Yushen Qian1, Satoshi Maruyama1, Haju Kim1, Erqi L Pollom1, Kiran A Kumar1, Alexander L Chin1, Jeremy P Harris1, Daniel T Chang1, Allison Pitt1, Eran Bendavid1, Douglas K Owens1, Ben Y Durkee1, Scott G Soltys1. 1. Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California; Department of Health Research and Policy, Stanford University, Stanford, California; Division of Management Science and Engineering, Department of Engineering, Stanford University, Stanford, California; VA Palo Alto Health Care System, and Center for Primary Care and Outcomes Research/Center for Health Policy, Department of Medicine, Stanford University, Stanford, California; Swedish American Hospital, a division of the University of Wisconsin, Rockford, Illinois.
Abstract
BACKGROUND: The addition of procarbazine, lomustine, vincristine (PCV) chemotherapy to radiotherapy (RT) for patients with high-risk (≥40 y old or subtotally resected) low-grade glioma (LGG) results in an absolute median survival benefit of over 5 years. We evaluated the cost-effectiveness of this treatment strategy. METHODS: A decision tree with an integrated 3-state Markov model was created to follow patients with high-risk LGG after surgery treated with RT versus RT+PCV. Patients existed in one of 3 health states: stable, progressive, or dead. Survival and freedom from progression were modeled to reflect the results of RTOG 9802 using time-dependent transition probabilities. Health utility values and costs of care were derived from the literature and national registry databases. Analysis was conducted from the health care perspective. Deterministic and probabilistic sensitivity analysis explored uncertainty in model parameters. RESULTS: Modeled outcomes demonstrated agreement with clinical data in expected benefit of addition of PCV to RT. The addition of PCV to RT yielded an incremental benefit of 4.77 quality-adjusted life-years (QALYs) (9.94 for RT+PCV vs 5.17 for RT alone) at an incremental cost of $48635 ($188234 for RT+PCV vs $139598 for RT alone), resulting in an incremental cost-effectiveness ratio of $10186 per QALY gained. Probabilistic sensitivity analysis demonstrates that within modeled distributions of parameters, RT+PCV has 99.96% probability of being cost-effectiveness at a willingness-to-pay threshold of $100000 per QALY. CONCLUSION: The addition of PCV to RT is a cost-effective treatment strategy for patients with high-risk LGG.
BACKGROUND: The addition of procarbazine, lomustine, vincristine (PCV) chemotherapy to radiotherapy (RT) for patients with high-risk (≥40 y old or subtotally resected) low-grade glioma (LGG) results in an absolute median survival benefit of over 5 years. We evaluated the cost-effectiveness of this treatment strategy. METHODS: A decision tree with an integrated 3-state Markov model was created to follow patients with high-risk LGG after surgery treated with RT versus RT+PCV. Patients existed in one of 3 health states: stable, progressive, or dead. Survival and freedom from progression were modeled to reflect the results of RTOG 9802 using time-dependent transition probabilities. Health utility values and costs of care were derived from the literature and national registry databases. Analysis was conducted from the health care perspective. Deterministic and probabilistic sensitivity analysis explored uncertainty in model parameters. RESULTS: Modeled outcomes demonstrated agreement with clinical data in expected benefit of addition of PCV to RT. The addition of PCV to RT yielded an incremental benefit of 4.77 quality-adjusted life-years (QALYs) (9.94 for RT+PCV vs 5.17 for RT alone) at an incremental cost of $48635 ($188234 for RT+PCV vs $139598 for RT alone), resulting in an incremental cost-effectiveness ratio of $10186 per QALY gained. Probabilistic sensitivity analysis demonstrates that within modeled distributions of parameters, RT+PCV has 99.96% probability of being cost-effectiveness at a willingness-to-pay threshold of $100000 per QALY. CONCLUSION: The addition of PCV to RT is a cost-effective treatment strategy for patients with high-risk LGG.
Authors: Christina K Speirs; Joseph R Simpson; Clifford G Robinson; Todd A DeWees; David D Tran; Gerry Linette; Michael R Chicoine; Ralph G Dacey; Keith M Rich; Joshua L Dowling; Eric C Leuthardt; Gregory J Zipfel; Albert H Kim; Jiayi Huang Journal: Int J Radiat Oncol Biol Phys Date: 2015-02-01 Impact factor: 7.038
Authors: Edward G Shaw; Meihua Wang; Stephen W Coons; David G Brachman; Jan C Buckner; Keith J Stelzer; Geoffrey R Barger; Paul D Brown; Mark R Gilbert; Minesh P Mehta Journal: J Clin Oncol Date: 2012-07-30 Impact factor: 44.544
Authors: David M Eddy; William Hollingworth; J Jaime Caro; Joel Tsevat; Kathryn M McDonald; John B Wong Journal: Med Decis Making Date: 2012 Sep-Oct Impact factor: 2.583
Authors: David B Altshuler; Padma Kadiyala; Felipe J Nuñez; Fernando M Nuñez; Stephen Carney; Mahmoud S Alghamri; Maria B Garcia-Fabiani; Antonela S Asad; Alejandro J Nicola Candia; Marianela Candolfi; Joerg Lahann; James J Moon; Anna Schwendeman; Pedro R Lowenstein; Maria G Castro Journal: Expert Opin Biol Ther Date: 2020-01-20 Impact factor: 4.388
Authors: Peter Abraham; Reith Sarkar; Michael G Brandel; Arvin R Wali; Robert C Rennert; Christian Lopez Ramos; Jennifer Padwal; Jeffrey A Steinberg; David R Santiago-Dieppa; Vincent Cheung; J Scott Pannell; James D Murphy; Alexander A Khalessi Journal: Radiology Date: 2019-03-26 Impact factor: 29.146