Pharmacokinetic-pharmacodynamic modelling of the cardiovascular effects of drugs – method development and application to magnesium in sheep

BACKGROUND: There have been few reports of pharmacokinetic models that have been linked to models of the cardiovascular system. Such models could predict the cardiovascular effects of a drug under a variety of circumstances. Limiting factors may be the lack of a suitably simple cardiovascular model, the difficulty in managing extensive cardiovascular data sets, and the lack of physiologically based pharmacokinetic models that can account for blood flow changes that may be caused by a drug. An approach for addressing these limitations is proposed, and illustrated using data on the cardiovascular effects of magnesium given intravenously to sheep. The cardiovascular model was based on compartments for venous and arterial blood. Blood flowed from arterial to venous compartments via a passive flow through a systemic vascular resistance. Blood flowed from venous to arterial via a pump (the heart-lung system), the pumping rate was governed by the venous pressure (Frank-Starling mechanism). Heart rate was controlled via the difference between arterial blood pressure and a set point (Baroreceptor control). Constraints were made to pressure-volume relationships, pressure-stroke volume relationships, and physical limits were imposed to produce plausible cardiac function curves and baseline cardiovascular variables. "Cardiovascular radar plots" were developed for concisely displaying the cardiovascular status. A recirculatory kinetic model of magnesium was developed that could account for the large changes in cardiac output caused by this drug. Arterial concentrations predicted by the kinetic model were linked to the systemic vascular resistance and venous compliance terms of the cardiovascular model. The kinetic-dynamic model based on a training data set (30 mmol over 2 min) was used to predict the results for a separate validation data set (30 mmol over 5 min). RESULTS: The kinetic-dynamic model was able to describe the training data set. A recirculatory kinetic model was a good description of the acute kinetics of magnesium in sheep. The volume of distribution of magnesium in the lungs was 0.89 L, and in the body was 4.02 L. A permeability term (0.59 L min(-1)) described the distribution of magnesium into a deeper (probably intracellular) compartment. The final kinetic-dynamic model was able to predict the validation data set. The mean prediction error for the arterial magnesium concentrations, cardiac output and mean arterial blood pressure for the validation data set were 0.02, 3.0 and 6.1%, respectively. CONCLUSION: The combination of a recirculatory model and a simple two-compartment cardiovascular model was able to describe and predict the kinetics and cardiovascular effects of magnesium in sheep

Public acceptability of financial incentives for smoking cessation in pregnancy and breastfeeding

Objective To survey public attitudes about incentives for smoking cessation in pregnancy and for breast feeding to inform trial design. Design Cross-sectional survey. Setting and participants British general public. Methods Seven promising incentive strategies had been identified from evidence syntheses and qualitative interview data from service users and providers. These were shopping vouchers for: (1) validated smoking cessation in pregnancy and (2) after birth; (3) for a smoke-free home; (4) for proven breast feeding; (5) a free breast pump; (6) payments to health services for reaching smoking cessation in pregnancy targets and (7) breastfeeding targets. Ipsos MORI used area quota sampling and home-administered computer-assisted questionnaires, with randomised question order to assess agreement with different incentives (measured on a five-point scale). Demographic data and target behaviour experience were recorded. Analysis used multivariable ordered logit models. Results Agreement with incentives was mixed (ranging from 34% to 46%) among a representative sample of 1144 British adults. Mean agreement score was highest for a free breast pump, and lowest for incentives for smoking abstinence after birth. More women disagreed with shopping vouchers than men. Those with lower levels of education disagreed more with smoking cessation incentives and a breast pump. Those aged 44 or under agreed more with all incentive strategies compared with those aged 65 and over, particularly provider targets for smoking cessation. Non-white ethnic groups agreed particularly with breastfeeding incentives. Current smokers with previous stop attempts and respondents who had breast fed children agreed with providing vouchers for the respective behaviours. Up to £40/month vouchers for behaviour change were acceptable (>85%). Conclusions Women and the less educated were more likely to disagree, but men and women of childbearing age to agree, with incentives designed for their benefit. Trials evaluating reach, impact on health inequalities and ethnic groups are required prior to implementing incentive interventions

Perceived barriers towards healthy eating and their association with fruit and vegetable consumption

Acknowledgements The authors would like to thank the anonymous reviewer, staff at the Health Economics Research Unit and the Rowett Institute of Nutrition and Health for helpful comments on the manuscript. Funding This work was supported by the Scottish Government Rural and Environment Science and Analytical Services (RESAS) division.Peer reviewedPostprin

What can secondary data tell us about household food insecurity in a high-income country context?

In the absence of routinely collected household food insecurity data, this study investigated what could be determined about the nature and prevalence of household food insecurity in Scotland from secondary data. Secondary analysis of the Living Costs and Food Survey (2007–2012) was conducted to calculate weekly food expenditure and its ratio to equivalised income for households below average income (HBAI) and above average income (non-HBAI). Diet Quality Index (DQI) scores were calculated for this survey and the Scottish Health Survey (SHeS, 2008 and 2012). Secondary data provided a partial picture of food insecurity prevalence in Scotland, and a limited picture of differences in diet quality. In 2012, HBAI spent significantly less in absolute terms per week on food and non-alcoholic drinks (£53.85) compared to non-HBAI (£86.73), but proportionately more of their income (29% and 15% respectively). Poorer households were less likely to achieve recommended fruit and vegetable intakes than were more affluent households. The mean DQI score (SHeS data) of HBAI fell between 2008 and 2012, and was significantly lower than the mean score for non-HBAI in 2012. Secondary data are insufficient to generate the robust and comprehensive picture needed to monitor the incidence and prevalence of food insecurity in Scotland.</p

"A Lot of People Are Struggling Privately. They Don’t Know Where to Go or They’re Not Sure of What to Do” : Frontline Service Provider Perspectives of the Nature of Household Food Insecurity in Scotland

Funding: This research was funded by NHS Health Scotland with additional funding support provided for Flora Douglas’ and Stephen Whybrow’s time from the Scottish Government’s RESAS programme. Core support to HERU from the Chief Scientist Office Scottish Government Health and Social Care Directorates and the University of Aberdeen is gratefully acknowledged. Acknowledgments: We would like to acknowledge Bill Gray and Dionne MacKinnon (BG NHS Health Scotland and DMcK, formerly of NHS Health Scotland) for their professional review and support during the project and our study participants for their time and expertise. We are also grateful to the anonymous reviewers of our paper for their time and extremely helpful contributions to this work.Peer reviewedPublisher PD

Implementation of the Australian Computer-Assisted Theragnostics (AusCAT) network for radiation oncology data extraction, reporting and distributed learning

Introduction: There is significant potential to analyse and model routinely collected data for radiotherapy patients to provide evidence to support clinical decisions, particularly where clinical trials evidence is limited or non-existent. However, in practice there are administrative, ethical, technical, logistical and legislative barriers to having coordinated data analysis platforms across radiation oncology centres. Methods: A distributed learning network of computer systems is presented, with software tools to extract and report on oncology data and to enable statistical model development. A distributed or federated learning approach keeps data in the local centre, but models are developed from the entire cohort. Results: The feasibility of this approach is demonstrated across six Australian oncology centres, using routinely collected lung cancer data from oncology information systems. The infrastructure was used to validate and develop machine learning for model-based clinical decision support and for one centre to assess patient eligibility criteria for two major lung cancer radiotherapy clinical trials (RTOG-9410, RTOG-0617). External validation of a 2-year overall survival model for non–small cell lung cancer (NSCLC) gave an AUC of 0.65 and C-index of 0.62 across the network. For one centre, 65% of Stage III NSCLC patients did not meet eligibility criteria for either of the two practice-changing clinical trials, and these patients had poorer survival than eligible patients (10.6 m vs. 15.8 m, P = 0.024). Conclusion: Population-based studies on routine data are possible using a distributed learning approach. This has the potential for decision support models for patients for whom supporting clinical trial evidence is not applicable

Implementation of the Australian Computer-Assisted Theragnostics (AusCAT) network for radiation oncology data extraction, reporting and distributed learning

Introduction There is significant potential to analyse and model routinely collected data for radiotherapy patients to provide evidence to support clinical decisions, particularly where clinical trials evidence is limited or non-existent. However, in practice there are administrative, ethical, technical, logistical and legislative barriers to having coordinated data analysis platforms across radiation oncology centres. Methods A distributed learning network of computer systems is presented, with software tools to extract and report on oncology data and to enable statistical model development. A distributed or federated learning approach keeps data in the local centre, but models are developed from the entire cohort. Results The feasibility of this approach is demonstrated across six Australian oncology centres, using routinely collected lung cancer data from oncology information systems. The infrastructure was used to validate and develop machine learning for model-based clinical decision support and for one centre to assess patient eligibility criteria for two major lung cancer radiotherapy clinical trials (RTOG-9410, RTOG-0617). External validation of a 2-year overall survival model for non-small cell lung cancer (NSCLC) gave an AUC of 0.65 and C-index of 0.62 across the network. For one centre, 65% of Stage III NSCLC patients did not meet eligibility criteria for either of the two practice-changing clinical trials, and these patients had poorer survival than eligible patients (10.6 m vs. 15.8 m, P = 0.024). Conclusion Population-based studies on routine data are possible using a distributed learning approach. This has the potential for decision support models for patients for whom supporting clinical trial evidence is not applicable

Determination of Baroreflex Sensitivity during the Modified Oxford Maneuver by Trigonometric Regressive Spectral Analysis

BACKGROUND: Differences in spontaneous and drug-induced baroreflex sensitivity (BRS) have been attributed to its different operating ranges. The current study attempted to compare BRS estimates during cardiovascular steady-state and pharmacologically stimulation using an innovative algorithm for dynamic determination of baroreflex gain. METHODOLOGY/PRINCIPAL FINDINGS: Forty-five volunteers underwent the modified Oxford maneuver in supine and 60° tilted position with blood pressure and heart rate being continuously recorded. Drug-induced BRS-estimates were calculated from data obtained by bolus injections of nitroprusside and phenylephrine. Spontaneous indices were derived from data obtained during rest (stationary) and under pharmacological stimulation (non-stationary) using the algorithm of trigonometric regressive spectral analysis (TRS). Spontaneous and drug-induced BRS values were significantly correlated and display directionally similar changes under different situations. Using the Bland-Altman method, systematic differences between spontaneous and drug-induced estimates were found and revealed that the discrepancy can be as large as the gain itself. Fixed bias was not evident with ordinary least products regression. The correlation and agreement between the estimates increased significantly when BRS was calculated by TRS in non-stationary mode during the drug injection period. TRS-BRS significantly increased during phenylephrine and decreased under nitroprusside. CONCLUSIONS/SIGNIFICANCE: The TRS analysis provides a reliable, non-invasive assessment of human BRS not only under static steady state conditions, but also during pharmacological perturbation of the cardiovascular system

Small-cell lung cancer in England: trends in survival and chemotherapy using the National Lung Cancer Audit

Background: The purpose of this study was to identify trends in survival and chemotherapy use for individuals with smallcell lung cancer (SCLC) in England using the National Lung Cancer Audit (NLCA). Methods: We used data from the NLCA database to identify people with histologically proven SCLC from 2004–2011. We calculated the median survival by stage and assessed whether patient characteristics changed over time. We also assessed whether the proportion of patients with records of chemotherapy and/or radiotherapy changed over time. Results: 18,513 patients were diagnosed with SCLC in our cohort. The median survival was 6 months for all patients, 1 year for those with limited stage and 4 months for extensive stage. 69% received chemotherapy and this proportion changed very slightly over time (test for trends p = 0.055). Age and performance status of patients remained stable over the study period, but the proportion of patients staged increased (p-value,0.001), mainly because of improved data completeness. There has been an increase in the proportion of patients that had a record of receiving both chemotherapy and radiotherapy each year (from 19% to 40% in limited and from 9% to 21% in extensive stage from 2004 to 2011). Patients who received chemotherapy with radiotherapy had better survival compared with any other treatment (HR 0.24, 95% CI 0.23–0.25). Conclusion: Since 2004, when the NLCA was established, the proportion of patients with SCLC having chemotherapy has remained static. We have found an upward trend in the proportion of patients receiving both chemotherapy and radiotherapy which corresponded to a better survival in this group, but as it only applied for a small proportion of patients, it was not enough to change the overall survival