Comparing Survival Extrapolation within All-Cause and Relative Survival Frameworks by Standard Parametric Models and Flexible Parametric Spline Models Using the Swedish Cancer Registry.

BACKGROUND: In health technology assessment, restricted mean survival time and life expectancy are commonly evaluated. Parametric models are typically used for extrapolation. Spline models using a relative survival framework have been shown to estimate life expectancy of cancer patients more reliably; however, more research is needed to assess spline models using an all-cause survival framework and standard parametric models using a relative survival framework. AIM: To assess survival extrapolation using standard parametric models and spline models within relative survival and all-cause survival frameworks. METHODS: From the Swedish Cancer Registry, we identified patients diagnosed with 5 types of cancer (colon, breast, melanoma, prostate, and chronic myeloid leukemia) between 1981 and 1990 with follow-up until 2020. Patients were categorized into 15 cancer cohorts by cancer and age group (18-59, 60-69, and 70-99 y). We right-censored the follow-up at 2, 3, 5, and 10 y and fitted the parametric models within an all-cause and a relative survival framework to extrapolate to 10 y and lifetime in comparison with the observed Kaplan-Meier survival estimates. All cohorts were modeled with 6 standard parametric models (exponential, Weibull, Gompertz, log-logistic, log-normal, and generalized gamma) and 3 spline models (on hazard, odds, and normal scales). RESULTS: For predicting 10-y survival, spline models generally performed better than standard parametric models. However, using an all-cause or a relative survival framework did not show any distinct difference. For lifetime survival, extrapolating from a relative survival framework agreed better with the observed survival, particularly using spline models. CONCLUSIONS: For extrapolation to 10 y, we recommend spline models. For extrapolation to lifetime, we suggest extrapolating in a relative survival framework, especially using spline models. HIGHLIGHTS: For survival extrapolation to 10 y, spline models generally performed better than standard parametric models did. However, using an all-cause or a relative survival framework showed no distinct difference under the same parametric model.Survival extrapolation to lifetime within a relative survival framework agreed well with the observed data, especially using spline models.Extrapolating parametric models within an all-cause survival framework may overestimate survival proportions at lifetime; models for the relative survival approach may underestimate instead.

Cost-effectiveness of Prostate Cancer Screening Using Magnetic Resonance Imaging or Standard Biopsy Based on the STHLM3-MRI Study.

Importance: The combination of prostate-specific antigen (PSA) testing with magnetic resonance imaging (MRI) for prostate cancer detection has rarely been evaluated in a screening context. The STHLM3-MRI screening-by-invitation study (NCT03377881) has reported the benefits of using MRI with subsequent combined targeted and standard biopsies compared with using standard biopsies alone. Objective: To investigate the cost-effectiveness of prostate cancer screening using MRI with combined targeted and standard biopsies compared with standard biopsies alone among men aged 55 to 69 years in Sweden, based on evidence from the STHLM3-MRI study. Design, Setting, and Participants: This economic evaluation study was conducted from a lifetime health care perspective using a microsimulation model to evaluate no screening and screening strategies among adult men in Sweden. Men aged 55 to 69 years in Sweden were simulated for no screening and screening strategies. Input parameters were obtained from the STHLM3-MRI study and recent reviews. One-way and probabilistic sensitivity analyses were performed in May 2022. Interventions: No screening, quadrennial PSA screening using standard biopsies alone, and MRI-based screening using combined targeted and standard biopsies. Main Outcomes and Measures: The number of tests, incidence, deaths, costs, quality-adjusted life-years (QALY), and incremental cost-effectiveness ratios (ICERs) were estimated. Results: A total 603 men were randomized to the standard arm, 165 of these participants (27.4%) did not undergo standard biopsy; 929 men were randomized to the experimental arm, 111 (11.9%) of whom did undergo MRI or any biopsy. Compared with no screening, the screening strategies were associated with reduced lifetime prostate cancer-related deaths by 6% to 9%. Screening with MRI and the combined biopsies resulted in an ICER of US $53 736, which is classified as a moderate cost per QALY gained in Sweden. Relative to screening with standard biopsies alone, MRI-based screening reduced the number of both lifetime biopsies and overdiagnosis by approximately 50% and had a high probability of being cost-effective than the traditional PSA screening. Conclusions and Relevance: For prostate cancer screening, this economic evaluation study found that PSA testing followed by MRI with subsequent combined targeted and standard biopsies had a high probability to be more cost-effective compared with the traditional screening pathway using PSA and standard biopsy. MRI-based screening may be considered for early detection of prostate cancer in Sweden.

Cost-Effectiveness Analysis of Prostate Cancer Screening in the UK: A Decision Model Analysis Based on the CAP Trial.

BACKGROUND AND OBJECTIVE: Most guidelines in the UK, Europe and North America do not recommend organised population-wide screening for prostate cancer. Prostate-specific antigen-based screening can reduce prostate cancer-specific mortality, but there are concerns about overdiagnosis, overtreatment and economic value. The aim was therefore to assess the cost effectiveness of eight potential screening strategies in the UK. METHODS: We used a cost-utility analysis with an individual-based simulation model. The model was calibrated to data from the 10-year follow-up of the Cluster Randomised Trial of PSA Testing for Prostate Cancer (CAP). Treatment effects were modelled using data from the Prostate Testing for Cancer and Treatment (ProtecT) trial. The participants were a hypothetical population of 10 million men in the UK followed from age 30 years to death. The strategies were: no screening; five age-based screening strategies; adaptive screening, where men with an initial prostate-specific antigen level of < 1.5 ng/mL are screened every 6 years and those above this level are screened every 4 years; and two polygenic risk-stratified screening strategies. We assumed the use of pre-biopsy multi-parametric magnetic resonance imaging for men with prostate-specific antigen ≥ 3 ng/mL and combined transrectal ultrasound-guided and targeted biopsies. The main outcome measures were projected lifetime costs and quality-adjusted life-years from a National Health Service perspective. RESULTS: All screening strategies increased costs compared with no screening, with the majority also increasing quality-adjusted life-years. At willingness-to-pay thresholds of £20,000 or £30,000 per quality-adjusted life-year gained, a once-off screening at age 50 years was optimal, although this was sensitive to the utility estimates used. Although the polygenic risk-stratified screening strategies were not on the cost-effectiveness frontier, there was evidence to suggest that they were less cost ineffective than the alternative age-based strategies. CONCLUSIONS: Of the prostate-specific antigen-based strategies compared, only a once-off screening at age 50 years was potentially cost effective at current UK willingness-to-pay thresholds. An additional follow-up of CAP to 15 years may reduce uncertainty about the cost effectiveness of the screening strategies.

Cost-Effectiveness of the Stockholm3 Test and Magnetic Resonance Imaging in Prostate Cancer Screening: A Microsimulation Study.

BACKGROUND: Stockholm3 is a risk model that combines the prostate-specific antigen (PSA) test, other plasma protein biomarkers, single nucleotide polymorphisms, and clinical variables. The STHLM3-MRI study (NCT03377881) found that the Stockholm3 test with magnetic resonance imaging (MRI) and combined targeted and systematic biopsies maintained the sensitivity for clinically significant cancers, and reduced the number of benign biopsies and clinically insignificant cancers. OBJECTIVE: To assess the cost-effectiveness of MRI-based screening for prostate cancer using either Stockholm3 as a reflex test or PSA alone. DESIGN, SETTING, AND PARTICIPANTS: A cost-utility analysis was performed from a lifetime societal perspective using a microsimulation model for men aged 55-69 yr in Sweden. Test characteristics were estimated from the STHLM3-MRI study. INTERVENTION: No screening and three quadrennial screening strategies, including either PSA ≥3 ng/ml or Stockholm3 with reflex test thresholds of PSA ≥1.5 or 2 ng/ml as criteria for referral to MRI, were performed, and those who were MRI positive had combined targeted and systematic biopsies. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Predictions included the number of tests, cancer incidence and mortality, costs, and quality-adjusted life-years. Uncertainties in key parameters were assessed using sensitivity analyses. RESULTS AND LIMITATIONS: Compared with no screening, the screening strategies were predicted to reduce prostate cancer deaths by 7-9% across a lifetime. The use of Stockholm3 with PSA ≥2 ng/ml resulted in a 60% reduction in MRI compared with screening using PSA. This Stockholm3 strategy was cost-effective with a probability of 70% at a cost-effectiveness threshold of €47 218 (500 000 Swedish Kronor). As a potential limitation, the economic perspective was specific to Sweden. CONCLUSIONS: Screening with the Stockholm3 test at a reflex threshold of PSA ≥2 ng/ml and MRI was predicted to be cost-effective in Sweden. PATIENT SUMMARY: The Stockholm3 test with image-based screening may reduce screening-related harms and costs, while maintaining the health benefits from early detection of prostate cancer.

Comparing Modeling Approaches for Discrete Event Simulations With Competing Risks Based on Censored Individual Patient Data: A Simulation Study and Illustration in Colorectal Cancer.

OBJECTIVES: This study aimed to provide detailed guidance on modeling approaches for implementing competing events in discrete event simulations based on censored individual patient data (IPD). METHODS: The event-specific distributions (ESDs) approach sampled times from event-specific time-to-event distributions and simulated the first event to occur. The unimodal distribution and regression approach sampled a time from a combined unimodal time-to-event distribution, representing all events, and used a (multinomial) logistic regression model to select the event to be simulated. A simulation study assessed performance in terms of relative absolute event incidence difference and relative entropy of time-to-event distributions for different types and levels of right censoring, numbers of events, distribution overlap, and sample sizes. Differences in cost-effectiveness estimates were illustrated in a colorectal cancer case study. RESULTS: Increased levels of censoring negatively affected the modeling approaches' performance. A lower number of competing events and higher overlap of distributions improved performance. When IPD were censored at random times, ESD performed best. When censoring occurred owing to a maximum follow-up time for 2 events, ESD performed better for a low level of censoring (ie, 10%). For 3 or 4 competing events, ESD better represented the probabilities of events, whereas unimodal distribution and regression better represented the time to events. Differences in cost-effectiveness estimates, both compared with no censoring and between approaches, increased with increasing censoring levels. CONCLUSIONS: Modelers should be aware of the different modeling approaches available and that selection between approaches may be informed by data characteristics. Performing and reporting extensive validation efforts remains essential to ensure IPD are appropriately represented.

Human exposome assessment platform.

The Human Exposome Assessment Platform (HEAP) is a research resource for the integrated and efficient management and analysis of human exposome data. The project will provide the complete workflow for obtaining exposome actionable knowledge from population-based cohorts. HEAP is a state-of-the-science service composed of computational resources from partner institutions, accessed through a software framework that provides the world's fastest Hadoop platform for data warehousing and applied artificial intelligence (AI). The software, will provide a decision support system for researchers and policymakers. All the data managed and processed by HEAP, together with the analysis pipelines, will be available for future research. In addition, the platform enables adding new data and analysis pipelines. HEAP's final product can be deployed in multiple instances to create a network of shareable and reusable knowledge on the impact of exposures on public health.

The cost-effectiveness of prostate cancer screening using the Stockholm3 test.

OBJECTIVES: The European Randomized Study of Screening for Prostate Cancer found that prostate-specific antigen (PSA) screening reduced prostate cancer mortality, however the costs and harms from screening may outweigh any mortality reduction. Compared with screening using the PSA test alone, using the Stockholm3 Model (S3M) as a reflex test for PSA ≥ 1 ng/mL has the same sensitivity for Gleason score ≥ 7 cancers while the relative positive fractions for Gleason score 6 cancers and no cancer were 0.83 and 0.56, respectively. The cost-effectiveness of the S3M test has not previously been assessed. METHODS: We undertook a cost-effectiveness analysis from a lifetime societal perspective. Using a microsimulation model, we simulated for: (i) no prostate cancer screening; (ii) screening using the PSA test; and (iii) screening using the S3M test as a reflex test for PSA values ≥ 1, 1.5 and 2 ng/mL. Screening strategies included quadrennial re-testing for ages 55-69 years performed by a general practitioner. Discounted costs, quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs) were calculated. RESULTS: Comparing S3M with a reflex threshold of 2 ng/mL with screening using the PSA test, S3M had increased effectiveness, reduced lifetime biopsies by 30%, and increased societal costs by 0.4%. Relative to the PSA test, the S3M reflex thresholds of 1, 1.5 and 2 ng/mL had ICERs of 170,000, 60,000 and 6,000 EUR/QALY, respectively. The S3M test was more cost-effective at higher biopsy costs. CONCLUSIONS: Prostate cancer screening using the S3M test for men with an initial PSA ≥ 2.0 ng/mL was cost-effective compared with screening using the PSA test alone.

Cost-effectiveness of cervical cancer screening with primary HPV testing for unvaccinated women in Sweden.

BACKGROUND: Sweden revised their cervical cancer screening program in 2017 to include cytology-based screening for women aged 23-29 years and primary human papillomavirus (HPV) testing for women aged 30-64 years; however, alternative strategies may be preferred. To inform cervical cancer prevention policies for unvaccinated women, we evaluated the cost-effectiveness of alternative screening strategies, including the current Swedish guidelines. METHODS: We adapted a mathematical simulation model of HPV and cervical cancer to the Swedish context using primary epidemiologic data. We compared the cost-effectiveness of alternative screening strategies that varied by the age to start screening, the age to switch from cytology to HPV testing, HPV strategies not preceded by cytology, screening frequency, and management of HPV-positive/cytology-negative women. RESULTS: We found that the current Swedish guidelines were more costly and less effective than alternative primary HPV-based strategies. All cost-efficient strategies involved primary HPV testing not preceded by cytology for younger women. Given a cost-effectiveness threshold of €85,619 per quality-adjusted life year gained, the optimal strategy involved 5-yearly primary HPV-based screening for women aged 23-50 years and 10-yearly HPV-based screening for women older than age 50 years. CONCLUSIONS: Primary screening based on HPV alone may be considered for unvaccinated women for those countries with similar HPV burdens.

Impact of model misspecification in shared frailty survival models.

Survival models incorporating random effects to account for unmeasured heterogeneity are being increasingly used in biostatistical and applied research. Specifically, unmeasured covariates whose lack of inclusion in the model would lead to biased, inefficient results are commonly modeled by including a subject-specific (or cluster-specific) frailty term that follows a given distribution (eg, gamma or lognormal). Despite that, in the context of parametric frailty models, little is known about the impact of misspecifying the baseline hazard or the frailty distribution or both. Therefore, our aim is to quantify the impact of such misspecification in a wide variety of clinically plausible scenarios via Monte Carlo simulation, using open-source software readily available to applied researchers. We generate clustered survival data assuming various baseline hazard functions, including mixture distributions with turning points, and assess the impact of sample size, variance of the frailty, baseline hazard function, and frailty distribution. Models compared include standard parametric distributions and more flexible spline-based approaches; we also included semiparametric Cox models. The resulting bias can be clinically relevant. In conclusion, we highlight the importance of fitting models that are flexible enough and the importance of assessing model fit. We illustrate our conclusions with two applications using data on diabetic retinopathy and bladder cancer. Our results show the importance of assessing model fit with respect to the baseline hazard function and the distribution of the frailty: misspecifying the former leads to biased relative and absolute risk estimates, whereas misspecifying the latter affects absolute risk estimates and measures of heterogeneity.

Phase of care prevalence for prostate cancer in New South Wales, Australia: A population-based modelling study.

OBJECTIVE: To develop a method for estimating the future numbers of prostate cancer survivors requiring different levels of care. DESIGN, SETTING AND PARTICIPANTS: Analysis of population-based cancer registry data for prostate cancer cases (aged 18-84 years) diagnosed in 1996-2007, and a linked dataset with hospital admission data for men with prostate cancer diagnosed during 2005-2007 in New South Wales (NSW), Australia. METHODS: Cancer registry data (1996-2007) were used to project complete prostate cancer prevalence in NSW, Australia for 2008-2017, and treatment information from hospital records (2005-2007) was used to estimate the inpatient care needs during the first year after diagnosis. The projected complete prevalence was divided into care needs-based groups. We first divided the cohort into two groups based on patient's age (<75 and 75-84 years). The younger cohort was further divided into initial care and monitoring phases. Cause of death data were used as a proxy for patients requiring last year of life prostate cancer care. Finally, episode data were used to estimate the future number of cases with metastatic progression. RESULTS: Of the estimated total of 60,910 men with a previous diagnosis of prostate cancer in 2017, the largest groups will be older patients (52.0%) and younger men who require monitoring (42.5%). If current treatment patterns continue, in the first year post-diagnosis 41% (1380) of patients (<75 years) will have a radical prostatectomy, and 52.6% (1752) will be likely to have either active surveillance, external beam radiotherapy or androgen deprivation therapy. About 3% will require care for subsequent metastases, and 1288 men with prostate cancer are likely to die from the disease in 2017. CONCLUSIONS: This method extends the application of routinely collected population-based data, and can contribute much to the knowledge of the number of men with prostate cancer and their health care requirements. This could be of significant use in planning future cancer care services and facilities in Australia.

Projecting prevalence by stage of care for prostate cancer and estimating future health service needs: protocol for a modelling study.

Introduction Current strategies for the management of prostate cancer are inadequate in Australia. We will, in this study, estimate current service needs and project the future needs for prostate cancer patients in Australia. Methods and analysis First, we will project the future prevalence of prostate cancer for 2010-2018 using data for 1972-2008 from the New South Wales (NSW) Central Cancer Registry. These projections, based on modelled incidence and survival estimates, will be estimated using PIAMOD (Prevalence, Incidence, Analysis MODel) software. Then the total prevalence will be decomposed into five stages of care: initial care, continued monitoring, recurrence, last year of life and long-term survivor. Finally, data from the NSW Prostate Cancer Care and Outcomes Study, including data on patterns of treatment and associated quality of life, will be used to estimate the type and amount of services that will be needed by prostate cancer patients in each stage of care. In addition, Central Cancer Registry episode data will be used to estimate transition rates from localised or locally advanced prostate cancer to metastatic disease. Medicare and Pharmaceutical Benefits data, linked with Prostate Cancer Care and Outcomes Study data, will be used to complement the Cancer Registry episode data. The methods developed will be applied Australia-wide to obtain national estimates of the future prevalence of prostate cancer for different stages of clinical care. Ethics and dissemination This study was approved by the NSW Population and Health Services Research Ethics Committee. Results of the study will be disseminated widely to different interest groups and organisations through a report, conference presentations and peer-reviewed articles.

Socioeconomic inequalities in the diffusion of health technology: Uptake of coronary procedures as an example.

This paper examines socioeconomic lags in the diffusion of high technology health care, focusing on the diffusion of coronary procedures in people with ischaemic heart disease. Using linked hospital and mortality data, we studied patients admitted to Western Australian hospitals with a first admission for acute myocardial infarction between 1989 and 2003 (n = 27,209). An outcome event was the receipt, within a year, of a coronary procedure-angiography, angioplasty and/or coronary artery bypass surgery (CABG). Socioeconomic status (SES) was assigned to each individual using the SEIFA Index of Disadvantage. Cox regression was used to model the association between SES and procedure rates in five consecutive three-year time periods. Angiography and CABG showed socioeconomic lags in diffusion, with rates peaking earlier in higher SES patients, such that the inequality patterns were consistent with the inverse equity hypothesis. The evidence for a lag in diffusion for angioplasty was weaker. Overall, that there is some evidence for a lag in diffusion of health technology indicates that it is essential to consider trends over time when examining the equity impact of health technologies.

Universal health care no guarantee of equity: comparison of socioeconomic inequalities in the receipt of coronary procedures in patients with acute myocardial infarction and angina.

BACKGROUND: In Australia there is a socioeconomic gradient in morbidity and mortality favouring socioeconomically advantaged people, much of which is accounted for by ischaemic heart disease. This study examines if Australia's universal health care system, with its mixed public/private funding and delivery model, may actually perpetuate this inequity. We do this by quantifying and comparing socioeconomic inequalities in the receipt of coronary procedures in patients with acute myocardial infarction (AMI) and patients with angina. METHODS: Using linked hospital and mortality data, we followed patients admitted to Western Australian hospitals with a first admission for AMI (n = 5539) or angina (n = 7401) in 2001-2003. An outcome event was the receipt, within a year, of a coronary procedure-angiography, angioplasty and/or coronary artery bypass surgery (CABG). Socioeconomic status was assigned to each individual using an area-based measure, the SEIFA Index of Disadvantage. Multivariable proportional hazards regression was used to model the association between socioeconomic status and procedure rates, allowing for censoring and adjustment of multiple covariates. Mediating models examined the effect of private health insurance. RESULTS: In the AMI patient cohort, socioeconomic gradients were not evident except that disadvantaged women were more likely than advantaged women to undergo CABG. In contrast, in the angina patient group there were clear socioeconomic gradients for all procedures, favouring more advantaged patients. Compared with patients in the most disadvantaged quintile of socioeconomic status, patients in the least disadvantaged quintile were 11% (1-21%) more likely to receive angiography, 52% (29-80%) more likely to undergo angioplasty and 30% (3-55%) more likely to undergo CABG. Private health insurance explained some of the socioeconomic variation in rates. CONCLUSIONS: Australia's universal health care system does not guarantee equity in the receipt of high technology health care for patients with ischaemic heart disease. While such a system might ensure equity for patients with AMI, where guidelines for treatment are relatively well established, this is not the case for angina patients, where health care may be less urgent and more discretionary.

Is inequity undermining Australia's 'universal' health care system? Socio-economic inequalities in the use of specialist medical and non-medical ambulatory health care.

OBJECTIVES: To quantify need-adjusted socio-economic inequalities in medical and non-medical ambulatory health care in Australia and to examine the effects of specific interventions, namely concession cards and private health insurance (PHI), on equity. METHODS: We used data from a 2004 survey of 10,905 Australian women aged 53 to 58 years. We modelled the association between socio-economic status and health service use--GPs, specialists, hospital doctors, allied and alternative health practitioners, and dentists--adjusting for health status and other confounding variables. We quantified inequalities using the relative index of inequality (RII) using Poisson regression. The contribution of concession cards and PHI in promoting equity/inequity was examined using mediating models. RESULTS: There was equality in the use of GP services, but socio-economically advantaged women were more likely than disadvantaged women to use specialist (RII=1.41, 95% CI:1.26-1.58), allied health (RII=1.21,1.12-1.30), alternative health (RII=1.29,1.13-1.47) and dental services (RII=1.61,1.48-1.75) after adjusting for need, and they were less likely to visit hospital doctors (RII=0.74,0.57-0.96). Concession cards reduced socio-economic inequality in GP but not specialist care. Inequality in dental and allied health services was partly explained by inequalities in PHI. CONCLUSIONS AND IMPLICATIONS: Substantial socio-economic inequity exists in use of specialist and non-medical ambulatory care in Australia. This is likely to exacerbate existing health inequalities, but is potentially amenable to change.

Differential impacts of health care in Australia: trend analysis of socioeconomic inequalities in avoidable mortality.

BACKGROUND: Recent avoidable mortality trends in Australia suggest that health care has made a substantial contribution to reducing mortality. This study investigates if the benefits of health care have been distributed equally by comparing declines in avoidable with non-avoidable mortality over time by socioeconomic status (SES). METHODS: We calculated avoidable and non-avoidable mortality rates in Australia by small areas for 1986, 1991, 1997 and 2002. We performed pooled cross-sectional trend analysis of indirectly standardized mortality rates by SES and year, modelling using Poisson regression with over-dispersion. Socioeconomic inequalities were quantified using the relative (RII) and slope (SII) index of inequality. RESULTS: The annual percentage decline in avoidable mortality at the higher end of the socioeconomic continuum (5.0%; 95% CI: 4.7-5.4%) was larger than at the lower end (3.5%; 3.2-3.8%), with increasing relative inequality between 1986 (RII = 1.54; 1.46-1.63) and 2002 (RII = 2.00; 1.95-2.06), greater than that in non-avoidable mortality (P = 0.036). In absolute terms, avoidable deaths fell annually by 7.4 (6.9-7.8) and 8.4 (7.9-8.9) deaths per 100 000 at the higher and lower end of the spectrum, respectively, with absolute inequality decreasing between 1986 (SII = 97.8; 87.6-107.9) and 2002 (SII = 81.5; 74.6-88.5). CONCLUSIONS: Health care has contributed to decreasing the absolute SES mortality gap. However, advantaged people have obtained a disproportionate benefit of health care, contributing to widening relative health inequalities. A universal heath care system does not guarantee equality in health-care-related outcomes.

The health effects of jobs: status, working conditions, or both?

BACKGROUND: This study investigates whether the association of job strain and insecurity with health differs by status. METHODS: A cross-sectional study of 2,249 employed workers aged 40-44 years conducted in two regions in south-east Australia in 2000 used a self-completed questionnaire to collect data. Multivariate analyses were used to compare depression, anxiety, physical health and general practitioner (GP) visits over 12 months across categories of job strain and insecurity for three status groups (high, middle and low). RESULTS: High job strain and job insecurity were independently associated with poor mental health, poor physical health and visits to the GP for all status groups when adjusted for confounders. High job strain was associated with depression (OR = 2.46, 95% CI 1.96-3.07), anxiety (OR = 2.56, 95% Cl 2.05-3.20), lower mean physical health scores (-1.11, 95% CI -1.98 - -0.23), and more visits to the GP (IRR = 1.20, 95% CI 1.05-1.37). High job insecurity also showed significant associations with depression (OR = 3.03, 95% Cl 2.03-4.53), anxiety (OR = 2.66, 95% CI 1.81-3.91), and GP visits (IRR = 1.27, 95% CI 1.01-1.60). There were no significant differences by status in the associations of job strain and insecurity with outcomes. CONCLUSION: High-status workers were just as likely as low-status workers to be exposed to adverse work conditions and both status groups showed similar health effects. IMPLICATIONS: Exposure to insecure and high-strain jobs is likely to rise as economies and labour markets respond to globalisation and political change. High status may not protect employees from either exposure or impact, thus widening the population health consequences of adverse work conditions.