The socioeconomic impact of cancer on patients and their relatives: Organisation of European Cancer Institutes task force consensus recommendations on conceptual framework, taxonomy, and research directions.

Loss of income and out-of-pocket expenditures are important causes of financial hardship in many patients with cancer, even in high-income countries. The far-reaching consequences extend beyond the patients themselves to their relatives, including caregivers and dependents. European research to date has been limited and is hampered by the absence of a coherent theoretical framework and by heterogeneous methods and terminology. To address these shortages, a task force initiated by the Organisation of European Cancer Institutes (OECI) produced 25 recommendations, including a comprehensive definition of socioeconomic impact from the perspective of patients and their relatives, a conceptual framework, and a consistent taxonomy linked to the framework. The OECI task force consensus statement highlights directions for future research with a view towards policy relevance. Beyond descriptive studies into the dimension of the problem, individual severity and predictors of vulnerability should be explored. It is anticipated that the consensus recommendations will facilitate and enhance future research efforts into the socioeconomic impact of cancer and cancer care, providing a crucial reference point for the development and validation of patient-reported outcome instruments aimed at measuring its broader effects.

Quality Appraisal in Systematic Literature Reviews of Studies Eliciting Health State Utility Values: Conceptual Considerations.

BACKGROUND: The increasing number of studies that generate health state utility values (HSUVs) and the impact of HSUVs on cost-utility analyses make a robust tailored quality appraisal (QA) tool for systematic reviews of these studies necessary. OBJECTIVE: This study aimed to address conceptual issues regarding QA in systematic reviews of studies eliciting HSUVs by establishing a consensus on the definitions, dimensions and scope of a QA tool specific to this context. METHODS: A modified Delphi method was used in this study. An international multidisciplinary panel of seven experts was purposively assembled. The experts engaged in two anonymous online survey rounds. After each round, the experts received structured and controlled feedback on the previous phase. Controlled feedback allowed the experts to re-evaluate and adjust their positions based on collective insights. Following these surveys, a virtual face-to-face meeting was held to resolve outstanding issues. Consensus was defined a priori at all stages of the modified Delphi process. RESULTS: The response rates to the first-round and second-round questionnaires and the virtual consensus meeting were 100%, 86% and 71%, respectively. The entire process culminated in a consensus on the definitions of scientific quality, QA, the three QA dimensions-reporting, relevance and  methodological quality-and the scope of a QA tool specific to studies that elicit HSUVs. CONCLUSIONS: Achieving this consensus marks a pivotal step towards developing a QA tool specific to systematic reviews of studies eliciting HSUVs. Future research will build on this foundation, identify QA items, signalling questions and response options, and develop a QA tool specific to studies eliciting HSUVs.

Developing a Conceptual Framework for Socioeconomic Impact Research in European Cancer Patients: A 'Best-Fit' Framework Synthesis.

BACKGROUND: Multiple studies have indicated a socioeconomic impact of cancer and cancer care on patients and their families. Existing instruments designed to measure this impact lack consensus in their conceptualization of the issue. Further, various terminologies have been used in the literature (e.g., financial burden, financial hardship, financial stress) without clear definitions and consistent conceptual background. Based on a targeted review of existing models addressing the socioeconomic impact of cancer, our goal was to develop a comprehensive framework from a European perspective. METHOD: A 'best-fit' framework synthesis was applied. First, we systematically identified existing models to generate a priori concepts. Second, we systematically identified relevant European qualitative studies and coded their results against these a priori concepts. Inclusion and exclusion criteria were predefined and applied thoroughly in these processes. Thematic analysis and team discussions were applied to finalize the (sub)themes in our proposed conceptual framework. Third, we examined model structures and quotes from qualitative studies to explore relationships among (sub)themes. This process was repeated until no further change in (sub)themes and their relationships emerged. RESULT: Eighteen studies containing conceptual models and seven qualitative studies were identified. Eight concepts and 20 sub-concepts were derived from the included models. After coding the included qualitative studies against the a priori concepts and following discussions among team members, seven themes and 15 sub-themes were included in our proposed conceptual framework. Based on the identified relationships, we categorized themes into four groups: causes, intermediate consequences, outcomes and risk factors. CONCLUSION: We propose a Socioeconomic Impact Framework based on a targeted review and synthesis of existing models in the field and adapted to the European perspective. Our work contributes as an input to a European consensus project on socioeconomic impact research by an Organization European Cancer Institute (OECI) Task Force.

Economic Burden of Pancreatic Cancer in Europe: a Literature Review.

PURPOSE: Pancreatic cancer is characterized by its high mortality, usually attributed to its diagnosis in already advanced stages. This article aims at presenting an overview of the economic burden of pancreatic cancer in Europe. METHODS: A systematic literature review was conducted. It made use of the search engines EconLit, Google Scholar, PubMed and Web of Science, and retrieved articles published after December 31st, 1992, and before April 1st, 2020. Study characteristics and cost information were extracted. Cost per patient and cost per patient per month (PPM) were calculated, and drivers of estimate heterogeneity was analysed. Results were converted into 2019 Euros. RESULTS: The literature review yielded 26 studies on the economic burden attributable to pancreatic cancer in Europe. Cost per patient was on average 40,357 euros (median 15,991), while figures PPM were on average 3,656 euros (median 1,536). Indirect costs were found to be on average 154,257 euros per patient or 14,568 euros PPM, while direct costs 20,108 euros per patient and 2,004 euros PPM. Nevertheless, variation on cost estimations was large and driven by study methodology, patient sample characteristics, such as type of tumour and cancer stage and cost components included in analyses, such as type of procedure. CONCLUSION: Pancreatic cancer direct costs PPM are in the upper bound relative to other cancer types; however, direct per patient costs are likely to be lower because of shorter survival. Indirect costs are substantial, mainly attributed to high mortality.

Quality appraisal for systematic literature reviews of health state utility values: a descriptive analysis.

BACKGROUND: Health state utility values (HSUVs) are an essential input parameter to cost-utility analysis (CUA). Systematic literature reviews (SLRs) provide summarized information for selecting utility values from an increasing number of primary studies eliciting HSUVs. Quality appraisal (QA) of such SLRs is an important process towards the credibility of HSUVs estimates; yet, authors often overlook this crucial process. A scientifically developed and widely accepted QA tool for this purpose is lacking and warranted. OBJECTIVES: To comprehensively describe the nature of QA in published SRLs of studies eliciting HSUVs and generate a list of commonly used items. METHODS: A comprehensive literature search was conducted in PubMed and Embase from 01.01.2015 to 15.05.2021. SLRs of empirical studies eliciting HSUVs that were published in English were included. We extracted descriptive data, which included QA tools checklists or good practice recommendations used or cited, items used, and the methods of incorporating QA results into study findings. Descriptive statistics (frequencies of use and occurrences of items, acceptance and counterfactual acceptance rates) were computed and a comprehensive list of QA items was generated. RESULTS: A total of 73 SLRs were included, comprising 93 items and 35 QA tools and good recommendation practices. The prevalence of QA was 55% (40/73). Recommendations by NICE and ISPOR guidelines appeared in 42% (16/40) of the SLRs that appraised quality. The most commonly used QA items in SLRs were response rates (27/40), statistical analysis (22/40), sample size (21/40) and loss of follow up (21/40). Yet, the most commonly featured items in QA tools and GPRs were statistical analysis (23/35), confounding or baseline equivalency (20/35), and blinding (14/35). Only 5% of the SLRS used QA to inform the data analysis, with acceptance rates of 100% (in two studies) 67%, 53% and 33%. The mean counterfactual acceptance rate was 55% (median 53% and IQR 56%). CONCLUSIONS: There is a considerably low prevalence of QA in the SLRs of HSUVs. Also, there is a wide variation in the QA dimensions and items included in both SLRs and extracted tools. This underscores the need for a scientifically developed QA tool for multi-variable primary studies of HSUVs.

Estimating health system opportunity costs: the role of non-linearities and inefficiency.

BACKGROUND: Empirical estimates of health system opportunity costs have been suggested as a basis for the cost-effectiveness threshold to use in Health Technology Assessment. Econometric methods have been used to estimate these in several countries based on data on spending and mortality. This study examines empirical evidence on four issues: non-linearity of the relationship between spending and mortality; the inclusion of outcomes other than mortality; variation in the efficiency with which expenditures generate health outcomes; and the relationship among efficiency, mortality rates and outcome elasticities. METHODS: Quantile Regression is used to examine non-linearities in the relationship between mortality and health expenditures along the mortality distribution. Data Envelopment Analysis extends the approach, using multiple measures of health outcomes to measure efficiency. These are applied to health expenditure data from 151 geographical units (Primary Care Trusts) of the National Health Service in England, across eight different clinical areas (Programme Budget Categories), for 3 fiscal years from 2010/11 to 2012/13. RESULTS: The results suggest differences in efficiency levels across geographical units and clinical areas as to how health resources generate outcomes, which indicates the capacity to adjust to a decrease in health expenditure without affecting health outcomes. Moreover, efficient units have lower absolute levels of mortality elasticity to health expenditure than inefficient ones. CONCLUSIONS: The policy of adopting thresholds based on estimates of a single system-wide cost-effectiveness threshold assumes a relationship between expenditure and health outcomes that generates an opportunity cost estimate which applies to the whole system. Our evidence of variations in that relationship and therefore in opportunity costs suggests that adopting a single threshold may exacerbate the efficiency and equity concerns that such thresholds are designed to counter. In most health care systems, many decisions about provision are not made centrally. Our analytical approach to understanding variability in opportunity cost can help policy makers target efficiency improvements and set realistic targets for local and clinical area health improvements from increased expenditure.

Survival and comorbidities in lung cancer patients: Evidence from administrative claims data in Germany.

Lung cancer is the most common cancer type worldwide and has the highest and second highest mortality rate for men and women respectively in Germany. Yet, the role of comorbid illnesses in lung cancer patient prognosis is still debated. We analyzed administrative claims data from one of the largest statutory health insurance (SHI) funds in Germany, covering close to 9 million people (11% of the national population); observation period was from 2005 to 2019. Lung cancer patients and their concomitant diseases were identified by ICD-10-GM codes. Comorbidities were classified according to the Charlson Comorbidity Index (CCI). Incidence, comorbidity prevalence and survival are estimated considering sex, age at diagnosis, and place of residence. Kaplan Meier curves with 95% confidence intervals were built in relation to common comorbidities. We identified 70,698 lung cancer incident cases in the sample. Incidence and survival figures are comparable to official statistics in Germany. Most prevalent comorbidities are chronic obstructive pulmonary disease (COPD) (36.7%), followed by peripheral vascular disease (PVD) (18.7%), diabetes without chronic complications (17.4%), congestive heart failure (CHF) (16.5%) and renal disease (14.7%). Relative to overall survival, lung cancer patients with CHF, cerebrovascular disease (CEVD) and renal disease are associated with largest drops in survival probabilities (9% or higher), while those with PVD and diabetes without chronic complications with moderate drops (7% or lower). The study showed a negative association between survival and most common comorbidities among lung cancer patients, based on a large sample for Germany. Further research needs to explore the individual effect of comorbidities disentangled from that of other patient characteristics such as cancer stage and histology.

Estimation of the stage-wise costs of breast cancer in Germany using a modeling approach.

Breast cancer (BC) is a heterogeneous disease representing a substantial economic burden. In order to develop policies that successfully decrease this burden, the factors affecting costs need to be fully understood. Evidence suggests that early-stage BC has a lower cost than a late stage BC. We aim to provide conservative estimates of BC's stage-wise medical costs from German healthcare and the payer's perspective. To this end, we conducted a literature review of articles evaluating stage-wise costs of BC in Germany through PubMed, Web of Science, and Econ Lit databases supplemented by Google Scholar. We developed a decision tree model to estimate BC-related medical costs in Germany using available treatment and cost information. The review generated seven studies; none estimated the stage-wise costs of BC. The studies were classified into two groups: case scenarios (five studies) and two studies based on administrative data. The first sickness funds data study (Gruber et al., 2012) used information from the year 1999 to approach BC attributable cost; their results suggest a range between €3,929 and €11,787 depending on age. The second study (Kreis, Plöthner et al., 2020) used 2011-2014 data and suggested an initial phase incremental cost of €21,499, an intermediate phase cost of €2,620, and a terminal phase cost of €34,513 per incident case. Our decision tree model-based BC stage-wise cost estimates were €21,523 for stage I, €25,679 for stage II, €30,156 for stage III, and €42,086 for stage IV. Alternatively, the modeled cost estimates are €20,284 for the initial phase of care, €851 for the intermediate phase of care, and €34,963 for the terminal phase of care. Our estimates for phases of care are consistent with recent German estimates provided by Kreis et al. Furthermore, the data collected by sickness funds are collected primarily for reimbursement purposes, where the German ICD-10 classification system defines a cancer diagnosis. As a result, claims data lack the clinical information necessary to understand stage-wise BC costs. Our model-based estimates fill the gap and inform future economic evaluations of BC interventions.

How Much Does It Cost to Research and Develop a New Drug? A Systematic Review and Assessment.

BACKGROUND: Debate over the viability of the current commercial research and development (R&D) model is ongoing. A controversial theme is the cost of bringing a new molecular entity (NME) to market. OBJECTIVE: Our aim was to evaluate the range and suitability of published R&D cost estimates as to the degree to which they represent the actual costs of industry. METHODS: We provided a systematic literature review based on articles found in the Pubmed, Embase and EconLit electronic databases, and in a previously published review. Articles published before March 2020 that estimated the total R&D costs were included (22 articles with 45 unique cost estimates). We included only literature in which the methods used to collect the information and to estimate the R&D costs were clearly described; therefore, three reports were excluded. We extracted average pre-launch R&D costs per NME and converted the values to 2019 US dollars (US$) using the gross domestic product (GDP) price deflator. We appraised the suitability of the R&D estimated costs by using a scoring system that captures three domains: (1) how success rates and development time used for cost estimation were obtained; (2) whether the study considered potential sources contributing to the variation in R&D costs; and (3) what the components of the cost estimation were. RESULTS: Estimates of total average capitalized pre-launch R&D costs varied widely, ranging from $161 million to $4.54 billion (2019 US$). Therapeutic area-specific estimates were highest for anticancer drugs (between $944 million and $4.54 billion). Our analysis identified a trend of increasing R&D costs per NME over time but did not reveal a relation between cost estimates and study ranking when the suitability scores were assessed. We found no evidence of an increase in suitability scores over time. CONCLUSION: There is no universally correct answer regarding how much it costs, on average, to research and develop an NME. Future studies should explicitly address previously neglected variables, which likely explain some variability in estimates, and consider the trade-off between the transparency and public accessibility of data and their specificity. Use of our proposed suitability scoring system may assist in addressing such issues.

Cost-effectiveness of risk-based breast cancer screening: A systematic review.

To analyse published evidence on the economic evaluation of risk-based screening (RBS), a full systematic literature review was conducted. After a quality appraisal, we compared the cost-effectiveness of risk-based strategies (low-risk, medium-risk and high-risk) with no screening and age-based screening. Studies were also analysed for modelling, risk stratification methods, input parameters, data sources and harms and benefits. The 10 modelling papers analysed were based on screening performance of film-based mammography (FBM) (three); digital mammography (DM) and FBM (two); DM alone (three); DM, ultrasound (US) and magnetic resonance imaging (one) and DM and US (one). Seven studies did not include the cost of risk-stratification, and one did not consider the cost of diagnosis. Disutility was incorporated in only six studies (one for screening and five for diagnosis). None of the studies reported disutility of risk-stratification (being considered as high-risk). Risk-stratification methods varied from only breast density (BD) to the combination of familial risk, genetic susceptibility, lifestyle, previous biopsies, Jewish ancestry and reproductive history. Less or no screening in low-risk women and more frequent mammography screening in high-risk women was more cost-effective compared to no screening and age-based screening. High-risk women screened annually yielded a higher mortality rate reduction and more quality-adjusted life years at the expense of higher cost and false positives. RBS can be cost effective compared to the alternatives. However, heterogeneity among risk-stratification methods, input parameters, and weaknesses in the methodologies hinder the derivation of robust conclusions. Therefore, further studies are warranted to assess newer technologies and innovative risk-stratification methods.

Economic evaluation of meningococcal vaccines: considerations for the future.

In 2018, a panel of health economics and meningococcal disease experts convened to review methodologies, frameworks, and decision-making processes for economic evaluations of vaccines, with a focus on evaluation of vaccines targeting invasive meningococcal disease (IMD). The panel discussed vaccine evaluation methods across countries; IMD prevention benefits that are well quantified using current methods, not well quantified, or missing in current cost-effectiveness methodologies; and development of recommendations for future evaluation methods. Consensus was reached on a number of points and further consideration was deemed necessary for some topics. Experts agreed that the unpredictability of IMD complicates an accurate evaluation of meningococcal vaccine benefits and that vaccine cost-effectiveness evaluations should encompass indirect benefits, both for meningococcal vaccines and vaccines in general. In addition, the panel agreed that transparency in the vaccine decision-making process is beneficial and should be implemented when possible. Further discussion is required to ascertain: how enhancing consistency of frameworks for evaluating outcomes of vaccine introduction can be improved; reviews of existing tools used to capture quality of life; how indirect costs are considered within models; and whether and how the weighting of quality-adjusted life-years (QALY), application of QALY adjustment factors, or use of altered cost-effectiveness thresholds should be used in the economic evaluation of vaccines.

CHALLENGES AND METHODOLOGIES IN USING PROGRESSION FREE SURVIVAL AS A SURROGATE FOR OVERALL SURVIVAL IN ONCOLOGY.

OBJECTIVES: A primary outcome in oncology trials is overall survival (OS). However, to estimate OS accurately requires a sufficient number of patients to have died, which may take a long time. If an alternative end point is sufficiently highly correlated with OS, it can be used as a surrogate. Progression-free survival (PFS) is the surrogate most often used in oncology, but does not always satisfy the correlation conditions for surrogacy. We analyze the methodologies used when extrapolating from PFS to OS. METHODS: Davis et al. previously reviewed the use of surrogate end points in oncology, using papers published between 2001 and 2011. We extend this, reviewing papers published between 2012 and 2016. We also examine the reporting of statistical methods to assess the strength of surrogacy. RESULTS: The findings from 2012 to 2016 do not differ substantially from those of 2001 to 2011: the same factors are shown to affect the relationship between PFS and OS. The proportion of papers reporting individual patient data (IPD), strongly recommended for full assessment of surrogacy, remains low: 33 percent. A wide range of methods has been used to determine the appropriateness of surrogates. While usually adhering to reporting standards, the standard of scholarship appears sometimes to be questionable and the reporting of results often haphazard. CONCLUSIONS: Standards of analysis and reporting PFS to OS surrogate studies should be improved by increasing the rigor of statistical reporting and by agreeing to a minimum set of reporting guidelines. Moreover, the use of IPD to assess surrogacy should increase.

Economies of scale and scope in publicly funded biomedical and health research: evidence from the literature.

BACKGROUND: Publicly funded biomedical and health research is expected to achieve the best return possible for taxpayers and for society generally. It is therefore important to know whether such research is more productive if concentrated into a small number of 'research groups' or dispersed across many. METHODS: We undertook a systematic rapid evidence assessment focused on the research question: do economies of scale and scope exist in biomedical and health research? In other words, is that research more productive per unit of cost if more of it, or a wider variety of it, is done in one location? We reviewed English language literature without date restriction to the end of 2014. To help us to classify and understand that literature, we first undertook a review of econometric literature discussing models for analysing economies of scale and/or scope in research generally (not limited to biomedical and health research). RESULTS: We found a large and disparate literature. We reviewed 60 empirical studies of (dis-)economies of scale and/or scope in biomedical and health research, or in categories of research including or overlapping with biomedical and health research. This literature is varied in methods and findings. At the level of universities or research institutes, studies more often point to positive economies of scale than to diseconomies of scale or constant returns to scale in biomedical and health research. However, all three findings exist in the literature, along with inverse U-shaped relationships. At the level of individual research units, laboratories or projects, the numbers of studies are smaller and evidence is mixed. Concerning economies of scope, the literature more often suggests positive economies of scope than diseconomies, but the picture is again mixed. The effect of varying the scope of activities by a research group was less often reported than the effect of scale and the results were more mixed. CONCLUSIONS: The absence of predominant findings for or against the existence of economies of scale or scope implies a continuing need for case by case decisions when distributing research funding, rather than a general policy either to concentrate funding in a few centres or to disperse it across many.

Bibliometric trends of health economic evaluation in Sub-Saharan Africa.

BACKGROUND: Collaboration between Sub-Saharan African researchers is important for the generation and transfer of health technology assessment (HTA) evidence, in order to support priority-setting in health. The objective of this analysis was to evaluate collaboration patterns between countries. METHODS: We conducted a rapid evidence assessment that included a random sample of health economic evaluations carried out in 20 countries (Angola, Botswana, Congo, Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia, Seychelles, South Africa, Swaziland, Tanzania, Zambia, Zimbabwe, Ghana, Kenya, Nigeria, Ethiopia, Uganda). We conducted bibliometric network analysis based on all first authors with a Sub-Saharan African academic affiliation and their co-authored publications ("network-articles"). Then we produced a connection map of collaboration patterns among Sub-Saharan African researchers, reflecting the number of network-articles and the country of affiliation of the main co-authors. RESULTS: The sample of 119 economic evaluations mostly related to treatments of communicable diseases, in particular HIV/AIDS (42/119, 35.29 %) and malaria (26/119, 21.85 %). The 39 first authors from Sub-Saharan African institutions together co-authored 729 network-articles. The network analysis showed weak collaboration between health economic researchers in Sub-Saharan Africa, with researchers being more likely to collaborate with Europe and North America than with other African countries. South Africa stood out as producing the highest number of health economic evaluations and collaborations. CONCLUSIONS: The development and evaluation of HTA research networks in Sub-Saharan Africa should be supported, with South Africa central to any such efforts. Organizations and institutions from high income countries interested in supporting priority setting in Sub-Saharan Africa should include promoting collaboration as part of their agendas, in order to take advantage of the potential transferability of results and methods of the available health economic analyses in Africa and internationally.

Mapping Priority Setting in Health in 17 Countries Across Asia, Latin America, and sub-Saharan Africa.

Abstract-As more low- and middle-income countries (LMICs) commit to universal health coverage (UHC), there is a growing need for rational priority setting using health technology assessment (HTA) and other policy tools. We describe an approach for rapidly mapping LMICs' capacity and needs for rational priority setting, aimed at identifying candidate countries where technical assistance would be most viable, and present our findings from applying this approach to three continents. Drawing on the multiple streams theory and a conceptual model of HTA in health systems, we developed qualitative and quantitative indicators for political commitment, current position along UHC journey, institutional and technical capacity, health system financing characteristics, and potential economies of scale in rational priority setting and associated data collection tools. We additionally defined criteria for shortlisting countries, emphasizing feasibility of technical assistance. We purposively sampled 17 countries and gathered data up to May 2014 from various sources and applied the shortlisting criteria to these countries. The four shortlisted countries (Indonesia, Myanmar, South Africa, Ghana) had varying capacities for rational priority setting and shared clear demand for rational priority setting as a means of achieving UHC. Indonesia was the strongest candidate for technical assistance, given the potential scale of impact on its large population and potential lessons for LMICs transitioning from aid. We conducted additional in-country scoping, and technical assistance to support HTA development in Indonesia is now underway. Our approach is of potential value to development funders and initiatives seeking to maximize the impact of their aid investments in support of UHC.

Government and charity funding of cancer research: public preferences and choices.

BACKGROUND: It is unclear how the public would respond to changes in government decisions about how much to spend on medical research in total and specifically on major disease areas such as cancer. Our aim was to elicit the views of the general public in the United Kingdom about how a change in government spending on cancer research might affect their willingness to donate, or to hypothecate a portion of their income tax payments, to cancer research charities. METHODS: A web-based stated preference survey was conducted in 2013. Respondents considered hypothetical scenarios regarding changes in the levels of government funding for medical research. In each scenario, respondents were asked to imagine that they could allocate £100 of the income tax they paid this year to one or more medical research charities. They were asked how they wished to allocate the £100 between cancer research charities and medical research charities concerned with diseases other than cancer. After having been given the opportunity to allocate £100 in this way, respondents were then asked if they would want to reduce or increase any personal out-of-pocket donations that they already make to cancer research and non-cancer medical research charities. Descriptive analyses and random effects modelling were used to examine patterns in the response data. RESULTS: The general tendency of respondents was to act to offset hypothetical changes in government spending. When asked to imagine that the government had reduced (or increased) its spending on cancer research, the general tendency of respondents was to state that they would give a larger (or smaller) allocation of their income tax to cancer research charities, and to increase (or reduce) their personal out-of-pocket donations to cancer research charities. However, most respondents' preferred allocation splits and changes in personal donations did not vary much from scenario to scenario. Many of the differences between scenarios were small and non-significant. CONCLUSIONS: The public's decisions about how much to donate to cancer research or other medical research charities are not greatly affected by (hypothetical) changes to government plans about the amount of public funding of cancer or other medical research.