| Literature DB >> 31101066 |
Howard L Kaufman1, Michael B Atkins2, Prasun Subedi3, James Wu4, James Chambers5, T Joseph Mattingly6, Jonathan D Campbell7, Jeff Allen8, Andrea E Ferris9, Richard L Schilsky10, Daniel Danielson11, J Leonard Lichtenfeld12, Linda House13, Wendy K D Selig14.
Abstract
The rapid development of immuno-oncology (I-O) therapies for multiple types of cancer has transformed the cancer treatment landscape and brightened the long-term outlook for many patients with advanced cancer. Responding to ongoing efforts to generate value assessments for novel therapies, multiple stakeholders have been considering the question of "What makes I-O transformative?" Evaluating the distinct features and attributes of these therapies, and better characterizing how patients experience them, will inform such assessments. This paper defines ways in which treatment with I-O is different from other therapies. It also proposes key aspects and attributes of I-O therapies that should be considered in any assessment of their value and seeks to address evidence gaps in existing value frameworks given the unique properties of patient outcomes with I-O therapy. The paper concludes with a "data needs catalogue" (DNC) predicated on the belief that multiple key, unique elements that are necessary to fully characterize the value of I-O therapies are not routinely or robustly measured in current clinical practice or reimbursement databases and are infrequently captured in existing research studies. A better characterization of the benefit of I-O treatment will allow a more thorough assessment of its benefits and provide a template for the design and prioritization of future clinical trials and a roadmap for healthcare insurers to optimize coverage for patients with cancers eligible for I-O therapy.Entities:
Keywords: Immuno-oncology; Immunotherapy; Patient experience; Patient reported outcomes (PROs); Value
Mesh:
Year: 2019 PMID: 31101066 PMCID: PMC6525438 DOI: 10.1186/s40425-019-0594-0
Source DB: PubMed Journal: J Immunother Cancer ISSN: 2051-1426 Impact factor: 13.751
Assessment of conventional value metrics in evaluating I-O therapies
| Conventional value metric (examples) | Why insufficent | Areas where new I-O value measures are needed |
|---|---|---|
Clinical Efficacy Assessment
| I-O therapies offer potential for durable response and due to delayed kinetics may not demonstrate early ORR or improvements in PFS | Milestone Survival; Treatment Free Survival |
| Safety Assessment | Late-stage cancer patients may be more willing to accept high risk of toxicity for possible benefit (durable response); long-term impact of adverse events not fully known | More nuanced evaluation of patient preferences based on their risk tolerance and profile; longer follow up studies post treatment |
| Patient Reported Outcome | Current measures fall short in measuring the value to patients of Treatment-free Survival; (extended time off treatment) | Treatment Free Survival impact on patient’s QoL; Hope for durable response |
Economic Measures, e.g. Cost of ongoing treatment; Cost of treatment for side effects; cost of lost productivity | Typically focuses on patient-related expenses or drug cost during active treatment | Return to productivity; Economic benefit of Treatment-Free Survival, including reduced expenditures on ongoing treatment, scans and other follow up; Amortize costs over the longer horizon of benefit in a “cure-rate” model; consider other stakeholder fiscal impact |
I-O specific elements to enhance traditional value calculations
| Costs (numerator considerations) | Net Prices vs. List Prices | Wholesale acquisition costs may significantly overestimate the true cost of a drug. We recommend accounting for discounts and rebates where appropriate to reflect the true price paid for the new therapy. |
| Consider alternate stakeholder perspectives | More research emphasis on a societal perspective – While many payers require a focus on the health sector specific costs, to fully understand the costs and benefits of a drug to society taking a societal perspective (accounting for caregiver costs, productivity gains/losses, etc.) in costeffectiveness analysis is warranted. | |
| Effects (denominator considerations) | QALY | Many economic models are sensitive to the variations of the utility value used for each health state. We recommend engaging current or former patients as advisors to validate the assumptions made with the base case QALY inputs as well as the sensitivity analysis. |
| Life Years | Conduct the same analysis with no QALY adjustment so that absolute mortality reductions can be easily reported for the decision-maker. | |
| Patient Specific | Identify other potential outcomes as denominators by engaging current and former patients. Addressing the outcomes that “matter” to patients can help decision-makers compare drugs within the same disease state for the specific population that it is impacting. Consider stratifying analyses based on risk tolerance of patient subpopulations. | |
| Other factors (beyond the incremental cost effectiveness ratio) | Value of Hope | The ISPOR Special Task Force identifies this as an area needing more research to quantify, but it is conceptually intuitive and very relevant to IO. A cancer patient facing a terminal diagnosis may be willing to risk taking a more novel therapy if his or her chances include the possibility of durable response and even functional cure. |
| Real Option Value | For a cancer patient, any innovation that can extend life (even at the same or worse quality of life) may give a patient a chance to live long enough for a new treatment to develop, possibly even a cure. | |
| Scientific Spillovers | New mechanisms of action may or may not benefit current patients, but we often fail to consider the steps in the path to future discovery. Without learning from the research in the 1950s, would we be here today with ~ 26 IO regimens benefitting thousands of patients? |