A genetic and spatial Bayesian analysis of mastitis resistance

A nationwide health card recording system for dairy cattle was introduced in Norway in 1975 (the Norwegian Cattle Health Services). The data base holds information on mastitis occurrences on an individual cow basis. A reduction in mastitis frequency across the population is desired, and for this purpose risk factors are investigated. In this paper a Bayesian proportional hazards model is used for modelling the time to first veterinary treatment of clinical mastitis, including both genetic and environmental covariates. Sire effects were modelled as shared random components, and veterinary district was included as an environmental effect with prior spatial smoothing. A non-informative smoothing prior was assumed for the baseline hazard, and Markov chain Monte Carlo methods (MCMC) were used for inference. We propose a new measure of quality for sires, in terms of their posterior probability of being among the, say 10% best sires. The probability is an easily interpretable measure that can be directly used to rank sires. Estimating these complex probabilities is straightforward in an MCMC setting. The results indicate considerable differences between sires with regards to their daughters disease resistance. A regional effect was also discovered with the lowest risk of disease in the south-eastern parts of Norway.     

The number needed to treat: a clinically useful nomogram in its proper context.

The number needed to treat is a meaningful way of expressing the benefit of an active treatment over a control. It can be used either for summarising the results of a therapeutic trial or for medical decision making about an individual patient, but its use at the bedside has been impeded by the need for time consuming calculations. A nomogram has therefore been devised that will greatly simplify the calculations. Since calculations are now easy, the number needed to treat can be used to access the value of several interventions, although it does have its limitations. In particular it should not be used when it is not known whether the relative risk reduction associated with an intervention is constant for all levels of risk, or for periods of time longer than that studied in the original trials.     

Influence of method of reporting study results on decision of physicians to prescribe drugs to lower cholesterol concentration.

OBJECTIVE--To determine whether the reporting of study results by using reductions in relative or absolute risk and the number needed to treat affects the views of physicians about the effectiveness of drugs to lower lipid concentrations and decisions about treatment. DESIGN--Random allocation of two questionnaires presenting the results of three end points of the Helsinki heart study as results from separate trials by using reduction in either relative or absolute risk. In both questionnaires one end point was also presented by showing person years of treatment needed to prevent one myocardial infarction. The effectiveness of lipid lowering drugs was assessed for all end points on an 11 point scale. For each study result the likelihood to treat hypercholesterolaemia of 7.5 mmol/l in a healthy man had to be indicated on a seven point scale. SUBJECTS--Random sample of 802 internists and general practitioners representative of providers of primary care in Switzerland. RESULTS--The response rate was 69.6% (558). For the prevention of fatal and non-fatal myocardial infarction the mean ratings of effectiveness of lipid lowering drugs were 0.45 (95% confidence interval 0.21 to 0.69) and 1.39 (1.09 to 1.68) scale points lower when the reduction of absolute risk or number needed to treat were reported instead of the relative risk reduction (both P < 0.001). Physicians receiving trial results for identical end points in form of absolute reduction of risk or number needed to treat were less inclined to treat hypercholesterolaemia (both P < 0.001). CONCLUSIONS--Physicians'' views of the effectiveness of lipid lowering drugs and the decision to prescribe such drugs is affected by the predominant use of reduction of relative risk in trial reports and advertisements.     

Quantification of Treatment Effect Modification on Both an Additive and Multiplicative Scale

BackgroundIn both observational and randomized studies, associations with overall survival are by and large assessed on a multiplicative scale using the Cox model. However, clinicians and clinical researchers have an ardent interest in assessing absolute benefit associated with treatments. In older patients, some studies have reported lower relative treatment effect, which might translate into similar or even greater absolute treatment effect given their high baseline hazard for clinical events.MethodsThe effect of treatment and the effect modification of treatment were respectively assessed using a multiplicative and an additive hazard model in an analysis adjusted for propensity score in the context of coronary surgery.ResultsThe multiplicative model yielded a lower relative hazard reduction with bilateral internal thoracic artery grafting in older patients (Hazard ratio for interaction/year = 1.03, 95%CI: 1.00 to 1.06, p = 0.05) whereas the additive model reported a similar absolute hazard reduction with increasing age (Delta for interaction/year = 0.10, 95%CI: -0.27 to 0.46, p = 0.61). The number needed to treat derived from the propensity score-adjusted multiplicative model was remarkably similar at the end of the follow-up in patients aged < = 60 and in patients >70.ConclusionsThe present example demonstrates that a lower treatment effect in older patients on a relative scale can conversely translate into a similar treatment effect on an additive scale due to large baseline hazard differences. Importantly, absolute risk reduction, either crude or adjusted, can be calculated from multiplicative survival models. We advocate for a wider use of the absolute scale, especially using additive hazard models, to assess treatment effect and treatment effect modification.     

5-alpha-Reductase Inhibitors Prevent the Progression of Benign Prostatic Hyperplasia

Lower urinary tract symptoms (LUTS) associated with clinical benign prostatic hyperplasia (BPH) are a common occurrence in aging men, causing bother and interference with daily activities and affecting disease-specific quality of life. There is increasing evidence to suggest that, in many patients, the signs and symptoms of BPH are progressive. Progression can be measured as continued growth of the prostate gland; worsening of symptoms, bother, or quality of life; deterioration of urinary flow rate; episodes of acute urinary retention (AUR); and need for prostate-related surgery. Furthermore, it has become clear that the risk of disease progression increases with age as well as with increasing prostate volume and serum prostate-specific antigen (PSA) level. The 5-alpha-reductase inhibitor finasteride has been shown not only to improve symptoms, bother, and quality of life but also to prevent progression to AUR and surgery, with a relative risk reduction of over 50%. As the risk for such progression is higher in patients with larger glands or higher serum PSA values at baseline, it is in those patients that finasteride induces an even greater risk reduction, making it a cost-effective treatment choice for patients with LUTS associated with prostatic enlargement.     

A minimum version of log-rank test for testing the existence of cancer cure using relative survival data

Cancer survival is one of the most important measures to evaluate the effectiveness of treatment and early diagnosis. The ultimate goal of cancer research and patient care is the cure of cancer. As cancer treatments progress, cure becomes a reality for many cancers if patients are diagnosed early and get effective treatment. If a cure does exist for a certain type of cancer, it is useful to estimate the time of cure. For cancers that impose excess risk of mortality, it is informative to understand the difference in survival between cancer patients and the general cancer-free population. In population-based cancer survival studies, relative survival is the standard measure of excess mortality due to cancer. Cure is achieved when the survival of cancer patients is equivalent to that of the general population. This definition of cure is usually called the statistical cure, which is an important measure of burden due to cancer. In this paper, a minimum version of the log-rank test is proposed to test the equivalence of cancer patients' survival using the relative survival data. Performance of the proposed test is evaluated by simulation. Relative survival data from population-based cancer registries in SEER Program are used to examine patients' survival after diagnosis for various major cancer sites.     

Testing and estimation of proportion (or risk) ratio under the matched‐pair design with multiple binary endpoints

The proportion ratio (PR) of responses between an experimental treatment and a control treatment is one of the most commonly used indices to measure the relative treatment effect in a randomized clinical trial. We develop asymptotic and permutation‐based procedures for testing equality of treatment effects as well as derive confidence intervals of PRs for multivariate binary matched‐pair data under a mixed‐effects exponential risk model. To evaluate and compare the performance of these test procedures and interval estimators, we employ Monte Carlo simulation. When the number of matched pairs is large, we find that all test procedures presented here can perform well with respect to Type I error. When the number of matched pairs is small, the permutation‐based test procedures developed in this paper is of use. Furthermore, using test procedures (or interval estimators) based on a weighted linear average estimator of treatment effects can improve power (or gain precision) when the treatment effects on all response variables of interest are known to fall in the same direction. Finally, we apply the data taken from a crossover clinical trial that monitored several adverse events of an antidepressive drug to illustrate the practical use of test procedures and interval estimators considered here.     

Measurement of nitrogenase activity in legume root nodules: In defense of the acetylene reduction assay

The closed acetylene reduction assay has been used as a measure of nitrogenase activity and an indicator of N₂ fixation in Rhizobium/legume symbioses for 25 years. However, starting 10 years ago this assay has come under harsh criticism as being inaccurate. Currently, confusion exists regarding the conditions under which the acetylene reduction assay can be used accurately, or whether it can be used at all as a measure of nitrogenase activity. This article reviews the circumstance that has lead to this confusion. The author argues that under the proper assay conditions and with the appropriate checks, the closed acetylene reduction assay is still a valuable tool in assessing relative differences in nitrogenase activity in Rhizobium/legume symbioses.     

Extensions of the probabilistic ranking metrics of competing treatments in network meta-analysis to reflect clinically important relative differences on many outcomes

One of the key features of network meta-analysis is ranking of interventions according to outcomes of interest. Ranking metrics are prone to misinterpretation because of two limitations associated with the current ranking methods. First, differences in relative treatment effects might not be clinically important and this is not reflected in the ranking metrics. Second, there are no established methods to include several health outcomes in the ranking assessments. To address these two issues, we extended the P-score method to allow for multiple outcomes and modified it to measure the mean extent of certainty that a treatment is better than the competing treatments by a certain amount, for example, the minimum clinical important difference. We suggest to present the tradeoff between beneficial and harmful outcomes allowing stakeholders to consider how much adverse effect they are willing to tolerate for specific gains in efficacy. We used a published network of 212 trials comparing 15 antipsychotics and placebo using a random effects network meta-analysis model, focusing on three outcomes; reduction in symptoms of schizophrenia in a standardized scale, all-cause discontinuation, and weight gain.     

Efficacy of Standard and Intensive Statin Treatment for the Secondary Prevention of Cardiovascular and Cerebrovascular Events in Diabetes Patients: A Meta-Analysis

Aims

To estimate the efficacy of standard and intensive statin treatment in the secondary prevention of major cardiovascular and cerebrovascular events in diabetes patients.

Methods

A systematic search was conducted in Medline over the years 1990 to September 2013. Randomized, double-blind, clinical trials comparing a standard-dose statin with placebo or a standard-dose statin with an intensive-dose statin for the secondary prevention of cardiovascular and cerebrovascular events in diabetes patients were selected. Trial and patient characteristics were extracted independently by two researchers. The combined effect on the composite primary endpoint was measured with a fixed-effect model. Potential publication bias was examined with a funnel plot.

Results

Five trials were included in the analysis comparing standard-dose statins with placebo with a total of 4 351 participants. Four trials were included for comparing standard-dose with intensive-dose statins, including 4 805 participants. Compared with placebo, standard-dose statin treatment resulted in a significant relative risk (RR) reduction of 15% in the occurrence of any major cardiovascular or cerebrovascular event (RR 0.85, 95% CI 0.79–0.91). Compared with standard-dose statin treatment, intensive-dose statin treatment resulted in an additional 9% relative risk reduction (RR 0.91, 95% CI 0.84–0.98).

Conclusion

Treatment with standard-dose statins to prevent cardiovascular or cerebrovascular events in diabetes patients with manifest cardiovascular disease results in an estimated 15% relative risk reduction and intensive-dose statin treatment adds 9%. If proven cost-effective, more intensive statin treatment should be recommended for diabetes patients at high cardiovascular risk.     

Application of the Hazard Quotient Method in Remedial Decisions: A Comparison of Human and Ecological Risk Assessments

This paper evaluates the relative roles of the human health hazard index (HI) and the ecological risk assessment hazard quotient (HQ) in remedial decision-making. Through an analysis of HI outcomes drawn from Superfund Records of Decision, the reduced importance of the HI statistic in human health risk assessments is demonstrated, and the high visibility of the ecological risk assessment (ERA) HQ for terrestrial receptors (birds and mammals) is underscored. Three HQ method limitations common to both HHRA and ERA, deriving either from the mathematical construct of the HQ (a simple binary measure, indicating that an animal's exposure either exceeds its toxicity value or does not) or from dose-response outcomes in animal trials, are reviewed. Two additional HQ limitations unique to ERA (i.e., a propensity for the HQ to easily exceed its threshold value, and a propensity for it to assume values that are unreasonably high), and deriving from the complexities of estimating bird and mammal dietary intakes of contaminants and the availability of toxicological effects information, are also identified. The paper cautions of the potential to err in concluding that terrestrial site receptors are at risk when the HQ threshold is exceeded, and regardless of the toxicological information (NOAELs, LOAELs, etc.) used. It recognizes that because other methods of terrestrial assessment are presently unavailable, HQs are sometimes, out of necessity, used to justify a remedial action. The analysis and discussion are intended to remind ecological risk assessors that the HQ is a measure of a level of concern only and not a measure of risk     

A measure of explained risk in the proportional hazards model

A measure of explained risk is developed for application with the proportional hazards model. The statistic, which is called the estimated explained relative risk, has a simple analytical form and is unaffected by censoring that is independent of survival time conditional on the covariates. An asymptotic confidence interval for the limiting value of the estimated explained relative risk is derived, and the role of individual factors in the computation of its estimate is established. Simulations are performed to compare the results of the estimated explained relative risk to other known explained risk measures with censored data. Prostate cancer data are used to demonstrate an analysis incorporating the proposed approach.     

Costs and cost effectiveness of health checks conducted by nurses in primary care: the Oxcheck study.

OBJECTIVE--To measure the costs and cost effectiveness of the Oxcheck cardiovascular risk factor screening and intervention programme. DESIGN--Cost effectiveness analysis of a randomised controlled trial using clinical and economic data taken from the trial. SETTING--Five general practices in Luton and Dunstable, England. SUBJECTS--2205 patients who attended a health check in 1989-90 and were scheduled for re-examination in 1992-3 (intervention group); 1916 patients who attended their initial health check in 1992-3 (control group). Participants were men and women aged 35-64 years. INTERVENTION--Health check conducted by nurse, with health education and follow up according to degree of risk. MAIN OUTCOME MEASURES--Cost of health check programme; cost per 1% reduction in coronary risk. RESULTS--Health check and follow up cost 29.27 pounds per patient. Estimated programme cost per 1% reduction in coronary risk per participant was between 1.46 pounds and 2.25 pounds; it was nearly twice as much for men as women. CONCLUSIONS--The cost to the practice of implementing Oxcheck-style health checks in an average sized practice of 7500 patients would be 47,000 pounds, a proportion of which could be paid for through staff pay reimbursements and Band Three health promotion target payments. This study highlights the considerable difficulties faced when calculating the costs and benefits of a health promotion programme. Economic evaluations should be integrated into the protocols of randomised controlled trials to enable judgments to be made on the relative cost effectiveness of different prevention strategies.     

Evaluation of Drugs for Treating Obesity

Criteria for the evaluation of new drugs to treat obesity are important as guides for designing clinical trials to test these agents. These criteria must be developed in relation to the realities of obesity, which is a chronic disease associated with morbidity and mortality that is increased by visceral fat deposits. The observation that patients regain weight after stopping drug treatment for obesity argues for the proposition that drugs work only when taken and NOT that the drugs are ineffective. The analogy between the development of treatments for obesity to those for the treatment of hypertension is used to highlight potential areas for new developments. Several features of an ideal drug for the treatment of obesity are suggested. Criteria for evaluating new drugs include both primary and secondary endpoints. The primary endpoint for an anti-obesity drug should be weight loss, possibly by category of success. Losses of total body fat or visceral fat might be alternative primary endpoints. Secondary endpoints include reduction in risk factors for associated diseases and improvement in the quality of life. In trials where vigorous placebo designs including highly aggressive behavior modification or very-low-calorie diets were used, it may be difficult or impossible to detect a response to a drug.     

Therapeutic priorities of Canadian internists.

We surveyed 175 members of the Canadian Society of Internal Medicine to determine how they would rank seven commonly used treatments as to their clinical usefulness. A total of 70% of the respondents judged that the treatment of severe hypertension was the most beneficial. Coronary artery bypass surgery and treatment with acetylsalicylic acid for transient ischemic attacks were ranked next most useful. Cholestyramine therapy for hypercholesterolemia, the treatment of mild hypertension, isoniazid therapy for inactive tuberculosis and carotid endarterectomy in patients with mild stroke formed the final cluster. Except for treatment of severe hypertension there was a wide variation in the physicians'' enthusiasm for the various treatments. Possible explanations for this variation include physicians'' lack of awareness of the results of clinical trials, the wide range of risk reductions found in various trials of the same therapy, an unwillingness by physicians to generalize from clinical trials to individual patients, individual physicians'' placement of different values on the morbidity associated with various diseases, and the fact that physicians may rarely explicitly compare the usefulness of therapies. In general, the number of patients needed to be treated to save one life better reflected the physicians'' judgements than did the relative risk reduction.     

Risk assessment for quantitative responses using a mixture model

A problem that frequently occurs in biological experiments with laboratory animals is that some subjects are less susceptible to the treatment than others. A mixture model has traditionally been proposed to describe the distribution of responses in treatment groups for such experiments. Using a mixture dose-response model, we derive an upper confidence limit on additional risk, defined as the excess risk over the background risk due to an added dose. Our focus will be on experiments with continuous responses for which risk is the probability of an adverse effect defined as an event that is extremely rare in controls. The asymptotic distribution of the likelihood ratio statistic is used to obtain the upper confidence limit on additional risk. The method can also be used to derive a benchmark dose corresponding to a specified level of increased risk. The EM algorithm is utilized to find the maximum likelihood estimates of model parameters and an extension of the algorithm is proposed to derive the estimates when the model is subject to a specified level of added risk. An example is used to demonstrate the results, and it is shown that by using the mixture model a more accurate measure of added risk is obtained.     

Comparison of total parathyroidectomy without autotransplantation and without thymectomy versus total parathyroidectomy with autotransplantation and with thymectomy for secondary hyperparathyroidism: TOPAR PILOT-Trial

Introduction

The clinical significance of a treatment effect demonstrated in a randomized trial is typically assessed by reference to differences in event rates at the group level. An alternative is to make individualized predictions for each patient based on a prediction model. This approach is growing in popularity, particularly for cancer. Despite its intuitive advantages, it remains plausible that some prediction models may do more harm than good. Here we present a novel method for determining whether predictions from a model should be used to apply the results of a randomized trial to individual patients, as opposed to using group level results.

Methods

We propose applying the prediction model to a data set from a randomized trial and examining the results of patients for whom the treatment arm recommended by a prediction model is congruent with allocation. These results are compared with the strategy of treating all patients through use of a net benefit function that incorporates both the number of patients treated and the outcome. We examined models developed using data sets regarding adjuvant chemotherapy for colorectal cancer and Dutasteride for benign prostatic hypertrophy.

Results

For adjuvant chemotherapy, we found that patients who would opt for chemotherapy even for small risk reductions, and, conversely, those who would require a very large risk reduction, would on average be harmed by using a prediction model; those with intermediate preferences would on average benefit by allowing such information to help their decision making. Use of prediction could, at worst, lead to the equivalent of an additional death or recurrence per 143 patients; at best it could lead to the equivalent of a reduction in the number of treatments of 25% without an increase in event rates. In the Dutasteride case, where the average benefit of treatment is more modest, there is a small benefit of prediction modelling, equivalent to a reduction of one event for every 100 patients given an individualized prediction.

Conclusion

The size of the benefit associated with appropriate clinical implementation of a good prediction model is sufficient to warrant development of further models. However, care is advised in the implementation of prediction modelling, especially for patients who would opt for treatment even if it was of relatively little benefit.     

Managing uncertainty: information and insurance under the risk of starvation

In an uncertain world, animals face both unexpected opportunities and danger. Such outcomes can select for two potential strategies: collecting information to reduce uncertainty, or insuring against it. We investigate the relative value of information and insurance (energy reserves) under starvation risk by offering model foragers a choice between constant and varying food sources over finite foraging bouts. We show that sampling the variable option (choosing it when it is not expected to be good) should decline both with lower reserves and late in foraging bouts; in order to be able to reap the reduction in uncertainty associated with exploiting a variable resource effectively, foragers must be able to afford and compensate for an initial increase in the risk of an energetic shortfall associated with choosing the option when it is bad. Consequently, expected exploitation of the varying option increases as it becomes less variable, and when the overall risk of energetic shortfall is reduced. In addition, little activity on the variable alternative is expected until reserves are built up early in a foraging bout. This indicates that gathering information is a luxury while insurance is a necessity, at least when foraging on stochastic and variable food under the risk of starvation.     

Ligand binding to a humanized anti-cocaine mAb detected by non-reducing SDS-PAGE

Monoclonal antibodies are very useful tools in experimental biology, as well as being valuable and effective therapeutic drugs. They can be targeted against proteins with varied functions, or against small molecules of interest to both researchers and clinicians, such as drugs of abuse, including cocaine. Since there is no currently FDA approved pharmacological treatment for cocaine abuse, our laboratory has developed an anti-cocaine mAb for the treatment of cocaine use disorders. This humanized anti-cocaine antibody, named h2E2, has been thoroughly characterized both functionally and structurally, in preparation for the start of clinical development. We previously showed that this mAb could be characterized by sequential thermal unfolding of antibody domains using non-reducing SDS-PAGE. We also demonstrated that ligand-induced protein stabilization can be used to quantitatively measure cocaine and cocaine metabolite binding to the h2E2 mAb, utilizing differential scanning fluorimetry. Here, we demonstrate the utility of non-reducing SDS-PAGE for the qualitative assessment of binding of cocaine and some of its metabolites, both to the intact mAb, as well as to fragments containing the antigen binding site (Fab and F(ab’)₂ fragments). These results clearly show a ligand concentration dependence of the stabilization of the cocaine binding domain in non-reducing SDS-PAGE, as well as visually differentiating the relative binding affinities of various cocaine metabolites. Thus, non-reducing SDS-PAGE is a simple and widely available technique that is useful as a measure of binding of cocaine and its metabolites to the h2E2 mAb, and it is likely that this technique will also be applicable to other small molecule-directed mAbs.     

Human albumin administration in critically ill patients: systematic review of randomised controlled trials

Objective: To quantify effect on mortality of administering human albumin or plasma protein fraction during management of critically ill patients. Design: Systematic review of randomised controlled trials comparing administration of albumin or plasma protein fraction with no administration or with administration of crystalloid solution in critically ill patients with hypovolaemia, burns, or hypoalbuminaemia. Subjects: 30 randomised controlled trials including 1419 randomised patients. Main outcome measure: Mortality from all causes at end of follow up for each trial. Results: For each patient category the risk of death in the albumin treated group was higher than in the comparison group. For hypovolaemia the relative risk of death after albumin administration was 1.46 (95% confidence interval 0.97 to 2.22), for burns the relative risk was 2.40 (1.11 to 5.19), and for hypoalbuminaemia it was 1.69 (1.07 to 2.67). Pooled relative risk of death with albumin administration was 1.68 (1.26 to 2.23). Pooled difference in the risk of death with albumin was 6% (95% confidence interval 3% to 9%) with a fixed effects model. These data suggest that for every 17 critically ill patients treated with albumin there is one additional death. Conclusions: There is no evidence that albumin administration reduces mortality in critically ill patients with hypovolaemia, burns, or hypoalbuminaemia and a strong suggestion that it may increase mortality. These data suggest that use of human albumin in critically ill patients should be urgently reviewed and that it should not be used outside the context of rigorously conducted, randomised controlled trials.

Key messages

• Human albumin solution has been used in the treatment of critically ill patients for over 50 years
• Currently, the licensed indications for use of albumin are emergency treatment of shock, acute management of burns, and clinical situations associated with hypoproteinaemia
• Our systematic review of randomised controlled trials showed that, for each of these patient categories, the risk of death in the albumin treated group was higher than in the comparison group
• The pooled relative risk of death with albumin was 1.68 (95% confidence interval 1.26 to 2.23) and the pooled difference in the risk of death was 6% (3% to 9%) or six additional deaths for every 100 patients treated
• We consider that use of human albumin solution in critically ill patients should be urgently reviewed