Early human occupation of Australia's eastern seaboard.

Secure archaeological evidence for human occupation on the eastern seaboard of Australia before ~ 25,000 years ago has proven elusive. This has prompted some researchers to argue that the coastal margins remained uninhabited prior to 25 ka. Here we show evidence for human occupation beginning between 30 ± 6 and 49 ± 8 ka at Wallen Wallen Creek (WWC), and at Middle Canalpin Creek (MCA20) between 38 ± 8 and 41 ± 8 ka. Both sites are located on the western side of Minjerribah (North Stradbroke Island), the second largest sand island in the world, isolated by rising sea levels in the early Holocene. The earliest occupation phase at both sites consists of charcoal and heavily retouched stone artefacts made from exotic raw materials. Heat-treatment of imported silcrete artefacts first appeared in sediment dated to ~ 30,000 years ago, making these amongst Australia's oldest dated heat-treated artefacts. An early human presence on Minjerribah is further suggested by palaeoenvironmental records of anthropogenic burning beginning by 45,000 years ago. These new chronologies from sites on a remnant portion of the continental margin confirm early human occupation along Sahul's now-drowned eastern continental shelf.

R and Shiny for Cost-Effectiveness Analyses: Why and When? A Hypothetical Case Study.

INTRODUCTION: Health economics models are typically built in Microsoft Excel® owing to its wide familiarity, accessibility and perceived transparency. However, given the increasingly rapid and analytically complex decision-making needs of both the pharmaceutical industry and the field of health economics and outcomes research (HEOR), the demands of cost-effectiveness analyses may be better met by the programming language R. OBJECTIVE: This case study provides an explicit comparison between Excel and R for contemporary cost-effectiveness analysis. METHODS: We constructed duplicate cost-effectiveness models using Excel and R (with a user interface built using the Shiny package) to address a hypothetical case study typical of contemporary health technology assessment. RESULTS: We compared R and Excel versions of the same model design to determine the advantages and limitations of the modelling platforms in terms of (i) analytical capability, (ii) data safety, (iii) building considerations, (iv) usability for technical and non-technical users and (v) model adaptability. CONCLUSIONS: The findings of this explicit comparison are used to produce recommendations for when R might be more suitable than Excel in contemporary cost-effectiveness analyses. We conclude that selection of appropriate modelling software needs to consider case-by-case modelling requirements, particularly (i) intended audience, (ii) complexity of analysis, (iii) nature and frequency of updates and (iv) anticipated model run time.

A Case Study Examining the Usefulness of Cure Modelling for the Prediction of Survival Based on Data Maturity.

INTRODUCTION: Mixture modelling is increasingly being considered where a potential cure leads to a long life. Traditional methods use relative survival models for frail populations or cure models that have improper survival functions with theoretical infinite lifespans. Additionally, much of the work uses population data with long follow-up or theoretical data for method development. OBJECTIVE: This case study uses life table data to create a proper survival function in a real-world clinical trial context. In particular, we discuss the impact of the length of trial follow-up on the accuracy of model estimation and the impact of extrapolation to capture long-term survival. METHODS: A review of recent National Institute for Health and Clinical Excellence (NICE) immuno-oncological and chimeric antigen receptor (CAR) T-cell therapy submissions was performed to assess industry uptake and NICE acceptance of survival analysis methods incorporating the potential for long-term survivorship. The case study analysed a simulated trial-based dataset investigating a curative treatment with long-term mortality based on population life tables. The analysis examined three timepoints corresponding to early trial, end-of-trial follow-up and complete follow-up. Mixture modelling approaches were considered, including both cure modelling and relative survival approaches. The curves were evaluated based on the ability to estimate cure fractions and mean life in years within the time span the models are based on and when extrapolating to capture long-term behaviour. The survival curves were fitted with Weibull distributions using non-mixture and mixture cure models. RESULTS: The performance of the cure modelling methods depended on the relative maturity of the data, indicating that care is needed when deciding when the methods should be applied. For progression-free survival, the cure fraction simulated was 15%. The cure fractions estimated using the traditional mixture cure model were 43% (95% confidence interval [CI] 30-57) at the first analysis time point (40 months), 15% (95% CI 12-20) at the end-of-study follow-up (153 months) and 0% (95% CI 0-100) at the end of follow-up. Other standard cure modelling methods produced similar results. For overall survival, we observed a similar pattern of goodness of fit, with a good fit for the end-of-study follow-up and poor fit for the other two data cuts. However, in this case, the estimate of the cure fraction was below the true value in the first analysis data. CONCLUSIONS: This case study suggests cure modelling works well with data in which the disease-specific events have had time to occur. Care is needed when extrapolating from immature data, and further information should support the estimation rather than relying on statistical estimates based on the trial alone.

Frequentist and Bayesian meta-regression of health state utilities for multiple myeloma incorporating systematic review and analysis of individual patient data.

This analysis presents the results of a systematic review for health state utilities in multiple myeloma, as well as analysis of over 9,000 observations taken from registry and trial data. The 27 values identified from 13 papers are then synthesised in a frequentist nonparametric bootstrap model and a Bayesian meta-regression. Results were similar between the frequentist and Bayesian models with low utility on disease diagnosis (approximately 0.55), raising to approximately 0.65 on first line treatment and declining slightly with each subsequent line. Stem cell transplant was also found to be a significant predictor of health-related quality of life in both individual patient data and meta-regression, with an increased utility of approximately 0.06 across different models. The work presented demonstrates the feasibility of Bayesian methods for utility meta-regression, whilst also presenting an internally consistent set of data from the analysis of registry data. To facilitate easy updating of the data and model, data extraction tables and model code are provided as Data S1. The main limitations of the model relate to the low number of studies available, particularly in highly pretreated patients.

Is foreign direct investment good for health in low and middle income countries? An instrumental variable approach.

There is a scarcity of quantitative research into the effect of FDI on population health in low and middle income countries (LMICs). This paper investigates the relationship using annual panel data from 85 LMICs between 1974 and 2012. When controlling for time trends, country fixed effects, correlation between repeated observations, relevant covariates, and endogeneity via a novel instrumental variable approach, we find FDI to have a beneficial effect on overall health, proxied by life expectancy. When investigating age-specific mortality rates, we find a stronger beneficial effect of FDI on adult mortality, yet no association with either infant or child mortality. Notably, FDI effects on health remain undetected in all models which do not control for endogeneity. Exploring the effect of sector-specific FDI on health in LMICs, we provide preliminary evidence of a weak inverse association between secondary (i.e. manufacturing) sector FDI and overall life expectancy. Our results thus suggest that FDI has provided an overall benefit to population health in LMICs, particularly in adults, yet investments into the secondary sector could be harmful to health.

The relationship between international trade and non-nutritional health outcomes: A systematic review of quantitative studies.

Markets throughout the world have been reducing barriers to international trade and investment in recent years. The resulting increases in levels of international trade and investment have subsequently generated research interest into the potential population health impact. We present a systematic review of quantitative studies investigating the relationship between international trade, foreign direct investment and non-nutritional health outcomes. Articles were systematically collected from the SCOPUS, PubMed, EconLit and Web of Science databases. Due to the heterogeneous nature of the evidence considered, the 16 included articles were subdivided into individual level data analyses, selected country analyses and international panel analyses. Articles were then quality assessed using a tool developed as part of the project. Nine of the studies were assessed to be high quality, six as medium quality, and one as low quality. The evidence from the quantitative literature suggests that overall, there appears to be a beneficial association between international trade and population health. There was also evidence of the importance of foreign direct investment, yet a lack of research considering the direction of causality. Taken together, quantitative research into the relationship between trade and non-nutritional health indicates trade to be beneficial, yet this body of research is still in its infancy. Future quantitative studies based on this foundation will provide a stronger basis on which to inform relevant national and international institutions about the health consequences of trade policies.

The Cost Effectiveness of Maintenance Schedules Following Pulmonary Rehabilitation in Patients with Chronic Obstructive Pulmonary Disease: An Economic Evaluation Alongside a Randomised Controlled Trial.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) affects approximately 3 million people in the UK. An 8-week pulmonary rehabilitation (PR) course is recommended under current guidelines. However, studies show that initial benefits diminish over time. OBJECTIVE: We present here an economic evaluation conducted alongside a randomised controlled trial (RCT) of a low-intensity maintenance programme over a time horizon of 1 year delivered in UK primary and secondary care settings. METHODS: Patients with COPD who completed at least 60 % of a standard 8-week PR programme were randomised to a 2-h maintenance session at 3, 6 and 9 months (n = 73) or treatment as usual (n = 75). Outcomes were change in Chronic Respiratory Questionnaire (CRQ) score, EQ-5D-based QALYs, cost (price year 2014) to the UK NHS and social services over the 12 months following initial PR, and incremental cost-effectiveness ratios (ICERs). RESULTS: At 12 months, incremental cost to the NHS and social services was -£204.04 (95 % CI -£1522 to £1114). Incremental CRQ and QALY gains were -0.007 (-0.461 to 0.447) and +0.015 (-0.050 to 0.079), respectively. Based on point estimates, PR maintenance therefore dominates treatment as usual from the perspective of the NHS and social services in terms of cost per QALY gained. Whether it is cost effective in terms of CRQ depends on whether the £204 per patient could be reinvested elsewhere to a CRQ gain of greater than 0.007. However, there is much decision uncertainty: 95 % CIs around increments did not exclude zero, and there is a 72.9 % (72.5 %) probability that the ICER is below £20,000 (£30,000) per QALY. CONCLUSION: Future research should explore whether more intensive maintenance regimens offer benefit to patients at reasonable cost.

To dare or not to dare? Risk management by owls in a predator-prey foraging game.

In a foraging game, predators must catch elusive prey while avoiding injury. Predators manage their hunting success with behavioral tools such as habitat selection, time allocation, and perhaps daring-the willingness to risk injury to increase hunting success. A predator's level of daring should be state dependent: the hungrier it is, the more it should be willing to risk injury to better capture prey. We ask, in a foraging game, will a hungry predator be more willing to risk injury while hunting? We performed an experiment in an outdoor vivarium in which barn owls (Tyto alba) were allowed to hunt Allenby's gerbils (Gerbillus andersoni allenbyi) from a choice of safe and risky patches. Owls were either well fed or hungry, representing the high and low state, respectively. We quantified the owls' patch use behavior. We predicted that hungry owls would be more daring and allocate more time to the risky patches. Owls preferred to hunt in the safe patches. This indicates that owls manage risk of injury by avoiding the risky patches. Hungry owls doubled their attacks on gerbils, but directed the added effort mostly toward the safe patch and the safer, open areas in the risky patch. Thus, owls dared by performing a risky action-the attack maneuver-more times, but only in the safest places-the open areas. We conclude that daring can be used to manage risk of injury and owls implement it strategically, in ways we did not foresee, to minimize risk of injury while maximizing hunting success.