Absolute benefit, number needed to treat and gain in life expectancy: which efficacy indices for measuring the treatment benefit?

Recommendations to prescribe in complex older adults: results of the CRIteria to assess appropriate Medication use among Elderly complex patients (CRIME) project

The occurrence of several geriatric conditions may influence the efficacy and limit the use of drugs prescribed to treat chronic conditions. Functional and cognitive impairment, geriatric syndromes (i.e. falls or malnutrition) and limited life expectancy are common features of old age, which may limit the efficacy of pharmacological treatments and question the appropriateness of treatment. However, the assessment of these geriatric conditions is rarely incorporated into clinical trials and treatment guidelines. The CRIME (CRIteria to assess appropriate Medication use among Elderly complex patients) project is aimed at producing recommendations to guide pharmacologic prescription in older complex patients with a limited life expectancy, functional and cognitive impairment, and geriatric syndromes, and providing physicians with a tool to improve the quality of prescribing, independent of setting and nationality. To achieve these aims, we performed the following: (i) Existing disease-specific guidelines on pharmacological prescription for the treatment of diabetes, hypertension, congestive heart failure, atrial fibrillation and coronary heart disease were reviewed to assess whether they include specific indications for complex patients; (ii) a literature search was performed to identify relevant articles assessing the pharmacological treatment of complex patients; (iii) A total of 19 new recommendations were developed based on the results of the literature search and expert consensus. In conclusion, the new recommendations evaluate the appropriateness of pharmacological prescription in older complex patients, translating the recommendations of clinical guidelines to patients with a limited life expectancy, functional and cognitive impairment, and geriatric syndromes. These recommendations cannot represent substitutes for careful clinical consideration and deliberation by physicians; the recommendations are not meant to replace existing clinical guidelines, but they may be used to help physicians in the prescribing process.

Effect model law: an approach for the implementation of personalized medicine

The effect model law states that a natural relationship exists between the frequency (observation) or the probability (prediction) of a morbid event without any treatment and the frequency or probability of the same event with a treatment. This relationship is called the effect model. It applies to a single individual, individuals within a population, or groups. In the latter case, frequencies or probabilities are averages of the group. The relationship is specific to a therapy, a disease or an event, and a period of observation. If one single disease is expressed through several distinct events, a treatment will be characterized by as many effect models. Empirical evidence, simulations with models of diseases and therapies and virtual populations, as well as theoretical derivation support the existence of the law. The effect model could be estimated through statistical fitting or mathematical modelling. It enables the prediction of the (absolute) benefit of a treatment for a given patient. It thus constitutes the theoretical basis for the design of practical tools for personalized medicine.

Treatment of patients with type 2 diabetes with exenatide once weekly versus oral glucose-lowering medications or insulin glargine: achievement of glycemic and cardiovascular goals

Background

Diabetes is associated with a higher risk for adverse cardiovascular outcomes. To improve the health outcomes of patients with type 2 diabetes (T2DM), the American Diabetes Association (ADA) recommended target goals for the improvement of glycemic control and the reduction of cardiovascular risk factors associated with the disease. This retrospective analysis calculated the absolute benefit increase (ABI) of using exenatide once weekly (QW), a glucagon-like peptide-1 (GLP-1) receptor agonist, vs an oral glucose-lowering medication or insulin glargine to achieve ADA-recommended goals. The number needed to treat (NNT) to achieve these goals was also calculated and provides a useful clinical metric for comparing potential therapies from different drug classes.

Methods

Patient data from three double-blind or open label, 26-week, randomized, controlled trials were retrospectively analyzed separately. ABI and NNT were calculated by comparing the percentage of patients treated with exenatide QW (N = 641) vs metformin (N = 246), sitagliptin (N = 329), pioglitazone (N = 328), or insulin glargine (N = 223), who achieved a single glycemic, weight, blood pressure, or lipid goal or a composite of these recommended goals, during the DURATION-2, -3, and -4 clinical trials.

Results

Significant ABIs favoring exenatide QW over all four glucose-lowering medications were observed for at least one HbA1c glycemic goal. NNTs of 4 and 5 were calculated when exenatide QW was compared to sitagliptin for attaining HbA1c goals of <7.0% and ≤6.5%, respectively. Additionally, significantly more patients using exenatide QW compared to sitagliptin, pioglitazone, or insulin glargine attained the composite goal of HbA1c <7% or ≤6.5%, without weight gain or hypoglycemia. Exenatide QW was also favored over sitagliptin and insulin glargine for the achievement of the composite goals of HbA1c <7% (or ≤6.5%), systolic blood pressure <130 mm Hg, and low-density lipoprotein <2.59 mmol/L. For most goals, exenatide QW and metformin had similar effects in treatment naïve patients.

Conclusions

This analysis assessed the between-therapy differences in achieving therapeutic goals with therapies commonly used for glycemic control in patients with T2DM. In clinical trials, exenatide QW assisted more patients in reaching the majority of ADA-recommended therapeutic goals than treatment with sitagliptin, pioglitazone, or insulin glargine.

Trial registration

NCT00637273, NCT00641056, NCT00676338

The global risk approach should be better applied in French hypertensive patients: a comparison between simulation and observation studies

Background

The prediction of the public health impact of a preventive strategy provides valuable support for decision-making. International guidelines for hypertension management have introduced the level of absolute cardiovascular risk in the definition of the treatment target population. The public health impact of implementing such a recommendation has not been measured.

Methodology/Principal Findings

We assessed the efficiency of three treatment scenarios according to historical and current versions of practice guidelines on a Realistic Virtual Population representative of the French population aged from 35 to 64 years: 1) BP≥160/95 mm Hg; 2) BP≥140/90 mm Hg and 3) BP≥140/90 mm Hg plus increased CVD risk. We compared the eligibility following the ESC guidelines with the recently observed proportion of treated amongst hypertensive individuals reported by the Etude Nationale Nutrition Santé survey. Lowering the threshold to define hypertension multiplied by 2.5 the number of eligible individuals. Applying the cardiovascular risk rule reduced this number significantly: less than 1/4 of hypertensive women under 55 years and less than 1/3 of hypertensive men below 45 years of age. This was the most efficient strategy. Compared to the simulated guidelines application, men of all ages were undertreated (between 32 and 60%), as were women over 55 years (70%). By contrast, younger women were over-treated (over 200%).

Conclusion

The global CVD risk approach to decide for treatment is more efficient than the simple blood pressure level. However, lack of screening rather than guideline application seems to explain the low prescription rates among hypertensive individuals in France. Multidimensional analyses required to obtain these results are possible only through databases at the individual level: realistic virtual populations should become the gold standard for assessing the impact of public health policies at the national level.

SCORE should be preferred to Framingham to predict cardiovascular death in French population

BACKGROUND

Numerous studies have examined the validity of available scores to predict the absolute cardiovascular risk.

DESIGN

We developed a virtual population based on data representative of the French population and compared the performances of the two most popular risk equations to predict cardiovascular death: Framingham and SCORE.

METHODS

A population was built based on official French demographic statistics and summarized data from representative observational studies. The 10-year coronary and cardiovascular death risk and their ratio were computed for each individual by SCORE and Framingham equations. The resulting rates were compared with those derived from national vital statistics.

RESULTS

Framingham overestimated French coronary deaths by 2.8 in men and 1.9 in women, and cardiovascular deaths by 1.5 in men and 1.3 in women. SCORE overestimated coronary death by 1.6 in men and 1.7 in women, and underestimated cardiovascular death by 0.94 in men and 0.85 in women. Our results revealed an exaggerated representation of coronary among cardiovascular death predicted by Framingham, with coronary death exceeding cardiovascular death in some individual profiles. Sensitivity analyses gave some insights to explain the internal inconsistency of the Framingham equations.

CONCLUSION

Evidence is that SCORE should be preferred to Framingham to predict cardiovascular death risk in French population. This discrepancy between prediction scores is likely to be observed in other populations. To improve the validation of risk equations, specific guidelines should be issued to harmonize the outcomes definition across epidemiologic studies. Prediction models should be calibrated for risk differences in the space and time dimensions.

Does flavanol intake influence mortality from nitric oxide-dependent processes? Ischemic heart disease, stroke, diabetes mellitus, and cancer in Panama

Substantial data suggest that flavonoid-rich food could help prevent cardiovascular disease and cancer. Cocoa is the richest source of flavonoids, but current processing reduces the content substantially. The Kuna living in the San Blas drink a flavanol-rich cocoa as their main beverage, contributing more than 900 mg/day and thus probably have the most flavonoid-rich diet of any population. We used diagnosis on death certificates to compare cause-specific death rates from year 2000 to 2004 in mainland and the San Blas islands where only Kuna live. Our hypothesis was that if the high flavanoid intake and consequent nitric oxide system activation were important the result would be a reduction in the frequency of ischemic heart disease, stroke, diabetes mellitus, and cancer--all nitric oxide sensitive processes. There were 77,375 deaths in mainland Panama and 558 deaths in the San Blas. In mainland Panama, as anticipated, cardiovascular disease was the leading cause of death (83.4 +/- 0.70 age adjusted deaths/100,000) and cancer was second (68.4 +/- 1.6). In contrast, the rate of CVD and cancer among island-dwelling Kuna was much lower (9.2 +/- 3.1) and (4.4 +/- 4.4) respectively. Similarly deaths due to diabetes mellitus were much more common in the mainland (24.1 +/- 0.74) than in the San Blas (6.6 +/- 1.94). This comparatively lower risk among Kuna in the San Blas from the most common causes of morbidity and mortality in much of the world, possibly reflects a very high flavanol intake and sustained nitric oxide synthesis activation. However, there are many risk factors and an observational study cannot provide definitive evidence.

Using economic analyses for local priority setting : the population cost-impact approach

INTRODUCTION

Standard methods of economic analysis may not be suitable for local decision making that is specific to a particular population.

BACKGROUND

We describe a new three-step methodology, termed 'population cost-impact analysis', which provides a population perspective to the costs and benefits of alternative interventions. The first two steps involve calculating the population impact and the costs of the proposed interventions relevant to local conditions. This involves the calculation of population impact measures (which have been previously described but are not currently used extensively) - measures of absolute risk and risk reduction, applied to a population denominator. In step three, preferences of policy-makers are obtained. This is in contrast to the QALY approach in which quality weights are obtained as a part of the measurement of benefit.

METHODS

We applied the population cost-impact analysis method to a comparison of two interventions - increasing the use of beta-adrenoceptor antagonists (beta-blockers) and smoking cessation - after myocardial infarction in a scaled-back notional local population of 100,000 people in England. Twenty-two public health professionals were asked via a questionnaire to rank the order in which they would implement four interventions. They were given information on both population cost impact and QALYs for each intervention.

RESULTS

In a population of 100,000 people, moving from current to best practice for beta-adrenoceptor antagonists and smoking cessation will prevent 11 and 4 deaths (or gain of 127 or 42 life-years), respectively. The cost per event prevented in the next year, or life-year gained, is less for beta-adrenoceptor antagonists than for smoking cessation. Public health professionals were found to be more inclined to rank alternative interventions according to the population cost impact than the QALY approach.

DISCUSSION

The use of the population cost-impact approach allows information on the benefits of moving from current to best practice to be presented in terms of the benefits and costs to a particular population. The process for deciding between alternative interventions in a prioritisation exercise may differ according to the local context. We suggest that the valuation of the benefit is performed after the benefits have been quantified and that it takes into account local issues relevant to prioritisation. It would be an appropriate next step to experiment with, and formalise, this part of the population cost-impact analysis to provide a standardised approach for determining willingness to pay and provide a ranking of priorities.

CONCLUSION

Our method adds a new dimension to economic analysis, the ability to identify costs and benefits of potential interventions to a defined population, which may be of considerable use for policy makers working at the local level.

Modélisation numérique et simulation : nouvelles applications en pharmacologie

The complexity of pathophysiological mechanisms is beyond the capabilities of traditional approaches. Many of the decision-making problems in public health, such as initiating mass screening, are complex. Progress in genomics and proteomics, and the resulting extraordinary increase in knowledge with regard to interactions between gene expression, the environment and behaviour, the customisation of risk factors and the need to combine therapies that individually have minimal though well documented efficacy, has led doctors to raise new questions: how to optimise choice and the application of therapeutic strategies at the individual rather than the group level, while taking into account all the available evidence? This is essentially a problem of complexity with dimensions similar to the previous ones: multiple parameters with nonlinear relationships between them, varying time scales that cannot be ignored etc. Numerical modelling and simulation (in silico investigations) have the potential to meet these challenges. Such approaches are considered in drug innovation and development. They require a multidisciplinary approach, and this will involve modification of the way research in pharmacology is conducted.