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

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

Research Questions 1)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?

Little Existing Evidence on These Issues Due to Empirical Challenges Traditional price index:P 1 Q 0 P 0 Q 0 P 1 /P 0 : 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.

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 among privately-insured patients.

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 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.

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

Data 1) Drug Prices from IMS,  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  IntrinsiQ: market share by regimen by quarter based on physician surveys for ) 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.

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 1.7m 2 and weighs 80kg.  Apply IMS prices per mg of active ingredient (separately for hospitals and physicians).

$126 $1,839 $13,039 $36, Note: prices are for a 24-week treatment cycle. Price of Drug Regimens Weighted by Market Shares ,600% increase

Outside option 5-FU/LV Irinotecan Irinotecan + 5-FU/LV Oxaliplatin + 5-FU/LV Bevacizumab + oxaliplatin + 5-FU/LV SEER data IntrinsiQ data Market Shares of 12 Largest Regimens:

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

Percentage of Phase 3 Trial Patients w/ a Grade 3 or Grade 4 Side Effect: Metastatic First-Line Therapies Note: capecitabine is a tablet

Hedonic Price Index  p jt : price of regimen j in quarter t.  X: attributes of each regimen (efficacy and side effects).  β: “implicit prices” of attributes (to physicians).  γ t : yield price index, controlling for changing attributes. ln(p jt ) = βX jt + Σ γ t d t + ε jt t=1993:2 t=2005:3

Hedonic Regression Coefficient Estimates VariableCoefficient Standard Error Efficacy Survival (months) 0.496** Response rate (%) 0.422** Response rate * 2 nd line-0.141** Time to progression (months)-2.58**0.019 Side effects Diarrhea 0.124** Nausea 0.059* Abdominal pain 0.336** Vomiting-0.019** Neutropenia-0.045** nd line therapy10.2**0.050 Tablet-0.101** Observations 492 R

Indexed to 1.0 in 1 st quarter of Irinotecan (1996:3) Capecitabine (1998:2) Oxaliplatin (2002:3) Cetuximab (2004:1) Bevacizumab (2004:1) 0.88 Note: (year : quarter) of entry. Hedonic Price Index,

 In each quarter (t), physician (i) chooses the drug (j) that maximizes his/her utility:  α: price sensitivity of a physician.  β: value of each attribute from a physician’s perspective.  ξ j : mean of unobserved attributes for regimen j.  Δξ jt : time-specific deviation from ξ j.  1 st estimation approach (BLP next): U ijt = αP jt + βX jt + ξ j + Δξ jt + ε ijt Quality-Adjusted Price Index ln(s jt ) – ln(s 0t ) = αP jt + βX jt + ξ j + Δξ jt + ε ijt  s jt : market share of regimen j in quarter t.  s 0t : 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.

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

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. Constructing a Quality-Adjusted Price Index U t – U t-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 by the EV.

Hedonic Price Index and Quality-Adjusted Price Index Quality-Adjusted Hedonic

Conclusions 1)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.