Andrew M. Jones

Azithromycin blocks autophagy and may predispose cystic fibrosis patients to mycobacterial infection

Azithromycin is a potent macrolide antibiotic with poorly understood antiinflammatory properties. Long-term use of azithromycin in patients with chronic inflammatory lung diseases, such as cystic fibrosis (CF), results in improved outcomes. Paradoxically, a recent study reported that azithromycin use in patients with CF is associated with increased infection with nontuberculous mycobacteria (NTM). Here, we confirm that long-term azithromycin use by adults with CF is associated with the development of infection with NTM, particularly the multi-drug-resistant species Mycobacterium abscessus, and identify an underlying mechanism. We found that in primary human macrophages, concentrations of azithromycin achieved during therapeutic dosing blocked autophagosome clearance by preventing lysosomal acidification, thereby impairing autophagic and phagosomal degradation. As a consequence, azithromycin treatment inhibited intracellular killing of mycobacteria within macrophages and resulted in chronic infection with NTM in mice. Our findings emphasize the essential role for autophagy in the host response to infection with NTM, reveal why chronic use of azithromycin may predispose to mycobacterial disease, and highlight the dangers of inadvertent pharmacological blockade of autophagy in patients at risk of infection with drug-resistant pathogens.

Burkholderia cenocepacia and Burkholderia multivorans: influence on survival in cystic fibrosis

Introduction:Burkholderia cepacia infection has been associated with a poor prognosis for patients with cystic fibrosis (CF). It is now recognised that organisms classified as B cepacia comprise a number of distinct genomic species each known as a genomovar of the B cepacia complex (BCC). The outcome of infection for CF patients with individual genomovars is unknown. The clinical outcome of infection with the two most commonly isolated genomovars (B cenocepacia and B multivorans) was studied at a specialist CF centre between 1982 and 2003. Methods: The numbers of patients who progressed from initial to chronic infection were assessed. Control groups were created by matching patients with chronic BCC infection by percentage forced expiratory volume in 1 second with patients with Pseudomonas aeruginosa infection. Outcome measures were survival time, deaths from “cepacia syndrome”, rate of decline in spirometry and body mass index (BMI), and treatment requirements. Results: Forty nine patients had an initial infection with either B multivorans (n = 16) or B cenocepacia (n = 33); 8/16 and 31/33, respectively, developed chronic infection (p<0.001). Deaths from “cepacia syndrome” occurred in both BCC groups. Patients with B cenocepacia infection had a shorter survival than patients with P aeruginosa infection (p = 0.01). There was no difference in survival between CF patients infected with B multivorans and P aeruginosa. There were no observed differences in changes in spirometry and BMI or treatment requirements between the BCC groups and respective controls. Conclusion: In CF, the genomovar status of BCC may influence both the likelihood of progression from initial to chronic infection and the overall survival of the patients.

MULTILEVEL MODELS AND HEALTH ECONOMICS

Multilevel analyses have become an accepted statistical technique in the field of education where over the past decade or so the methods have been developed to explore the relationships between pupil characteristics and the characteristics of the schools they attend. More recently, widespread use has extended to other social sciences and health research. However, to date, little use has been made of these techniques within the health economics literature. This paper presents an introductory account of multilevel models and describes some of the areas of health economics research that may benefit from their use.

Health, income and relative deprivation: Evidence from the BHPS

It is believed that income affects health directly but it is argued that indirect income effects due to relative deprivation may be equally important. This paper investigates these relationships using parametric and semiparametric panel data models which ameliorate problems of mis-specification and unobservable heterogeneity. By allowing for a flexible functional form of income we ensure that coefficients on relative deprivation variables are not an artefact of a highly non-linear relationship between health and income. The results provide strong evidence for the impact of income on self-reported measures of health for men and women. These results are robust across a range of techniques and are resilient to the inclusion of measures of relative deprivation. The parametric results for relative deprivation largely reject its influence on health, although there is some evidence of an effect in the semiparametric models.

The role of tobacco taxes in starting and quitting smoking: Duration analysis of British data

This paper presents new evidence on the determinants of starting and quitting smoking using duration data from the British Health and Lifestyle Survey (HALS). Self-reported data in individual smoking histories coupled with availability of a long time series for the tax rate on cigarettes are used to construct a longitudinal data set in which the tax rate is treated as a time varying covariate. This overcomes the problem of the lack of cross section variation in process that has plagued previous studies of smoking in Britain. The study is the first to identify tax-price elasticities for starting and quitting in Britain. Results for age of starting smoking prior to quitting are reported for Cox, Weibull and gamma models. All of the models are estimated separately for males and females and extensive diagnostic tests are used to guide model specification. A sensitivity analysis is used to assess the robustness of the estimated tax elasticities for starting and quitting. Since the early 1990s successive governments have had a commitment to annual increases in the real level of tobacco taxes, to achieve health policy objectives and encourage people to stop smoking. Our estimated price elasticities directly relate to the impact of above inflation tax rises on the number of years smoked by current smokers. The estimates of the impact of tax on the probability of starting and the age of starting are not encouraging as we do not find a significant effect. However the point estimates of the elasticity of quitting are well defined for males and robust for both males and females. All of our point estimates are in the range -0.40 to -0.63. If the typical number of years smoked is 25 years this implies that the 5% real increase in tobacco duty would lead, on average, to a reduction of between 6 and 9.5 months of smoking for each smoker. Recent estimates suggest that there are around 12.1 million current smokers in the UK (ASH 1999). Thus the potential saving in total number of years smoked across the population is substantial.

Health, addiction, social interaction and the decision to quit smoking

The decision to quit smoking is treated as a choice under uncertainty in an empirical model that incorporates health, medical advice, addiction, and social interaction. Probit models are estimated for attempts and success in quitting with data from the Health and Lifestyle Survey. The results show a clear role for addiction, social interaction and current health status. The evidence on the effectiveness of medical advice is ambiguous.

Charitable donations by UK households: evidence from the Family Expenditure Survey

This paper reports estimates based on both standard Tobit and generalized Tobit techniques of the determinants of charitable giving in the UK using 1984 Family Expenditure Survey data. This is the first such study using UK data. Separate estimates are presented of the determinants of participation and of the level of donations by giving households. Participation is seen to be sensitive to income, the tax-price of giving, and a range of demographic variables, while the level of donations varies primarily with income. Donations are found to be inelastic with respect to changes in disposable income.

Household Consumption of Cheese: An Inverse Hyperbolic Sine Double-Hurdle Model with Dependent Errors

The dependent double-hurdle model is generalized by an inverse hyperbolic sine transformation of the dependent variable. The resulting specification features a flexible parameterization, accommodates heteroskedastic errors, and nests a range of common limited dependent variable models. Results for U.S. household cheese consumption suggest that the homoskedastic and normal double-hurdle model is misspecified. Income elasticities are small and vary across household groups. Foodstamp recipients are more responsive to income changes than nonrecipients. Foodstamp recipients are also less likely to consume cheese but, conditional on consumption, spend more than nonrecipients. Copyright 1997, Oxford University Press.

Emerging Treatments in Cystic Fibrosis

There are a number of potential drugs for the treatment of cystic fibrosis (CF) currently undergoing clinical studies. A number of antibacterials formulated for delivery by inhalation are at various stages of study; these include dry-powder inhaler versions of colistin, tobramycin and ciprofloxacin, and formulations of azteonam, amikacin, levofloxacin, ciprofloxacin and fosfomycin/tobramycin for nebulization. Clinical trials of anti-inflammatory agents, including glutathione, phosphodiesterase-5 inhibitors such as sildenafil, oral acetylcysteine, simvastatin, methotrexate, docosahexaenoic acid, hydroxychloroquine, pioglitazone and α1-antitrypsin, are ongoing. Ion channel modulating agents, such as lancovutide (Moli1901, duramycin) and denufosol, which activate alternate (non-CF transmembrane regulator [CFTR]) chloride channels, and GS 9411, a sodium channel antagonist, are now at the stages of clinical study and if successful, will offer a new category of therapeutic agent for the treatment of CF. Correction of the underlying gene effect, either by agents that help to correct the dysfunctional CFTR, such as ataluren, VX-770 and VX-809, or by gene transfer (gene therapy), is a particularly exciting prospect as a new therapy for CF and clinical studies are ongoing. This article reviews the exciting potential drug treatments for CF currently being evaluated in clinical studies, and also highlights some of the challenges faced by research and clinical teams in assessing the efficacy of potential new therapies for CF.

Chapter 6 – Health Econometrics*

A decade ago, Newhouse (1987) assessed the balance of trade between imports from the econometrics literature into health economics, and exports from health economics to a wider audience. While it is undoubtedly true that imports of concepts and techniques still dominate the balance, the literature reviewed in this chapter shows that the range and volume of applied econometric work in health economics has increased dramatically over the past ten years. Examples of good practice in health econometrics make extensive use of tests for misspecification and explicit model selection criteria. Robust and distribution-free estimators are of increasing importance, and the chapter gives examples of nonparametric, and semiparametric estimators applied to sample selection, simultaneous equations, count data, and survival models. Published replications of empirical results remain relatively rare. One way in which this deficit may be remedied is through the appearance of more systematic reviews of econometric studies. The use of experimental data remains an exception and most applied studies continue to rely on observational data from secondary sources. However applied work in health economics is likely to be influenced by the debate concerning the use of data from social experiments. The chapter illustrates the impressive diversity of applied econometric work over the past decade. Most of the studies reviewed here use individual level data and this has led to the use of a wide range of nonlinear models, including qualitative and limited dependent variables, along with count, survival and frontier models. Because of the widespread use of observational data, particular attention has gone into dealing with problems of self-selection and heterogeneity bias. This is likely to continue in the future, with the emphasis on robust estimators applied to longitudinal and other complex datasets.