{"subscriber":false,"subscribedOffers":{}} New Anticancer Drugs Associated With Large Increases In Costs And Life Expectancy | Health Affairs

Research Article

New Anticancer Drugs Associated With Large Increases In Costs And Life Expectancy

Affiliations
  1. David H. Howard ( [email protected] ) is an associate professor in the Department of Health Policy and Management at Emory University, in Atlanta, Georgia.
  2. Michael E. Chernew is professor in the Department of Health Care Policy at Harvard Medical School, in Boston, Massachusetts.
  3. Tamer Abdelgawad is senior director, International Policy, at Pfizer Inc. in New York City.
  4. Gregory L. Smith is vice president, Outcomes and Evidence, Oncology, and Global Health and Value, at Pfizer Inc.
  5. Josephine Sollano is head, Outcomes and Evidence and Global Health and Value, at Pfizer Inc.
  6. David C. Grabowski is a professor in the Department of Health Care Policy at Harvard Medical School.
PUBLISHED:Free Accesshttps://doi.org/10.1377/hlthaff.2016.0286

Abstract

Spending on anticancer drugs has risen rapidly over the past two decades. A key policy question is whether new anticancer drugs offer value, given their high cost. Using data from the Surveillance, Epidemiology, and End Results (SEER)–Medicare database, we assessed the value of new cancer treatments in routine clinical practice for patients with metastatic breast, lung, or kidney cancer or chronic myeloid leukemia in the periods 1996–2000 and 2007–11. We found that there were large increases in medical costs, but also large gains in life expectancy. For example, among patients with breast cancer who received physician-administered drugs, lifetime costs—including costs for outpatient and inpatient care—increased by $72,000 and life expectancy increased by thirteen months. Changes in life expectancy and costs were much smaller among patients who did not receive these drugs.

TOPICS

Many costly new anticancer drugs have been introduced in the past two decades. The launch prices of anticancer drugs—the prices manufacturers set immediately after drugs are approved by the Food and Drug Administration (FDA)—have been rising by 10 percent per year. 1 A key policy question is whether these drugs offer sufficient benefits to justify their costs. Critics of the drug industry believe that prices are excessive. For example, a group of over a hundred prominent oncologists recently called on Congress to develop a process to establish the “fair price” of new drugs based on their value to patients. 2

Clinical trials have examined whether new anticancer medications improve survival, but survival benefits observed in routine practice may differ from those in trials for a number of reasons. First, treatment in trials is guided by protocols. 3 Real-world use may be governed by different patterns of therapy use, drug switching, and combination therapy. Second, physicians may learn through experience how to better manage side effects, allowing patients to remain on a drug for longer than the typical duration of treatment in its clinical trial. Third, physicians can and often do use anticancer drugs in patients who would have been excluded from Phase III clinical trials. 4 Fourth, clinical trial investigators may achieve better medication adherence among trial subjects than is observed in routine clinical practice. 5 Moreover, the clinical trial literature tells us relatively little about the cost of new treatments.

In this study we used data from the Surveillance, Epidemiology, and End Results (SEER)–Medicare database to assess the value of new cancer treatments for patients with metastatic breast, lung, or kidney tumors or systemic chronic myeloid leukemia (CML) in the period 1996–2011. We estimated and compared changes in life expectancy and lifetime medical costs.

Background

During our study period the FDA approved over twenty-five drugs for breast, lung, or kidney tumors or CML (for a full list of the drugs, see online Appendix Exhibit 1). 6 Eleven drugs were approved for metastatic breast cancer alone. Before 1996 only one drug (aldesleukin) had been approved for the treatment of metastatic kidney cancer, and the six kidney cancer drugs approved in the study period greatly expanded the treatment options. The FDA approved imatinib for CML in 2001 on the basis of a single-arm noncomparative study. The survival benefits of imatinib have never been quantified in a randomized trial, but all available evidence indicates that the drug has led to substantial improvements in survival. 7 Over twenty drugs have been approved for metastatic lung cancer (three of them approved during the study period). The prognosis for patients with metastatic lung cancer is still poor, however, and few patients survive beyond two years after diagnosis.

Previous studies have examined the value of anticancer drugs, and cancer treatments more generally, by using real-world data to examine how survival and costs change over time as new treatments are introduced into practice. For example, Rebecca Woodward and colleagues evaluated the value of medical care for non-small-cell lung cancer in the elderly US population and found that in the period 1983–97, life expectancy increased by 0.60 months and per patient costs increased by $20,157 (in 2000 dollars), which implies a cost-effectiveness ratio of $403,142 per life-year. 8 Elsewhere the lead author and his colleagues have reported even larger increases in life expectancy and costs for patients diagnosed with metastatic colorectal cancer in 1995–2005. 9 Pei-Jung Lin and colleagues found that new therapies for CML were associated with a cost of $74,000 per life-year gained, 10 and Wesley Yin and colleagues found that the monetary value of benefits for the CML treatment imatinib was over three times as large as the cost. 7

A more recent study reported that the net benefit to the United States from increased spending on anticancer drugs in the period 2004–14 was $32.6 billion. 11 However, the conclusion rests on the assumption that 50 percent of the improvement in premature death from cancer is attributable to the use of new drugs. A similar study comparing cancer survival and costs in the United States and in European countries concluded that the monetized value of increases in survival exceeded the extra cost of care. 12

Studies that include patients regardless of the stage of their cancer at diagnosis 8,12 have been criticized for failing to account for the fact that patients are more likely to be diagnosed earlier in the course of their disease today than in the past (which produces so-called lead-time bias). 13,14 Also, these studies capture both real gains from earlier detection and improvements to stage-specific therapies. Our interest was in the latter.

Our study used more recent data than previous work. Since the mid-2000s, a number of new, costly drugs have been approved. Also, we restricted our study sample to patients receiving treatment for metastatic or systemic disease, which reduced the potential for lead-time bias resulting from changes in screening and detection patterns over time. Also, such patients are not candidates for curative surgery or radiotherapy: Their treatment consists of oral or physician-administered intravenous drugs. Thus, our study tightens the link between survival gains and changes in drug therapy.

Study Data And Methods

Data And Study Sample

We analyzed data from the SEER–Medicare database, which includes records from SEER tumor registries linked with Medicare claims for patients eligible for Medicare. Claims data include information on Medicare reimbursements, physician-administered drugs, and—for patients enrolled in Medicare Part D (prescription drug coverage)—oral drugs. The SEER tumor registries cover 28 percent of the US population.

We used International Classification of Diseases for Oncology (ICD-O-3) codes 15 to identify patients diagnosed in the period January 1, 1996–December 31, 2011, with systemic CML (the data do not identify the phase of CML at diagnosis) or metastatic kidney, breast, or lung tumors. We included only those patients who were ages sixty-six and older (to allow for at least one year of Medicare claims before their diagnosis) and continuously enrolled in Part A and Part B for at least twelve months before and twenty-four months after diagnosis (or until death, for patients who died within twenty-four months of diagnosis).

We selected these tumor types to study based on their prevalence; the release of new anticancer drugs during our study period; and, in the case of breast and kidney tumors, the absence of previous research on trends in survival and postdiagnosis medical spending.

We excluded patients with early-stage nonmetastatic disease; those who had previously been diagnosed with cancer; and those for whom the source reporting the tumor was listed as “death certificate only,” “autopsy only,” or “nursing home/hospice,” because most nursing home or hospice patients are not candidates for drug therapy. We compared life expectancy and Medicare reimbursements between patients diagnosed in 1996–2000 and in 2007–11. We measured comorbidities in the year before diagnosis. 16

Estimating Life Expectancy

Outcomes for patients with metastatic tumors are commonly measured in terms of median survival. However, for the purpose of assessing the value of care, it is important to measure average survival (life expectancy).

The study data captured survival time through December 31, 2013. For patients diagnosed in the period 1996–2000, we observed survival time for a maximum of eighteen years. We adapted previously developed methods (described in detail in the Appendix) 6 to project survival time beyond the date of the last follow-up. 9,17,18

We used a slightly different approach to project life expectancy for patients diagnosed during the period 2007–11, to take advantage of information about mortality rates from earlier patient cohorts. We projected survival beyond the end of follow-up in the sample of patients diagnosed in 2007–11 based on the mortality risks of patients diagnosed in 2001–06.

We validated our approach by artificially censoring survival records for patients with breast cancer diagnosed in the period 1999–2001 and comparing life expectancy projections based on our method to actual survival. Our method performed well compared to other commonly used approaches (for a comparison of actual survival and projected survival times estimated using different methods, see Appendix Exhibit 5). 6

Estimating Lifetime Medical Costs

We projected patients’ lifetime medical costs—including costs for drugs, outpatient visits, and hospital admissions—from the point of diagnosis until death using the so-called phase-of-care approach. 17,19 Costs represent the sum of Medicare reimbursements for inpatient, skilled nursing facility, outpatient, hospice, and home health care and for durable medical equipment. They include costs for cancer care and for treatment of unrelated conditions. We also included payments for oral drugs in cost estimates for the period 2007–11, based on average Part D payments for patients enrolled in a Part D plan for at least twelve months following diagnosis. Costs did not include out-of-pocket spending. We stated costs in 2012 dollars, using the Inpatient Hospital Market Basket for institutional payments and the Medicare Economic Index for physician payments (for more details on our approach, see Appendix Exhibit 6). 6

We calculated average Medicare costs in the first year after diagnosis for patients who died within twelve months. For patients who were still alive at one year, we calculated costs in the first six months, end-of-life costs in the six months before death (for those who died during the study period), and average monthly costs in the intervening period. We calculated end-of-life costs using the subsample of patients who survived at least twelve months but died during the study period. We used these figures and the projected survival curves to estimate lifetime medical costs from the time of diagnosis until death.

Analysis

We compared changes in life expectancy and lifetime medical costs for patients with breast or lung cancer who were treated with physician-administered anticancer drugs and those who were not treated with such drugs. We classified patients as having received physician-administered anticancer drugs if they had a physician or outpatient claim listing a Healthcare Common Procedure Coding System code associated with the receipt of anticancer drugs within six months of diagnosis. It was not possible to divide patients with kidney cancer or leukemia into comparable treatment and no-treatment groups because of the introduction of new oral drugs.

We used Wilcoxon rank-sum tests to assess differences in continuous variables between time periods and chi-square tests to assess differences in binary variables. We drew a thousand bootstrap samples to calculate confidence intervals for our estimates of life expectancy and lifetime costs.

To determine whether our results were biased by changes in the composition of the sample because of the addition of new SEER registries in 2000, we conducted a sensitivity analysis in which we limited the sample to patients in SEER registries in operation since before 1996. To determine whether our results were biased by changes in the composition of the sample over time with respect to age or comorbidity status, we separately estimated results for the subsamples of patients ages 66–74 and those with no comorbidities.

Limitations

Our analysis had a number of limitations. First, our sample included only Medicare patients ages sixty-six and older. Younger patients, who are less frail and face a lower risk of death from competing causes, may be more likely to benefit from cancer treatment.

Second, we assumed that patients diagnosed with metastatic disease in the period 1996–2000 were similar to patients diagnosed in 2007–11. This assumption of no lead-time bias would be incorrect if patients were diagnosed earlier in the course of their disease because of increases in the use and effectiveness of imaging for other conditions. However, recent analyses suggest that survival gains are primarily attributable to improvements in treatment instead of increases in screening and detection rates. 20,21 Limiting our sample to patients diagnosed with metastatic disease minimized bias resulting from changes in detection patterns because of increased screening.

Third, Medicare changed the way it pays for physician-administered drugs beginning in 2005, but we did not adjust cost estimates to account for the change.

Fourth, comparisons of patients with breast or lung cancer who did and who did not receive intravenous anticancer drugs assumed that these populations remained stable with respect to characteristics that affect survival and costs. Prediagnosis costs and the proportion of people with three or more comorbidities increased over time in both groups, but the increases were larger among patients who received drugs (Appendix Exhibit 2). 6

Finally, our estimates did not fully reflect the impact of drugs introduced in the period 2007–11, since only people diagnosed toward the end of the study period would have benefited from the latest drugs.

Study Results

Sample Characteristics

Our sample consisted of 73,024 cancer patients across the four tumor types, of whom 62,865 had lung cancer—which reflects the high incidence of the disease and the high proportion of patients with lung cancer who are diagnosed with metastatic disease ( Exhibit 1 ). The sample included 25,174 patients who were diagnosed in the period 1996–2000 and 47,850 who were diagnosed in 2007–11. The difference in the sample size in the two periods primarily reflects the aging of the US population and the addition of new SEER tumor registries. The average age of the patients was similar across time periods. However, more patients in the later period had three or more comorbidities, which might reflect worsening population health status or increased rates of detection.

Exhibit 1 Characteristics of 73,024 US cancer patients ages 66 and older diagnosed in 1996–2000 or 2007–11

Breast cancerLung cancerKidney cancerCML
Characteristic1996–20002007–111996–20002007–111996–20002007–111996–20002007–11
Average age (years)777876 77 **78787878
Three or more comorbidities25% 37% **29% 43% **33% 45% **36% 54% **
Hospice a20 26 **38 47 **47471215
Receiving IV anticancer drugs a343423 28 **121117 7 **
One year survival rate50 54 **14 18 **18 22 **49 60 **
Costs in the year:
 Before diagnosis b$4,872 $6,136 **$6,454 $7,467 **$6,309$7,505$8,625 $11,438 **
 After diagnosis b$38,398 $45,244 **$35,493 $39,488 **$34,134$38,304$36,548$37,554
Receiving oral anticancer drugs cd1.2%d3.0%d10.0%d36.8%
Part D costs in the year after diagnosis cd$2,892d$2,538d$5,959d$19,630
Number of patients2,3744,24521,41241,4536531,1027351,050

SOURCE Authors’ analysis of data from the Surveillance, Epidemiology, and End Results (SEER)–Medicare database. NOTES Costs are in 2012 dollars. CML is chronic myeloid leukemia.

aWithin six months after diagnosis.

bExcluding Part D costs.

cFor patients enrolled in Part D.

dNot available. The Medicare Part D program for oral drugs began in 2006.

**p<0.05

The share of patients with lung cancer who received physician-administered anticancer drugs increased, but the share of patients with breast cancer who received such drugs was unchanged ( Exhibit 1 ). As might be expected, patients who received drugs were younger than those who did not (Appendix Exhibit 2). 6 The share of patients with kidney cancer or CML who received physician-administered drugs declined over time, but relatively large shares of these patients diagnosed in 2007–11 received oral anticancer drugs ( Exhibit 1 ), which probably reflected the introduction of new oral drugs.

It is difficult to interpret changes in total costs (including drug and nondrug costs) in the year after diagnosis. The introduction of costly new therapies increases these costs, but by prolonging survival, the drugs push the high costs associated with end-of-life care further into the future. As survival improves, costs incurred in the year after diagnosis for end-of-life care decrease. For this reason, it is important to examine lifetime medical costs instead of costs in the first year or two after diagnosis.

Survival

Survival among patients with breast cancer who did not receive anticancer drugs was similar in the groups diagnosed in 1996–2000 and in 2007–11 ( Exhibit 2 ), which suggests that the characteristics of patients diagnosed with metastatic breast cancer did not change over time. However, the proportion of patients who received physician-administered anticancer drugs who were alive at various time points up to sixty months after diagnosis increased over time.

Exhibit 2 Breast cancer patient survival rates, by period of diagnosis and treatment

Exhibit 2
SOURCE Authors’ analysis of data from the Surveillance, Epidemiology, and End Results (SEER)–Medicare database. NOTE Therapy refers to physician-administered drug therapy.

Life Expectancy And Lifetime Costs

Exhibit 3 shows the main results of our study. Details, including estimated life expectancy and lifetime costs and confidence intervals for each study cohort, are presented in Appendix Exhibits 7–10. 6

Exhibit 3 Changes in life expectancy and increases in lifetime medical costs for patients from 1996–2000 to 2007–11

Exhibit 3
SOURCE Authors’ analysis of data from the Surveillance, Epidemiology, and End Results (SEER)–Medicare database. NOTES Therapy refers to physician-administered drug therapy. The error bars represent 95% confidence intervals. Costs are in 2012 dollars.

Among patients with metastatic breast cancer who were treated with physician-administered anticancer drugs, average life expectancy increased over time by 13.2 months, and lifetime medical costs increased by $72,200 ( Exhibit 3 ). Among those who did not receive physician-administered drugs, life expectancy increased by 2.0 months, and costs increased by $8,900. The life expectancy increase in this group could be attributable to improvements in supportive care or lead-time bias.

Life expectancy and costs for patients with lung cancer who were treated with physician-administered anticancer drugs increased over time by 3.9 months and $23,200 dollars, respectively, while remaining basically unchanged for patients who did not receive such drugs.

Life expectancy among patients with kidney cancer increased by 7.9 months, and lifetime costs increased by $44,700. Several oral drugs for kidney cancer were approved in 2007 or later. Survival and cost estimates do not fully reflect the impact of these drugs because they were not in widespread use for the entire 2007–11 period.

Patients with CML experienced the largest gain in life expectancy (22.1 months), which can probably be attributed to the introduction of imatinib in 2001. Lifetime medical costs for these patients increased by $142,200, of which $126,300 was attributable to Part D spending. Estimates of life expectancy gains and cost increases for patients with kidney cancer or CML are averages across patients who did and did not receive anticancer drug therapy. Most of the patients in our sample with CML or kidney cancer did not receive physician-administered or oral anticancer drugs.

Changes in inflation-adjusted inpatient spending were small or negative (Appendix Exhibits 7–10). 6 Increases in spending on physician-administered drugs were also small, relative to the changes in total spending. Increases in outpatient spending accounted for the largest share of increases in total spending, which possibly reflects longer survival times.

The Value Of Care

Estimates of the incremental cost per life-year (the change in costs divided by the change in survival time) ranged from $59,100 for breast cancer to $77,200 for CML (Appendix Exhibits 7–10). 6 We made a number of adjustments to make these estimates comparable to the cost-effectiveness estimates typically reported in the medical literature. We increased costs by 20 percent to represent patients’ out-of-pocket costs, which were not captured in our baseline estimates; multiplied survival gains by 0.7 to convert life-years into quality-adjusted life-years; 22 and discounted survival and costs at a 3 percent annual rate to account for the social rate of time preference.

After making these adjustments, we calculated the following cost-effectiveness ratios: for breast cancer, $114,000 (95% confidence interval: 73,000, 148,900); for lung cancer, $124,900 (95% CI: 94,200, 115,500); for kidney cancer, $144,800 (95% CI: 94,500, to 180,400); and for CML, $145,900 (95% CI: 101,800 to 151,300). These ratios were near or below most estimates of the value of a quality-adjusted life-year. 23

Cost-effectiveness ratios for the subsamples of patients with breast or lung cancer who received physician-administered anticancer drugs were similar to those for the entire sample. Results from sensitivity analyses (Appendix Exhibits 7–10) 6 were similar to those from the baseline analysis.

We included Part D costs in the estimates for the period 2007–11 but not for 1996–2000. This approach overstated increases in costs over time by ignoring spending for oral drugs before the introduction of Medicare Part D in 2006. Cost-effectiveness ratios were more favorable if we excluded Part D costs from the numerator.

Discussion

Increases in the cost of treating patients with metastatic breast, lung, or kidney tumors or CML were accompanied by meaningful improvements in survival. We were not able to directly attribute changes in life expectancy and costs to the use of specific drugs. However, because we included only those patients diagnosed with metastatic disease, most of the increases were probably due to the adoption of new anticancer drugs.

Among patients with breast or lung cancer, changes in life expectancy relative to costs were much larger for those treated with physician-administered anticancer drugs than for those who were not. One cannot compare outcomes between patients who did and did not receive anticancer drugs at a single point in time because the patients differ in terms of average age, comorbidities, and other characteristics. However, the fact that survival gains were concentrated among patients who received drugs suggests that changes in life expectancy and costs were mainly attributable to changes in drug therapy—and were not attributable to changes in the timing of diagnosis or other factors that would have affected all patients diagnosed with metastatic disease.

Even though life expectancy for patients diagnosed with metastatic breast, kidney, or lung cancer has improved, it remains low—especially for lung cancer. Thus, there is the potential for future research and development on new drugs to produce substantial benefits. Research indicates that, in comparison with other new drugs, new anticancer drugs have generally received favorable regulatory treatment yet still spend more time in clinical development and have a higher likelihood of failure after entering Phase III clinical trials. 24 In 2004 the FDA suggested that the incentives and opportunities to develop new drugs depended on public-sector investment in basic research, developments in translational medicine, and regulatory reforms that increase drug development. 25 These opportunities and challenges persist for new anticancer drugs.

Conclusion

There is a vigorous debate over the value of new anticancer drugs. Oncology opinion leaders have mostly focused on drugs’ prices as an indication of cost. The American Society of Clinical Oncology recently proposed a framework for scoring the value of new anticancer drugs that emphasizes the use of survival benefit estimates from randomized trials and drug prices. 26 Our results highlight the importance of considering outcomes and overall costs in routine practice when assessing the value of anticancer drugs as a group. Our results also raise the question of whether back-of-the-envelope calculations based on drugs’ prices and the survival benefits reported in clinical trials provide an accurate measure of value.

ACKNOWLEDGMENTS

Results from this study were presented at Bates White Life Sciences Symposium, Washington, D.C., May 24, 2016. This study used the Surveillance, Epidemiology, and End Results (SEER)–Medicare database. The interpretation and reporting of these data are the sole responsibility of the authors. The authors acknowledge the efforts of the National Cancer Institute (NCI); the Office of Research, Development, and Information at the Centers for Medicare and Medicaid Services; Information Management Services, Inc.; and the SEER program tumor registries in the creation of the SEER-Medicare database. The collection of cancer incidence data used in this study was supported by the California Department of Public Health, as part of the statewide cancer reporting program mandated by California Health and Safety Code section 103885; the NCI’s SEER program, under Contract No. HHSN261201000140C awarded to the Cancer Prevention Institute of California, Contract No. HHSN261201000035C awarded to the University of Southern California, and Contract No. HHSN261201000034C awarded to the Public Health Institute; and the National Program of Cancer Registries of the Centers for Disease Control and Prevention (CDC), under Agreement No. U58DP003862-01 awarded to the California Department of Public Health. The ideas and opinions expressed herein are those of the authors, and endorsement by the California Department of Public Health, the NCI, and the CDC or their contractors and subcontractors is not intended nor should be inferred. Funding was provided by Pfizer, Inc.

NOTES

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