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A Quality-Adjusted Price Index for Colorectal Cancer Drugs Claudio Lucarelli Sean Nicholson

A Quality-Adjusted Price Index for Colorectal Cancer Drugs Claudio Lucarelli Sean Nicholson Cornell University June 2, 2007. New (Expensive) Technology Is the Engine Driving Increases in Medical Spending Causes of Growth in Medical Spending, 1950-1987. Aging of population. 15%.

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A Quality-Adjusted Price Index for Colorectal Cancer Drugs Claudio Lucarelli Sean Nicholson

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  1. A Quality-Adjusted Price Index for Colorectal Cancer Drugs Claudio Lucarelli Sean Nicholson Cornell University June 2, 2007

  2. New (Expensive) Technology Is the Engine Driving Increases in Medical Spending Causes of Growth in Medical Spending, 1950-1987 Aging of population 15% Technological change: new drugs, procedures, devices, and increased “intensity” of care. More generous insurance coverage (lower price to patient at point of care) 12% 63-68% 5-10% Increase in personal income Source: Newhouse, “Medical Care Costs: How Much Welfare Loss?”, Journal of Economic Perspectives, Summer 1992.

  3. Research Questions • Does the value of new colorectal cancer chemotherapy • drugs exceed their cost? • 2) Did colorectal cancer drug prices rise or fall between • 1993 and 2005 once one correctly controls for the • changing attributes/quality of the drugs? • Policy implication: should the government (and private • insurers) increase or reduce the incentives for • pharmaceutical and biotech firms to invest in new • medical technologies?

  4. Little Existing Evidence on These Issues Due to Empirical Challenges Traditional price index: P1Q0 P0Q0 P1/P0: price increase holding quantity fixed at Year 0 level. Challenges in health care: 1) Often do not observe the transaction price (P). 2) Due to insurance and physician’s role as agent, consumer purchases do not necessarily reveal marginal valuation. 3) Quantities (Q) change over time as physicians/patients adopt new medical technologies. 4) Patient outcomes (quality) change over time.

  5. Evidence on Quality-Adjusted Health Care Prices 1) Heart attack treatment (Cutler, McClellan, Newhouse, Remler, 1998) - average annual real price increase of 0.7% per year. - prices fell 1.1% per year when account for improved mortality (assume a year of life is worth $25,000). 2) Depression (Berndt, Bir, Busch, Frank, Normand, 2002) - expert panel estimated probability of full remission associated with each observed treatment method. - estimate incremental spending per full remission case relative to the expected effect of a placebo. - incremental quality-adjusted prices fell about 2% per year between 1991-1996 among privately-insured patients.

  6. Why Colorectal Cancer? • 112,000 new cases diagnosed per year in the United States. 52,000 deaths per year in the U.S. • 5 new drugs launched in the U.S. between 1996 and 2004. Drug prices and spending increasing substantially. • Consistent information on efficacy and side effects of each drug based on phase 3 clinical trials. • Most chemotherapy drugs are infused into a patient in a physician’s office (59%) or hospital clinic (28%). • Physicians take ownership of oncology drugs; we observe the price they pay wholesalers.

  7. Schematic of Colon Cancer Treatment Patient Diagnosed Cancer is stage 1, 2, or 3 Surgeon removes section of colon Cancer is stage 4 1st Line metastatic chemo Cancer metastasizes Adjuvant chemo (30%) 70% of chemo patients 2nd Line metastatic chemo No recurrence

  8. Data • 1) Drug Prices from IMS, 1993-2005 • Invoice/transaction amount actually paid by a customer type (e.g., MD offices) and quantity of drugs purchased for each quarter. • We calculate average (across NDC codes) price per mg of active ingredient. 2) Regimen (combination of drugs) Market Shares • SEER: claims-based market share by regimen by quarter for Medicare patients for 1993-2001. • IntrinsiQ: market share by regimen by quarter based on physician surveys for 2002-2005. 3) Regimen-Specific Dose Per Drug Per Patient • National Comprehensive Cancer Network: typical quantity of each drug used in each regimen for a representative patient. 4) Drug Attributes • Overall survival rates, time to progression of cancer, tumor response rates, and side effects experienced by Phase 3 trial patients, as reported in package inserts, published articles, and conference abstracts.

  9. Calculating the Price of a Regimen • Assume every patient receives 24 weeks of chemotherapy. • Use mg dosage levels recommended by National Comprehensive Cancer Network (see last pages of handout for details) • Assume representative patient has a surface area of 1.7m2 and weighs 80kg. • Apply IMS prices per mg of active ingredient (separately for hospitals and physicians).

  10. Price of Drug Regimens Weighted by Market Shares 1993-2005 $36,305 2,600% increase $13,039 $1,839 $126 1993 1995 1997 1999 2001 2003 2005 Note: prices are for a 24-week treatment cycle.

  11. Market Shares of 12 Largest Regimens: 1993-2005 5-FU/LV SEER data IntrinsiQ data Oxaliplatin + 5-FU/LV Bevacizumab + oxaliplatin + 5-FU/LV Irinotecan + 5-FU/LV Outside option Irinotecan 1993 1995 1997 1999 2001 2003 2005

  12. Efficacy of Drugs From Phase 3 Clinical Trials: 1st line Therapy for Metastatic Colorectal Cancer (Median, months) (Median, months) Note: capecitabine is a tablet.

  13. Percentage of Phase 3 Trial Patients w/ a Grade 3 or Grade 4 Side Effect: Metastatic First-Line Therapies 40 30 20 10 0 Note: capecitabine is a tablet.

  14. Hedonic Price Index t=2005:3 ln(pjt) = βXjt + Σγtdt + εjt t=1993:2 • pjt: price of regimen j in quarter t. • X: attributes of each regimen (efficacy and side effects). • β: “implicit prices” of attributes (to physicians). • γt: yield price index, controlling for changing attributes.

  15. Hedonic Regression Coefficient Estimates VariableCoefficientStandard Error Efficacy Survival (months) 0.496** 0.0049 Response rate (%) 0.422** 0.0027 Response rate * 2nd line -0.141** 0.0013 Time to progression (months) -2.58** 0.019 Side effects Diarrhea 0.124** 0.0011 Nausea 0.059* 0.0012 Abdominal pain 0.336** 0.0028 Vomiting -0.019** 0.0009 Neutropenia -0.045** 0.0005 2nd line therapy 10.2** 0.050 Tablet -0.101** 0.0086 Observations 492 R2 0.99

  16. Hedonic Price Index, 1993-2005 Bevacizumab (2004:1) Oxaliplatin (2002:3) Indexed to 1.0 in 1st quarter of 1993 0.88 Cetuximab (2004:1) Irinotecan (1996:3) Capecitabine (1998:2) 1993 1995 1997 1999 2001 2003 2005 Note: (year : quarter) of entry.

  17. Quality-Adjusted Price Index • In each quarter (t), physician (i) chooses the drug (j) that maximizes his/her utility: Uijt = αPjt + βXjt + ξj + Δξjt+ εijt • α: price sensitivity of a physician. • β: value of each attribute from a physician’s perspective. • ξj: mean of unobserved attributes for regimen j. • Δξjt: time-specific deviation from ξj. • 1st estimation approach (BLP next): ln(sjt)– ln(s0t) = αPjt + βXjt + ξj + Δξjt+ εijt • sjt: market share of regimen j in quarter t. • s0t: market share of outside option in quarter t. • instrument for P w/ # of drugs in the market and the sum of the observed attributes of the competitor regimens.

  18. Quality-Adjusted Regression Coefficient Estimates VariableCoefficientStandard Error Price (instrumented) -0.706** 0.079 Efficacy Survival (months) 0.248** 0.0085 Response rate (%) 0.208** 0.051 Response rate * 2nd line 0.118** 0.031 Time to progression (months) -0.945** 0.338 Side effects Diarrhea -0.0015 0.021 Nausea 0.129** 0.0047 Abdominal pain 0.188** 0.0088 Vomiting -0.010* 0.057 Neutropenia -0.043** 0.012 Tablet -2.26** 0.313 Observations 216 R2 0.75

  19. Constructing a Quality-Adjusted Price Index 1) Quantify the Equivalent Variation (EV): How much income could be taken away from (or given to) an individual to leave him indifferent between facing the old choice set -- attributes and prices -- and the new improved (inferior) choice set. Ut – Ut-1 -α 2) Translate EV into a Quality-Adjusted Price Index: find the amount by which prices would have to change in order to produce the same welfare effect as expressed bythe EV.

  20. Hedonic Price Index and Quality-Adjusted Price Index 1993 - 2005 Quality-Adjusted Hedonic

  21. Conclusions • Important to control for product attributes: naïve price • index greatly overstates the “true” price change. • 2) New colon cancer drugs provide welfare increases that • justify their higher prices. • 3) Pharmaceutical/biotech companies capture most of the • welfare increases associated with the new drugs, which • provides strong incentives for innovation. • 4) When these drugs lose patent protection, presumably • consumers would capture more of the welfare gains. • 5) Hedonic index fails to capture value of “extending the • range” type of innovation, whereas quality-adjusted does.

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