Geriatric assessment-identified deficits in older cancer patients with normal performance status.

BACKGROUND: We investigated whether a brief geriatric assessment (GA) would identify important patient deficits that could affect treatment tolerance and care outcomes within a sample of older cancer patients rated as functionally normal (80%-100%) on the Karnofsky performance status (KPS) scale. METHODS: Cancer patients aged ≥65 years were assessed using a brief GA that included both professionally and patient-scored KPS and measures of comorbidity, polypharmacy, cognition, function, nutrition, and psychosocial status. Data were analyzed using descriptive statistics and multivariable logistic regression. RESULTS: The sample included 984 patients: mean age was 73 years (range: 65-99 years), 74% were female, and 89% were white. GA was conducted before (23%), during (41%), or after (36%) treatment. Overall, 54% had a breast cancer diagnosis (n = 528), and 46% (n = 456) had cancers at other sites. Moreover, 81% of participants (n = 796) had both professionally and self-rated KPS ≥80, defined as functionally normal, and those patients are the focus of analysis. In this subsample, 550 (69%) had at least 1 GA-identified deficit, 222 (28%) had 1 deficit, 140 (18%) had 2 deficits, and 188 (24%) had ≥3 deficits. Specifically, 43% reported taking ≥9 medications daily, 28% had decreased social activity, 25% had ≥4 comorbidities, 23% had ≥1 impairment in instrumental activities of daily living, 18% had a Timed Up and Go time ≥14 seconds, 18% had ≥5% unintentional weight loss, and 12% had a Mental Health Index score ≤76. CONCLUSION: Within this sample of older cancer patients who were rated as functionally normal by KPS, GA identified important deficits that could affect treatment tolerance and outcomes.

Genotype-guided tamoxifen dosing increases active metabolite exposure in women with reduced CYP2D6 metabolism: a multicenter study.

PURPOSE: We examined the feasibility of using CYP2D6 genotyping to determine optimal tamoxifen dose and investigated whether the key active tamoxifen metabolite, endoxifen, could be increased by genotype-guided tamoxifen dosing in patients with intermediate CYP2D6 metabolism. PATIENTS AND METHODS: One hundred nineteen patients on tamoxifen 20 mg daily ≥ 4 months and not on any strong CYP2D6 inhibiting medications were assayed for CYP2D6 genotype and plasma tamoxifen metabolite concentrations. Patients found to be CYP2D6 extensive metabolizers (EM) remained on 20 mg and those found to be intermediate (IM) or poor (PM) metabolizers were increased to 40 mg daily. Eighty-nine evaluable patients had tamoxifen metabolite measurements repeated 4 months later. RESULTS: As expected, the median baseline endoxifen concentration was higher in EM (34.3 ng/mL) compared with either IM (18.5 ng/mL; P = .0045) or PM (4.2 ng/mL; P < .001). When the dose was increased from 20 mg to 40 mg in IM and PM patients, the endoxifen concentration rose significantly; in IM there was a median intrapatient change from baseline of +7.6 ng/mL (-0.6 to 23.9; P < .001), and in PM there was a change of +6.1 ng/mL (2.6 to 12.5; P = .020). After the dose increase, there was no longer a significant difference in endoxifen concentrations between EM and IM patients (P = .84); however, the PM endoxifen concentration was still significantly lower. CONCLUSION: This study demonstrates the feasibility of genotype-driven tamoxifen dosing and demonstrates that doubling the tamoxifen dose can increase endoxifen concentrations in IM and PM patients.

A Markov model assessing the effectiveness and cost-effectiveness of FOLFOX compared with FOLFIRI for the initial treatment of metastatic colorectal cancer.

OBJECTIVE: To analyze the efficacy and cost-effectiveness of FOLFOX compared with FOLFIRI for patients with metastatic colorectal cancer. METHOD: We developed a Markov decision model using a hypothetical cohort of patients with metastatic colorectal cancer to compare beginning chemotherapy with FOLFOX or FOLFIRI. Probabilities of toxicities, including neutropenia, diarrhea, and neuropathy, were based on published literature for FOLFOX and FOLFIRI. Costs for physician and hospital services unadjusted for geographic location were estimated using Centers for Medicare and Medicaid services reimbursement data. Drug costs were estimated using Medicare B reimbursement and the Federal Supply Schedule. Health outcomes were measured in quality-adjusted life years (QALYs). Univariate and probabilistic sensitivity analyses were performed to address uncertainty in the model parameters. RESULTS: The FOLFOX strategy provided 1.003 QALYs at a cost of $29,865, whereas FOLFIRI provided 0.921 QALYs at a cost of $24,551. The incremental cost-effectiveness ratio for FOLFOX treatment was $65,170/QALY. In 10,000 probabilistic Monte Carlo simulations, FOLFOX was cost-effective in 48.59% of trials using a $50,000/QALY threshold. The most influential variables in univariate sensitivity analysis were the expected years of survival associated with each chemotherapy regimen. CONCLUSIONS: FOLFOX and FOLFIRI are similar in terms of costs and benefits. The slight QALY benefits associated with FOLFOX are within the range of $100,000/QALY, an accepted threshold in oncology.

Cost-effectiveness of MRI compared to mammography for breast cancer screening in a high risk population.

BACKGROUND: Breast magnetic resonance imaging (MRI) is a sensitive method of breast imaging virtually uninfluenced by breast density. Because of the improved sensitivity, breast MRI is increasingly being used for detection of breast cancer among high risk young women. However, the specificity of breast MRI is variable and costs are high. The purpose of this study was to determine if breast MRI is a cost-effective approach for the detection of breast cancer among young women at high risk. METHODS: A Markov model was created to compare annual breast cancer screening over 25 years with either breast MRI or mammography among young women at high risk. Data from published studies provided probabilities for the model including sensitivity and specificity of each screening strategy. Costs were based on Medicare reimbursement rates for hospital and physician services while medication costs were obtained from the Federal Supply Scale. Utilities from the literature were applied to each health outcome in the model including a disutility for the temporary health state following breast biopsy for a false positive test result. All costs and benefits were discounted at 5% per year. The analysis was performed from the payer perspective with results reported in 2006 U.S. dollars. Univariate and probabilistic sensitivity analyses addressed uncertainty in all model parameters. RESULTS: Breast MRI provided 14.1 discounted quality-adjusted life-years (QALYs) at a discounted cost of $18,167 while mammography provided 14.0 QALYs at a cost of $4,760 over 25 years of screening. The incremental cost-effectiveness ratio of breast MRI compared to mammography was $179,599/QALY. In univariate analysis, breast MRI screening became < $50,000/QALY when the cost of the MRI was < $315. In the probabilistic sensitivity analysis, MRI screening produced a net health benefit of -0.202 QALYs (95% central range: -0.767 QALYs to +0.439 QALYs) compared to mammography at a willingness-to-pay threshold of $50,000/QALY. Breast MRI screening was superior in 0%, < $50,000/QALY in 22%, > $50,000/QALY in 34%, and inferior in 44% of trials. CONCLUSION: Although breast MRI may provide health benefits when compared to mammographic screening for some high risk women, it does not appear to be cost-effective even at willingness to pay thresholds above $120,000/QALY.

Development of query strategies to identify a histologic lymphoma subtype in a large linked database system.

BACKGROUND: Large linked databases (LLDB) represent a novel resource for cancer outcomes research. However, accurate means of identifying a patient population of interest within these LLDBs can be challenging. Our research group developed a fully integrated platform that provides a means of combining independent legacy databases into a single cancer-focused LLDB system. We compared the sensitivity and specificity of several SQL-based query strategies for identifying a histologic lymphoma subtype in this LLDB to determine the most accurate legacy data source for identifying a specific cancer patient population. METHODS: Query strategies were developed to identify patients with follicular lymphoma from a LLDB of cancer registry data, electronic medical records (EMR), laboratory, administrative, pharmacy, and other clinical data. Queries were performed using common diagnostic codes (ICD-9), cancer registry histology codes (ICD-O), and text searches of EMRs. We reviewed medical records and pathology reports to confirm each diagnosis and calculated the sensitivity and specificity for each query strategy. RESULTS: Together the queries identified 1538 potential cases of follicular lymphoma. Review of pathology and other medical reports confirmed 415 cases of follicular lymphoma, 300 pathology-verified and 115 verified from other medical reports. The query using ICD-O codes was highly specific (96%). Queries using text strings varied in sensitivity (range 7-92%) and specificity (range 86-99%). Queries using ICD-9 codes were both less sensitive (34-44%) and specific (35-87%). CONCLUSIONS: Queries of linked-cancer databases that include cancer registry data should utilize ICD-O codes or employ structured free-text searches to identify patient populations with a precise histologic diagnosis.

Practical approach for using Medicare data to estimate costs for cost-effectiveness analysis.

Many methods have been used to measure costs for cost-effectiveness analysis in healthcare. A central challenge in cost estimation is determining the direct cost of medical goods and services from a societal perspective. This review applies the methodology for calculating Medicare reimbursements for physician services, hospital services and medications as a means of estimating healthcare costs from a US societal perspective. This review provides the tools and information needed to calculate direct medical costs related to in- and outpatient services provided by physicians and hospitals, as well as drug costs using Medicare reimbursement data. The data used in calculating Medicare reimbursements was obtained from the Centers for Medicare and Medicaid Services website. Methods for estimating costs for a particular service in a specific location using Medicare and Medicaid Services are described and demonstrated. A method based on Medicare data that uses the unadjusted geographic practice cost index and standard hospital base rate to estimate healthcare costs that can be generalized to the US population is described and demonstrated. This review provides cost-effectiveness analysts with the tools needed to calculate healthcare service costs for economic research. It contains links to all websites needed for obtaining Medicare and Medicaid Services data and provides a step-by-step analysis of the methodology involved in calculating costs. A practical guide for applying the methodology used by Medicare and Medicaid Services to calculate direct medical costs in order to estimate US societal costs in cost-effectiveness analysis is provided.