Survival Modeling for the Estimation of Transition Probabilities in Model-Based Economic Evaluations in the Absence of Individual Patient Data: A Tutorial

Diaby, Vakaramoko; Adunlin, Georges; Montero, Alberto J.

doi:10.1007/s40273-013-0123-9

Cited by 110 publications

(78 citation statements)

References 11 publications

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“…Using the final PFS Kaplan–Meier curves of the BOLERO-2 trial, survival modeling techniques were applied to determine transition probabilities from stable (with or without adverse events) to progression-free states [9]. This application consisted in (i) reconstructing individual patient data (IPD) based on published final PFS Kaplan–Meier curves of the BOLERO-2 trial, (ii) fitting parametric distributions to reconstructed data, and (iii) estimating transition probabilities for Markov modeling.…”

Section: Methodsmentioning

confidence: 99%

“…The formula for transition probabilities for treatment arm 0 (exemestane alone) and 1 (everolimus plus exemestane) was represented by Eqs. 1 and 2, respectively [9]. …”

Section: Methodsmentioning

confidence: 99%

“…The value 0.030142 is the scale of the distribution for treatment arm 1 (λ 1 ). The value 0.6187177 is the shape of the distribution for treatment arm 0 (γ 1 ) [9]. More details can be obtained from the published tutorial [9].…”

Section: Methodsmentioning

confidence: 99%

“…The value 0.6187177 is the shape of the distribution for treatment arm 0 (γ 1 ) [9]. More details can be obtained from the published tutorial [9]. Transition probabilities from stable without adverse events to stable with adverse events states were obtained directly from the BOLERO-2 trial [7].…”

Section: Methodsmentioning

confidence: 99%

See 3 more Smart Citations

Cost-effectiveness analysis of everolimus plus exemestane versus exemestane alone for treatment of hormone receptor positive metastatic breast cancer

Diaby

Adunlin

Zeichner

et al. 2014

Breast Cancer Res Treat

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Everolimus in combination with exemestane significantly improved progression-free survival compared to exemestane alone in patients previously treated with non-steroidal aromatase inhibitors in the BOLERO-2 trial. As a result, this combination has been approved by the food and drug administration to treat postmenopausal women with hormone receptor positive and HER2 negative metastatic breast cancer. A cost-effectiveness analysis was conducted to determine whether everolimus represents good value for money, utilizing data from BOLERO-2. A decision-analytic model was used to estimate the incremental cost-effectiveness ratio between treatment arms of the BOLERO-2 trial. Costs were obtained from the Center for Medicare Services drug payment table and physician fee schedule. Benefits were expressed as quality-adjusted progression-free survival weeks (QAPFW) and quality-adjusted progression-free years (QAPFY), with utilities/disutilities derived from the literature. Deterministic and probabilistic sensitivity analyses were performed. A willingness to pay threshold of 1–3 times the per capita gross domestic product was adopted, as per the definition of the World Health Organization. The U.S. per capita gross domestic product in 2013 was $49,965; thus, a threshold varying between $49,965 and $149,895 was considered. Everolimus/exemestane had an incremental benefit of 11.88 QAPFW (0.22 QAPFY) compared to exemestane and an incremental cost of $60,574. This translated into an ICER of $265,498.5/QAPFY. Univariate sensitivity analyses showed important variations of the ICER, ranging between $189,836.4 and $530,947/QAPFY. A tornado analysis suggested that the key drivers of our model, by order of importance, included health utility value for stable disease, everolimus acquisition costs, and transition probabilities from the stable to the progression states. The Monte-Carlo simulation showed results that were similar to the base-case analysis. This cost-effectiveness analysis showed that everolimus plus exemestane is not cost-effective compared to exemestane alone. Further research is needed to investigate the cost-effectiveness of the drug combination within sub-groups of the population studied in BOLERO-2.

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Section: Methodsmentioning

confidence: 99%

“…The formula for transition probabilities for treatment arm 0 (exemestane alone) and 1 (everolimus plus exemestane) was represented by Eqs. 1 and 2, respectively [9]. …”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Cost-effectiveness analysis of everolimus plus exemestane versus exemestane alone for treatment of hormone receptor positive metastatic breast cancer

Diaby

Adunlin

Zeichner

et al. 2014

Breast Cancer Res Treat

Self Cite

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“…In order to overcome this problem, we manually determined the final parameter estimates by visually comparing the model predicted curves with the Kaplan-Meier plots for OS presented in the original article. 16) Some previous reports used a method of computer digitization to extract the numeric data from Kaplan-Meier plots, 29,30) or another report 31) obtained the values for hazard rate based only on median OS values without performing a curve fitting under such a limited situation. Although our method to visually determine the parameters may cause some biases in the modeling results, our present method is one alternative way to reproducibly obtain the model predicted survival curves when the data available from literature are limited.…”

Section: Discussionmentioning

confidence: 99%

Time-Series Modeling and Simulation for Comparative Cost-Effective Analysis in Cancer Chemotherapy: An Application to Platinum-Based Regimens for Advanced Non-small Cell Lung Cancer

Chisaki

Nakamura

Yano

2017

Biological & Pharmaceutical Bulletin

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The purpose of this study was to propose a time-series modeling and simulation (M&S) strategy for probabilistic cost-effective analysis in cancer chemotherapy using a Monte-Carlo method based on data available from the literature. The simulation included the cost for chemotherapy, for pharmaceutical care for adverse events (AEs) and other medical costs. As an application example, we describe the analysis for the comparison of four regimens, cisplatin plus irinotecan, carboplatin plus paclitaxel, cisplatin plus gemcitabine (GP), and cisplatin plus vinorelbine, for advanced non-small cell lung cancer. The factors, drug efficacy explained by overall survival or time to treatment failure, frequency and severity of AEs, utility value of AEs to determine QOL, the drugs' and other medical costs in Japan, were included in the model. The simulation was performed and quality adjusted life years (QALY) and incremental cost-effectiveness ratios (ICER) were calculated. An index, percentage of superiority (%SUP) which is the rate of the increased cost vs. QALYgained plots within the area of positive QALY-gained and also below some threshold values of the ICER, was calculated as functions of threshold values of the ICER. An M&S process was developed, and for the simulation example, the GP regimen was the most cost-effective, in case of threshold values of the ICER $70000/ year, the %SUP for the GP are more than 50%. We developed an M&S process for probabilistic cost-effective analysis, this method would be useful for decision-making in choosing a cancer chemotherapy regimen in terms of pharmacoeconomic.Key words pharmacoeconomic; cost-effectiveness; cancer chemotherapy; Monte Carlo simulation; modeling and simulation; non-small cell lung cancer In cancer chemotherapy, an important concern for patients is the efficacy of treatment, usually expressed by indices such as survival time and performance status. The high cost of cancer chemotherapy is a burden for both patients and the national economy; for example, the total cost of cancer therapy in the United States reported by National Cancer Institute (NCI) was $157 billion in 2010.1) It has also been reported that these costs may increase at a faster rate than overall medical expenditure 2) because new targeted anticancer therapies such as monoclonal antibodies and small-molecule inhibitors will be adopted as standard therapies, and therefore, more efficient but more expensive therapies will be used.A concept of pharmacoeconomics has been applied to a clinical pharmacy practice, 3,4) and a health care evaluation. 5)Several types of cost-effective analyses have been performed for choosing the optimal chemotherapy regimens for cancer patients. [6][7][8] The objectives of these cost-effective analyses were to compare two or more regimens from the viewpoint of increasing cost per increasing efficacy. From a pharmaceutical viewpoint, in order to choose the optimal regimen that provides the best cost-effective ratio, information regarding both treatments' efficacy and the frequency an...

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Evaluation of the Cost-effectiveness of Doublet Therapy in MetastaticBRAFVariant Colorectal Cancer

et al. 2021

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IMPORTANCEThe BEACON trial showed that combination therapy with encorafenib (BRAF inhibitor) and cetuximab (EGFR inhibitor) was associated with prolonged overall survival compared with standard chemotherapy in patients with metastatic BRAF variant colorectal cancer. However, the cost-effectiveness of using these agents in this clinical setting is unknown. OBJECTIVETo create a cost-effectiveness model to compare doublet therapy (encorafenib plus cetuximab) with standard chemotherapy (cetuximab plus irinotecan or cetuximab plus folinic acid, fluorouracil, and irinotecan) in treating patients with metastatic BRAF variant colorectal cancer. DESIGN, SETTING, AND PARTICIPANTS This economic evaluation constructed a Markov model to compare the lifetime cost and utility of doublet therapy and standard chemotherapy. Parametric survival modeling was used to extrapolate the effectiveness of each line of therapy from large clinical trials. One-way and probabilistic sensitivity analyses assessed the uncertainty in the model. Patients mirrored the cohorts in the BEACON trial: they had metastatic BRAF variant colorectal cancer and were followed up as they progressed through multiple lines of therapy, best supportive care, and death. Data collection and data analysis were performed from November 15, 2019, to July 14, 2020. MAIN OUTCOMES AND MEASURESThe main outcome was the incremental cost-effectiveness ratio, which was calculated using the cumulative cost and effectiveness in quality-adjusted life years (QALYs), of doublet therapy compared with standard chemotherapy. RESULTSThe model patient cohort had a mean age of 61 years, and 53% of the patients were women, 66% had 1 previous line of therapy, and 8% had high microsatellite instability. Doublet therapy was associated with an improvement of 0.15 QALYs compared with standard chemotherapy.

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Survival Modeling for the Estimation of Transition Probabilities in Model-Based Economic Evaluations in the Absence of Individual Patient Data: A Tutorial

Cited by 110 publications

References 11 publications

Cost-effectiveness analysis of everolimus plus exemestane versus exemestane alone for treatment of hormone receptor positive metastatic breast cancer

Cost-effectiveness analysis of everolimus plus exemestane versus exemestane alone for treatment of hormone receptor positive metastatic breast cancer

Time-Series Modeling and Simulation for Comparative Cost-Effective Analysis in Cancer Chemotherapy: An Application to Platinum-Based Regimens for Advanced Non-small Cell Lung Cancer

Evaluation of the Cost-effectiveness of Doublet Therapy in MetastaticBRAFVariant Colorectal Cancer

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