Model solutions for ethical allocation during cancer medicine shortages

Over the past decade, intermittent shortages of life-saving cancer medicines have occurred in multiple high-income countries (HICs), forcing oncologists to ration treatments.^1,2 Haematological malignancies have been particularly affected by recent shortages of vincristine, asparaginase, nelarabine, and azacitidine. Cancer medicine scarcity in HICs stems from a paucity of incentives to produce low-margin generic medicines or maintain high-quality supply, consolidation within the pharmaceutical industry, and an absence of supply chain transparency.³ In low-income and middle-income countries (LMICs), these problems are compounded by decreased availability of cancer-directed resources, resulting in both intermittent shortages and the total absence of some essential cancer medicines.

In both HICs and LMICs, policy development, direct supply programmes, and proactive pharmacy management are leading to some expansion of access to cancer medicines.³ However, despite substantial gains, drug scarcity will continue to affect patients with cancer in both HICs and LMICs for the foreseeable future.³ High costs and limited production of some blood cancer therapeutics, such as nelarabine and asparaginase, also place patients with blood cancers at higher risk of shortages. Existing shortage allocation guidance is based on normative ethical frameworks, which are well reasoned but have drawbacks and few data to support their use. Recently, simulation modelling methods have advanced, providing fresh insight into how to approach these situations.^4–6

Published guidance on scarce cancer medicine allocation has most often followed goal-directed ethical frameworks. Goals include promoting equality, maximising benefit, minimising harm, and prioritising societal considerations. Equality aims to encourage fairness (eg, lottery). Maximising benefit prioritises survival (or surrogate-outcome gains) per scarce drug volume. Minimising harm ranks outcomes by therapeutic alternatives or life expectancy. Priority by societal consideration relieves social debts, such as preference for clinical trial participants, or (more controversially) rewards social worth, such as a skillset that benefits the community. Because many of these goals have prima facie acceptability, they frequently create clinical dilemmas when combined and applied. Various frameworks have attempted to reconcile such problems^7,8 but putting them into use can be difficult. Indeed, ventilator and remdesivir shortages during the COVID-19 pandemic have shown that a framework’s usefulness depends largely on how well it can be applied to a specific shortage.

Procedure-based frameworks have recognised the limitations of goal-directed schemes and instead focus on best practices during shortage management. A common approach is the modified accountability for reasonableness framework,⁹ the core components of which include transparent allocation scheme development and application; using principles with prima facie relevance (eg, considering patient age when disease severity and treatment response varies by age); making allocation decisions enforceable; allowing appeals; and uniformly applying allocation in similar situations. Beyond allowing for appeals for individual decisions, this framework also recognises that the scheme itself should be iteratively reviewed and adjusted.

A procedural framework for managing cancer medicine shortages might be applied by convening an allocation committee comprising relevant health-care professionals, bioethicists, and patient advocates to adjudicate cases brought by clinicians to prioritise patients for scarce therapy. Such a committee would develop a shortage-specific allocation scheme with stakeholder input and adjust allocation on the basis of the outcomes of previous decisions. Substantial drawbacks remain: prioritisation criteria are less fixed and more subject to capricious application, and the effect of allocation remains uncertain until many patients are treated.

Fortunately, methodological advances can now hybridise these approaches and develop allocation frameworks that are practical, goal-based, and pretested. Simulation modelling can evaluate relevant principles and procedures through computerised abstractions of a shortage. These models leverage available pharmacy and patient data, applying various combinations of allocation principles and procedures to understand if the selected scheme results in intended or unintended consequences, and to what degree any scheme reaches its intended goals.

This approach also helps decision makers to recognise which assumptions must be made and to confront biases if results do not match their presuppositions. Moreover, the strengths of both goal-directed and procedural approaches are incorporated, and their drawbacks reduced. Such methods are already used in organ donation and ventilator allocation.^5,6 Our group have begun piloting this approach for cancer medicine shortages and assessing its limitations and stakeholder acceptability in HICs.¹⁰ Existing models estimating national cancer medicine demand can also be extended to LMICs and those with centralised medicine supply.

Cancer medicine shortages will continue in all settings. To address them, policy, research, and clinical innovation should not only focus on how to extend medication access for future patients, but also on how to improve the distribution of scarce chemotherapy for those currently in need. Collaboration between bioethicists, oncologists, health services researchers, and patients will be essential for designing and implementing allocation that is both ethically and scientifically sound.