Legitimacy of medicines funding in the era of accelerated access

Objectives: In recent years, numerous frameworks have been developed to enhance the legitimacy of health technology assessment processes. Despite efforts to implement these “legitimacy frameworks”, medicines funding decisions can still be perceived as lacking in legitimacy. We therefore sought to examine stakeholder views on factors that they think should be considered when making decisions about the funding of high-cost breast cancer therapies, focusing on those that are not included in current frameworks and processes. Methods: We analyzed published discourse on the funding of high-cost breast-cancer therapies. Relevant materials were identified by searching the databases Google, Google Scholar and Factiva in August 2014 and July 2016 and these were analyzed thematically. Results: We analyzed 50 published materials and found that stakeholders, for the most part, want to be able to access medicines more quickly and at the same time as other patients and for decision-makers to be more flexible with regards to evidence requirements and to use a wider range of criteria when evaluating therapies. Many also advocated for existing process to be accelerated or bypassed in order to improve access to therapies. Conclusions: Our results illustrate that a stakeholder-derived conceptualization of legitimacy emphasizes principles of accelerated access, and is not fully accounted for by existing frameworks and processes aimed at promoting legitimacy. However, further research examining the ethical, political and clinical implications of the stakeholder claims raised here is needed before firm policy recommendations can be made. Keywords pharmaceutical funding decisions; resource allocation; stakeholder engagement; breast cancer; accelerated acces

A unified wavelet-based modelling framework for non-linear system identification: the WANARX model structure

A new unified modelling framework based on the superposition of additive submodels, functional components, and wavelet decompositions is proposed for non-linear system identification. A non-linear model, which is often represented using a multivariate non-linear function, is initially decomposed into a number of functional components via the wellknown analysis of variance (ANOVA) expression, which can be viewed as a special form of the NARX (non-linear autoregressive with exogenous inputs) model for representing dynamic input–output systems. By expanding each functional component using wavelet decompositions including the regular lattice frame decomposition, wavelet series and multiresolution wavelet decompositions, the multivariate non-linear model can then be converted into a linear-in-theparameters problem, which can be solved using least-squares type methods. An efficient model structure determination approach based upon a forward orthogonal least squares (OLS) algorithm, which involves a stepwise orthogonalization of the regressors and a forward selection of the relevant model terms based on the error reduction ratio (ERR), is employed to solve the linear-in-the-parameters problem in the present study. The new modelling structure is referred to as a wavelet-based ANOVA decomposition of the NARX model or simply WANARX model, and can be applied to represent high-order and high dimensional non-linear systems

Opportunities in cancer imaging: a review of oesophageal, gastric and colorectal malignancies

The incidence of gastrointestinal (GI) malignancy is increasing worldwide. In particular, there is a concerning rise in incidence of GI cancer in younger adults. Direct endoscopic visualisation of luminal tumour sites requires invasive procedures, which are associated with certain risks, but remain necessary because of limitations in current imaging techniques and the continuing need to obtain tissue for diagnosis and genetic analysis; however, management of GI cancer is increasingly reliant on non-invasive, radiological imaging to diagnose, stage, and treat these malignancies. Oesophageal, gastric, and colorectal malignancies require specialist investigation and treatment due to the complex nature of the anatomy, biology, and subsequent treatment strategies. As cancer imaging techniques develop, many opportunities to improve tumour detection, diagnostic accuracy and treatment monitoring present themselves. This review article aims to report current imaging practice, advances in various radiological modalities in relation to GI luminal tumour sites and describes opportunities for GI radiologists to improve patient outcomes

The wavelet-NARMAX representation : a hybrid model structure combining polynomial models with multiresolution wavelet decompositions

A new hybrid model structure combing polynomial models with multiresolution wavelet decompositions is introduced for nonlinear system identification. Polynomial models play an important role in approximation theory, and have been extensively used in linear and nonlinear system identification. Wavelet decompositions, in which the basis functions have the property of localization in both time and frequency, outperform many other approximation schemes and offer a flexible solution for approximating arbitrary functions. Although wavelet representations can approximate even severe nonlinearities in a given signal very well, the advantage of these representations can be lost when wavelets are used to capture linear or low-order nonlinear behaviour in a signal. In order to sufficiently utilise the global property of polynomials and the local property of wavelet representations simultaneously, in this study polynomial models and wavelet decompositions are combined together in a parallel structure to represent nonlinear input-output systems. As a special form of the NARMAX model, this hybrid model structure will be referred to as the WAvelet-NARMAX model, or simply WANARMAX. Generally, such a WANARMAX representation for an input-output system might involve a large number of basis functions and therefore a great number of model terms. Experience reveals that only a small number of these model terms are significant to the system output. A new fast orthogonal least squares algorithm, called the matching pursuit orthogonal least squares (MPOLS) algorithm, is also introduced in this study to determine which terms should be included in the final model

Incidence and severity of self-reported chemotherapy side effects in routine care: A prospective cohort study

© 2017 Pearce et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Aim: Chemotherapy side effects are often reported in clinical trials; however, there is little evidence about their incidence in routine clinical care. The objective of this study was to describe the frequency and severity of patient-reported chemotherapy side effects in routine care across treatment centres in Australia. Methods: We conducted a prospective cohort study of individuals with breast, lung or colorectal cancer undergoing chemotherapy. Side effects were identified by patient self-report. The frequency, prevalence and incidence rates of side effects were calculated by cancer type and grade, and cumulative incidence curves for each side effect computed. Frequencies of side effects were compared between demographic subgroups using chi-squared statistics. Results: Side effect data were available for 449 eligible individuals, who had a median follow-up of 5.64 months. 86% of participants reported at least one side effect during the study period and 27% reported a grade IV side effect, most commonly fatigue or dyspnoea. Fatigue was the most common side effect overall (85%), followed by diarrhoea (74%) and constipation (74%). Prevalence and incidence rates were similar across side effects and cancer types. Age was the only demographic factor associated with the incidence of side effects, with older people less likely to report side effects. Conclusion: This research has produced the first Australian estimates of self-reported incidence of chemotherapy side effects in routine clinical care. Chemotherapy side effects in routine care are common, continue throughout chemotherapy and can be serious. This work confirms the importance of observational data in providing clinical practice-relevant information to decision-makers

Energy expenditure during common sitting and standing tasks: examining the 1.5 MET definition of sedentary behaviour

Background: Sedentary behavior is defined as any waking behavior characterized by an energy expenditure of 1.5 METS or less while in a sitting or reclining posture. This study examines this definition by assessing the energy cost (METs) of common sitting, standing and walking tasks. Methods: Fifty one adults spent 10 min during each activity in a variety of sitting tasks (watching TV, Playing on the Wii, Playing on the PlayStation Portable (PSP) and typing) and non-sedentary tasks (standing still, walking at 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4, and 1.6 mph). Activities were completed on the same day in a random order following an assessment of resting metabolic rate (RMR). A portable gas analyzer was used to measure oxygen uptake, and data were converted to units of energy expenditure (METs). Results: Average of standardized MET values for screen-based sitting tasks were: 1.33 (SD: 0.24) METS (TV), 1.41 (SD: 0.28) (PSP), and 1.45 (SD: 0.32) (Typing). The more active, yet still seated, games on the Wii yielded an average of 2.06 (SD: 0.5) METS. Standing still yielded an average of 1.59 (SD: 0.37) METs. Walking MET values increased incrementally with speed from 2.17 to 2.99 (SD: 0.5 - 0.69) METs. Conclusions: The suggested 1.5 MET threshold for sedentary behaviors seems reasonable however some sitting based activities may be classified as non-sedentary. The effect of this on the definition of sedentary behavior and associations with metabolic health needs further investigation

Improved model identification for non-linear systems using a random subsampling and multifold modelling (RSMM) approach

In non-linear system identification, the available observed data are conventionally partitioned into two parts: the training data that are used for model identification and the test data that are used for model performance testing. This sort of 'hold-out' or 'split-sample' data partitioning method is convenient and the associated model identification procedure is in general easy to implement. The resultant model obtained from such a once-partitioned single training dataset, however, may occasionally lack robustness and generalisation to represent future unseen data, because the performance of the identified model may be highly dependent on how the data partition is made. To overcome the drawback of the hold-out data partitioning method, this study presents a new random subsampling and multifold modelling (RSMM) approach to produce less biased or preferably unbiased models. The basic idea and the associated procedure are as follows. First, generate K training datasets (and also K validation datasets), using a K-fold random subsampling method. Secondly, detect significant model terms and identify a common model structure that fits all the K datasets using a new proposed common model selection approach, called the multiple orthogonal search algorithm. Finally, estimate and refine the model parameters for the identified common-structured model using a multifold parameter estimation method. The proposed method can produce robust models with better generalisation performance

Persistence and Adherence to Cardiovascular Medicines in Australia

BACKGROUND: The burden of cardiovascular disease is increasing, with many people treated for multiple cardiovascular conditions. We examined persistence and adherence to medicines for cardiovascular disease treatment or prevention in Australia. METHODS AND RESULTS: Using national dispensing claims for a 10% random sample of people, we identified adults (≥18 years) initiating antihypertensives, statins, oral anticoagulants, or antiplatelets in 2018. We measured persistence to therapy using a 60-day permissible gap, and adherence using the proportion of days covered up to 3 years from initiation, and from first to last dispensing. We reported outcomes by age, sex, and cardiovascular multimedicine use. We identified 83 687 people initiating antihypertensives (n=37 941), statins (n=34 582), oral anticoagulants (n=15 435), or antiplatelets (n=7726). Around one-fifth of people discontinued therapy within 90 days, with 50% discontinuing within the first year. Although many people achieved high adherence (proportion of days covered ≥80%) within the first year, these rates were higher when measured from first to last dispensing (40.5% and 53.2% for statins; 55.6% and 80.5% for antiplatelets, respectively). Persistence was low at 3 years (17.5% antiplatelets to 37.3% anticoagulants). Persistence and adherence increased with age, with minor differences by sex. Over one-third of people had cardiovascular multimedicine use (reaching 92% among antiplatelet users): they had higher persistence and adherence than people using medicines from only 1 cardiovascular group. CONCLUSIONS: Persistence to cardiovascular medicines decreases substantially following initiation, but adherence remains high while people are using therapy. Cardiovascular multimedicine use is common, and people using multiple cardiovascular medicines have higher rates of persistence and adherence

Socio-demographic and health service factors associated with antibiotic dispensing in older Australian adults

© 2019 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Background Widespread use of antibiotics has led to the development of antibiotic resistance. However, there are limited data describing antibiotic use in the community setting, and examining factors associated with greater use. Our study aimed to quantify antibiotic dispensing in older adults in the community according to socio-demographics and health services use. Methods Prospective analysis of a population-based cohort study of 239,981 adults aged 45 years in Australia (the Sax Institute’s 45 and Up Study). Data on socio-demographics and health from a questionnaire, were linked to 2015 antibiotic dispensing data from the Pharmaceutical Benefits Scheme (PBS), as well as other administrative health databases. We estimated the Defined Daily Dose (DDD) of systemic antibiotics dispensed, defined by an Anatomic Therapeutic Classification code beginning with J01, in 2015. We also conducted Poisson regression with robust standard errors to identify factors associated with antibiotic dispensing. Results Overall, 49.3% of 45 and Up Study participants had at least one systemic antibiotic dispensed in 2015 with a total of 392,856 prescriptions dispensed and an average of 36.5 DDDs/1000-persons/day in the study population. The quantity of antibiotics dispensed increased with increasing age (25.6 DDDs/1000/day in 15 general practitioner consultations in the last year (80.5 and 88.3 DDDs/1000/day, respectively). These factors remained strongly associated with greater antibiotic dispensing after adjusting for age, sex, education, income, area of residence and co-morbidities. Conclusions Residence in aged care facilities and high GP visits are associated with greater antibiotic dispensing. This study provides important evidence regarding high use groups for antimicrobial stewardship

High risk prescribing in older adults: Prevalence, clinical and economic implications and potential for intervention at the population level

Background: High risk prescribing can compromise independent wellbeing and quality of life in older adults. The aims of this project are to determine the prevalence, risk factors, clinical consequences, and costs of high risk prescribing, and to assess the impact of interventions on high risk prescribing in older people. Methods. The proposed project will utilise data from the 45 and Up Study, a large scale cohort of 267,153 men and women aged 45 and over recruited during 2006-2009 from the state of New South Wales, Australia linked to a range of administrative health datasets. High risk prescribing will be assessed using three indicators: polypharmacy (use of five or more medicines); Beers Criteria (an explicit measure of potentially inappropriate medication use); and Drug Burden Index (a pharmacologic dose-dependent measure of cumulative exposure to anticholinergic and sedative medicines). Individual risk factors from the 45 and Up Study questionnaire, and health system characteristics from health datasets that are associated with the likelihood of high risk prescribing will be identified. The main outcome measures will include hospitalisation (first admission to hospital, total days in hospital, cause-specific hospitalisation); admission to institutionalised care; all-cause mortality, and, where possible, cause-specific mortality. Economic costs to the health care system and implications of high risk prescribing will be also investigated. In addition, changes in high risk prescribing will be evaluated in relation to certain routine medicines-related interventions. The statistical analysis will be conducted using standard pharmaco-epidemiological methods including descriptive analysis, univariate and multivariate regression analysis, controlling for relevant confounding factors, using a number of different approaches. Discussion. The availability of large-scale data is useful to identify opportunities for improving prescribing, and health in older adults. The size of the 45 and Up Study, along with linkage to health databases provides an important opportunity to investigate the relationship between high risk prescribing and adverse outcomes in a real-world population of older adults. © 2013 Gnjidic et al.; licensee BioMed Central Ltd