Patient Preferences for Investigating Cancer-Related Symptoms in Australian General Practice: A Discrete Choice Experiment.

BACKGROUND: Striking the right balance between early cancer diagnosis and the risk of excessive testing for low-risk symptoms is of paramount importance. Patient-centred care must also consider patient preferences for testing. AIM: To investigate diagnostic testing preferences of the Australian public for symptoms associated with oesophagogastric (OG), bowel, or lung cancer. DESIGN AND SETTING: One of three discrete choice experiments (DCEs) related to either OG, bowel, or lung cancer were administered to a nationally representative sample of Australians aged 40 and above. METHODS: Each DCE comprised three scenarios with symptom positive predictive values (PPVs) for undiagnosed cancer ranging from 1% to 3%. The numerical risk was concealed from participants. DCE attributes encompassed the testing strategy, GP familiarity, test and result waiting times, travel duration, and test cost. Preferences were estimated using conditional and mixed logit models. RESULTS: A total of 3013 individuals participated in one of three DCEs: OG (n=1004), Bowel (n=1006), and Lung (n=1003). Preferences were chiefly driven by waiting time, test cost followed by the test type. There was preference for more invasive tests. When confronted with symptoms carrying an extremely low risk (symptom PPV of 1% or less), participants were more inclined to abstain from testing. CONCLUSIONS: Access-related factors, particularly waiting times and testing costs, emerged as the most pivotal elements influencing preferences, underscoring the substantial impact of these systemic factors on patient choices regarding investigations.

Fitness effects of a demography-dispersal trade-off in expandingSaccharomyces cerevisiaemats.

Fungi expand in space and time to form complex multicellular communities. The mechanisms by which they do so can vary dramatically and determine the life-history and dispersal traits of expanding populations. These traits influence deterministic and stochastic components of evolution, resulting in complex eco-evolutionary dynamics during colony expansion. We perform experiments on budding yeast strains genetically engineered to display rough-surface and smooth-surface phenotypes in colony-like structures called 'mats'. Previously, it was shown that the rough-surface strain has a competitive advantage over the smooth-surface strain when grown on semi-solid media. We experimentally observe the emergence and expansion of segments with a distinct smooth-surface phenotype during rough-surface mat development. We propose a trade-off between dispersal and local carrying capacity to explain the relative fitness of these two phenotypes. Using a modified stepping-stone model, we demonstrate that this trade-off gives the high-dispersing, rough-surface phenotype a competitive advantage from standing variation, but that it inhibits this phenotype's ability to invade a resident smooth-surface population via mutation. However, the trade-off improves the ability of the smooth-surface phenotype to invade in rough-surface mats, replicating the frequent emergence of smooth-surface segments in experiments. Together, these computational and experimental findings advance our understanding of the complex eco-evolutionary dynamics of fungal mat expansion.

Systematic Review and Narrative Synthesis of Economic Evaluations of Prostate Cancer Diagnostic Pathways Incorporating Prebiopsy Magnetic Resonance Imaging.

Context: Prebiopsy magnetic resonance imaging (MRI) of the prostate has been shown to increase the accuracy of the diagnosis of clinically significant prostate cancer. However, evidence is still evolving about how best to integrate prebiopsy MRI into the diagnostic pathway and for which patients, and whether MRI-based pathways are cost effective. Objective: This systematic review aimed to assess the evidence for the cost effectiveness of prebiopsy MRI-based prostate cancer diagnostic pathways. Evidence acquisition: INTERTASC search strategies were adapted and combined with terms for prostate cancer and MRI, and used to search a wide range of databases and registries covering medicine, allied health, clinical trials, and health economics. No limits were set on country, setting, or publication year. Included studies were full economic evaluations of prostate cancer diagnostic pathways with at least one strategy including prebiopsy MRI. Model-based studies were assessed using the Philips framework, and trial-based studies were assessed using the Critical Appraisal Skills Programme checklist. Evidence synthesis: A total of 6593 records were screened after removing duplicates, and eight full-text papers, reporting on seven studies (two model based) were included in this review. Included studies were judged to have a low-to-moderate risk of bias. All studies reported cost-effectiveness analyses based in high-income countries but had significant heterogeneity in diagnostic strategies, patient populations, treatment strategies, and model characteristics. Prebiopsy MRI-based pathways were cost effective compared with pathways relying on ultrasound-guided biopsy in all eight studies. Conclusions: Incorporation of prebiopsy MRI into prostate cancer diagnostic pathways is likely to be more cost effective in than that into pathways relying on prostate-specific antigen and ultrasound-guided biopsy. The optimal prostate cancer diagnostic pathway design and method of integrating prebiopsy MRI are not yet known. Variations between health care systems and diagnostic approaches necessitate further evaluation for a particular country or setting to know how best to apply prebiopsy MRI. Patient summary: In this report, we looked at studies that measured the health care costs and benefits and harms to patients of using prostate magnetic resonance imaging (MRI), to decide whether men need a prostate biopsy for possible prostate cancer. We found that using prostate MRI before biopsy is likely to be less costly for health care services and probably has better outcomes for patients being investigated for prostate cancer. It is still unclear what the best way to use prostate MRI is.

Women's priorities towards ovarian cancer testing: a best-worst scaling study.

OBJECTIVE: To investigate the importance of key characteristics relating to diagnostic testing for ovarian cancer and to understand how previous test experience influences priorities. DESIGN: Case 1 best-worst scaling embedded in an online survey. SETTING: Primary care diagnostic testing in England and Wales. PARTICIPANTS: 150 women with ovaries over 40 years old living in England and Wales. METHODS: We used best-worst scaling, a preference-based survey method, to elicit the relative importance of 25 characteristics relating to ovarian cancer testing following a systematic review. Responses were modelled using conditional logit regression. Subgroup analysis investigated variations based on testing history. MAIN OUTCOME MEASURES: Relative importance scores. RESULTS: 'Chance of dying from ovarian cancer' (0.380, 95% CI 0.26 to 0.49) was the most important factor to respondents, closely followed by 'test sensitivity' (0.308, 95% CI 0.21 to 0.40). In contrast, 'time away from usual activities' (-0.244, 95% CI -0.33 to -0.15) and 'gender of healthcare provider' (-0.243, 95% CI -0.35 to -0.14) were least important to respondents overall. Women who had previously undergone testing placed higher importance on certain characteristics including 'openness of healthcare providers' and 'chance of diagnosing another condition' at the expense of reduced emphasis on characteristics such as 'pain and discomfort' and 'time away from usual activities'. CONCLUSIONS: The results clearly demonstrated items at the extreme, which were most and least important to women considering ovarian cancer testing. Differences in priorities by testing history demonstrate an experience effect, whereby preferences adapt over time based on evidence and experience. Acknowledging these differences helps to identify underlying barriers and facilitators for women with no test experience as well as shortcomings of current service based on women with experience.

Attributes Used for Cancer Screening Discrete Choice Experiments: A Systematic Review.

BACKGROUND: Evidence from discrete choice experiments can be used to enrich understanding of preferences, inform the (re)design of screening programmes and/or improve communication within public campaigns about the benefits and harms of screening. However, reviews of screening discrete choice experiments highlight significant discrepancies between stated choices and real choices, particularly regarding willingness to undergo cancer screening. The identification and selection of attributes and associated levels is a fundamental component of designing a discrete choice experiment. Misspecification or misinterpretation of attributes may lead to non-compensatory behaviours, attribute non-attendance and responses that lack external validity. OBJECTIVES: We aimed to synthesise evidence on attribute development, alongside an in-depth review of included attributes and methodological challenges, to provide a resource for researchers undertaking future studies in cancer screening. METHODS: A systematic review was conducted to identify discrete choice experiments estimating preferences towards cancer screening, dated between 1990 and December 2020. Data were synthesised narratively. In-depth analysis of attributes led to classification into four categories: test specific, service delivery, outcomes and monetary. Attribute significance and relative importance were also analysed. The International Society for Pharmacoeconomics and Outcomes Research conjoint analysis checklist was used to assess the quality of reporting. RESULTS: Forty-nine studies were included at full text. They covered a range of cancer sites: over half (26/49) examined colorectal screening. Most studies elicited general public preferences (34/49). In total, 280 attributes were included, 90% (252/280) of which were significant. Overall, test sensitivity and mortality reduction were most frequently found to be the most important to respondents. CONCLUSIONS: Improvements in reporting the identification, selection and construction of attributes used within cancer screening discrete choice experiments are needed. This review also highlights the importance of considering the complexity of choice tasks when considering risk information or compound attributes. Patient and public involvement and stakeholder engagement are recommended to optimise understanding of unavoidably complex choice tasks throughout the design process. To ensure quality and maximise comparability across studies, further research is needed to develop a risk-of-bias measure for discrete choice experiments.

Lattice-based Monte Carlo simulation of the effects of nutrient concentration and magnetic field exposure on yeast colony growth and morphology.

Yeasts exist in communities that expand over space and time to form complex structures and patterns. We developed a lattice-based framework to perform spatial-temporal Monte Carlo simulations of budding yeast colonies exposed to different nutrient and magnetic field conditions. The budding patterns of haploid and diploid yeast cells were incorporated into the framework, as well as the filamentous growth that occurs in yeast colonies under nutrient limiting conditions. Simulation of the framework predicted that magnetic fields decrease colony growth rate, solidity, and roundness. Magnetic field simulations further predicted that colony elongation and boundary fluctuations increase in a nutrient- and ploidy-dependent manner. These in-silico predictions are an important step towards understanding the effects of the physico-chemical environment on microbial colonies and for informing bioelectromagnetic experiments on yeast colony biofilms and fungal pathogens.