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Introduction While no direct comparative data exist for crizotinib in ROS1+ non-small cell lung cancer (NSCLC), studies have suggested clinical benefit with this targeted agent. The objective of this study was to assess the cost-effectiveness of crizotinib compared to standard platinum-doublet chemotherapy for first-line treatment of ROS1+ advanced NSCLC. Methods A Markov model was developed with a 10-year time horizon from the perspective of the Canadian publicly-funded health care system. Health states included progression-free survival (PFS), up to two further lines of therapy post-progression, palliation and death. Given a lack of comparative data and small study samples, crizotinib or chemotherapy studies with advanced ROS1+ NSCLC patients were identified and time-to-event data from digitized Kaplan-Meier curves were collected to pool PFS data. Costs of drugs, treatment administration, monitoring, adverse events and palliative care were included in 2018 Canadian dollars, with 1.5% discounting. An incremental cost-effectiveness ratio (ICER) was estimated probabilistically using 5000 simulations. Results In the base-case probabilistic analysis, crizotinib produced additional 0.885 life-years and 0.772 quality-adjusted life-years (QALYs) at an incremental cost of $238,077, producing an ICER of $273,286/QALY gained. No simulations were found to be cost-effective at a willingness-to-pay threshold of $100,000/QALY gained. A scenario analysis assuming efficacy equivalent to the ALK+ NSCLC population showed a slightly more favorable cost-effectiveness profile for crizotinib. Conclusions Available data appear to support superior activity of crizotinib compared to chemotherapy in ROS1+ advanced NSCLC. At the list price, crizotinib was not cost-effective at commonly accepted willingness-to-pay thresholds across a wide range of sensitivity analyses.

Background For novel cancer treatments, effectiveness in clinical practice is not always aligned with clinical efficacy results. As such it is important to understand a treatment’s real-world effectiveness. We examined real-world population-based comparative effectiveness of second-line ipilimumab versus non-ipilimumab treatments (chemotherapy or targeted treatments). Methods We used a cohort of melanoma patients receiving systemic treatment for advanced disease since April 2005 from Ontario, Canada. Patients were identified from provincial drug databases and the Ontario Cancer Registry who received second-line ipilimumab from 2012 to 2015 (treated) or second-line non-ipilimumab treatment prior to 2012 (historical controls). Historical controls were chosen, to permit the most direct comparison to pivotal trial findings. The cohort was linked to administrative databases to identify baseline characteristics and outcomes. Kaplan-Meier curves and multivariable Cox regression models were used to assess overall survival (OS). Observed potential confounders were adjusted for using inverse probability of treatment weighting (IPTW). Results We identified 329 patients with metastatic melanoma (MM) who had received second-line treatments (189 treated; 140 controls). Patients receiving second-line ipilimumab were older (61.7 years vs 55.2 years) compared to historical controls. Median OS were 6.9 (95% CI: 5.4–8.3) and 4.95 (4.3–6.0) months for ipilimumab and controls, respectively. The crude 1-year, 2-year, and 3-year OS probabilities were 34.3% (27–41%), 20.6% (15–27%), and 15.2% (9.6–21%) for ipilimumab and 17.1% (11–23%), 7.1% (2.9–11%), and 4.7% (1.2–8.2%) for controls. Ipilimumab was associated with improved OS (IPTW HR = 0.62; 95% CI: 0.49–0.78; p Conclusions This real-world analysis suggests second-line ipilimumab is associated with an improvement in OS for MM patients in routine practice.

In evaluating new oncology medicines, two common modeling approaches are state transition (e.g., Markov and semi-Markov) and partitioned survival. Partitioned survival models have become more prominent in oncology health technology assessment processes in recent years. Our experience in conducting and evaluating models for economic evaluation has highlighted many important and practical pitfalls. As there is little guidance available on best practices for those who wish to conduct them, we provide guidance in the form of 'Key steps for busy analysts,' who may have very little time and require highly favorable results. Our guidance highlights the continued need for rigorous conduct and transparent reporting of economic evaluations regardless of the modeling approach taken, and the importance of modeling that better reflects reality, which includes better approaches to considering plausibility, estimating relative treatment effects, dealing with post-progression effects, and appropriate characterization of the uncertainty from modeling itself.

PharmacoEconomics DOI 10.1007/s40273-015-0278-7 LETTER TO THE EDITOR Does it Matter Whether Canada’s Separate Health Technology Assessment Process for Cancer Drugs has an Economic Rationale? Jeffrey S. Hoch 1,2,3,4 • Jaclyn Beca 1,2,3 • Mona Sabharwal 5 • Scott W. Livingstone 6 Anthony L. A. Fields 7 The Author(s) 2015. This article is published with open access at Springerlink.com ‘‘What our health-care systems need to do with their limited budgets is maximize value and no dimensions of health … will be a good measure of value because people consider other aspects in their evaluations … We must back out of the dead end that is pursuing overall efficiency’’ [1]. 1 Introduction We are grateful for the opportunity to comment on the results of McDonald et al. [2]. In this note, we summarize their findings, build on their interpretations, and suggest future directions for researchers interested in improving a health technology assessment (HTA) process. 2 Summary of the Findings McDonald et al. searched for reasons why Canada and other countries might separate their cancer drug HTA process. They appraised whether any of the rationales they & Jeffrey S. Hoch jeffrey.hoch@utoronto.ca Pharmacoeconomics Research Unit, Cancer Care Ontario, Toronto, ON, Canada Jaclyn Beca becaj@smh.ca Canadian Centre for Applied Research in Cancer Control (ARCC), Toronto, ON, Canada Mona Sabharwal monas@cadth.ca Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada Scott W. Livingstone scott.livingstone@saskcancer.ca Pan-Canadian Oncology Drug Review (pCODR), Canadian Agency for Drugs and Technologies in Health (CADTH), Toronto, ON, Canada Saskatchewan Cancer Agency, Saskatoon, SK, Canada University of Alberta, 11560 University Ave NW, Edmonton, AB T6G 1Z2, Canada Anthony L. A. Fields afields@ualberta.ca found were derived from the assumption commonly made by health economists that ‘‘the goal of society or decision makers is to maximize the total aggregate health benefit conferred to a population for a given level of resources’’. They found that this rationale was not used by Canada or any country to support the use of a separate HTA process for cancer drugs. The researchers were also not able to find another country besides Canada that had a separate cancer drug HTA process. These findings may seem surprising: Canada is the only country in the world that has a separate cancer drug HTA process; and McDonald et al. could find no justification based in economic theory for a separate process. To be clear, the authors reported that other countries (e.g. Den- mark, Belgium, the UK) set aside a separate budget for cancer drugs, and the authors found several ‘‘non-eco- nomic’’ rationales for Canada’s separate HTA process. There are two potential interpretations of these search re- sults: (1) the search missed something or (2) there really is no economic rationale in print for a separate cancer drug HTA process. Although their study might not be Centre for Excellence in Economic Analysis Research (CLEAR), Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON, Canada

Cost-effectiveness evidence is increasingly considered in the reimbursement decisions of pharmaceuticals. In some jurisdictions such as the UK and Canada, pharmaceutical manufacturers are required to submit economic evaluations when seeking reimbursement. Our objectives were to describe the role of economic evidence in the cancer drug review process in Canada, and to investigate the nature of problems encountered in the review and interpretation of economic evidence used in the process. We conducted a retrospective review of cancer drug review meeting minutes and reviewers’ comments on pharmacoeconomic studies submitted to the oncology drug review process in Canada. We used pharmacoeconomic reviewers’ reports and relevant cancer drug review expert advisory committee meeting minutes during the first year of the review process (April 2007 to March 2008). Fifteen economic submissions were reviewed. One-third of the studies had flaws significant enough that the advisory committee could not determine the cost effectiveness of the drugs from the results. The common issues outlined by the reviewers and committee were related to the uncertainty of comparative clinical benefits, quality of life and costs. The reviewers felt that few analyses provided sufficient sensitivity analyses around key variables to assess the robustness of results. Most problems identified by reviewers are simple to fix and do not involve advanced methods. Canada has a separate review process for making cancer drug funding recommendations, and this process uses both clinical and economic evidence. The committee could not determine the value for money of the drugs from several of the submitted pharmacoeconomic analyses. Transparent analyses and detailed critique of evidence are crucial to the use of economic evidence in reimbursement decisions. Rigorous evaluation is resource intensive and may benefit from a shared drug review process among several jurisdictions.