The Clinical Emergency Data Registry: Structure, Use, and Limitations for Research

The Clinical Emergency Data Registry (CEDR) is a qualified clinical data registry that collects data from participating emergency departments (EDs) in the United States for quality measurement, improvement, and reporting purposes. This article aims to provide an overview of the data collection and validation process, describe the existing data structure and elements, and explain the potential opportunities and limitations for ongoing and future research use. CEDR data are primarily collected for quality reporting purposes and are obtained from diverse sources, including electronic health records and billing data that are de-identified and stored in a secure, centralized database. The CEDR data structure is organized around clinical episodes, which contain multiple data elements that are standardized using common data elements and are mapped to established terminologies to enable interoperability and data sharing. The data elements include patient demographics, clinical characteristics, diagnostic and treatment procedures, and outcomes. Key limitations include the limited generalizability due to the selective nature of participating EDs and the limited validation and completeness of data elements not currently used for quality reporting purposes, including demographic data. Nonetheless, CEDR holds great potential for ongoing and future research in emergency medicine due to its large-volume, longitudinal, near real-time, clinical data. In 2021, the American College of Emergency Physicians authorized the transition from CEDR to the Emergency Medicine Data Institute, which will catalyze investments in improved data quality and completeness for research to advance emergency care.

Implementing Multilevel Network Meta-Regression for Time-To-Event Outcomes: A Case Study in Relapsed Refractory Multiple Myeloma

OBJECTIVES

Multilevel network meta-regression (ML-NMR) leverages individual patient data (IPD) and aggregate data from a network of randomized controlled trials (RCTs) to assess the comparative efficacy of multiple treatments, while adjusting for between-study differences. We provide an overview of ML-NMR for time-to-event outcomes and apply it to an illustrative case study, including example R code.

METHODS

The case study evaluated the comparative efficacy of idecabtagene vicleucel (ide-cel), selinexor+dexamethasone (Sd), belantamab mafodotin (BM), and conventional care (CC) for patients with triple-class exposed relapsed/refractory multiple myeloma in terms of overall survival. Single-arm clinical trials and real-world data were naively combined to create an aggregate data artificial RCT (aRCT) (MAMMOTH-CC versus DREAMM-2-BM versus STORM-2-Sd) and an IPD aRCT (KarMMa-ide-cel versus KarMMa-RW-CC). With some assumptions, we incorporated continuous covariates with skewed distributions, reported as median and range. The ML-NMR models adjusted for number of prior lines, triple-class refractory status, and age and were compared using the leave-one-out information criterion. We summarized predicted hazard ratios and survival (95% credible intervals) in the IPD aRCT population.

RESULTS

The Weibull ML-NMR model had the lowest leave-one-out information criterion. Ide-cel was more efficacious than Sd, BM, and CC in terms of overall survival. Effect modifiers had minimal impact on the model, and only triple-class refractory was a prognostic factor.

CONCLUSIONS

We demonstrate an application of ML-NMR for time-to-event outcomes and introduce code that can be used to aid implementation. Given its benefits, we encourage practitioners to utilize ML-NMR when population adjustment is necessary for comparisons of multiple treatments.

Challenges of Incorporating Life Cycle Drug Pricing in Cost-Effectiveness Models: A Review of Methods and Modeling Suggestions

OBJECTIVES

This study aimed to conduct a review of existing methods used to incorporate life cycle drug pricing (LCDP) in cost-effectiveness analyses (CEAs), identify common methodological challenges, and suggest modeling approaches for prospectively implementing LCDP in CEA.

METHODS

Two complementary searches were conducted in PubMed, combined with hand searching and reference mining, to identify English language full-text articles that explored (1) how drug prices change over time and (2) methods used to apply dynamic pricing in cost-effectiveness models (CEMs). Relevant articles were reviewed, and authors discussed the common methodological practices used in the literature and their associated challenges on prospectively implementing LCDP in CEMs. For each key challenge identified, we provide modeling suggestions to address the issue.

RESULTS

We screened 1200 studies based on title and abstract; 117 were reviewed for eligibility, and 47 individual studies were included across both searches. Variations in prices over a product's life cycle are complex and multifactorial, and models applying LCDP in CEA varied in their methodology. We identified 4 key challenges to modeling LCDP in CEA, including how to model price trends before and after loss of exclusivity, how to capture the effect of price changes on future patient cohorts, and how to report results.

CONCLUSION

Accurately quantifying the impact of LCDP requires careful consideration of multiple aspects pertaining to both the evolution of drug prices and how to reflect these in CEA. Although uncertainties remain, our findings can aid implementation and evaluation of LCDP in economic evaluations.

Artificial Intelligence to Automate Network Meta-Analyses: Four Case Studies to Evaluate the Potential Application of Large Language Models

BACKGROUND

The emergence of artificial intelligence, capable of human-level performance on some tasks, presents an opportunity to revolutionise development of systematic reviews and network meta-analyses (NMAs). In this pilot study, we aim to assess use of a large-language model (LLM, Generative Pre-trained Transformer 4 [GPT-4]) to automatically extract data from publications, write an R script to conduct an NMA and interpret the results.

METHODS

We considered four case studies involving binary and time-to-event outcomes in two disease areas, for which an NMA had previously been conducted manually. For each case study, a Python script was developed that communicated with the LLM via application programming interface (API) calls. The LLM was prompted to extract relevant data from publications, to create an R script to be used to run the NMA and then to produce a small report describing the analysis.

RESULTS

The LLM had a > 99% success rate of accurately extracting data across 20 runs for each case study and could generate R scripts that could be run end-to-end without human input. It also produced good quality reports describing the disease area, analysis conducted, results obtained and a correct interpretation of the results.

CONCLUSIONS

This study provides a promising indication of the feasibility of using current generation LLMs to automate data extraction, code generation and NMA result interpretation, which could result in significant time savings and reduce human error. This is provided that routine technical checks are performed, as recommend for human-conducted analyses. Whilst not currently 100% consistent, LLMs are likely to improve with time.

Artificial Intelligence to Automate Health Economic Modelling: A Case Study to Evaluate the Potential Application of Large Language Models

BACKGROUND

Current generation large language models (LLMs) such as Generative Pre-Trained Transformer 4 (GPT-4) have achieved human-level performance on many tasks including the generation of computer code based on textual input. This study aimed to assess whether GPT-4 could be used to automatically programme two published health economic analyses.

METHODS

The two analyses were partitioned survival models evaluating interventions in non-small cell lung cancer (NSCLC) and renal cell carcinoma (RCC). We developed prompts which instructed GPT-4 to programme the NSCLC and RCC models in R, and which provided descriptions of each model's methods, assumptions and parameter values. The results of the generated scripts were compared to the published values from the original, human-programmed models. The models were replicated 15 times to capture variability in GPT-4's output.

RESULTS

GPT-4 fully replicated the NSCLC model with high accuracy: 100% (15/15) of the artificial intelligence (AI)-generated NSCLC models were error-free or contained a single minor error, and 93% (14/15) were completely error-free. GPT-4 closely replicated the RCC model, although human intervention was required to simplify an element of the model design (one of the model's fifteen input calculations) because it used too many sequential steps to be implemented in a single prompt. With this simplification, 87% (13/15) of the AI-generated RCC models were error-free or contained a single minor error, and 60% (9/15) were completely error-free. Error-free model scripts replicated the published incremental cost-effectiveness ratios to within 1%.

CONCLUSION

This study provides a promising indication that GPT-4 can have practical applications in the automation of health economic model construction. Potential benefits include accelerated model development timelines and reduced costs of development. Further research is necessary to explore the generalisability of LLM-based automation across a larger sample of models.

Retrospective Comparison of Survival Projections for CAR T-Cell Therapies in Large B-Cell Lymphoma

BACKGROUND

Durable remission has been observed in patients with relapsed or refractory (R/R) large B-cell lymphoma (LBCL) treated with chimeric antigen receptor (CAR) T-cell therapy. Consequently, hazard functions for overall survival (OS) are often complex, requiring the use of flexible methods for extrapolations.

OBJECTIVES

We aimed to retrospectively compare the predictive accuracy of different survival extrapolation methods and evaluate the validity of goodness-of-fit (GOF) criteria-based model selection for CAR T-cell therapies in R/R LBCL.

METHODS

OS data were sourced from JULIET, ZUMA-1, and TRANSCEND NHL 001. Standard parametric, mixture cure, cubic spline, and mixture models were fit to multiple database locks (DBLs), with varying follow-up durations. GOF was assessed using the Akaike information criterion and Bayesian information criterion. Predictive accuracy was calculated as the mean absolute error (MAE) relative to OS observed in the most mature DBL.

RESULTS

For all studies, mixture cure and cubic spline models provided the best predictive accuracy for the least mature DBL (MAE 0.013‒0.085 and 0.014‒0.128, respectively). The predictive accuracy of the standard parametric and mixture models showed larger variation (MAE 0.024‒0.162 and 0.013‒0.176, respectively). With increasing data maturity, the predictive accuracy of standard parametric models remained poor. Correlation between GOF criteria and predictive accuracy was low, particularly for the least mature DBL.

CONCLUSIONS

Our analyses demonstrated that mixture cure and cubic spline models provide the most accurate survival extrapolations of CAR T-cell therapies in LBCL. Furthermore, GOF should not be the only criteria used when selecting the optimal survival model.

Challenges in conducting fractional polynomial and standard parametric network meta-analyses of immune checkpoint inhibitors for first-line advanced renal cell carcinoma

Aim: Network meta-analyses (NMAs) increasingly feature time-varying hazards to account for non-proportional hazards between different drug classes. This paper outlines an algorithm for selecting clinically plausible fractional polynomial NMA models. Methods: The NMA of four immune checkpoint inhibitors (ICIs) + tyrosine kinase inhibitors (TKIs) and one TKI therapy for renal cell carcinoma (RCC) served as case study. Overall survival (OS) and progression free survival (PFS) data were reconstructed from the literature, 46 models were fitted. The algorithm entailed a-priori face validity criteria for survival and hazards, based on clinical expert input, and predictive accuracy against trial data. Selected models were compared with statistically best-fitting models. Results: Three valid PFS and two OS models were identified. All models overestimated PFS, the OS model featured crossing ICI + TKI versus TKI curves as per expert opinion. Conventionally selected models showed implausible survival. Conclusion: The selection algorithm considering face validity, predictive accuracy, and expert opinion improved the clinical plausibility of first-line RCC survival models.

A review of HTA guidelines on societal and novel value elements

OBJECTIVES

Health technology assessment (HTA) organizations vary in terms of how they conduct assessments. We assess whether and to what extent HTA bodies have adopted societal and novel elements of value in their economic evaluations.

METHODS

After categorizing "societal" and "novel" elements of value, we reviewed fifty-three HTA guidelines. We collected data on whether each guideline mentioned each societal or novel element of value, and if so, whether the guideline recommended the element's inclusion in the base case, sensitivity analysis, or qualitative discussion in the HTA.

RESULTS

The HTA guidelines mention on average 5.9 of the twenty-one societal and novel value elements we identified (range 0-16), including 2.3 of the ten societal elements and 3.3 of the eleven novel value elements. Only four value elements (productivity, family spillover, equity, and transportation) appear in over half of the HTA guidelines, whereas thirteen value elements are mentioned in fewer than one-sixth of the guidelines, and two elements receive no mention. Most guidelines do not recommend value element inclusion in the base case, sensitivity analysis, or qualitative discussion in the HTA.

CONCLUSIONS

Ideally, more HTA organizations will adopt guidelines for measuring societal and novel value elements, including analytic considerations. Importantly, simply recommending in guidelines that HTA bodies consider novel elements may not lead to their incorporation into assessments or ultimate decision making.

Next-generation enhanced-efficiency fertilizers for sustained food security

Nitrogen losses in agricultural systems can be reduced through enhanced-efficiency fertilizers (EEFs), which control the physicochemical release from fertilizers and biological nitrogen transformations in soils. The adoption of EEFs by farmers requires evidence of consistent performance across soils, crops and climates, paired with information on the economic advantages. Here we show that the benefits of EEFs due to avoided social costs of nitrogen pollution considerably outweigh their costs-and must be incorporated in fertilizer policies. We outline new approaches to the design of EEFs using enzyme inhibitors with modifiable chemical structures and engineered, biodegradable coatings that respond to plant rhizosphere signalling molecules.

Economic Threshold Analysis of Supplementing Dairy Cow Diets with Betaine and Fat during a Heat Challenge: A Pre- and Post-Experimental Comparison

Simple Summary

Economic analysis can be used before animal experiments to estimate the change in production that would be needed for experimental treatments to be as equally profitable as the control treatment. After the experiment, the results can be examined to assess if the production threshold was met. This approach was applied before and after an animal experiment that tested the effect of feeding dietary supplements on the milk production of dairy cows experiencing a heat event in climate-controlled chambers. Heat stress reduces the milk yield of cows, but the inclusion of supplements such as betaine and fat could lessen the impact. The pre-experimental economic threshold analysis showed that cows fed a diet containing betaine, fat, or betaine plus fat would need to produce 1%, 9% and 11% more milk, respectively, to be equally as profitable as the control diet. Results from the subsequent animal experiment combined with previously modelled projections of heat stress conditions showed that supplementing diets with fat or betaine, but not in combination could exceed the milk production threshold required to be as profitable as the control diet.

Abstract

Ex ante economic analysis can be used to establish the production threshold for a proposed experimental diet to be as profitable as the control treatment. This study reports (1) a pre-experimental economic analysis to estimate the milk production thresholds for an experiment where dietary supplements were fed to dairy cows experiencing a heat challenge, and (2) comparison of these thresholds to the milk production results of the subsequent animal experiment. The pre-experimental thresholds equated to a 1% increase in milk production for the betaine supplement, 9% increase for the fat supplement, and 11% increase for fat and betaine in combination, to achieve the same contribution to farm profit as the control diet. For the post-experimental comparison, previously modelled climate predictions were used to extrapolate the milk production results from the animal experiment over the annual hot-weather period for the dairying region in northern Victoria, Australia. Supplementing diets with fat or betaine had the potential to produce enough extra milk to exceed the production thresholds, making either supplement a profitable alternative to feeding the control diet during the hot-weather period. Feeding fat and betaine in combination failed to result in the extra milk required to justify the additional cost when compared to the control diet.

The Potential of Deep Roots to Mitigate Impacts of Heatwaves and Declining Rainfall on Pastures in Southeast Australia

Declines in growing-season rainfall and increases in the frequency of heatwaves in southern Australia necessitate effective adaptation. The Sustainable Grazing Systems Pasture Model (SGS) was used to model the growth of three pasture species differing in root depth and root distribution under three different climate scenarios at two sites. The modelled metabolisable energy intake (in MJ) was used in a partial discounted net cash flow budget. Both the biophysical and economic modelling suggest that deep roots were advantageous in all climate scenarios at the long growing season site but provided no to little advantage at the short growing season site, likely due to the deep-rooted species drying out the soil profile earlier. In scenarios including climate change, the DM production of the deep-rooted species at the long growing season site averaged 386 kg/ha/year more than the more shallow-rooted species, while at the site with a shorter growing season it averaged 205 kg/ha/year less than the shallower-rooted species. The timing of the extra growth and pasture persistence strongly influenced the extent of the benefit. At the short growing season site other adaptation options such as summer dormancy will likely be necessary.

What Did Time Tell Us? A Comparison and Retrospective Validation of Different Survival Extrapolation Methods for Immuno-Oncologic Therapy in Advanced or Metastatic Renal Cell Carcinoma

BACKGROUND

The immuno-oncologic (IO) mechanism of action may lead to an overall survival (OS) hazard that changes over time, producing shapes that standard parametric extrapolation methods may struggle to reflect. Furthermore, selection of the most appropriate extrapolation method for health technology assessment is often based on trial data with limited follow-up.

OBJECTIVE

To examine this problem, we fitted a range of extrapolation methods to patient-level survival data from CheckMate 025 (NCT01668784, CM-025), a phase III trial comparing nivolumab with everolimus for previously treated advanced renal cell carcinoma (aRCC), to assess their predictive accuracy over time.

METHODS

Six extrapolation methods were examined: standard parametric models, natural cubic splines, piecewise models combining Kaplan-Meier data with an exponential or non-exponential distribution, response-based landmark models, and parametric mixture models. We produced three database locks (DBLs) at minimum follow-ups of 15, 27, and 39 months to align with previously published CM-025 data. A three-step evaluation process was adopted: (1) selection of the distribution family for each method in each of the three DBLs, (2) internal validation comparing extrapolation-based landmark and mean survival with the latest CM-025 dataset (minimum follow-up, 64 months), and (3) external validation of survival projections using clinical expert opinion and long-term follow-up data from other nivolumab studies in aRCC (CheckMate 003 and CheckMate 010).

RESULTS

All extrapolation methods, with the exception of mixture models, underestimated landmark and mean OS for nivolumab compared with CM-025 long-term follow-up data. OS estimates for everolimus tended to be more accurate, with four of the six methods providing landmark OS estimates within the 95% confidence interval of observed OS as per the latest dataset. The predictive accuracy of survival extrapolation methods fitted to nivolumab also showed greater variation than for everolimus. The proportional hazards assumption held for all DBLs, and a dependent log-logistic model provided reliable estimates of longer-term survival for both nivolumab and everolimus across the DBLs. Although mixture models and response-based landmark models provided reasonable estimates of OS based on the 39-month DBL, this was not the case for the two earlier DBLs. The piecewise exponential models consistently underestimated OS for both nivolumab and everolimus at clinically meaningful pre-specified landmark time points.

CONCLUSIONS

This aRCC case study identified marked differences in the predictive accuracy of survival extrapolation methods for nivolumab but less so for everolimus. The dependent log-logistic model did not suffer from overfitting to early DBLs to the same extent as more complex methods. Methods that provide more degrees of freedom may accurately represent survival for IO therapy, particularly if data are more mature or external data are available to inform the long-term extrapolations.

The impact of ewe lamb mating and different feeding strategies over summer–autumn on profit and risk: a case study in south-west Victoria

Context Mating ewe lambs at ~7 months of age is viewed as a way to increase the profit of sheep farms in south-west Victoria, Australia. For a successful mating and high reproductive rate, ewe lambs need to be of >40 kg liveweight and condition score 3 at mating. The region has a temperate Mediterranean climate, and as such, dry summer pastures do not provide adequate nutrition for the weight gain required over summer and autumn if ewe lambs are to be mated early. There is limited economic information on the whole-farm benefits and risks associated with different feeding strategies for meeting the feed requirements of mating ewe lambs. Aims The aims were to test, for a prime-lamb system, whether profit would be increased by the mating of ewe lambs and whether there would be a reduction in whole-farm business risk. We hypothesised that different forage systems would offer profit and risk advantages over current dry-pasture and supplement systems for growing out ewe lambs. Method The biophysical and economic characteristics of a prime-lamb case-study farm were modelled to examine how six different pasture and forage systems for mating ewe lambs would perform under varying seasonal, price and cost conditions. Systems 1 and 2 were based on perennial ryegrass and subterranean clover pastures. System 1 compared lambing at 2 years of age, and System 2 lambing at 1 year of age. The other four systems simulated the use of different forages on a portion of the farm to grow out the ewe lambs for lambing at 1 year of age: System 3, spring-sown forage brassica rape; System 4, spring-sown winter-type canola; and System 5, lucerne; System 6, as for System 4 but at a higher lamb marking rate. Results and conclusions Lambing at 1 year of age increased profit and reduced business risk compared with lambing at 2 years of age. Use of spring-sown canola or lucerne forage for ewe-lamb mating provided the best returns on capital relative to the risk involved. Use of spring-sown canola reduced variability of annual returns, in part because of the diversification of income received from both lamb and canola. Implications The results of this modelling study indicate that some feed systems can increase farm profit and reduce business risk.

A whole-farm investment analysis of a partial mixed ration feeding system for dairy cows

Aim A dairy farm in south-west Victoria was analysed to discern the impact on profit and risk of changing from a feeding system in the base case where grain was fed in the dairy and forage in the paddock, to a partial mixed ration (PMR) or a formulated grain mix (FGM) feeding system. Context A PMR feeding system involves feeding a well formulated mixed ration to a grazing dairy herd and typically requires the use of specialised machinery to mix and feed out the forage and grain components of the ration together onto a feed pad. In a FGM feeding system, the same formulated ration fed in the PMR system is used, but the grain component of the ration is fed using the existing feeding system in the dairy with the hay component fed in the paddock. Method The analysis used data from experiments recently performed to establish milk responses to mixed ration feeding under Australian conditions. The case study farm comprised 244 ha and a herd of 420 self-replacing Holstein-Friesian cows that calved from May to July. The herd feeding system was based on grazed pasture, grain fed in the dairy at milking and hay fed in the paddock. Supplementary feed comprised ~50% of metabolisable energy in the diet of the milking cows. The pre-existing feeding system was altered to incorporate either a PMR system or a FGM system. An increased herd size of an extra 100 cows, plus the PMR or FGM systems, was also tested. Key results All systems analysed were more profitable than the base case. Increasing the herd by 100 cows was the most profitable option for both the PMR and FGM systems, but intensifying the system by increasing cow numbers also had the most variability in profit. Conclusions and implications The FGM system was the most profitable system because milk production could be increased without the costs of extra labour, depreciation and repairs and maintenance associated with using a mixer wagon to feed the ration. The FGM system presents an option for farmers to expand or intensify their systems without needing to construct a feed pad or invest in extra machinery and equipment.

Comparison of accelerometer-derived physical activity levels between individuals with and without cancer: a UK Biobank study

Aim: To identify the difference in physical activity (PA) levels between individuals with and without cancer, and to estimate all-cause mortality associated with this difference. Methods: Current cancer, cancer survivor and cancer-free groups were identified from the UK Biobank. We used multivariate and Cox regression to estimate PA differences and association of PA with all-cause mortality. Results: Compared with the cancer-free individuals, participants in the two cancer groups had fewer minutes in moderate-to-vigorous PA per day in adjusted analyses. The PA difference was associated with higher mortality in the current cancer group. Conclusion: Patients with a history of cancer were less active than those without cancer, and PA is associated with increased mortality. PA improvement strategies in cancer patients must be explored.

Automated extraction of treatment patterns from social media posts: an exploratory analysis in renal cell carcinoma

Aim: The use of health-related social media forums by patients is increasing and the size of these forums creates a rich record of patient opinions and experiences, including treatment histories. This study aimed to understand the possibility of extracting treatment patterns in an automated manner for patients with renal cell carcinoma, using natural language processing, rule-based decisions, and machine learning. Patients & methods: Obtained results were compared with those from published observational studies. Results: 42 comparisons across seven therapies, three lines of treatment, and two-time periods were made; 37 of the social media estimates fell within the variation seen across the published studies. Conclusion: This exploratory work shows that estimating treatment patterns from social media is possible and generates results within the variation seen in published studies, although further development and validation of the approach is needed.

Validity of social media for assessing treatment patterns in oncology patients: a case study in melanoma

There is a need to understand how patients are managed in the real world to better understand disease burden and unmet need. Traditional approaches to gather these data include the use of electronic medical record (EMR) or claims databases; however, in many cases data access policies prevent rapid insight gathering. Social media may provide a potential source of real-world data to assess treatment patterns, but the limitations and biases of doing so have not yet been evaluated. Here, we assessed whether patient treatment patterns extracted from publicly available patient forums compare to results from more traditional EMR and claims databases. We observed that the 95% confidence intervals of proportions of treatments received at first, second, and third line for advanced/metastatic melanoma generated from unstructured social media data overlapped with 95% confidence intervals from proportions obtained from 1 or more traditional EMR/Claims databases. Social media may offer a valid data option to understand treatment patterns in the real world.

Why does a point of care guided transfusion algorithm not improve blood loss and transfusion practice in patients undergoing high-risk cardiac surgery? A prospective randomized controlled pilot study

Background

Adult cardiac surgery is often complicated by elevated blood losses that account for elevated transfusion requirements. Perioperative bleeding and transfusion of blood products are major risk factors for morbidity and mortality. Timely diagnostic and goal-directed therapies aim at the reduction of bleeding and need for allogeneic transfusions.

Methods

Single-centre, prospective, randomized trial assessing blood loss and transfusion requirements of 26 adult patients undergoing elective cardiac surgery at high risk for perioperative bleeding. Primary endpoint was blood loss at 24 h postoperatively. Random assignment to intra- and postoperative haemostatic management following either an algorithm based on conventional coagulation assays (conventional group: platelet count, aPTT, PT, fibrinogen) or based on point-of-care (PoC-group) monitoring, i.e. activated rotational thromboelastometry (ROTEM®) combined with multiple aggregometry (Multiplate®). Differences between groups were analysed using nonparametric tests for independent samples.

Results

The study was terminated after interim analysis (n = 26). Chest tube drainage volume was 360 ml (IQR 229-599 ml) in the conventional group, and 380 ml (IQR 310-590 ml) in the PoC-group (p = 0.767) after 24 h. Basic patient characteristics, results of PoC coagulation assays, and transfusion requirements of red blood cells and fresh frozen plasma did not differ between groups. Coagulation results were comparable. Platelets were transfused in the PoC group only.

Conclusion

Blood loss via chest tube drainage and transfusion amounts were not different comparing PoC- and central lab-driven transfusion algorithms in subjects that underwent high-risk cardiac surgery. Routine PoC coagulation diagnostics do not seem to be beneficial when actual blood loss is low. High risk procedures might not suffice as a sole risk factor for increased blood loss.

Trial registration

NCT01402739, Date of registration July 26, 2011.

Real-world data and the patient perspective: the PROmise of social media?

Understanding the patient perspective is fundamental to delivering patient-centred care. In most healthcare systems, however, patient-reported outcomes are not regularly collected or recorded as part of routine clinical care, despite evidence that doing so can have tangible clinical benefit. In the absence of the routine collection of these data, research is beginning to turn to social media as a novel means to capture the patient voice. Publicly available social media data can now be analysed with relative ease, bypassing many logistical hurdles associated with traditional approaches and allowing for accelerated and cost-effective data collection. Existing work has shown these data can offer credible insight into the patient experience, although more work is needed to understand limitations with respect to patient representativeness and nuances of captured experience. Nevertheless, linking social media to electronic medical records offers a significant opportunity for patient views to be systematically collected for health services research and ultimately to improve patient care.

Application of dynamic modeling for survival estimation in advanced renal cell carcinoma

Objective

In oncology, extrapolation of clinical outcomes beyond trial duration is traditionally achieved by parametric survival analysis using population-level outcomes. This approach may not fully capture the benefit/risk profile of immunotherapies due to their unique mechanisms of action. We evaluated an alternative approach—dynamic modeling—to predict outcomes in patients with advanced renal cell carcinoma. We compared standard parametric fitting and dynamic modeling for survival estimation of nivolumab and everolimus using data from the phase III CheckMate 025 study.

Methods

We developed two statistical approaches to predict longer-term outcomes (progression, treatment discontinuation, and survival) for nivolumab and everolimus, then compared these predictions against follow-up clinical trial data to assess their proximity to observed outcomes. For the parametric survival analyses, we selected a probability distribution based on its fit to observed population-level outcomes at 14-month minimum follow-up and used it to predict longer-term outcomes. For dynamic modeling, we used a multivariate Cox regression based on patient-level data, which included risk scores, and probability and duration of response as predictors of longer-term outcomes. Both sets of predictions were compared against trial data with 26- and 38-month minimum follow-up.

Results

Both statistical approaches led to comparable fits to observed trial data for median progression, discontinuation, and survival. However, beyond the trial duration, mean survival predictions differed substantially between methods for nivolumab (30.8 and 51.5 months), but not everolimus (27.2 and 29.8 months). Longer-term follow-up data from CheckMate 025 and phase I/II studies resembled dynamic model predictions for nivolumab.

Conclusions

Dynamic modeling can be a good alternative to parametric survival fitting for immunotherapies because it may help better capture the longer-term benefit/risk profile and support health-economic evaluations of immunotherapies.

Can health-related quality of life (HRQoL) predict conditional survival (CS) in metastatic renal cell carcinoma? Results from a large phase 3 trial

691

Background: In the absence of mature overall survival (OS) endpoints, interim clinical trial data can be used to predict long-term survival in patients (pts) with advanced malignancies and inform trial continuation, treatment preference, and reimbursement decisions. Research shows that HRQoL assessments can be associated with OS, offering potential utility for validated HRQoL scales. We describe a predictive model used to determine the extent to which HRQoL data could predict CS (survival conditional on progression at either 6 or 12 months). Methods: Using pt-level data from a large phase III trial of nivolumab vs everolimus, a simulation approach with a survival random forest algorithm identified factors statistically important in predicting CS from a large number of covariates measured at baseline. Stepwise Cox proportional hazard survival models were fitted using covariates identified as important. Baseline scores and change over time were tested to determine the influence on the predictive power of the HRQoL data. Results: For both nivolumab and everolimus, baseline FKSI values were significant predictors of CS; median survival times roughly doubled for pts with baseline FKSI scores ≥30 vs pts with scores < 30 (nivolumab, 31.3-16.6; everolimus, 26.6-11). Baseline FKSI scores were the most important predictor vs the other baseline covariates from the survival random forest simulation, and a statistically significant covariate when fitting a stepwise Cox proportional hazard survival model. Change in scores over time influenced CS for pts with high baseline scores, and pts who demonstrated improvement in scores vs baseline had significantly higher CS vs pts with low baseline and no improvement in scores vs baseline. However, when examining change in HRQoL score over time, the statistical importance of the covariate begins to diminish due to high correlations with factors such as adverse events and weight change. Conclusions: We found that HRQoL data, specifically the FKSI, could be useful in predicting CS, especially at the onset of a trial. The importance of the FKSI score in predicting CS could be a powerful complement to existing clinical prognostic factors.

Benefits and costs of grazing various proportions of perennial ryegrass and chicory for dairy production

Understanding the economic trade-off between changes in the supplementary feed required and the cost of pasture renovation is important when considering investing in alternative forages. Perennial ryegrass (Lolium perenne L.) is the main pasture species used for dairy production in temperate Australia. Alternatives to perennial ryegrass are grown to complement the seasonal growth pattern of perennial ryegrass, and to potentially increase annual dry matter (DM) yield. A case study analysis of a dairy farm in Gippsland was used to explore the benefits and costs over 15 years when either 0%, 20% or 40% of the milking area was sown to chicory (Cichorium intybus L.), with the balance sown to perennial ryegrass. Chicory was part of a 3-year pasture renovation cycle; in the year of establishment, annual ryegrass was sown in the autumn, with chicory sown in spring, followed by 27 months of production. This was compared with a 5-year renovation cycle of perennial ryegrass. Stocking rates of 3.3 and 2.5 cows/ha were modelled. A whole farm budget approach with stochastic simulation was used to quantify the potential effect on profit and risk. The profitability of growing chicory depended on the balance among (1) savings in supplementary feed costs during summer and autumn, and (2) possible reductions in the overall supply of DM during winter and early spring, and (3) increased pasture renovation costs. Stocking rate influenced the most profitable percentage of land sown to chicory. When stocking rate was 3.3 cows/ha, sowing 20% of the milking area to chicory returned a net present value (NPV) over 15 years AU$31 000 greater, on average, than did sowing 0% chicory, and AU$46 000 greater than sowing 40% chicory. With 2.5 cows/ha, sowing 40% of the milking area to chicory returned an NPV AU$39 000–AU$102 000 greater, on average, than did sowing either 20% or 0% chicory, respectively. The ratio of perennial ryegrass to chicory had little effect on the variability of NPV. For an individual farm, the most profitable percentage will fluctuate over time with variations in prices, seasonal conditions and management choices.

Development of a system to rank perennial ryegrass cultivars according to their economic value to dairy farm businesses in south-eastern Australia

Dairy production systems in south-eastern Australia are based primarily on grazed pasture. Perennial ryegrass (Lolium perenne L.) is the major grass species used in this region and farmers are faced with the challenge of choosing from more than 60 commercially available cultivars. This paper describes the development of a system termed as a forage value index that ranks the overall performance of perennial ryegrass cultivars relative to cultivar Victorian according to the summation of the estimated difference in the value of seasonal dry-matter (DM) yield of the cultivars. Average predicted seasonal DM yields were calculated by analysing the results of eight available perennial ryegrass plot trials across south-eastern Australia, using a multi-environment, multi-harvest linear mixed model. The differences in the model-predicted DM yield of each cultivar was compared with cultivar Victorian in each of five seasonal periods (autumn, winter, early spring, late spring, summer) to generate a series of performance values (1 per period) for each cultivar. Each performance value was then multiplied by an economic value (AU$/kg extra pasture grown) relating to each of four regions (Gippsland, northern Victoria, south-western Victoria, Tasmania) and seasonal period and aggregated to generate an overall forage value index rating for each cultivar. Economic values ranged from AU$0.11 to AU$0.39 per extra kilogram of DM grown, depending on the season and region, which translated into estimated benefits on dairy farms of up to AU$183 per ha per year for farmers that use high-yielding cultivars in place of cultivar Victorian perennial ryegrass.

Evaluating the economics of concentrate feeding decisions in grazing dairy cows

Purchased concentrates are a significant variable cost of a dairy business. Farm economic theory states that feeding supplements will enable a dairy farmer to improve profit as long as the marginal revenue received from the milk produced exceeds the marginal cost of the supplement. To do this, the quantities of milk, milk protein and milk fat produced from a unit of concentrate added to the diet are needed. Recent research has compiled results from short-term concentrate feeding experiments conducted in Victoria over a 30-year period. Using these data, relationships for the response of milk production to cereal grain supplements in dairy cows grazing temperate pastures have been developed and shown to be a better predictor than previous relationships. These response functions were used in the present study to investigate the economics of tactical (short-term; weekly, monthly or seasonally) and strategic (medium- to longer-term) supplementary feeding decisions in a pasture-based system, including, specifically, how much concentrate should be fed in a particular farm situation, given a certain feed cost and milk price. In the present paper, the relevant production economics method is explained and applied to determine the amount of supplement to feed that will maximise the margin of total extra milk income minus the total cost of supplement, thereby adding the most to farm profit. Currently, when dairy farmers make decisions about how much more supplement to feed their herd, they are making implicit judgements about the extra milk, and other potential benefits, that they expect to result as well as what the milk will be worth. More finely tuned decisions about feeding supplements based on comparing marginal cost and marginal revenue would add more to farm profit than decisions based on other common criteria, such as feeding supplement for maximum milk production. While some farmers may already be feeding supplements close to the point where marginal cost equals marginal revenue, the formal method of marginal analysis reported here makes explicit what is done implicitly at present and tests farmers’ intuitive decision-making. More detailed information about the responses to supplements and the costs and benefits of feeding supplements under particular circumstances at different times through the lactation has the potential to enable better, more profitable decisions to be made about feeding cows and managing the whole farm.

Evaluating the economics of short-term partial mixed ration feeding decisions for dairy cows

Recent research in Australia has measured the marginal milk production responses of cows grazing perennial-based pastures to supplements offered as a partial mixed ration (PMR). In the present study, the milk responses to PMR feeding developed under a restricted pasture allowance were used to examine the contribution to farm profit of decisions about short-term feeding (weekly, monthly). A short-term, or tactical, decision was considered to be one where the infrastructure and equipment needed to mix and feed out a formulated ration were already available. The decision was, therefore, the choice of whether to feed supplements as grain in the dairy at milking and forage in the paddock, or to feed the supplements as a mixed ration on a feed pad. Both of these options were assumed to exist for the farmer decision-maker, with the comparison of rations being based solely on the costs of supplement and milk income. The Control diet in the experiments comprised cereal grain fed in the dairy and pasture silage fed in the paddock, simulating a situation where pasture available for grazing was limiting. The PMR diet consisted of cereal grain, maize grain, maize silage and lucerne hay combined in a mixer wagon and fed on a feed pad. The PMR + canola diet was similar to the PMR diet, but included canola meal. The profitability of the diets for different amounts of supplement intake was compared by estimating the total income from milk produced minus the cost of the supplements. The results indicated that feeding the diet comprising PMR plus canola meal in early lactation contributed more to farm profit than did the Control diet of feeding grain in the dairy and forage in the paddock, or PMR feeding without canola meal, because of higher milk production. At a supplement intake of 12 kg DM/cow.day, the PMR + canola diet added AU$0.97/cow.day and AU$2.11/cow.day more to profit than the Control and PMR without canola meal diets, respectively. For a farm already equipped with a feed pad and mixer wagon, the benefits of feeding a mixed ration exceed the costs in early lactation. In late lactation, each diet made similar contributions to farm profit because of similar milk production.

The humanistic burden of advanced non-small cell lung cancer on patients and their caregivers

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Background: A diagnosis of advanced non-small cell lung cancer (aNSCLC) presents significant physical, emotional and financial challenges for patients and their caregivers. This study provides insight into the humanistic burden on patients and their caregivers, as the disease progresses. Methods: Data were taken from a chart review and a cross-sectional study of a NSCLC patients and caregivers in France, Germany and Italy. Physicians provided data on patients’ age, sex, stage, line of therapy and ECOG (Eastern Cooperative Oncology Group) performance status (PS). The patient survey assessed the patients’ health state (EQ-5D), impact on work/activities (WPAI) and on quality of life (EORTC QLQ-C30). The caregiver survey included the WPAI and Zarit Burden Interview (ZBI). Patient and caregiver outcomes were stratified by the patients’ ECOG PS from 0 to 4 (best to worst status). Statistical significance was assessed using Kruskal-Wallis tests. Results: 1,030 patients completed the survey (mean (SD) age: 64.5 years (10.1), 65.9% male); the majority were stage IV (88.4%) and most (70.5%) were receiving 1st line therapy. Caregiver forms were completed by 41.5% of patients’ caregivers; mean (SD) age: 53.5 years (12.5), 72.6% female; most were the patients’ partner (54.9%) or child (31.9%). In total, 19.4%, 43.5%, 27.4% and 9.7% of patients had a current ECOG PS of 0, 1, 2 or 3/4, respectively. All outcomes stratified by ECOG PS are reported below (all P < 0.0001). Conclusions: As patients’ functionality deteriorates, so do their outcomes relating to health utility, impairment and quality of life. This deterioration also increases the burden on the caregiver. This study was sponsored by Bristol-Myers Squibb. [Table: see text]

Simulation Modelling in Ophthalmology: Application to Cost Effectiveness of Ranibizumab and Aflibercept for the Treatment of Wet Age-Related Macular Degeneration in the United Kingdom

BACKGROUND

Previously developed models in ophthalmology have generally used a Markovian structure. There are a number of limitations with this approach, most notably the ability to base patient outcomes on best-corrected visual acuity (BCVA) in both eyes, which may be overcome using a different modelling structure. Simulation modelling allows for this to be modelled more precisely, and therefore may provide more accurate and relevant estimates of the cost effectiveness of ophthalmology interventions.

OBJECTIVE

This study aimed to explore the appropriateness of simulation modelling in ophthalmology, using the disease area of wet age-related macular degeneration (wAMD) as an example.

METHODS

A de novo economic model was built using a patient-level simulation, which compared ranibizumab with aflibercept in wAMD. Disease progression was measured using BCVA. Health-related quality of life (HRQoL) was estimated using a regression analysis linking BCVA in each eye to utility. The analysis was from the perspective of the National Health Service in the UK. Five different regression models were explored and were based on BCVA in either one eye or both eyes.

RESULTS

The model outputs provide some evidence to support the hypothesis that the analyses using the two-eye models for estimating HRQoL generate a more accurate estimation of incremental quality-adjusted life-years (QALYs) associated with the positive treatment effect for ranibizumab versus aflibercept. Second-order analysis broadly supported these findings, and showed that the variation in incremental costs was slightly lower than in incremental QALYs. The second-order analysis estimated similar incremental costs and a greater overall variation in incremental QALYs than the first-order analysis, suggesting important non-linearities within the model.

CONCLUSIONS

This analysis suggests that patient-level simulation models may be well suited to representing the real-world patient pathway in wAMD, particularly when aspects of disease progression cannot be adequately captured using a Markov structure. The benefits of a simulation approach can be demonstrated in the modelling of HRQoL as a function of BCVA in both eyes.

Comparing the profitability of a dairy business with alternative investments

In the present study, the profitability of a dairy-farm case study evaluated over the period 2003–2004 to 2014–2015 was compared with the performance of other dairy farms and other non-agricultural investments over the same time. Investments are generally made on the expectation that a net return will be earned that justifies using capital in one particular way rather than an alternative way. The expected, and actual, returns from capital invested in different assets will differ according to the risks involved. Investors choose an investment, and mixes of investments, that align with their goals, preferences for risk and anticipated returns over time. Dairy farming involves investing in assets, such as land and improvements, water, livestock, plant and equipment, and people, which are managed to produce milk and ultimately to earn a competitive return on capital. With uncertain seasonal conditions, fluctuating costs and prices, declining terms of trade, wide ranges of equity and management abilities, and a steady decline in the number of commercial farm businesses, it may be tempting to presume that investing in farming, and dairy farming in particular, is a hard road, leading to lower and more variable returns than investing in non-agricultural investment opportunities in the economy. This need not be the case. Analysis of how a dairy business in northern Victoria performed from 2003–2004 to 2014–2015 showed that this farm did well compared with (i) other dairy businesses in Victoria and (ii) alternative investments, such as shares, bonds and property, over the same time. Compound annual return to capital for the dairy farm over the 12 years studied was 12.4% (real, before tax). Over half the return came from the farming operations and the remainder came from owning assets that appreciated in value, particularly in this case, water. The dairy business that was studied was well managed and earned higher annual average returns than the average returns of investments with similar risk elsewhere in the economy, such as shares, and matched it with the best performing of these alternative investments.

Expanding a dairy business affects business and financial risk

Australia’s dairy farmers have expanded the size of their businesses in response to rising costs and falling prices. Dairy farmers pursuing increases in wealth encounter a greater risk associated with increased size, complexity and output. It is the consequences of risk that matter. Risk in a farm business can be partitioned into either business risk or financial risk. Previous research on changes to farm systems has primarily focussed on the impact of business risk, with less regard for financial risk. Our analysis has shown that expanding a farm business is likely to increase financial risk more than business risk. Before committing to the decision to expand their businesses, dairy farmers have control over the amount they borrow and, thus, some control over the exposure of their businesses to additional financial risk. Knowing the extra risk associated with extra debt is additional information that contributes to more informed decisions. In this research, an approach to assessing the change in business and financial risk associated with different expansion options is demonstrated.

Pasture and the theory of diversification

Diversifying farm activities can reduce the business risk of agricultural production. The aim of the present study was to investigate the effect of diversifying the types of dairy pastures sown on (1) the average seasonal growth rate (kg DM/ha/day) of pasture and (2) the variability of seasonal growth rate of pasture over time by diversifying the types of pastures grown on a dairy farm. This approach is similar to the approach used to assess the diversification of annual cropping activities, although repeated harvest of pasture by grazing animals and the seasonality of pasture DM production complicates the question. The question investigated was ‘How does substituting chicory (Cichorium intybus L.) or tall fescue (Festuca arundinaceae Schreb.) monocultures for a perennial ryegrass (Lolium perenne L.)–white clover (Trifolium repens L.) pasture in increasing proportions affect (1) the average growth rate (kg DM/ha.day) of pasture and (2) the variability of growth rate of pasture in each season?’. The biophysical model DairyMod was used to simulate 30 years growth of a mixed sward of perennial ryegrass and white clover and monocultures of chicory and tall fescue for two rain-fed locations in the high-rainfall zone of southern Australia. Including chicory in the pasture base had the potential to increase pasture growth rate during the summer–early autumn period compared with growing perennial ryegrass–white clover alone. This increase in pasture growth rate increased variability, and reduced growth rates in late autumn–winter and spring. The simulated growth rates of tall fescue and perennial ryegrass were strongly correlated in all seasons; hence, tall fescue did not reduce the variability of total DM. Further analysis would include price correlations and variability and consider the whole-farm implications. The analysis presented here for the high-rainfall zone showed that introducing alternative forages may have benefits in terms of increasing pasture growth rates at critical times of the production year, but the variability of the growth rate was not reduced.

Ranibizumab, verteporfin photodynamic therapy or observation for the treatment of myopic choroidal neovascularization: cost effectiveness in the UK

Purpose

The aim of this study was to evaluate the cost effectiveness of ranibizumab compared with verteporfin photodynamic therapy (vPDT) or no treatment (observation) in patients with visual impairment due to myopic choroidal neovascularization (CNV).

Methods

A Markov model with health states defined by best-corrected visual acuity and a 3-month cycle length was developed. It had a healthcare provider (UK National Health Service and personal social services) perspective, a lifetime time horizon, and was based on 2011 prices; future costs and health outcomes were discounted at 3.5 % per annum. Baseline characteristics were based on the phase III RADIANCE (Ranibizumab and vPDT Evaluation in Myopic CNV) study, and year 1 health-state transitions were based on this and the VIP (Verteporfin in Photodynamic Therapy) study. Extensive sensitivity analyses tested the robustness of the model.

Results

The lifetime cost of treating myopic CNV with ranibizumab was £12,866, whereas vPDT and observation were associated with total costs of £14,421 and £8,163, respectively. Ranibizumab treatment produced higher cumulative quality-adjusted life-years (QALYs; 12.99) than vPDT (12.60) or observation (12.45). Ranibizumab treatment was therefore dominant, with greater health gains and lower overall costs than vPDT. Ranibizumab was cost effective compared with observation, with an incremental cost-effectiveness ratio of £8,778/QALY. In the probabilistic sensitivity analysis, ranibizumab had a 100 % and 88 % probability of being cost effective compared with vPDT and observation, respectively, at a willingness-to-pay threshold of £20,000/QALY.

Conclusion

This study indicates that ranibizumab therapy is dominant over vPDT for the treatment of visual impairment due to CNV secondary to pathologic myopia in the UK healthcare setting and cost effective compared with observation.

Electronic supplementary material

The online version of this article (doi:10.1007/s40266-014-0216-y) contains supplementary material, which is available to authorized users.

Supplementary feeding options to alleviate the impacts of decreased water availability on dairy-farm economic performance in northern Victoria

The anticipated effects of climate change, competing demands from the environment, industry and urban users, and changes in water policy are likely to reduce the amount and increase the variability of water allocations to dairy farmers in northern Victoria. The way two irrigated dairy farms that differed in feedbase characteristics, herd size and farm area, would operate and perform with reduced and more variable water allocations was examined over 10 years. Strategies to manage the impact of changed water availability were tested; namely, increasing milk production by feeding more supplementary feed, changing the feed system to present supplements in a partial mixed ration (PMR), and increasing milk production by using a PMR. Neither farm was profitable under medium climate change, or if the conditions that generated the low inflows of water into irrigation supply dams between 1996–97 and 2006–07 prevailed, unless changes were made to the farm system. Feeding supplements in a well formulated mixed ration have the potential to increase the efficiency of metabolisable energy use and offers the opportunity to increase feed intake and milk production. A PMR system enabled one of the farms to maintain and increase profit under medium climate change conditions; however, risk, measured as variability in profit, also increased. Under more severe reductions in water availability, neither of the farms examined was profitable over the run of years. Changes to the farm system other than feeding additional supplementary feed to increase milk production and/or using a PMR system, would be needed to counteract the effects of reduced and more variable water availability and maintain profit.

A UK-based cost-utility analysis of indacaterol, a once-daily maintenance bronchodilator for patients with COPD, using real world evidence on resource use

INTRODUCTION

Chronic Obstructive Pulmonary Disease (COPD) is a chronic, progressive disease that is not curable. However, there are effective treatments available. In the UK, long-acting bronchodilators are first-line treatments for COPD patients requiring maintenance therapy, and there are several options available. The aim of this study is to establish, from the UK National Health Service (NHS) perspective, the cost-effectiveness profile of indacaterol, the first once-daily long-acting beta2-agonist (LABA), compared with tiotropium and salmeterol, in patients with moderate to severe COPD. In assessing the cost-effectiveness of COPD therapies, this study has the advantage of using real world evidence on the resource use associated with COPD management across the spectrum of the disease.

METHODS

A Markov model was developed with four health states following the GOLD classification for severity of airflow limitation. The model time horizon was 3 years, and the cycle length was 3 months. From each state, patients could experience a severe or non-severe exacerbation, move to a different COPD state, remain in the current state or die. Transition probabilities were based on data from the indacaterol clinical trials. The majority of the resource use data was taken from the Optimum Patient Care Research Database (OPCRD), which contains data from over 20,000 COPD patients in England and Scotland. Cost data were taken from UK-based sources and published literature and presented for the cost year 2011. Health-related quality of life was the main outcome of interest and utility data for the COPD states were based on data from the indacaterol clinical trials and disutility due to exacerbations were taken from the literature. Both one way and probabilistic sensitivity analyses were performed to test the robustness of the results.

RESULTS

Indacaterol dominated in the comparison with salmeterol producing an incremental QALY gain of 0.008 and cost savings of £110 per patient over a 3-year time horizon. In the comparison with tiotropium over the same time horizon, indacaterol remained the dominant strategy, producing an incremental QALY gain of 0.008 and cost savings of £248 per patient. The one-way sensitivity analysis indicates that the proportion of patients in each of the COPD stages and the mortality rate associated with Very Severe COPD are the variables with the largest impact on the results. The probabilistic sensitivity analyses showed that over 72 % and 89 % of the iterations when compared with salmeterol and tiotropium, respectively, produced dominant results for indacaterol.

CONCLUSION

The analyses demonstrate that indacaterol dominates both tiotropium and salmeterol in the base case and is likely to remain cost-effective under a range of assumptions.

Dairying in the Antipodes: recent past, near prospects

The majority of dairy farmers and processors in Australia and New Zealand are considered world class due to their ability to produce dairy products at a cost that is competitive on the world market without requirement for subsidy. International and domestic forces beyond the farm influence the international competitiveness of Antipodean dairy systems, as much or more than, the within-farm characteristics of the systems. Critical external forces include: world population growth, protein demand from increasingly wealthy developing countries, dairy supply from domestic and international producers, international dairy prices and exchange rate volatility. Within farm, the keys to persistent profitability, business survival, and growth will continue to be management ability and labour skill as well as the relationship between milksolids (milk fat + milk protein) produced per system and total production costs. Domestic forces will include competition for resources such as land, water, quality labour and capital, and public expectation that farms will meet the costs of community environmental and welfare objectives. Public and industry investment in research, development and extension in innovations that increase productivity is essential if dairying is to remain competitive. The operation of the comparative advantage principle determines which industries thrive, or decline, in an economy. New Zealand dairying has a strong comparative advantage over alternative pastoral industries which will continue. In Australia, the comparative advantage of dairy farming over alternative activities is less clear-cut. History shows that the best farmers and processors handle risks such as market and climate volatility and other challenges better than others, and their prospects are positive. However, world class performers in the future dairy industry will certainly not be all, or even the majority, of the current population of dairy farmers.

Potential impacts of negative associative effects between concentrate supplements, pasture and conserved forage for milk production and dairy farm profit

A case study and whole-farm modelling approach was used to examine the potential impacts of negative associative effects on milk production and economic performance of two dairy farms in northern Victoria. The two case studies differed in herd and farm size, calving pattern, forages grown and use of labour, but both had production systems based on grazed pasture, grain fed in the dairy at milking and conserved hay fed out in the paddock. The feeding system of each farm was altered by implementing a partial mixed ration (PMR), where cows grazed once a day and received supplements in a well formulated mix once a day. Negative associative effects between feeds were included in the biophysical modelling by deriving a relationship from published studies between declining neutral detergent fibre digestibility and increasing grain intake. Before applying a PMR system, both farms were profitable and earning competitive rates of return after tax, with mean real internal rate of return higher than 5%, and positive mean annual operating profit and mean net present value, at a discount rate of 5%. Feeding a PMR enabled both farms to increase profitability and internal rate of return, particularly if milk production was increased as well, but only when associative effects were less than those in the feeding system based on grain fed in the dairy and hay in the paddock. Increased profitability was also associated with higher standard deviation in annual operating profit, internal rate of return and net present value, in other words risk increased under the PMR feeding system, as the businesses would be more vulnerable to fluctuating supplementary feed prices.

The impact of system changes to a dairy farm in south-west Victoria: risk and increasing profitability

A case study modelling approach was used to examine changes to a dairy farm in south-west Victoria to maintain or increase profit in the future 5–10 years in the face of some ‘cost-price squeeze’, emphasising impacts on both returns and risk. Five changes to the status quo system were analysed. Each involved increasing pasture consumption on the milking area and non-milking leased area (where appropriate). The five changes were: (1) reducing leased non-milking area by 100 ha; (2) converting 60 ha of non-milking leased area to milking area, reducing leased non-milking area by 100 ha and reducing stocking rate on the milking area; (3) converting 187 ha of leased non-milking area to milking area, increasing herd size to 800 cows and reducing stocking rate on the milking area; (4) discarding all leased area, reducing herd size to 370 cows and reducing stocking rate; and (5) converting 127 ha of non-milking leased area to milking area, discarding all other lease arrangements and reducing stocking rate. Mean ± standard deviation of nominal owner’s equity at the end of Year 10 was $2.59M ± $1.33M, $5.42M ± $1.26M, $5.76M ± $1.21M, $7.47M ± $1.64M, $6.01M ± $0.78M and $6.10M ± $1.19M for the status quo and development options 1–5, respectively. For most but not all of the development options, the risk associated with the profit, cash and equity as measured by a range of indicators improved markedly over the performance of the farm system under the status quo. Both substantial increases and decreases in herd size were attractive. Irrespective of the direction of change in herd size, the most profitable options involved reducing stocking rate per ha and reducing purchased supplementary feed compared with the status quo. Significantly, changing to increase productivity greatly reduced the risk of having less equity at the end of Year 10 than the starting equity. Optimising the amount of home-grown grazed feed, and using purchased supplements efficiently are important, particularly if the milk being sold is subject to export market prices and variation. The most appropriate changes to dairy farm businesses in response to changes in the operating environment will vary from farm to farm – but maintaining the status quo in the face of change is not an option that meets farm family goals.

Hepatitis C virus NS3-4A serine protease inhibitors: SAR of moiety with improved potency

We have discovered that introduction of appropriate amino acid derivatives at P'2 position improved the binding potency of P3-capped alpha-ketoamide inhibitors of HCV NS3 serine protease. X-ray crystal structure of one of the inhibitors (43) bound to the protease revealed the importance of the P'2 moiety.

Binding affinities and geometries of various metal ligands in peptide deformylase inhibitors

Removal of the N-terminal formyl group from newly synthesized proteins by the enzyme peptide deformylase (PDF) is essential for normal growth of bacteria but not higher organisms. Recently, PDF has been explored as a target for novel antibiotics. Screening a collection of natural products for antimicrobial activity identified actinonin and two matlystatin analogs as potent PDF inhibitors. A number of synthetic analogs of these natural products were prepared and their inhibitory potency determined. Previous work has shown that PDF is an iron metalloproteinase also containing a catalytic glutamic acid residue. Ligation of the ferrous cation is an essential feature of potent inhibitors. The structures of actinonin, a matlystatin analog and a synthetic inhibitor complexed with PDF were determined by crystallography. A quantum mechanics/molecular mechanics (QM/MM) method was used to reproduce the geometry of known complexes, to predict the protonation state in the active site and to predict the geometry of additional complexes. The requirement for protonation of the active site glutamate anion is an important factor in understanding the potency of inhibitors with acidic iron-ligating groups such as hydroxamate and carboxylate. Even though potent inhibitors of PDF have been discovered, their bacteriostatic mechanism of action and the rapid development of resistance in vitro may limit their potential as antibacterial drugs.

A novel recombinant single-chain hepatitis C virus NS3-NS4A protein with improved helicase activity

Hepatitis C virus (HCV) nonstructural protein 3 (NS3) has been shown to possess protease and helicase activities and has also been demonstrated to spontaneously associate with nonstructural protein NS4A (NS4A) to form a stable complex. Previous attempts to produce the NS3/NS4A complex in recombinant baculovirus resulted in a protein complex that aggregated and precipitated in the absence of nonionic detergent and high salt. A single-chain form of the NS3/NS4A complex (His-NS4A21-32-GSGS-NS3-631) was constructed in which the NS4A core peptide is fused to the N-terminus of the NS3 protease domain as previously described (Taremi et al., 1998). This protein contains a histidine tagged NS4A peptide (a.a. 21-32) fused to the full-length NS3 (a.a. 3-631) through a flexible tetra amino acid linker. The recombinant protein was expressed to high levels in Escherichia coli, purified to homogeneity, and examined for NTPase, nucleic acid unwinding, and proteolytic activities. The single-chain recombinant NS3-NS4A protein possesses physiological properties equivalent to those of the NS3/NS4A complex except that this novel construct is stable, soluble and sixfold to sevenfold more active in unwinding duplex RNA. Comparison of the helicase activity of the single-chain recombinant NS3-NS4A with that of the full-length NS3 (without NS4A) and that of the helicase domain alone suggested that the presence of the protease domain and at least the NS4A core peptide are required for optimal unwinding activity.

Identification of a decapeptide with the binding reactivity for tumor-associated TAG72 antigen from a phage displayed library

Peptide ligands for tumor-associated TAG72 antigen were identified by screening a large, diverse decapeptide library expressed on the surface of filamentous phages. Fifty-eight clones of phages were selected from the eluates after the third round of biopanning and their DNA inserts were sequenced. A dominant decapeptide HYVSIELPDH (14/58) was found with the binding reactivity for TAG72 antigen in the TAG72-binding ELISA and Western dot blotting. It also showed a preferential binding to colonic adenocarcinomatous cells expressing the TAG72 antigen in the histochemical study. Therefore, this anti-TAG72 decapeptide may be useful in serving as the starting point with regard to further designing peptidomimetics for potential pharmaceuticals.