Interpreting the clinical utility of a pharmacogenomic marker based on observational association studies

The author accepted manuscript (post print) is made available in accordance with with publisher copyright policy.It is increasingly recognized that the clinical utility of a pharmacogenomic marker is a fundamental characteristic influencing the likelihood of successful clinical translation. Although appropriately designed and executed randomized controlled trials generally provide the most valid evidence for the clinical utility of a pharmacogenomic marker, such evidence may not always be available. Observational pharmacogenomic association studies are a common form of evidence available, but the assessment of clinical utility based on such evidence is often not straightforward. This paper aims to provide insight into this issue using a range of illustrative examples

Reducing perinatal mortality among Indigenous babies in Queensland: should the first priority be better primary health care or better access to hospital care during confinement?

BACKGROUND: The perinatal mortality rate among Indigenous Australians is still double that of the rest of the community. The aim of our study was to estimate the extent to which increased risk of low birthweight and preterm birth among Indigenous babies in Queensland account for their continuing mortality excess. If a large proportion of excess deaths can be explained by the unfavourable birthweight and gestational age distribution of Indigenous babies, then that would suggest that priority should be given to implementing primary health care interventions to reduce the risk of low birthweight and preterm birth (eg, interventions to reduce maternal smoking or genitourinary infections). Conversely, if only a small proportion is explained by birthweight and gestational age, then other strategies might need to be considered such as improving access to high-quality hospital care around the time of confinement. METHODOLOGY: Population-based, descriptive study of perinatal mortality rates among Indigenous and non-Indigenous babies, in Queensland, stratified by birthweight and gestational age. RESULTS: Indigenous babies are twice as likely to die as their non-Indigenous counterparts (rate ratio1998–2002: 2.01; 95%ci 1.77, 2.28). However, within separate strata of birth weight and gestational age, Indigenous and non-Indigenous rates are similar. The Mantel-Haenszel rate ratio adjusted for birth weight and gestational age was 1.13 (0.99, 1.28). This means that most of the excess mortality in Indigenous babies is largely due to their unfavourable birth weight and gestational-age distributions. If Indigenous babies had the same birth weight and gestational age distribution as their non-Indigenous counterparts, then the relative disparity would be reduced by 87% and 20 fewer Indigenous babies would die in Queensland each year. CONCLUSION: Our results suggest that Indigenous mothers at high risk of poor outcome (for example those Indigenous mothers in preterm labour) have good access to high quality medical care around the time of confinement. The main reason Indigenous babies have a high risk of death is because they are born too early and too small. Thus, to reduce the relative excess of deaths among Indigenous babies, priority should be given to primary health care initiatives aimed at reducing the prevalence of low birth weight and preterm birth

Survival of indigenous and non-Indigenous Queenslanders after a diagnosis of lung cancer: a matched cohort study

Objective: To compare survival of Indigenous and non-Indigenous lung cancer patients and to investigate any corresponding differences in stage, treatment and comorbidities.Design and setting: Cohort study of 158 Indigenous and 152 non-Indigenous patients (frequency-matched on age, sex and rurality) diagnosed with lung cancer between 1996 and 2002 and treated in Queensland public hospitals.Main outcome measures: Survival after diagnosis of lung cancer; effects of stage at diagnosis, treatment, comorbidities and histological subtype on lung cancer-specific survival.Results: Survival of Indigenous lung cancer patients was significantly lower than that of non-Indigenous patients (median survival, 4.3 v 10.3 months; hazard ratio, 1.48; 95% CI, 1.14–1.92). Of 158 Indigenous patients, 72 (46%) received active treatment with chemotherapy, radiotherapy or surgery compared with 109 (72%) of the 152 non-Indigenous patients, and this treatment disparity remained after adjusting for histological subtype, stage at diagnosis, and comorbidities (adjusted risk ratio, 0.65; 95% CI, 0.53–0.73). The treatment disparity explained most of the survival deficit: the hazard ratio reduced to 1.10 (95% CI, 0.83–1.44) after inclusion of treatment variables in the proportional hazards survival model. The remaining survival deficit was explained by the higher prevalence of comorbidities among Indigenous cancer patients, mainly diabetes.Conclusion: Survival after a diagnosis of lung cancer is worse for Indigenous patients than for non-Indigenous patients, and differences in treatment between the two groups are mainly responsible

Gestational age specific stillbirth risk among Indigenous and non-Indigenous women in Queensland, Australia: a population based study.

BACKGROUND: In Australia, significant disparity persists in stillbirth rates between Aboriginal and Torres Strait Islander (Indigenous Australian) and non-Indigenous women. Diabetes, hypertension, antepartum haemorrhage and small-for-gestational age (SGA) have been identified as important contributors to higher rates among Indigenous women. The objective of this study was to examine gestational age specific risk of stillbirth associated with these conditions among Indigenous and non-Indigenous women. METHODS: Retrospective population-based study of all singleton births of at least 20 weeks gestation or at least 400 grams birthweight in Queensland between July 2005 and December 2011 using data from the Queensland Perinatal Data Collection, which is a routinely-maintained database that collects data on all births in Queensland. Multivariate logistic regression was used to calculate adjusted odds ratios (aOR) and 95 % confidence intervals, adjusting for maternal demographic and pregnancy factors. RESULTS: Of 360987 births analysed, 20273 (5.6 %) were to Indigenous women and 340714 (94.4 %) were to non-Indigenous women. Stillbirth rates were 7.9 (95 % CI 6.8-9.2) and 4.1 (95 % CI 3.9-4.3) per 1000 births, respectively. For both Indigenous and non-Indigenous women across most gestational age groups, antepartum haemorrhage, SGA, pre-existing diabetes and pre-existing hypertension were associated with increased risk of stillbirth. There were mixed results for pre-eclampsia and eclampsia and a consistently raised risk of stillbirth was not seen for gestational diabetes. CONCLUSION: This study highlights gestational age specific stillbirth risk for Indigenous and non-Indigenous women; and disparity in risk at term gestations. Improving access to and utilisation of appropriate and responsive healthcare may help to address disparities in stillbirth risk for Indigenous women.Ibinabo Ibiebele is a recipient of the National Health and Medical Research Council Postgraduate Public Health scholarship and the University of Queensland Research Scholarship.This is the final version of the article. It first appeared from BioMed Central via http://dx.doi.org/10.1186/s12884-016-0943-

Cancer survival for Aboriginal and Torres Strait Islander Australians: a national study of survival rates and excess mortality

BackgroundNational cancer survival statistics are available for the total Australian population but not Indigenous Australians, although their cancer mortality rates are known to be higher than those of other Australians. We aimed to validate analysis methods and report cancer survival rates for Indigenous Australians as the basis for regular national reporting.MethodsWe used national cancer registrations data to calculate all-cancer and site-specific relative survival for Indigenous Australians (compared with non-Indigenous Australians) diagnosed in 2001-2005. Because of limited availability of Indigenous life tables, we validated and used cause-specific survival (rather than relative survival) for proportional hazards regression to analyze time trends and regional variation in all-cancer survival between 1991 and 2005.ResultsSurvival was lower for Indigenous than non-Indigenous Australians for all cancers combined and for many cancer sites. The excess mortality of Indigenous people with cancer was restricted to the first three years after diagnosis, and greatest in the first year. Survival was lower for rural and remote than urban residents; this disparity was much greater for Indigenous people. Survival improved between 1991 and 2005 for non-Indigenous people (mortality decreased by 28%), but to a much lesser extent for Indigenous people (11%) and only for those in remote areas; cancer survival did not improve for urban Indigenous residents.ConclusionsCancer survival is lower for Indigenous than other Australians, for all cancers combined and many individual cancer sites, although more accurate recording of Indigenous status by cancer registers is required before the extent of this disadvantage can be known with certainty. Cancer care for Indigenous Australians needs to be considerably improved; cancer diagnosis, treatment, and support services need to be redesigned specifically to be accessible and acceptable to Indigenous people

A study of head and neck cancer treatment and survival among indigenous and non-indigenous people in Queensland, Australia, 1998 to 2004

Background: Overall, Indigenous Australians with cancer are diagnosed with more advanced disease, receive less cancer treatment and have poorer cancer survival than non-Indigenous Australians. The prognosis for Indigenous people with specific cancers varies however, and their prognosis for cancers of the head and neck is largely unknown. We therefore have compared clinical characteristics, treatment and survival between Indigenous and non-Indigenous people diagnosed with head and neck cancer in Queensland, Australia. Methods: Rates were based on a cohort of Indigenous people (n = 67), treated in public hospitals between 1998 and 2004 and frequency-matched on age and location to non-Indigenous cases (n = 62) also treated in the public health system. Data were obtained from hospital records and the National Death Index. We used Pearson's Chi-squared analysis to compare categorical data (proportions) and Cox proportional hazard models to assess survival differences.Results: There were no significant differences in socioeconomic status, stage at diagnosis or number and severity of comorbidities between Indigenous and non-Indigenous patients, although Indigenous patients were more likely to have diabetes. Indigenous people were significantly less likely to receive any cancer treatment (75% vs. 95%, P = 0.005) and, when cancer stage, socioeconomic status, comorbidities and cancer treatment were taken into account, they experienced greater risk of death from head and neck cancer (HR 1.88, 1.10, 3.22) and from all other causes (HR 5.83, 95% CI 1.09, 31.04).Conclusion: These findings show for the first time that Indigenous Australians with head and neck cancer receive less cancer treatment and suggest survival disparity could be reduced if treatment uptake was improved. There is a need for a greater understanding of the reasons for such treatment and survival disparities, including the impact of the poorer overall health on cancer outcomes for Indigenous Australians

Detecting the start of an influenza outbreak using exponentially weighted moving average charts

Background. Influenza viruses cause seasonal outbreaks in temperate climates, usually during winter and early spring, and are endemic in tropical climates. The severity and length of influenza outbreaks vary from year to year. Quick and reliable detection of the start of an outbreak is needed to promote public health measures. Methods. We propose the use of an exponentially weighted moving average (EWMA) control chart of laboratory confirmed influenza counts to detect the start and end of influenza outbreaks. Results. The chart is shown to provide timely signals in an example application with seven years of data from Victoria, Australia. Conclusions. The EWMA control chart could be applied in other applications to quickly detect influenza outbreaks