Value of clinical trial narrative data to estimate the costs of adverse event management: a feasibility study.

Aims: The objective of this feasibility study was to determine the extent to which data from randomized controlled trials (RCTs) may serve as a useful source for collecting health care resource use (HCRU) for the purposes of estimating costs of managing adverse events (AEs), specifically, grade 3-4 nausea and thrombocytopenia, which may be experienced during chemotherapy treatment.Materials and Methods: The feasibility study was conducted in four steps: (1) HCRU data were extracted from patient narratives in four phase 3 RCTs in non-small cell lung cancer; (2) missing HCRU data were imputed; (3) unit costs were applied to the resulting HCRU data set and costs of managing AEs were estimated; and (4) the overall utility of using RCT data as a source for estimating costs of AEs was evaluated.Results: 33 nausea and 68 thrombocytopenia AEs met eligibility criteria and were evaluated in this study. Medication usage was recorded as a treatment in 76% of nausea AEs, although only 14% of the instances of medication usage included the minimum data elements required for costing. Platelet transfusions were provided in 24% of thrombocytopenia AEs; however, in only one instance were the minimum data elements recorded. Of nausea and thrombocytopenia AEs, 18% and 72%, respectively, required no missing data assumptions or imputation.Limitations: Only two AEs were considered, and they may not be representative of all AEs in terms of suitability for use in estimating HCRU and costs of managing AEs. Not all grade 3-4 AEs met the criteria for requiring a patient narrative. HCRU data in the narratives were incomplete.Conclusions: The usefulness of RCTs for estimating the costs of AEs may be improved by using a standardized form to collect HCRU data for key AEs, including an appropriate level of detail required to estimate costs of managing the AEs.

Development and validation of a claims-based approach to proxy ECOG performance status across ten tumor groups.

AIM: To develop a claims-based prediction model of poor performance status (PS) in commercially insured and Medicare supplemental beneficiaries with cancer. PATIENTS & METHODS: Retrospective analysis was conducted of electronic medical records (EMR) from community oncology practices linked to MarketScan claims. Multivariable logistic regression predicted PS scores from the EMR using claims-based diagnostic and procedure codes. RESULTS: The study included 8442 patients diagnosed with cancer from 2007 to 2015. Overall, 8.1% of patients had poor EMR-based PS. Bootstrapping results from the final model showed sensitivity and specificity of approximately 75% with a predicted probability cutpoint = 0.078, c-statistic = 0.821 and pseudo-R2 = 0.25. CONCLUSION: Patients with poor PS can be identified in claims data. This prediction model enables future studies evaluating cancer treatments and outcomes to account for PS.

A Claims-Based Examination of Health Care Costs Among Spouses of Patients With Alzheimer's Disease.

BACKGROUND: Spouses of Alzheimer's disease patients (AD spouses) may experience substantial health effects associated with their partner's chronic cognitive and behavioral dysfunction. Studies examining associations between the medical experiences of AD spouses in the period before and after their partner's AD diagnosis are limited, particularly those which measure health care resource use and cost. METHODS: AD patients were identified through multiple Medicare claims containing an AD diagnostic code. Their spouses were identified through special coding in the Medicare eligibility records. The AD spouses were matched demographically to the spouses of Medicare beneficiaries without a history of AD. Longitudinal and annual cross-sectional Medicare cost comparisons utilized log-transformed linear regression. The longitudinal period of observation began 12 months before the AD patient's initial claim listing AD and continued for up to 38 months afterwards. RESULTS: The study identified 16,322 AD spouses. Total per person costs were 24% higher in AD spouses than in the controls ($694/month vs $561/month). AD spouses' excess costs began 3 months before their partners' AD diagnoses and continued for ≥30 months. Being an AD spouse predicted 29% higher Medicare costs after adjustment for chronic health status (P < .001). Increasing AD patient care complexity had a substantial impact on AD spouse Medicare costs (P < .001). CONCLUSIONS: This study documents a link between the health status of AD spouses and AD patients. Additional research is required to elicit the mechanism behind the association between AD spouse and AD patient diagnosis.

Frequency of skeletal-related events and associated healthcare resource use and costs in US patients with multiple myeloma.

OBJECTIVE: A potential complication for all new multiple myeloma (MM) patients is the clinical presentation of osteolytic lesions which increase the risk for skeletal-related events (SREs). However, the contribution of SREs to the overall economic impact of MM is unclear. The impact of SREs on healthcare resource utilization (HCRU) and costs for US patients with MM was analyzed in Truven Health Marketscan Commercial Claims and Medicare Supplemental Databases. METHODS: Adults diagnosed with MM between January 1, 2005 and December 31, 2010 with ≥2 claims ≥30 days apart (first claim = index date) were included. SREs included: hypercalcemia, pathologic fracture, surgery for the prevention and treatment of pathologic fractures or spinal cord compression, and radiation for bone pain. Rates of HCRU (outpatient [OP], inpatient [IP], emergency room [ER], orthopedic consultation [OC], and ancillary) and healthcare costs were compared between MM patients with and without SREs. Inverse propensity weighting was applied to adjust for potential bias. RESULTS: Of 1028 MM patients (mean age = 67, standard deviation = 13.2), 596 patients with ≥1 SRE and 432 without SREs were assessed. HCRU rates in IP, ER, and ancillary (p < 0.01) and mean total costs of OP, IP, and ER were significantly higher (p < 0.05) for patients with vs without SREs during follow-up. HCRU rates also increased with SRE frequency (p < 0.05 in OP, IP, ER, OC, and ancillary), as did mean total healthcare costs, except for OC (p < 0.001). LIMITATIONS: A broad assessment of pharmacotherapy for the treatment of MM was not an objective of the current study. Bisphosphonate use was evaluated; however, results were descriptively focused on frequency of utilization only and were not included in the broader cost and HCRU analysis. CONCLUSIONS: Among US patients with MM, higher SRE frequency was associated with a significant trend of higher HCRU and total healthcare costs in several settings.

The time horizon matters: results of an exploratory study varying the timeframe in time trade-off and standard gamble utility elicitation.

INTRODUCTION: The purpose of this study was to examine whether the time horizon of time trade-off (TTO) and standard gamble (SG) utility assessment influences utility scores and discrimination between health states. METHODS: In two phases, UK general population participants rated three osteoarthritis health states in TTO and SG procedures with two time horizons: (1) 10-year and (2) a time horizon derived from self-reported additional life expectancy (ALE). The two time horizons were compared in terms of mean utilities and discrimination among health states. RESULTS: In Phase 1, the 10-year tasks were completed by 80 participants, 35 of whom also completed utility assessment with the ALE. In Phase 2, all 101 participants completed procedures with both time horizons. Utility scores tended to be lower with the ALE than the 10-year, a difference that was statistically significant for two health states with SG in Phase 1 (P < 0.05), two health states with TTO in Phase 2 (P < 0.01), and one health state with SG in Phase 2 (P < 0.001). In Phase 1, rates of discrimination between mild and moderate osteoarthritis health states were significantly higher with the ALE than the 10-year (TTO: P = 0.03; SG: P = 0.001). This pattern of discrimination was similar in Phase 2. DISCUSSION: Results suggest that the time horizon could influence utility scores and discrimination among health states. When designing utility evaluations, researchers should carefully consider the time horizon so that the value of health states is accurately represented in cost-utility models.

Comparison of demographics, treatment patterns, health care utilization, and costs among elderly patients with extensive-stage small cell and metastatic non-small cell lung cancers.

BACKGROUND: Limited data exist regarding real-world treatment patterns, resource utilization, and costs of extensive-stage small cell lung cancer (esSCLC) among elderly patients in the United States. While abundant data are available on treatment patterns in metastatic non-small cell lung cancer (mNSCLC), to our knowledge no data exist comparing costs and resource use between patients with esSCLC or mNSCLC. METHODS: We retrospectively analyzed administrative claims data (2000-2008) of patients aged ≥65 years from the linked Surveillance, Epidemiology and End Results (SEER)-Medicare database. Patients were selected on the basis of having newly diagnosed esSCLC (n=5,855) or mNSCLC (n=24,090) during 1/1/2000-12/31/2005, and were required to have received cancer-directed therapy. Survival and other measures were compared between esSCLC and mNSCLC patients using Kaplan-Meier log-rank and univariate chi-square and t-tests. Study measures were followed from first diagnosis date of either esSCLC or mNSCLC until the earlier of death or end of the database. RESULTS: Survival between the cohorts did not differ significantly: mean of 10.4 months for esSCLC patients versus 11.1 months for mNSCLC; median survival was 7.4 months versus 5.9 months. A higher percentage of mNSCLC patients (vs. esSCLC) received radiation therapy (75.6% vs. 65.4%; P < 0.001) and surgery (13.6% vs. 7.8%; P < 0.001) during the metastatic disease period. Conversely, a higher percentage of esSCLC patients than mNSCLC patients received chemotherapy (85.5% vs. 60.3%; P < 0.001), red blood-cell transfusion (20.7% vs. 10.9%; P < 0.001), platelet transfusion (5.6% vs. 1.8%; P < 0.001), and growth-factor support (59.0% vs. 39.5%; P < 0.001). esSCLC patients incurred higher lifetime disease-related costs ($44,167 vs. $37,932; P < 0.001) and all-cause costs ($70,549 vs. $67,176; P < 0.001) than mNSCLC patients. CONCLUSIONS: Lifetime total and disease-related costs per patient were high. Increased use of chemotherapy, supportive care therapies (including growth factors), and disease-related hospitalizations were observed in esSCLC patients as compared with mNSCLC patients. Disease-related and all-cause costs for esSCLC also exceeded those of mNSCLC, except for hospice and skilled nursing services. Survival and per-patient costs for both groups underscore the unmet medical need for more effective therapies in patients with esSCLC or mNSCLC.

Using U.S. Medicare records to evaluate the indirect health effects on spouses: a case study in Alzheimer's disease patients.

BACKGROUND: The burden experienced by spouses of patients with Alzheimer's disease (AD) may have negative consequences for their physical health. We describe here a method for analyzing United States Medicare records to determine the changes in health service use and costs experienced by spouses after their marital partner receives an AD diagnosis. METHODS: We initially identified all beneficiaries in the 2001-2005 Medicare 5% sample who had multiple claims listing the ICD-9 diagnostic code for AD, 331.0. The 5% sample includes spouses who share a Medicare account with their marital partners because they lack a sufficient work history for full eligibility on their own. A matched cohort study assessed incremental health costs in the spouses of AD patients versus a control group of spouses of non-AD patients. Longitudinal and cross-sectional analyses tracked the impact of a patient's AD diagnosis on his or her spouse's healthcare costs. RESULTS: Our method located 54,593 AD patients of whom 11.5% had spouses identifiable via a shared Medicare account. AD diagnosis in one member of a couple was associated with significantly higher monthly Medicare payments for the other member's healthcare. The spouses' elevated costs commenced 2 to 3 months before their partners' AD diagnosis and persisted over the follow-up period. After 31 months, the cumulative additional Medicare reimbursements totaled a mean $4,600 in the spouses of AD patients. This excess was significant even after accounting for differences in baseline health status between the cohorts. CONCLUSION: The study methodology provides a framework for comprehensively evaluating medical costs of both chronically ill patients and their spouses. This method also provides monthly data, which makes possible a longitudinal evaluation of the cost effects of specific health events. The observed correlations provide a coherent demonstration of the interdependence between AD patients' and spouses' health. Future research should examine caregiving burden and other possible factors contributing to the AD spouses' health outcomes. It should also extend the method presented here to evaluations of other chronic diseases of the elderly.

Challenges to time trade-off utility assessment methods: when should you consider alternative approaches?

In recent years, the time trade-off (TTO) method, most commonly with a 10-year time horizon, has been the most frequently used approach for direct health state utility assessment, likely due to National Institute for Health and Care Excellence (NICE) preference for comparability with the EQ-5D, which has a utility scoring algorithm derived via this method. Although comparability to previous utility studies is important, there are situations when the TTO method may not be appropriate. The purpose of the current review is to highlight challenges to the TTO method. Five challenges to the TTO method are discussed: mild health states, small differences among health states, temporary health states, pediatric health states, and assessment of samples with particular characteristics. Some of these challenges are associated with the 10-year time horizon, while other situations may raise issues for TTO methods regardless of the time horizon. Alternative approaches for valuing health states are suggested.

Impact of caregiver and parenting status on time trade-off and standard gamble utility scores for health state descriptions.

BACKGROUND: The purpose of this study was to examine the effect of caregiver status on time trade-off (TTO) and standard gamble (SG) health state utility scores. Respondents were categorized as caregivers if they reported that either children or adults depended on them for care. METHODS: This study was a secondary analysis of data from three studies in which general population samples rated health state descriptions. Study 1: UK; four osteoarthritis health states. Study 2: UK; three adult ADHD health states. Study 3: US; 16 schizophrenia health states. All three studies included time trade-off assessment. Study 1 also included standard gamble. Descriptive statistics were calculated to examine willingness to trade in TTO or gamble in SG. Utilities for caregivers and non-caregivers were compared using t-tests and ANCOVA models. RESULTS: There were 364 respondents including 106 caregivers (n = 30, 47, and 29 in Studies 1, 2, and 3) and 258 non-caregivers. Most caregivers were parents of dependent children (78.3%). Compared to non-caregivers, caregivers had more responses at the ceiling (i.e., utility = 0.95), indicating less willingness to trade time or gamble. All utilities were higher for caregivers than non-caregivers (mean utility difference between groups: 0.07 to 0.16 in Study 1 TTO; 0.03 to 0.17 in Study 1 SG; 0.06 to 0.10 in Study 2 TTO; 0.11 to 0.22 in Study 3 TTO). These differences were statistically significant for at least two health states in each study (p < 0.05). Results of sensitivity analyses with two caregiver subgroups (parents of dependent children and parents of any child regardless of whether the child was still dependent) followed the same pattern as results of the primary analysis. The parent subgroups were generally less willing to trade time or gamble (i.e., resulting in higher utility scores) than comparison groups of non-parents. CONCLUSIONS: Results indicate that caregiver status, including being a parent, influences responses in time trade-off health state valuation. Caregivers (i.e., predominantly parents) were less willing than non-caregivers to trade time, resulting in higher utility scores. This pattern was consistent across multiple health states in three studies. Standard gamble results followed similar patterns, but with less consistent differences between groups. It may be useful to consider parenting/caregiving status when collecting, interpreting, or using utility data because this demographic variable could influence results.

Healthcare costs, treatment patterns, and resource utilization among pancreatic cancer patients in a managed care population.

BACKGROUND: Pancreatic adenocarcinoma has few effective treatment options and poor survival. The objective of this study was to characterize treatment patterns and estimate the costs and resource use associated with its treatment in a commercially-insured US population. METHODS: In this retrospective claims-based analysis, individuals ≥18 years old with evidence of pancreatic adenocarcinoma between January 1, 2001 and December 31, 2010 were selected from a managed care database. Treatment phase (either initial non-metastatic or metastatic) was determined using a claims-based algorithm. Patients in the pancreatic cancer population were matched 1:3 to a control population. Resource use (events/person-years), treatment patterns, and healthcare costs (per-patient per-month, PPPM) were determined during a variable length follow-up period (from first pancreatic cancer diagnosis to earliest of death, disenrollment, or study end). RESULTS: In this study, 5262 pancreatic cancer patients were matched to 15,786 controls. Rates of office visits, inpatient visits, ER visits, and inpatient stays, and mean total all-cause healthcare costs PPPM ($15,480 vs $1001) were significantly higher among cancer patients than controls (all p < 0.001). Mean inpatient costs were the single largest cost driver ($9917 PPPM). Also, mean total all-cause healthcare costs were significantly higher during the metastatic treatment phase vs the initial treatment phase of non-metastatic disease ($21,637 vs $10,358, p < 0.001). CONCLUSIONS: These results indicate that pancreatic cancer imposes a substantial burden on the US healthcare system, and that treatment of more advanced disease is significantly more costly than initial treatment of non-metastatic disease. LIMITATIONS: Additional research is needed to validate the accuracy of the claims-based algorithms used to identify the treatment phase.

Drug reimbursement recommendations by the National Institute for Health and Clinical Excellence: have they impacted the National Health Service budget?

OBJECTIVE: Determine whether reimbursement restrictions recommended by the National Institute for Health and Clinical Excellence (NICE) have impacted the United Kingdom (UK) National Health Service (NHS) budget. METHODS: Data were abstracted from NICE guidance documents and costing statements through March 2011. Estimated maximum and adjusted potential budget impact (PBI) on the NHS was derived using estimates of the UK marketing-approved population and the annual cost for the new drug. Descriptive and logistic analyses were used to estimate the correlation between the degree of restrictions on reimbursement recommended by NICE for each new drug indication and the PBI controlling for clinical effectiveness and cost-effectiveness. RESULTS: PBI was significantly correlated with the degree of reimbursement restrictions. In descriptive analysis, the adjusted PBI for drugs that were recommended without restrictions was £20.3 million (SD = 22.2) compared with £49.8 million (SD = 90.8) for those recommended with restrictions and £71.1 million (SE = 99.9) for those not recommended. In logistic analysis, the odds ratio for less restrictive reimbursement was 0.848 (95% CI, 0.762-0.945) for each £20 million increase in the adjusted PBI. Results were similar using the maximum PBI. CONCLUSIONS: After controlling for clinical effectiveness and cost-effectiveness, the degree of reimbursement restriction recommended by NICE remains significantly correlated with the PBI, despite that fact that the NICE decision process does not consider budget impact. This correlation might be due to NICE consideration of effectiveness and cost-effectiveness for subgroups of the approved population.

Do different clinical evidence bases lead to discordant health-technology assessment decisions? An in-depth case series across three jurisdictions.

BACKGROUND: Health-technology assessment (HTA) plays an important role in informing drug-reimbursement decision-making in many countries. HTA processes for the Pharmaceutical Benefits Advisory Committee (PBAC) in Australia, the Common Drug Review (CDR) in Canada, and the National Institute for Health and Clinical Excellence (NICE) in England and Wales are among the most established in the world. In this study, we performed nine in-depth case studies to assess whether different clinical evidence bases may have influenced listing recommendations made by PBAC, CDR, and NICE. METHODS: Nine drugs were selected for which the three agencies had provided listing recommendations for the same indication between 2007 and 2010. We reviewed the evidence considered for each listing recommendation, identified the similarities and differences among the clinical evidence bases considered, and evaluated the extent to which different clinical evidence bases could have contributed to different decisions based on HTA body comments and public assessment of the evidence. RESULTS: HTA agencies reached the same recommendation for reimbursement (recommended for listing) for four drugs and different recommendations for five drugs. In all cases, each agency used different evidence bases in their recommendations. The agencies considered overlapping sets of clinical comparators and trials when evaluating the same drug. While PBAC and NICE considered indirect and/or mixed-treatment comparisons, CDR did not. In some cases, CDR and/or NICE excluded trials from review if the drug and/or the comparator were not administered according to the relevant marketing authorization. CONCLUSIONS: In the listing recommendations reviewed, considerable variability exists in the clinical evidence considered by PBAC, CDR, and NICE for drug-listing recommendations. Differences in evidence resulted from differences in the consideration of indirect and mixed-treatment comparison data and differences in medical practice in each jurisdiction.

Relationship between financial impact and coverage of drugs in Australia.

OBJECTIVES: The aim of this study was to estimate the relationship between the financial impact of a new drug and the recommendation for reimbursement by the Australian Pharmaceutical Benefits Advisory Committee (PBAC). METHODS: Data in the PBAC summary database were abstracted for decisions made between July 2005 and November 2009. Financial impact-the upper bound of the values presented in the PBAC summary database-was categorized as ≤A$0, >A$0 up to A$10 million, A$10 million up to A$30 million, and >A$30 million per year. Descriptive, logistic, survival, and recursive partitioning decision analyses were used to estimate the relationship between the financial impact of a new drug indication and the recommendation for reimbursement. Multivariable analyses controlled for other clinical and economic variables, including cost per quality-adjusted life-year gained. RESULTS: Financial impact was a significant predictor of the recommendation for reimbursement. In the logistic analysis, the odds ratios of reimbursement for drug submissions with financial impacts ≥A$10 million to ≥A$30 million or >A$0 to

Differences among formulary submission guidelines: implications for health technology assessment.

OBJECTIVES: This article provides a detailed understanding of the differences in selected formulary submission guidelines supplied by various health technology assessment (HTA) agencies and indicates how these differences can impact the evidence base used to populate the HTA. METHODS: Detailed summaries of the recommended methods for evidence generation, organized by topic areas relevant for clinical and economic data, for twelve countries in Europe, North America, and Australia where HTA processes are well developed were prepared. Using these summaries, we provide examples of the likely impact these differences in recommended methods could have on the evidence base used to evaluate new health technologies. RESULTS: Areas where recommendations differed included methodologies for systematic literature reviews (e.g., preferred databases and study designs for inclusion); selection of appropriate comparators; guidance on critical appraisal and synthesis of clinical evidence; appropriate sources for health value measures, resource use, and cost data; and approaches to uncertainty analyses. Performing literature searches that capture all relevant studies and then creating subsets of the literature based on a listing of country-specific requirements could allow for direct comparison of the evidence bases associated with the different guidelines. CONCLUSIONS: If the formulary submission guidelines were followed as written, different (although overlapping) bodies of evidence likely would be generated for each country, which could contribute to disparate assessments and recommendations. This comparison of the formulary submission guidelines could contribute to an understanding of why clinical and reimbursement decisions vary across countries.

Health service utilization among Alzheimer's disease patients: evidence from managed care.

BACKGROUND: The objective of this study was to assess the disease burden of Alzheimer's disease (AD) in a commercial managed care setting by comparing direct health care costs and adverse event outcomes between patients with AD and without AD. METHODS: The study design used eligibility, medical, and pharmacy claims data from a large, national, geographically diverse, fee-for-service U.S. managed health plan. Commercially insured patients aged 65 years and older with a pharmacy benefit with evidence of AD (n = 4,450) and a control group without AD (n = 13,650) were matched by age, gender, plan location, and length of enrollment. Adverse event outcomes, comorbid conditions, and annualized health care costs were compared. Incremental costs were calculated by using a two-part model to estimate the burden of illness; incremental cost confidence intervals were estimated by bootstrap analysis. RESULTS: Patients with AD had generally higher health care costs and higher risk of acute adverse outcomes than the control cohort. Annual adjusted total health care costs per patient were approximately $1,418 greater for the AD cohort. Patients with AD had an unadjusted fracture risk of 14.6% versus 6.2% in the matched cohort and accidental injury/falls risk of 27.4% versus 11.4%. CONCLUSIONS: Few studies have examined the disease burden of AD in commercial managed care settings. Similar to results of comparative studies with Medicare data, the disease burden is greater for patients with AD compared with a matched control cohort, with a different mix and a greater number of comorbid health care conditions partially accounting for this difference. As membership in commercial and Medicare managed care plans increases, plans will need to develop effective mechanisms to manage the health care of high-risk, high-cost patients with AD.

Utilization and cost of health care services associated with primary malignant brain tumors in the United States.

OBJECTIVES: To evaluate the economic burden of primary malignant brain tumors in a commercially insured population in the United States, and to identify the primary drivers of health care resource use and cost. PATIENTS AND METHODS: A retrospective cohort analysis was performed using a 1998-2000 database containing inpatient, outpatient, and pharmacy claims for employees, their dependents, and early retirees of over 50 large US employers with wide geographic distribution. Patients were followed from first brain tumor diagnosis until death, termination of health benefits coverage, or study end. Controls without any cancer diagnosis were matched at a 3:1 ratio by demographic characteristics and length of follow-up. RESULTS: Patients with malignant brain tumors (n = 653) had significantly greater health service utilization and costs for hospitalizations, emergency room visits, outpatient office visits, laboratory tests, radiology services, and pharmacy-dispensed drugs (all P < 0.05) than did controls (n = 1959). Regression-adjusted mean monthly costs were $6364 for brain tumor patients, compared with $277 for controls (P < 0.0001). The primary cost driver was inpatient care ($4502 per month). Total costs during the study period were $49,242 for those with brain tumors and $2790 for controls (P < 0.0001). CONCLUSION: Patients with malignant brain tumors accrued health care costs that were 20 times greater than demographically matched control subjects without cancer. The costs for inpatient services were the primary drivers of total health resource use. Despite their low incidence, primary malignant brain tumors produce a substantial burden on the US health care system. There is a marked need for improved and new approaches to treatment to reduce the resource use and to offset health care costs associated with this disease.

Medical costs associated with non-Hodgkin's lymphoma in the United States during the first two years of treatment.

OBJECTIVES: To determine the direct costs of medical care associated with aggressive and indolent non-Hodgkin's lymphoma (NHL) in the United States; to show how costs for aggressive NHL change over time by examining costs related to initial, secondary and palliative treatment phases; and to evaluate the economic consequences of treatment failure in aggressive NHL. PATIENTS AND METHODS: A retrospective cohort analysis of 1999 - 2000 direct costs in newly diagnosed NHL patients and controls (subjects without any cancer) was conducted using the MarketScan medical and drug claims database of large employers across the United States. Treatment failure analysis was conducted for aggressive NHL patients, and was defined by the need for secondary treatment or palliative care after initial therapy. Cost of treatment failure was calculated as difference in regression-adjusted costs between patients with initial therapy only and patients experiencing initial treatment failure. RESULTS: Patients with aggressive (n = 356) and indolent (n = 698) NHL had significantly greater health service utilization and associated costs (all P < 05) than controls (n = 1068 for aggressive, n = 2094 for indolent). Mean monthly costs were 5871 dollars for aggressive NHL vs. 355 dollars for controls (P < 0001) and 3833 dollars for indolent NHL vs. 289 dollars for controls (P < 0001). The primary cost drivers were hospitalization (aggressive NHL = 44% of total costs, indolent NHL = 50%) and outpatient office visits (aggressive NHL = 39%, indolent NHL = 34%). For aggressive NHL, mean monthly initial treatment phase costs (10,970 dollars) and palliative care costs (9836 dollars) were higher than costs incurred during secondary phase (3302 dollars). The mean cost of treatment failure in aggressive NHL was 14,174 dollars per month, and 85,934 dollars over the study period. CONCLUSION: The treatment of NHL was associated with substantial health care costs. Patients with aggressive lymphomas tended to accrue higher costs, compared with those with indolent lymphomas. These costs varied over time, with the highest costs occurring during the initial treatment and palliative care phases. Treatment failure was the most expensive treatment pattern. New strategies to prevent or delay treatment failure in aggressive NHL could help reduce the economic burden of NHL.

Burden of pancreatic cancer and disease progression: economic analysis in the US.

OBJECTIVES: The few studies that have estimated the costs of pancreatic cancer were limited by small sample sizes, geography or patient age range. Using a large nationwide claims database, this study examines the cost of pancreatic cancer beginning with initial diagnosis and the additional costs when disease progresses. METHODS: A retrospective cohort study was conducted using a claims database of 3 million individuals covered by large US employers. The study population consisted of patients newly diagnosed with pancreatic cancer in 1999-2000 and a demographically matched control group. Utilization and costs were summarized as monthly means. Changes in cancer severity and treatment over time were used to approximate disease progression and its associated costs. RESULTS: The study included 412 pancreatic cancer patients and 1,236 controls. The mean follow-up time was 7.5 months. Regression-adjusted monthly costs attributable to pancreatic cancer were USD 7,279; over 60% resulted from hospitalizations. Patients with disease progression (over 50%) incurred an additional USD 15,143 per month compared to patients without disease progression. CONCLUSION: Compared to patients without cancer, the costs of pancreatic cancer patients were substantial, especially when patients experienced disease progression. New therapies that prevent or delay disease progression could potentially offset the costs to patients, providers and society.

The cost of treating anxiety: the medical and demographic correlates that impact total medical costs.

The purpose of this retrospective, multivariate analysis is to examine how medical conditions and demographic characteristics affect the costs of treating individuals diagnosed with anxiety. Data from MarketScan Databases [The MEDSTAT Group, 2000] were used to identify individuals with new episodes of anxiety. Multivariate analysis was used, with the dependent variable being the log of total medical costs. This analysis controlled for demographic characteristics, medical comorbidities, anxiety diagnosis, and prior resource utilization. A smearing estimate is used to calculate the total medical costs for patients with any anxiety disorder. The mean estimated total medical cost for individuals diagnosed with any anxiety disorder was $6,475. The multivariate model indicates that controlling for demographics and other disease states, generalized anxiety disorder (GAD), panic disorders, and posttraumatic stress disorder (PTSD) are associated with a $2,138, $1,603, and $3,940 increase, respectively, in the total medical cost (P < .0001). The incremental impact of depression, other anxiety disorders, and prior mental health diagnoses on the total medical costs were $1,945, $1,900, and $1,515, respectively (P < .0001). Individuals with the highest costs, and therefore the greatest need for intervention, are anxious patients with depression, individuals diagnosed with PTSD or GAD, and individuals diagnosed with both anxiety and a comorbid medical condition such as an acute myocardial infarction or diabetes.