markups by wholesalers or hospitals, nor does it include any confidential rebates paid by manufacturers to purchasers. In addition, we focus on only treatments for the 6 most common tumor types; as such, our results have limited generalizability to other forms of cancer. Finally, to estimate therapy prices, we assume that average treatment duration is equal to the duration indicated on the drug label. In practice, individual patients’ duration of therapy may be longer or shorter than is suggested by the label because of factors such as mortality, discontinuation, and extended treatment at the discretion of the physician.


Previous research has suggested that we should be skeptical of the notion that prices are rising solely because effectiveness is rising.4 Our study also casts doubt on an explanation for price growth that relies solely on rising R&D costs: If this were so, firms would necessarily respond by launching drugs capable of earning higher revenues. Our findings suggest instead a relationship between price growth and average patient counts, although the precise nature of this relationship is not fully clear. One possible explanation for declining patient counts is relatively slow growth in effectiveness over time; this would improve the ability of older drugs to remain on the market. The consequences of this longevity would be reduced market share and reduced revenue for newer drugs. A second possible hypothesis for declining patient counts would be increased competition: All else being equal, an increase in the number of drugs approved for a given tumor type would lead to a decline in the average number of patients per drug. This explanation, however, would also suggest an increase in price competition, which is inconsistent with the observed data.

A final possible explanation for the trends we observe is growth in the development of drugs that target patients with specific biomarkers (sometimes referred to as personalized medicine) within the targeted oncology market. By design, these drugs target subsets of the total population of patients with the indicated cancer. Shrinking patient counts might be in part the result of more personalized therapies that treat narrower indications. For example, trastuzumab is indicated for human epidermal growth factor receptor-2–overexpressing breast cancer, which comprises only 15% to 20% of invasive breast cancer cases.15 Mechanically, personalization leads to lower revenue when we hold prices constant. From another perspective, this is a cost to society of personalization: Without significant offsetting price growth, personalized therapies generate lower revenues and returns to innovators; this reduction in returns may reduce the rate of drug discovery in the long run.16 More research is needed on these and other hypotheses for the causes of drug price growth and the observed decline in average patient counts.

Despite acknowledged limitations, this study provides surprising new data on declining patient populations treated by targeted cancer agents. This pattern is likely an important and, to our knowledge, previously undescribed factor that lies behind trends in revenues and rewards from innovation in oncology.

Author Affiliations: Precision Health Economics (JS, JV-O, DV, DL), Oakland, CA; Genentech (HPG), South San Francisco, CA.

Source of Funding: This study was funded by Genentech.

Author Disclosures: Dr Vanderpuye-Orgle is an employee of and owns stock in Amgen, Inc, which manufactures oncology therapies. Mr Goertz is employed by Genentech/Roche and owns Roche stock; Genentech manufactures and sells several of the oncology therapies covered in this manuscript. Dr Lakdawalla is a consultant to Precision Health Economics, a healthcare consultancy with clients in the life science and insurance industries, including firms that market oncology treatments; he holds equity in Precision Medicine Group, parent company of Precision Health Economics. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (JS, JV-O, HPG, DL); acquisition of data (JS, DV); analysis and interpretation of data (JS, JV-O, HPG, DL); drafting of the manuscript (JS, DV); critical revision of the manuscript for important intellectual content (JS, JV-O, HPG, DL); statistical analysis (JS); provision of patients or study materials (HPG); obtaining funding (HPG); administrative, technical, or logistic support (JS, DV); and supervision (JS, HPG, DL).

Address Correspondence to: Jesse Sussell, PhD, Precision Health Economics, 555 12th St, Ste 1725, Oakland, CA 94607. Email:

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