Options for change in the Australian cervical cancer screening program in context of HPV detection and vaccination

Introduction:
Cervical cancer screening has been implemented for over a decade in Australia and has significantly reduced the mortality and morbidity of the disease. The emergence of new technologies for cervical cancer, such as the Human Papillomavirus (HPV) vaccine and DNA testing has encouraged debate regarding the effective use of resources in cervical cancer prevention. The present study evaluates the cost-effectiveness, from a health sector perspective, of various screening strategies in the era of these new technologies.

Methods:
A stochastic epidemiological model using a discrete event and continuous algorithm was developed to describe the natural history of cervical cancer. By allowing one member of the cohort into the model at a time, this micro-simulation model encompasses the characteristics of heterogeneity and can track individual life histories. To evaluate the cost-effectiveness of the HPV vaccine a Markov model was built to simulate the effect on the incidence of HPV and subsequent cervical cancer. A number of proposed screening strategies were evaluated with the stochastic model for the application of HPV DNA testing, with changes in the screening interval and target population. Health outcomes were measured by Disability-Adjusted Life-Years (DALYs), adjusted for application within an evaluation setting (i.e. the mortality component of the DALY was adjusted by a disability weight when early mortality due to cervical cancer is avoided). Costs in complying with the Australian updated guidelines were assessed by pathway analysis to estimate the resources associated with cervical cancer and its pre-cancerous lesion treatment. Sensitivity analyses were performed to investigate the key parameters that influenced the cost-effectiveness results.

Results:
Current practice has already brought huge health gain by preventing more than 4,000 deaths and saving more than 86,000 life-years in a cohort of a million women. Any of the alternative screening strategies alter the total amount of health gain by a small margin compared to current practice. The results of incremental analyses of the alternative screening strategies compared to current practice suggest the adoption of the HPV DNA test as a primary screening tool every 3 years commencing at age 18, or the combined pap smear/HPV test every 3 years commencing at age 25, are more costly than current practice but with reasonable ICERs (AUD$1,810 per DALY and AUD$18,600 per DALY respectively). Delaying commencement of Pap test screening to age 25 is less costly than current practice, but involves considerable health loss. The sensitivity analysis shows, however, that the screening test accuracy has a significant impact on these conclusions. Threshold analysis indicates that a sensitivity ranging from 0.80 to 0.86 for the combined test in women younger than 30 is required to produce an acceptable incremental cost-effectiveness ratio.

Conclusions:
The adoption of HPV and combined test with an extended screening interval is more costly but affordable, resulting in reasonable ICERs. They appear good value for money for the Australian health care system, but need more information on test accuracy to make an informed decision. Potential screening policy change under current Australian HPV Vaccination Program is current work in progress. A Markov model is built to simulate the effect on the incidence of HPV and subsequent cervical cancer. Adoption of HPV DNA test as a primary screening tool in the context of HPV vaccination is under evaluation.

Dusting off the epidemiological triad: could it work with obesity

The search for effective ways of dealing with obesity has centred on biological research and clinical management. However, obesity needs to be conceptualized more broadly if the modern pandemic is to be arrested. The epidemiological triad (hosts, agent/vectors and environments) has served us well in dealing with epidemics in the past, and may be worth re-evaluating to this end. Education, behaviour change and clinical practices deal predominantly with the host, although multidisciplinary practices such as shared-care might also be expected to impact on other corners of the triad. Technology deals best with the agent of obesity (energy imbalance) and it's vectors (excessive energy intake and/or inadequate energy expenditure), and policy and social change are needed to cope with the environment. The value of a broad model like this, rather than specific isolated approaches, is that the key players such as legislators, health professionals, governments and industry can see their roles in attenuating and eventually reversing the epidemic. It also highlights the need to intervene at all levels in obesity control and reduces the relevance of arguments about nature vs. nurture.


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Cardiovascular risk prediction model development and assessment

The aim of this article is to review the development and assessment of cardiovascular risk prediction models and to discuss the predictive value of a risk factor as well as to introduce new assessment methods to evaluate a risk prediction model. Many cardiovascular risk prediction models have been developed during the past three decades. However, there has not been consistent agreement regarding how to appropriately assess a risk prediction model, especially when new markers are added to an existing model. The area under the receiver operating characteristic (ROC) curve has traditionally been used to assess the discriminatory ability of a risk prediction model. However, recent studies suggest that this method has its limitations and cannot be the sole approach to evaluate the usefulness of a new marker. New assessment methods are being developed to appropriately assess a risk prediction model and they will be gradually used in clinical and epidemiological studies.

Selection of working correlation structure and best model in GEE analyses of longitudinal data

The Generalized Estimating Equations (GEE) method is one of the most commonly used statistical methods for the analysis of longitudinal data in epidemiological studies. A working correlation structure for the repeated measures of the outcome variable of a subject needs to be specified by this method. However, statistical criteria for selecting the best correlation structure and the best subset of explanatory variables in GEE are only available recently because the GEE method is developed on the basis of quasi-likelihood theory. Maximum likelihood based model selection methods, such as the widely used Akaike Information Criterion (AIC), are not applicable to GEE directly. Pan (2001) proposed a selection method called QIC which can be used to select the best correlation structure and the best subset of explanatory variables. Based on the QIC method, we developed a computing program to calculate the QIC value for a range of different distributions, link functions and correlation structures. This program was written in Stata software. In this article, we introduce this program and demonstrate how to use it to select the most parsimonious model in GEE analyses of longitudinal data through several representative examples.

Ocular exposure to UV-B in sunlight: the Melbourne Visual Impairment Project model

Quantification of ocular exposure to ultraviolet-B radiation (UV-B) has become an important public health issue, with reports that the ozone layer is being depleted worldwide. Ocular exposure to UV-B is determined by ambient UV-B levels, the duration of outdoor exposure, the proportion of ambient UV-B that reaches the eye, and the use of ocular protection. We have developed a simplified model for quantifying lifetime ocular UV-B exposure that can be used in large epidemiological surveys. Exposure to UV-B is assessed and quantified using a model based on personal exposure over the six summer months. Data available for a population-based sample of 1150 people in the age range 40-98 years revealed a distribution in average annual lifetime ocular UV-B exposure similar to that reported in a previous study on which this model is based, and also demonstrate that people can recall lifetime personal behaviour related to ocular protection. It takes 12 minutes on average to collect these data. This model can be employed by researchers worldwide for uniform assessment of ocular UV-B exposure.

An integrated model of care for inflammatory bowel disease sufferers in Australia: development and the effects of its implementation.

BACKGROUND: Psychological comorbidities are associated with poor outcome and increased healthcare utilization in patients with inflammatory bowel disease (IBD). However, a model of care addressing the biopsychosocial dimension of disease is not routinely applied in IBD. This review describes the development of such a model and the effects of its implementation in a hospital-based cohort of patients with IBD. METHODS: Three different approaches were used: 1) collecting baseline epidemiological data on mental health comorbidities; 2) raising awareness of and targeting mental health problems; 3) examining the effects of the model implementation. RESULTS: High rates of anxiety and depressive symptoms (36% and 13%, respectively) that are maintained over time were identified in IBD patients presenting at a metropolitan teaching hospital. Patients with documented psychological comorbidities were more likely to be hospitalized than those without (odds ratio [OR] = 4.13, 95% confidence interval [CI]: 1.25, 13.61). Improvements in disease activity, anxiety, depression, quality of life, and coping have been noted when cognitive-behavioral therapy (CBT) was provided to patients. A drop in the use of opiates (P = 0.037) and hospitalization rates (from 48% to 30%) in IBD patients has been noted as a result of introduction of the changed model of care. In addition, the mean total cost of inpatient care was lower for IBD patients than controls (US$12,857.48 [US$15,236.79] vs. US$ 30,467.78 [US$ 53,760.20], P = 0.005). CONCLUSION: Our data to date suggest that an integrated model of care for patients with IBD may yield superior long-term outcomes in terms of medication use and hospitalization rates and reduce healthcare costs.