Smoking and use of primary care services : findings from a population-based cohort study linked with administrative claims data

Background: Available evidence suggests that smokers have a lower propensity than others to use primary care services. But previous studies have incorporated only limited adjustment for confounding and mediating factors such as income, access to services and health status. We used data from a large prospective cohort study (the 45 and Up Study), linked to administrative claims data, to quantify the relationship between smoking status and use of primary care services, including specific preventive services, in a contemporary Australian population. Methods: Baseline questionnaire data from the 45 and Up Study were linked to administrative claims (Medicare) data for the 12-month period following study entry. The main outcome measures were Medicare benefit claimed for unreferred services, out-of-pocket costs (OOPC) paid, and claims for specific preventive services (immunisations, health assessments, chronic disease management services, PSA tests and Pap smears). Rate ratios with 95% confidence intervals were estimated using a hierarchical series of models, adjusted for predisposing, access-and health-related factors. Separate hurdle (two part) regression models were constructed for Medicare benefit and OOPC. Poisson models with robust error variance were used to model use of each specific preventive service. Results: Participants included 254,382 people aged 45 years and over of whom 7.3% were current smokers. After adjustment for predisposing, access-and health-related factors, current smokers were very slightly less likely to have claimed Medicare benefit than never smokers. Among those who claimed benefit, current smokers claimed similar total benefit, but recent quitters claimed significantly greater benefit, compared to never-smokers. Current smokers were around 10% less likely than never smokers to have paid any OOPC. Current smokers were 15-20% less likely than never smokers to use immunisations, Pap smears and prostate specific antigen tests. Conclusions: Current smokers were less likely than others to use primary care services that incurred out of pocket costs, and specific preventive services. This was independent of a wide range of predisposing, access-and health-related factors, suggesting that smokers have a lower propensity to seek health care. Smokers may be missing out on preventive services from which they would differentially benefit

Ascertaining invasive breast cancer cases; the validity of administrative and self-reported data sources in Australia

Background: Statutory State-based cancer registries are considered the ‘gold standard’ for researchers identifying cancer cases in Australia, but research using self-report or administrative health datasets (e.g. hospital records) may not have linkage to a Cancer Registry and need to identify cases. This study investigated the validity of administrative and self-reported data compared with records in a State-wide Cancer Registry in identifying invasive breast cancer cases. Methods: Cases of invasive breast cancer recorded on the New South Wales (NSW) Cancer Registry between July 2004 and December 2008 (the study period) were identified for women in the 45 and Up Study. Registry cases were separately compared with suspected cases ascertained from: i) administrative hospital separations records; ii) outpatient medical service claims; iii) prescription medicines claims; and iv) the 45 and Up Study baseline survey. Ascertainment flags included diagnosis codes, surgeries (e.g. lumpectomy), services (e.g. radiotherapy), and medicines used for breast cancer, as well as self-reported diagnosis. Positive predictive value (PPV), sensitivity and specificity were calculated for flags within individual datasets, and for combinations of flags across multiple datasets. Results: Of 143,010 women in the 45 and Up Study, 2039 (1.4%) had an invasive breast tumour recorded on the NSW Cancer Registry during the study period. All of the breast cancer flags examined had high specificity (\u3e97.5%). Of the flags from individual datasets, hospital-derived ‘lumpectomy and diagnosis of invasive breast cancer’ and ‘(lumpectomy or mastectomy) and diagnosis of invasive breast cancer’ had the greatest PPV (89% and 88%, respectively); the later having greater sensitivity (59% and 82%, respectively). The flag with the highest sensitivity and PPV ≥ 85% was \u27diagnosis of invasive breast cancer\u27 (both 86%). Self-reported breast cancer diagnosis had a PPV of 50% and sensitivity of 85%, and breast radiotherapy had a PPV of 73% and a sensitivity of 58% compared with Cancer Registry records. The combination of flags with the greatest PPV and sensitivity was ‘(lumpectomy or mastectomy) and (diagnosis of invasive breast cancer or breast radiotherapy)’ (PPV and sensitivity 83%). Conclusions: In the absence of Cancer Registry data, administrative and self-reported data can be used to accurately identify cases of invasive breast cancer for sample identification, removing cases from a sample, or risk adjustment. Invasive breast cancer can be accurately identified using hospital-derived diagnosis alone or in combination with surgeries and breast radiotherapy

Evaluation of alternative respiratory syndromes for specific syndromic surveillance of influenza and respiratory syncytial virus: a time series analysis

<p>Abstract</p> <p>Background</p> <p>Syndromic surveillance is increasingly being evaluated for its potential for early warning of increased disease activity in the population. However, interpretation is hampered by the difficulty of attributing a causative pathogen. We described the temporal relationship between laboratory counts of influenza and respiratory syncytial virus (RSV) detection and alternative groupings of Emergency Department (ED) respiratory diagnoses.</p> <p>Methods</p> <p>ED and laboratory data were obtained for the south-eastern area of Sydney, NSW for the period 1 June 2001 - 1 December 2006. Counts of ED visits and laboratory confirmed positive RSV and influenza cases were aggregated by week. Semi-parametric generalized additive models (GAM) were used to determine the association between the incidence of RSV and influenza and the incidence of respiratory syndrome ED presentations while controlling for temporal confounders.</p> <p>Results</p> <p>For every additional RSV laboratory count, ED diagnoses of bronchiolitis increased by 3.1% (95%CI: 2.7%-3.5%) in the same week. For every additional influenza laboratory count, ED diagnoses of influenza-like illness increased by 4.7% (95%CI: 4.2%-5.2%) one week earlier.</p> <p>Conclusion</p> <p>In this study, large increases in ED diagnoses of bronchiolitis and influenza-like illness were independent and proxy indicators for RSV and influenza activity, respectively.</p

Defining the True Sensitivity of Culture for the Diagnosis of Melioidosis Using Bayesian Latent Class Models

BACKGROUND: Culture remains the diagnostic gold standard for many bacterial infections, and the method against which other tests are often evaluated. Specificity of culture is 100% if the pathogenic organism is not found in healthy subjects, but the sensitivity of culture is more difficult to determine and may be low. Here, we apply Bayesian latent class models (LCMs) to data from patients with a single Gram-negative bacterial infection and define the true sensitivity of culture together with the impact of misclassification by culture on the reported accuracy of alternative diagnostic tests. METHODS/PRINCIPAL FINDINGS: Data from published studies describing the application of five diagnostic tests (culture and four serological tests) to a patient cohort with suspected melioidosis were re-analysed using several Bayesian LCMs. Sensitivities, specificities, and positive and negative predictive values (PPVs and NPVs) were calculated. Of 320 patients with suspected melioidosis, 119 (37%) had culture confirmed melioidosis. Using the final model (Bayesian LCM with conditional dependence between serological tests), the sensitivity of culture was estimated to be 60.2%. Prediction accuracy of the final model was assessed using a classification tool to grade patients according to the likelihood of melioidosis, which indicated that an estimated disease prevalence of 61.6% was credible. Estimates of sensitivities, specificities, PPVs and NPVs of four serological tests were significantly different from previously published values in which culture was used as the gold standard. CONCLUSIONS/SIGNIFICANCE: Culture has low sensitivity and low NPV for the diagnosis of melioidosis and is an imperfect gold standard against which to evaluate alternative tests. Models should be used to support the evaluation of diagnostic tests with an imperfect gold standard. It is likely that the poor sensitivity/specificity of culture is not specific for melioidosis, but rather a generic problem for many bacterial and fungal infections

Investigation of relative risk estimates from studies of the same population with contrasting response rates and designs

Background: There is little empirical evidence regarding the generalisability of relative risk estimates from studies which have relatively low response rates or are of limited representativeness. The aim of this study was to investigate variation in exposure-outcome relationships in studies of the same population with different response rates and designs by comparing estimates from the 45 and Up Study, a population-based cohort study (self-administered postal questionnaire, response rate 18%), and the New South Wales Population Health Survey (PHS) (computer-assisted telephone interview, response rate ~60%). Methods: Logistic regression analysis of questionnaire data from 45 and Up Study participants (n = 101,812) and 2006/ 2007 PHS participants (n = 14,796) was used to calculate prevalence estimates and odds ratios (ORs) for comparable variables, adjusting for age, sex and remoteness. ORs were compared using Wald tests modelling each study separately, with and without sampling weights. Results: Prevalence of some outcomes (smoking, private health insurance, diabetes, hypertension, asthma) varied between the two studies. For highly comparable questionnaire items, exposure-outcome relationship patterns were almost identical between the studies and ORs for eight of the ten relationships examined did not differ significantly. For questionnaire items that were only moderately comparable, the nature of the observed relationships did not differ materially between the two studies, although many ORs differed significantly. Conclusions: These findings show that for a broad range of risk factors, two studies of the same population with varying response rate, sampling frame and mode of questionnaire administration yielded consistent estimates of exposure-outcome relationships. However, ORs varied between the studies where they did not use identical questionnaire items

Allopurinol versus usual care in UK patients with ischaemic heart disease (ALL-HEART): a multicentre, prospective, randomised, open-label, blinded-endpoint trial

BACKGROUND: Allopurinol is a urate-lowering therapy used to treat patients with gout. Previous studies have shown that allopurinol has positive effects on several cardiovascular parameters. The ALL-HEART study aimed to determine whether allopurinol therapy improves major cardiovascular outcomes in patients with ischaemic heart disease. METHODS: ALL-HEART was a multicentre, prospective, randomised, open-label, blinded-endpoint trial done in 18 regional centres in England and Scotland, with patients recruited from 424 primary care practices. Eligible patients were aged 60 years or older, with ischaemic heart disease but no history of gout. Participants were randomly assigned (1:1), using a central web-based randomisation system accessed via a web-based application or an interactive voice response system, to receive oral allopurinol up-titrated to a dose of 600 mg daily (300 mg daily in participants with moderate renal impairment at baseline) or to continue usual care. The primary outcome was the composite cardiovascular endpoint of non-fatal myocardial infarction, non-fatal stroke, or cardiovascular death. The hazard ratio (allopurinol vs usual care) in a Cox proportional hazards model was assessed for superiority in a modified intention-to-treat analysis (excluding randomly assigned patients later found to have met one of the exclusion criteria). The safety analysis population included all patients in the modified intention-to-treat usual care group and those who took at least one dose of randomised medication in the allopurinol group. This study is registered with the EU Clinical Trials Register, EudraCT 2013-003559-39, and ISRCTN, ISRCTN32017426. FINDINGS: Between Feb 7, 2014, and Oct 2, 2017, 5937 participants were enrolled and then randomly assigned to receive allopurinol or usual care. After exclusion of 216 patients after randomisation, 5721 participants (mean age 72·0 years [SD 6·8], 4321 [75·5%] males, and 5676 [99·2%] white) were included in the modified intention-to-treat population, with 2853 in the allopurinol group and 2868 in the usual care group. Mean follow-up time in the study was 4·8 years (1·5). There was no evidence of a difference between the randomised treatment groups in the rates of the primary endpoint. 314 (11·0%) participants in the allopurinol group (2·47 events per 100 patient-years) and 325 (11·3%) in the usual care group (2·37 events per 100 patient-years) had a primary endpoint (hazard ratio [HR] 1·04 [95% CI 0·89–1·21], p=0·65). 288 (10·1%) participants in the allopurinol group and 303 (10·6%) participants in the usual care group died from any cause (HR 1·02 [95% CI 0·87–1·20], p=0·77). INTERPRETATION: In this large, randomised clinical trial in patients aged 60 years or older with ischaemic heart disease but no history of gout, there was no difference in the primary outcome of non-fatal myocardial infarction, non-fatal stroke, or cardiovascular death between participants randomised to allopurinol therapy and those randomised to usual care. FUNDING: UK National Institute for Health and Care Research

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

A framework for human microbiome research

A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies

Structure, function and diversity of the healthy human microbiome

Author Posting. © The Authors, 2012. This article is posted here by permission of Nature Publishing Group. The definitive version was published in Nature 486 (2012): 207-214, doi:10.1038/nature11234.Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.This research was supported in part by National Institutes of Health grants U54HG004969 to B.W.B.; U54HG003273 to R.A.G.; U54HG004973 to R.A.G., S.K.H. and J.F.P.; U54HG003067 to E.S.Lander; U54AI084844 to K.E.N.; N01AI30071 to R.L.Strausberg; U54HG004968 to G.M.W.; U01HG004866 to O.R.W.; U54HG003079 to R.K.W.; R01HG005969 to C.H.; R01HG004872 to R.K.; R01HG004885 to M.P.; R01HG005975 to P.D.S.; R01HG004908 to Y.Y.; R01HG004900 to M.K.Cho and P. Sankar; R01HG005171 to D.E.H.; R01HG004853 to A.L.M.; R01HG004856 to R.R.; R01HG004877 to R.R.S. and R.F.; R01HG005172 to P. Spicer.; R01HG004857 to M.P.; R01HG004906 to T.M.S.; R21HG005811 to E.A.V.; M.J.B. was supported by UH2AR057506; G.A.B. was supported by UH2AI083263 and UH3AI083263 (G.A.B., C. N. Cornelissen, L. K. Eaves and J. F. Strauss); S.M.H. was supported by UH3DK083993 (V. B. Young, E. B. Chang, F. Meyer, T. M. S., M. L. Sogin, J. M. Tiedje); K.P.R. was supported by UH2DK083990 (J. V.); J.A.S. and H.H.K. were supported by UH2AR057504 and UH3AR057504 (J.A.S.); DP2OD001500 to K.M.A.; N01HG62088 to the Coriell Institute for Medical Research; U01DE016937 to F.E.D.; S.K.H. was supported by RC1DE0202098 and R01DE021574 (S.K.H. and H. Li); J.I. was supported by R21CA139193 (J.I. and D. S. Michaud); K.P.L. was supported by P30DE020751 (D. J. Smith); Army Research Office grant W911NF-11-1-0473 to C.H.; National Science Foundation grants NSF DBI-1053486 to C.H. and NSF IIS-0812111 to M.P.; The Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231 for P.S. C.; LANL Laboratory-Directed Research and Development grant 20100034DR and the US Defense Threat Reduction Agency grants B104153I and B084531I to P.S.C.; Research Foundation - Flanders (FWO) grant to K.F. and J.Raes; R.K. is an HHMI Early Career Scientist; Gordon&BettyMoore Foundation funding and institutional funding fromthe J. David Gladstone Institutes to K.S.P.; A.M.S. was supported by fellowships provided by the Rackham Graduate School and the NIH Molecular Mechanisms in Microbial Pathogenesis Training Grant T32AI007528; a Crohn’s and Colitis Foundation of Canada Grant in Aid of Research to E.A.V.; 2010 IBM Faculty Award to K.C.W.; analysis of the HMPdata was performed using National Energy Research Scientific Computing resources, the BluBioU Computational Resource at Rice University