Estimating effectiveness and cost of biologics for rheumatoid arthritis: application of a validated algorithm to commercial insurance claims.

PURPOSE: The aim of this analysis was to implement a claims-based algorithm to estimate biologic cost per effectively treated patient for biologics approved for moderate to severe rheumatoid arthritis (RA). METHODS: This retrospective analysis included commercially insured adults (aged 18-63 years) with RA in a commercial database, who initiated biologic treatment with abatacept, adalimumab, etanercept, golimumab, or infliximab between 2007 and 2010. The algorithm defined effectiveness as having all of the following: high adherence, no biologic dose increase, no biologic switching, no new nonbiologic disease-modifying antirheumatic drug, no increased or new oral glucocorticoid use, and no more than 1 glucocorticoid injection. For each biologic, cost per effectively treated patient was defined as total drug and administration costs (from allowed amounts on claims), divided by the number of patients categorized as effectively treated. FINDINGS: Of 15,351 patients, 12,018 (78.3%) were women, and the mean (SD) age was 49.7 (9.6) years. The algorithm categorized treatment as effective in the first year for 30% (1899/6374) of etanercept, 30% (1396/4661) of adalimumab, 20% (560/2765) of infliximab, 27% (361/1338) of abatacept, and 29% (62/213) of golimumab treated patients. The 1-year biologic cost per effectively treated patient, as defined by the algorithm, was nominally lower for subcutaneously injected biologics than for infused biologics. The 1-year biologic cost per effectively treated patient, as defined by the algorithm, was lowest for etanercept ($49,952), followed by golimumab ($50,189), adalimumab ($52,858), abatacept ($71,866), and infliximab ($104,333). IMPLICATIONS: Algorithm-defined effectiveness was similar for biologics other than infliximab. The 1-year biologic cost per effectively treated patient, as defined by the algorithm, was nominally lower for subcutaneously injected biologics than for infused biologics.

Persistence with and adherence to fingolimod compared with other disease-modifying therapies for the treatment of multiple sclerosis: a retrospective US claims database analysis.

OBJECTIVE: Achieving therapeutic goals in multiple sclerosis (MS) requires strict adherence to treatment schedules. This retrospective study analyzed persistence with, and adherence to, fingolimod compared with injectable/infusible disease-modifying therapies (DMTs) in patients with MS. METHODS: Patients in the PharMetrics Plus™ US administrative claims database with at least one prescription for, or administration of, fingolimod, glatiramer acetate (GA), interferon (IFN), or natalizumab (index DMT) between October 1, 2010 and September 30, 2011 were included. Patients were naïve to index DMT (no claim in the previous 360 days) and had an MS diagnosis code within 360 days of the first index DMT prescription. Outcomes were persistence, risk of discontinuing index DMT (evaluated by a Cox proportional hazards model), adherence (measured using the medication possession ratio [MPR] and proportion of days covered [PDC] in patients with at least two index DMT prescriptions), and the risk of being non-adherent (MPR <80% and PDC <80%, assessed using a logistic regression model). RESULTS: The study included 3750 patients (fingolimod, n = 889; GA, n = 1233; any IFN, n = 1341; natalizumab, n = 287). Discontinuation rates (fingolimod, 27.9%; GA, 39.5%; IFN, 43.7%; natalizumab, 39.5%; all p < 0.001) and risk of discontinuation were significantly higher (hazard ratios vs fingolimod [95% confidence interval]: GA, 1.75 [1.49-2.07]; IFN, 2.01 [1.71-2.37]; natalizumab, 1.53 [1.22-1.91]) for patients receiving other DMTs compared with fingolimod. The risk of being non-adherent was also lower for patients in the fingolimod cohort than the other treatment cohorts, irrespective of whether non-adherence was defined as MPR <80% (p < 0.05 for all) or PDC <80% (p < 0.05 for GA and IFN). LIMITATIONS: As with all studies assessing real-world treatment patterns it is unclear if medications were used as prescribed. CONCLUSIONS: In a real-world setting, persistence with, and adherence to, oral fingolimod was higher than for injectable and infusible DMTs.

Use of a validated algorithm to estimate the annual cost of effective biologic treatment for rheumatoid arthritis.

OBJECTIVES: To estimate biologic cost per effectively treated patient with rheumatoid arthritis (RA) using a claims-based algorithm for effectiveness. METHODS: Patients with RA aged 18-63 years in the IMS PharMetrics Plus database were categorized as effectively treated if they met all six criteria: (1) a medication possession ratio ≥80% (subcutaneous) or at least as many infusions as specified in US labeling (intravenous); (2) no biologic dose increase; (3) no biologic switch; (4) no new non-biologic disease-modifying anti-rheumatic drug; (5) no new or increased oral glucocorticoid; and (6) ≤1 glucocorticoid injection. Biologic cost per effectively treated patient was defined as total cost of the index biologic (drug plus intravenous administration) divided by the number of patients categorized by the algorithm as effectively treated. Similar methods were used for the index biologic in the second year and for a second biologic after a switch. RESULTS: Rates that the index biologic was categorized as effective in the first year were 31.0% etanercept (2243/7247), 28.6% adalimumab (1426/4991), 28.6% abatacept (332/1160), 27.2% golimumab (71/261), and 20.2% infliximab (474/2352). Mean biologic cost per effectively treated patient, per the algorithm, was $50,141 etanercept, $53,386 golimumab, $56,942 adalimumab, $73,516 abatacept, and $114,089 infliximab. Biologic cost per effectively treated patient, using this algorithm, was lower for patients who continued the index biologic in the second year and higher after switching. CONCLUSIONS: When a claims-based algorithm was applied to a large commercial claims database, etanercept was categorized as the most effective and had the lowest estimated 1-year biologic cost per effectively treated patient. This proxy for effectiveness from claims databases was validated against a clinical effectiveness scale, but analyses of the second year or the year after a biologic switch were not included in the validation. Costs of other medications were not included in cost calculations.

Relapse rates in patients with multiple sclerosis switching from interferon to fingolimod or glatiramer acetate: a US claims database study.

BACKGROUND: Approximately one-third of patients with multiple sclerosis (MS) are unresponsive to, or intolerant of, interferon (IFN) therapy, prompting a switch to other disease-modifying therapies. Clinical outcomes of switching therapy are unknown. This retrospective study assessed differences in relapse rates among patients with MS switching from IFN to fingolimod or glatiramer acetate (GA) in a real-world setting. METHODS: US administrative claims data from the PharMetrics Plus™ database were used to identify patients with MS who switched from IFN to fingolimod or GA between October 1, 2010 and March 31, 2012. Patients were matched 1∶1 using propensity scores within strata (number of pre-index relapses) on demographic (e.g. age and gender) and disease (e.g. timing of pre-index relapse, comorbidities and symptoms) characteristics. A claims-based algorithm was used to identify relapses while patients were persistent with therapy over 360 days post-switch. Differences in both the probability of experiencing a relapse and the annualized relapse rate (ARR) while persistent with therapy were assessed. RESULTS: The matched sample population contained 264 patients (n = 132 in each cohort). Before switching, 33.3% of patients in both cohorts had experienced at least one relapse. During the post-index persistence period, the proportion of patients with at least one relapse was lower in the fingolimod cohort (12.9%) than in the GA cohort (25.0%), and ARRs were lower with fingolimod (0.19) than with GA (0.51). Patients treated with fingolimod had a 59% lower probability of relapse (odds ratio, 0.41; 95% confidence interval [CI], 0.21-0.80; p = 0.0091) and 62% fewer relapses per year (rate ratio, 0.38; 95% CI, 0.21-0.68; p = 0.0013) compared with those treated with GA. CONCLUSIONS: In a real-world setting, patients with MS who switched from IFNs to fingolimod were significantly less likely to experience relapses than those who switched to GA.

Comparative effectiveness of fingolimod versus interferons or glatiramer acetate for relapse rates in multiple sclerosis: a retrospective US claims database analysis.

OBJECTIVE: Disease-modifying therapies, such as fingolimod, interferon (IFN) and glatiramer acetate (GA), have differing effects on relapse rates in patients with multiple sclerosis (MS), but little is known about the real-world differences in relapse rates with these treatments. This retrospective study assessed relapse rates in patients with active MS initiating fingolimod, IFN or GA therapy in a real-world setting. METHODS: Using administrative claims data from the US PharMetrics Plus database, we identified previously treated and untreated patients with MS who initiated fingolimod, IFN or GA treatment between 1 October 2010 and 31 March 2011 and had experienced a relapse in the previous year. A claims-based algorithm was used to identify relapses over the persistence period in patients with 540 days of post-index continuous enrolment. A logistic regression model assessed the probability of having at least one relapse and a generalized linear model estimated differences in annualized relapse rates (ARRs). RESULTS: The study enrolled 525 patients (fingolimod, n = 128; combined IFN/GA cohort, n = 397) of the 31,041 initially identified. Similar findings for fingolimod and IFN/GA were observed for the unadjusted proportion of patients experiencing relapses (31.3% vs. 34.0%, respectively; p = 0.5653) and ARRs (0.50 vs. 0.55, respectively) while persistent to treatment. After adjusting for baseline differences, fingolimod was associated with a 52% reduction in the probability of having a relapse (odds ratio, 0.48; 95% confidence interval [CI], 0.28-0.84; p = 0.0097) and a 50% reduction in ARR (rate ratio, 0.50; 95% CI, 0.34-0.75; p = 0.0006) compared with IFN/GA. LIMITATIONS: Identification of relapses is based on the claims in the database rather than on a clinical assessment. CONCLUSIONS: In a real-world setting, fingolimod was shown to be associated with significantly lower relapse rates than IFN/GA in patients with MS who had a history of relapses.

Incidence of venous thromboembolism among chemotherapy-treated patients with lung cancer and its association with mortality: a retrospective database study.

Cancer patients, especially those with lung cancer and undergoing chemotherapy, have an elevated risk for venous thromboembolism (VTE). This study assessed incidence, timing, and risk factors for VTE (specifically receipt of chemotherapy), along with the association between VTE and survival among lung cancer patients receiving chemotherapy. Using Florida Medicaid administrative claims data (2000-2008), patients with any diagnosis of primary lung cancer were selected. Patients with recent prior VTE and those enrolled in Medicare or an HMO were excluded. Crude rates of VTE per 100 person years were estimated, and Cox proportional hazards models were developed to assess risk factors for VTE in the lung cancer population, and the association between VTE and survival among patients undergoing chemotherapy. Of 15,749 lung cancer patients, 7,052 (2,242 receiving chemotherapy and 4,810 not receiving chemotherapy) met cohort selection criteria. The incidence of VTE was 10.8 per 100 person-years (PYs) in the chemotherapy cohort and 6.8 per 100 PYs in the non-chemotherapy cohort. Among patients on chemotherapy developing VTE, median time to occurrence was 109 days, with 61 and 82 % of patients experiencing an event within six and 12 months, respectively. In multivariate analyses, the adjusted risk of VTE was 30 % higher among patients undergoing chemotherapy. Comorbidity and the presence of a central venous catheter also were significantly associated with a greater risk of developing VTE. Moreover, patients in the chemotherapy cohort who developed VTE had a significantly faster time-to-death (adjusted hazard ratio [HR] = 1.97; 95 % CI 1.69-2.29).VTE was common among lung cancer patients, especially among patients receiving chemotherapy, with the majority of VTE events occurring within 6 months of initiation of chemotherapy. The presence of a VTE event was significantly associated with an increased risk of mortality.

The relationship between use of antidepressants and resource utilization among patients with manic or mixed bipolar disorder episodes: findings from a managed care setting.

OBJECTIVE: Treatment guidelines for bipolar disorder (BD) recommend the tapering of antidepressants (ADs) for patients with a recent acute manic or mixed episode. This study assessed rates of AD use and the association between such use and BD-related re-hospitalizations among patients with BD. METHODS: Using the IMS LifeLink® Health Plan Claims Database from 1/1/2004 to 6/30/2007, we identified adults 18+ years of age with an acute psychiatric event ("index event"), defined as a hospitalization, emergency room visit, or physician visit, with a prescription for a new BD medication with a primary diagnosis of BD I mania (ICD-9-CM: 296.0x, 296.4x) or BD I mixed (ICD-9-CM: 296.6x). All patients were required to be eligible for the 12 months before index and during the 12-month post-index period, and have a BD-related hospitalization (any diagnosis of any BD subgroup) in the pre-index period. Patients with schizophrenia at any time during the study period were excluded. Study measures included: rates of AD use (minimum of 30 days of available AD therapy within 120 days after the index event) and the association of such use with post-index BD-related hospitalizations. RESULTS: 2126 patients met study criteria (mean age 44 years; 57% female; 53% BD I mania). 32% of all patients had AD use in the post-index period. Compared to BD I patients without AD use in the post-index period, those with AD use had 1.43 to 1.50 times the odds of being re-hospitalized for BD in the follow-up period. Other significant positive predictors included being female and presence of substance abuse. LIMITATIONS: Administrative claims data do not provide information on symptoms, which may influence continuation of antidepressants. CONCLUSIONS: In this administrative claims database, nearly one-third of patients with BD I manic or mixed subgroups had AD use following an acute event. The positive association observed between AD use and re-hospitalization needs to be confirmed in clinical studies.

Medical care costs and survival associated with hepatocellular carcinoma among the elderly.

BACKGROUND & AIMS: We assessed the burden of hepatocellular carcinoma (HCC), in terms of mortality and medical care costs, based on analysis of the Surveillance, Epidemiology and End Results (SEER)-Medicare database. METHODS: We analyzed data from the SEER-Medicare database on patients 66 years or older who were diagnosed with primary HCC from 1991 to 2007, entitled for Medicare Parts A and B, and not enrolled in health maintenance organizations (n = 5712). Controls were individuals without HCC, identified from a 5% sample of Medicare beneficiaries residing in SEER areas; they were matched 1:1 with individuals with HCC (cases) for age, sex, race, and geographic region (average age, 75 y; 34.7% female). Kaplan-Meier analysis was used to estimate survival distributions. Costs were reported in 2009 dollars; per-patient-per-month (PPPM) costs were compared between cases and controls using the Wilcoxon rank sum test. RESULTS: The largest proportion of cases had localized disease (38.2%), followed by regional (24.0%), unstaged (20.4%), and distant (17.3%) disease. The median survival times were 5 months for cases and 60 months for controls; they were 3 months for patients with distant disease, 4 months for patients with regional disease, and 9 months for those with localized disease. The mean PPPM costs were $7863 for cases and $1243 for controls (P < .001). These costs were primarily driven by inpatient (mean, $5439 vs $682 without HCC; P < .001) and hospice (mean $554 vs $42 without HCC; P < .001) care. Mean PPPM costs by stage were $7265 for localized disease, $8072 for regional disease, and $9585 for distant disease (P < .001 for trend). CONCLUSIONS: Based on analysis of the SEER-Medicare database, costs for patients with HCC are approximately 6- to 8-fold higher than for those without this cancer. Patients with distant HCC had the greatest costs. These findings highlight that HCC is a substantial medical cost burden for elderly patients.

The economic costs to United States hospitals of invasive fungal infections in transplant patients.

BACKGROUND: Patients with a solid organ transplant (SOTs) and hematopoietic stem cell or bone marrow transplants (HSC/BMTs) are at risk of contracting invasive fungal infections (IFIs). Data on the economic burden of IFIs in the United States are sparse. METHODS: We conducted a retrospective matched cohort study using the 2004-2005 Healthcare Cost and Utilization Project Nationwide Inpatient Sample. The IFI cohort included patients with ICD-9-CM codes indicating a transplant procedure and an IFI. Matched controls (transplant recipients without an IFI) were chosen based on age (10 year categories), sex, region, hospital type, year, and transplant type. Mortality, length of stay, and costs were reported overall, by transplant type, and by type of mycosis. RESULTS: Nine thousand eight hundred ninety-six patients underwent SOT, and 4661 underwent HSC/BMT. Of these, 80 (0.8%) SOT and 111 (2.4%) HSC/BMT patients had an IFI. Mean age was 41.8 years (SOT) and 37.8 years (HSC/BMT). Aspergillosis was the most common infection. Patients with an IFI had a 5-fold increase in mortality, an additional 19.2 hospital days, and $55,400 in excess costs compared with patients without an IFI. Excess mortality, length of stay, and costs varied by type of transplant and mycosis. CONCLUSION: The clinical and economic burden of IFIs in transplant recipients may be high.

Medication adherence and hospitalization among patients with schizophrenia treated with antipsychotics.

OBJECTIVE: This analysis assessed rates of medication adherence and predictors of nonadherence and hospitalization among patients treated with long-acting injectable and oral antipsychotic therapies. METHODS: Data were from a retrospective analysis of Florida Medicaid recipients with schizophrenic disorder (ICD-9-CM code 295.XX) who received a prescription for an antipsychotic between July 1, 2004, and June 30, 2005. Patients were required to have filled one additional antipsychotic prescription during follow-up. Adherence measures included medication possession ratio (MPR), medication persistence, medication consistency, and maximum gap in treatment. Multivariate logistic regression models identified predictors of nonadherence and hospitalization. RESULTS: Patients were considered adherent if they had an MPR ≥ .8. A total of 12,032 patients met selection criteria. The mean ± SD MPR was .79 ± .23, medication persistence was 94.1% ± 16.4%, medication consistency was 83.3% ± 16.4%, and the maximum gap in treatment was 29.7 ± 41.4 days. Thirty-seven percent of patients were hospitalized for any cause, and 32% had a psychiatric hospitalization. Predictors of nonadherence included newly starting treatment; younger age; a substance abuse diagnosis; use of a mood stabilizer, antidepressant, anxiolytic, or anticholinergic; and receipt of long-acting first-generation antipsychotics. Receipt of long-acting second-generation therapy or receipt of both first- and second-generation medications was associated with lower likelihood of nonadherence. Predictors of hospitalization risk included a diagnosis of other psychoses or substance abuse, anticholinergic use, and nonadherence to therapy. CONCLUSIONS: Results document rates of antipsychotic adherence and predictors of nonadherence and hospitalization. Findings may be useful to health plan administrators, formulary decision makers, and physicians.

Development of an interactive model of the burden of future coronary heart disease from an employer perspective.

OBJECTIVE: To create a computer-based model for employers to better understand the burden of coronary heart disease (CHD) to their organizations. METHODS: A user-friendly model was developed to allow employers to evaluate the burden of CHD. Inputs include the demographic distribution by age and sex, prevalence of CHD and CHD risk factors, direct and indirect medical costs of CHD events, and discount and inflation rates. The model contains prediction equations derived from National Health and Nutrition Examination Survey data and Framingham Heart Study equations, used with employer inputs to predict future CHD events and expenditures. RESULTS: Interactive graphs are presented for the employer's covered population alongside regional benchmarks. The time horizon and population may be adjusted. CONCLUSIONS: This interactive model illustrates how pragmatic outcomes research can be converted into a transparent model addressing health care budget issues that is readily understood by corporate managers.

Relationship between glycemic control and diabetes-related hospital costs in patients with type 1 or type 2 diabetes mellitus.

BACKGROUND: Diabetes mellitus requires continuous medical care and patient self-management in order to prevent short-term complications and decrease the risk of long-term complications, which can result in substantial increases in the total economic burden of the disease. Findings from randomized clinical trials have shown that improved glycemic control may reduce the risk of long-term complications as long as a target for hemoglobin A1c is not set below 7% for intensive glycemic control. However, limited data from clinical practice are available regarding the relationship between glycemic control and medical costs associated with diabetes care. OBJECTIVE: To assess the potential relationships between glycemic levels, diabetes-related hospitalizations, and hospital costs among adult patients with either type 1 or type 2 diabetes mellitus who were assigned to a primary care provider (PCP) in a clinic that was affiliated with a managed care organization (MCO). METHODS: A retrospective cohort analysis was conducted using data from approximately 200,000 members of the Fallon Clinic Health Plan who were assigned to a clinic PCP at any time during a 5-year study period beginning January 1, 2002, and ending December 31, 2006. Patients aged 30 years or older with at least 2 medical claims with any listed diagnosis of diabetes mellitus (ICD-9-CM code 250.xx) during the study period and 2 or more A1c values within 1 year of each other during the study period (mean 7.6 tests over 39 months; median=6.8), were identified and stratified into 1 of 5 groups defined by 1% increments of A1c, based on their mean A1c values during the entire study period. A1c data were available only for tests ordered by a clinic provider; tests ordered by other specialists in the MCO's network were absent from the database. The study follow-up period started with each patient's first A1c test (index date) and continued until plan disenrollment, death, or December 31, 2006, whichever was earlier (end date), regardless of when the diagnosis of diabetes mellitus was made. Study measures included the proportion of patients with 1 or more diabetes-related hospitalizations, number of diabetes-related inpatient stays, and the associated estimated hospitalization costs over the follow-up period. Diabetes-related hospitalizations were identified based on a diagnosis, in any of 10 diagnosis fields, for 1 of 16 selected complications of diabetes identified by the authors. Hospital costs were estimated using discharge data (diagnoses and costs calculated from cost-to-charge ratios) contained in the 2004 Healthcare Cost and Utilization Project (HCUP) database and inflated to 2007 dollars using the medical care component of the Consumer Price Index. Multivariate models controlled for age, sex, number of A1c tests, diagnosis of cancer, and follow-up time. A multivariate logistic regression analysis was conducted with the occurrence of at least 1 diabetes-related hospital admission as the dependent variable. In the logistic regression analysis, follow-up time was defined as time from the index date to the date of the first diabetes-related hospitalization, plan disenrollment, death, or the study end date, whichever occurred first. A generalized linear model with a Poisson distribution and a log link was employed to estimate the rate of hospital admissions. In the Poisson regression analysis, follow-up time was defined as duration of the entire study follow-up period and was an offset variable. Costs were estimated using a 2-part model: first, we calculated the probability of having a hospitalization, as determined by the logistic regression above; second, a generalized linear model with a negative binomial distribution and a log link was used to predict the mean cost of diabetes-related hospitalizations only for patients with an inpatient stay, with the duration of the entire study follow-up period as an offset variable. We calculated the mean per patient cost of diabetes-related hospitalizations by multiplying the probability of having a hospitalization (as determined by the first part of the model) by the mean costs for patients who had such admissions (as determined by the second part of the model). RESULTS: 9,887 patients met study selection criteria. Mean A1c level was < 7% for 5,649 (57.1%) patients, 7% to < 8% for 2,747 (27.8%), 8% to < 9% for 1,002 (10.1%), 9% to < 10% for 312 (3.2%), and 10% or more for 177 (1.8%). Over a mean (median) 40 (40) months of follow-up (interquartile range = 30-50 months), 28.7% (n = 2,838) of patients had 1 or more diabetes- related hospital admissions. In the logistic regression analysis, odds of having at least 1 diabetes-related hospital stay did not significantly differ for patients with mean A1c of < 7% compared with patients in most higher mean A1c categories (7% to < 8%, 8% to < 9%, or 9% to < 10%); however, odds of having a diabetes-related hospitalization were significantly higher for patients with mean A1c of 10% or more compared with patients with mean A1c of < 7% (odds ratio = 2.13, 95% confidence interval = 1.36-3.33). In the negative binomial regression analysis of those with at least 1 hospital admission, estimated costs per hospitalized patient increased by mean A1c level. In the Poisson regression analysis, the rate of diabetes-related hospitalizations significantly increased by A1c level (13 per 100 patient-years for patients with mean A1c of < 7% vs. 30 per 100 patient-years for mean A1c of 10% or more when covariates were held at mean levels, P<0.001). In the 2-part model results, adjusted mean estimated costs of diabetes-related hospitalizations per study patient were $2,792 among those with mean A1c of < 7% and $6,759 among those with mean A1c of 10% or more. CONCLUSIONS: In this managed-care plan, the odds of having at least 1 diabetes-related hospitalization were not significantly associated with higher mean A1c except for patients with mean A1c of at least 10%. However, higher mean A1c levels were associated with significantly higher estimated hospitalization costs among those with at least 1 hospitalization and with higher rates of diabetes-related hospital utilization per 100 patient-years.

Trends in healthcare utilization among older Americans with colorectal cancer: a retrospective database analysis.

BACKGROUND: Analyses of utilization trends (cost drivers) allow us to understand changes in colorectal cancer (CRC) costs over time, better predict future costs, identify changes in the use of specific types of care (eg, hospice), and provide inputs for cost-effectiveness models. This retrospective cohort study evaluated healthcare resource use among US Medicare beneficiaries diagnosed with CRC between 1992 and 2002. METHODS: Cohorts included patients aged 66+ newly diagnosed with adenocarcinoma of the colon (n = 52,371) or rectum (n = 18,619) between 1992 and 2002 and matched patients from the general Medicare population, followed until death or December 31, 2005. Demographic and clinical characteristics were evaluated by cancer subsite. Resource use, including the percentage that used each type of resource, number of hospitalizations, and number of hospital and skilled nursing facility days, was evaluated by stage and subsite. The number of office, outpatient, and inpatient visits per person-year was calculated for each cohort, and was described by year of service, subsite, and treatment phase. Hospice use rates in the last year of life were calculated by year of service, stage, and subsite for CRC patients who died of CRC. RESULTS: CRC patients (mean age: 77.3 years; 44.9% male) used more resources than controls in every category (P < .001), with the largest differences seen in hospital days and home health use. Most resource use (except hospice) remained relatively steady over time. The initial phase was the most resource intense in terms of office and outpatient visits. Hospice use among patients who died of CRC increased from 20.0% in 1992 to 70.5% in 2004, and age-related differences appear to have evened out in later years. CONCLUSION: Use of hospice care among CRC decedents increased substantially over the study period, while other resource use remained generally steady. Our findings may be useful for understanding CRC cost drivers, tracking trends, and forecasting resource needs for CRC patients in the future.

Lifetime and treatment-phase costs associated with colorectal cancer: evidence from SEER-Medicare data.

BACKGROUND & AIMS: This study provides detailed estimates of lifetime and phase-specific colorectal cancer (CRC) treatment costs. METHODS: This retrospective cohort study included patients aged 66 years and older, newly diagnosed with CRC in a Surveillance Epidemiology and End Results (SEER) registry (1996-2002), matched 1:1 (by age, sex, and geographic region) to patients without cancer from a 5% sample of Medicare beneficiaries. The Kaplan-Meier sample average estimator was used to estimate observed 10-year costs, which then were extrapolated to 25 years. A secondary analysis computed costs on a per-survival-year basis to adjust for differences in mortality by stage and age. Costs were expressed in 2006 US$, with future costs discounted 3% per year. RESULTS: Our sample included 56,838 CRC patients (41,256 colon cancer [CC] patients and 15,582 rectal cancer [RC] patients; mean +/- SD age, 77.7 +/- 7.1 y; 55% women; and 86% white). Lifetime excess costs were $29,500 for CC and $26,500 for RC patients. Per survival year, stage IV CRC patients incurred $31,000 in excess costs compared with $3000 for stage 0 patients. CRC patients incurred excess costs of $33,500 in the initial phase, $4500/y in the continuing phase, and $14,500 in the terminal phase. RC patients had lower costs than CC patients in the initial phase, but higher costs in both the continuing and terminal phases. CONCLUSIONS: Excess costs associated with CRC are striking and vary considerably by treatment phase, cancer subsite, and stage at diagnosis. Interventions aimed at earlier diagnosis and prevention have the potential to reduce cancer-related health care costs.