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This paper proposes a methodology for using survey data to understand the composition of elites, through analysing the pool of potential members. An occupational-based measure of ‘potential power elite’ (PPE) is created and compared with other measures of occupational advantage. It is argued that this measure can be utilised to explore if the processes causing certain social groups to be under-represented in elite positions are around selection or the population recruited from. We provide analysis of elite positions in the UK and Sweden, demonstrating differences in terms of the potential pool of elite members and the occupational histories of people of those employed in roles associated with elite recruitment. We argue that understanding the composition of the PPE provides a more nuanced analysis of the processes of meritocracy in accessing positions of power and social influence. [ABSTRACT FROM PUBLISHER]

Large age-dependant differences in temporal trends in 1- and 5-year relative survival have been observed in patients with acute myeloid leukaemia (AML) in Sweden. This investigation used an alternative approach to studying patient survival that simultaneously estimated the proportion of patients cured from their cancer and the survival of the ‘uncured’. We conducted a population-based study including 6439 AML patients aged 19–80 years in Sweden between 1973 and 2001. Mixture cure models were estimated, with age at diagnosis categorised (19–40, 41–60, 61–70 and 71–80) and year of diagnosis modelled using splines. In 1975 the cure proportion was ≤6% in all age groups and the median survival time for ‘uncured’ patients was <0·5 years. In 2000 the cure proportion was 68% (95% confidence interval 56–77%) in the youngest group, and 32% (25–39%), 8% (3–21%), and 4% (2–8%) in the other groups, respectively. The median survival times for ‘uncured’ were 0·74 (0·43–1·26), 0·71 (0·53–0·97), 0·69 (0·51–0·95) and 0·37 (0·31–0·44) years, respectively. A dramatic improvement in the cure proportion was seen in younger patients, whereas improvement in older ages was mainly within the survival of the ‘uncured’. This novel approach of analysing survival data could be a valuable tool for physicians, patients, health care planners and health economists. [ABSTRACT FROM AUTHOR]

Purpose: This study introduces a novel method for estimating the variance of life expectancy since diagnosis (LEC) and loss in life expectancy (LLE) for cancer patients within a relative survival framework in situations where life tables based on the entire general population are not accessible. LEC and LLE are useful summary measures of survival in population-based cancer studies, but require information on the mortality in the general population. Our method addresses the challenge of incorporating the uncertainty of expected mortality rates when using a sample from the general population. Methods: To illustrate the approach, we estimated LEC and LLE for patients diagnosed with colon and breast cancer in Sweden. General population mortality rates were based on a random sample drawn from comparators of a matched cohort. Flexible parametric survival models were used to model the mortality among cancer patients and the mortality in the random sample from the general population. Based on the models, LEC and LLE together with their variances were estimated. The results were compared with those obtained using fixed expected mortality rates. Results: By accounting for the uncertainty of expected mortality rates, the proposed method ensures more accurate estimates of variances and, therefore, confidence intervals of LEC and LLE for cancer patients. This is particularly valuable for older patients and some cancer types, where underestimation of the variance can be substantial when the entire general population data are not accessible. Conclusion: The method can be implemented using existing software, making it accessible for use in various cancer studies. The provided example of Stata code further facilitates its adoption. [ABSTRACT FROM AUTHOR]

Background: Multi-state models are used to study several clinically meaningful research questions. Depending on the research question of interest and the information contained in the data, different multi-state structures and modelling choices can be applied. We aim to explore different research questions using a series of multi-state models of increasing complexity when studying repeated prescriptions data, while also evaluating different modelling choices. Methods: We develop a series of research questions regarding the probability of being under antidepressant medication across time using multi-state models, among Swedish women diagnosed with breast cancer (n = 18,313) and an age-matched population comparison group of cancer-free women (n = 92,454) using a register-based database (Breast Cancer Data Base Sweden 2.0). Research questions were formulated ranging from simple to more composite ones. Depending on the research question, multi-state models were built with structures ranging from simpler ones, like single-event survival analysis and competing risks, up to complex bidirectional and recurrent multi-state structures that take into account the recurring start and stop of medication. We also investigate modelling choices, such as choosing a time-scale for the transition rates and borrowing information across transitions. Results: Each structure has its own utility and answers a specific research question. However, the more complex structures (bidirectional, recurrent) enable accounting for the intermittent nature of prescribed medication data. These structures deliver estimates of the probability of being under medication and total time spent under medication over the follow-up period. Sensitivity analyses over different definitions of the medication cycle and different choices of timescale when modelling the transition intensity rates show that the estimates of total probabilities of being in a medication cycle over follow-up derived from the complex structures are quite stable. Conclusions: Each research question requires the definition of an appropriate multi-state structure, with more composite ones requiring such an increase in the complexity of the multi-state structure. When a research question is related with an outcome of interest that repeatedly changes over time, such as the medication status based on prescribed medication, the use of novel multi-state models of adequate complexity coupled with sensible modelling choices can successfully address composite, more realistic research questions. [ABSTRACT FROM AUTHOR]

A recent overview of cancer survival trends 1990–2016 in the Nordic countries reported continued improvements in age-standardized breast cancer survival among women. The aim was to estimate age-specific survival trends over calendar time, including life-years lost, to evaluate if improvements have benefited patients across all ages in the Nordic countries. Data on breast cancers diagnosed 1990–2016 in Denmark, Finland, Iceland, Norway, and Sweden were obtained from the NORDCAN database. Age-standardized and age-specific relative survival (RS) was estimated using flexible parametric models, as was reference-adjusted crude probabilities of death and life-years lost. Age-standardized period estimates of 5-year RS in women diagnosed with breast cancer ranged from 87% to 90% and 10-year RS from 74% to 85%. Ten-year RS increased with 15–18 percentage points from 1990 to 2016, except in Sweden (+9 percentage points) which had the highest survival in 1990. The largest improvements were observed in Denmark, where a previous survival disadvantage diminished. Most recent 5-year crude probabilities of cancer death ranged from 9% (Finland, Sweden) to 12% (Denmark, Iceland), and life-years lost from 3.3 years (Finland) to 4.6 years (Denmark). Although survival improvements were consistent across different ages, women aged ≥70 years had the lowest RS in all countries. Period estimates of 5-year RS were 94–95% in age 55 years and 84–89% in age 75 years, while 10-year RS were 88–91% in age 55 years and 69–84% in age 75 years. Women aged 40 years lost on average 11.0–13.8 years, while women lost 3.8–6.0 years if aged 55 and 1.9–3.5 years if aged 75 years. Survival for Nordic women with breast cancer improved from 1990 to 2016 in all age groups, albeit with larger country variation among older women where survival was also lower. Women over 70 years of age have not had the same survival improvement as women of younger age. [ABSTRACT FROM AUTHOR]

Background: A relative survival approach is often used in population-based cancer studies, where other cause (or expected) mortality is assumed to be the same as the mortality in the general population, given a specific covariate pattern. The population mortality is assumed to be known (fixed), i.e. measured without uncertainty. This could have implications for the estimated standard errors (SE) of any measures obtained within a relative survival framework, such as relative survival (RS) ratios and the loss in life expectancy (LLE). We evaluated the existing approach to estimate SE of RS and the LLE in comparison to if uncertainty in the population mortality was taken into account.Methods: The uncertainty from the population mortality was incorporated using parametric bootstrap approach. The analysis was performed with different levels of stratification and sizes of the general population used for creating expected mortality rates. Using these expected mortality rates, SEs of 5-year RS and the LLE for colon cancer patients in Sweden were estimated.Results: Ignoring uncertainty in the general population mortality rates had negligible (less than 1%) impact on the SEs of 5-year RS and LLE, when the expected mortality rates were based on the whole general population, i.e. all people living in a country or region. However, the smaller population used for creating the expected mortality rates, the larger impact. For a general population reduced to 0.05% of the original size and stratified by age, sex, year and region, the relative precision for 5-year RS was 41% for males diagnosed at age 85. For the LLE the impact was more substantial with a relative precision of 1286%. The relative precision for marginal estimates of 5-year RS was 3% and 30% and for the LLE 22% and 313% when the general population was reduced to 0.5% and 0.05% of the original size, respectively.Conclusions: When the general population mortality rates are based on the whole population, the uncertainty in the estimates of the expected measures can be ignored. However, when based on a smaller population, this uncertainty should be taken into account, otherwise SEs may be too small, particularly for marginal values, and, therefore, confidence intervals too narrow. [ABSTRACT FROM AUTHOR]

Objective: To examine differences in the relative survival and excess death rates of patients with colorectal cancer in Norway, Sweden and England. Methods: All individuals diagnosed with colorectal cancer (ICD10 (International Classification of Diseases, 10th revision) C18-C20) between 1996 and 2004 in England, Norway and Sweden were included in this population-based study of patients with colorectal cancer. The main outcome measures were 5-year cumulative relative period of survival and excess death rates stratified by age and period of follow-up. Results: The survival of English patients with colorectal cancer was significantly lower than was observed in both Norway and Sweden. Five-year age-standardised colon cancer relative survival was 51.1% (95% CI 50.1% to 52.0%) in England compared with 57.9% (95% CI 55.2% to 60.5%) in Norway and 59.9% (95% CI 57.7% to 62.0%) in Sweden. Five-year rectal cancer survival was 52.3% (95% CI 51.1% to 53.5%) in England compared with 60.7% (95% CI 57.0% to 64.2%) and 59.8% (95% CI 56.9% to 62.6%) in Norway and Sweden, respectively. The lower survival for colon cancer in England was primarily due to a high number of excess deaths among older patients in the first 3 months after diagnosis. In patients with rectal cancer, excess deaths remained elevated until 2 years of follow-up. If the lower excess death rate in Norway applied in the English population, then 890 (13.6%) and 654 (16.8%) of the excess deaths in the colon and rectal cancer populations, respectively, could have been prevented at 5 years follow-up. Most of these avoidable deaths occurred shortly after diagnosis. Conclusions: There was significant variation in survival between the countries, with the English population experiencing a poorer outcome, primarily due to a relatively higher number of excess deaths in older patients in the short term after diagnosis. It seems likely, therefore, that in England a greater proportion of the population present with more rapidly fatal disease (especially in the older age groups) than in Norway or Sweden. [ABSTRACT FROM AUTHOR]

Differences in cancer survival between the Nordic countries have previously been reported. The aim of this study was to examine whether these differences in outcome remain, based on updated information from five national cancer registers. The data used for the analysis was from the NORDCAN database focusing on nine common cancers diagnosed 1990–2016 in Denmark, Finland, Iceland, Norway and Sweden with maximum follow-up through 2017. Relative survival (RS) was estimated at 1 and 5 years using flexible parametric RS models, and percentage point differences between the earliest and latest years available were calculated. A consistent improvement in both 1- and 5-year RS was found for most studied sites across all countries. Previously observed differences between the countries have been attenuated. The improvements were particularly pronounced in Denmark that now has cancer survival similar to the other Nordic countries. The reasons for the observed improvements in cancer survival are likely multifactorial, including earlier diagnosis, improved treatment options, implementation of national cancer plans, uniform national cancer care guidelines and standardized patient pathways. The previous survival disadvantage in Denmark is no longer present for most sites. Continuous monitoring of cancer survival is of importance to assess the impact of changes in policies and the effectiveness of health care systems. [ABSTRACT FROM AUTHOR]

Expected or reference mortality rates are commonly used in the calculation of measures such as relative survival in population-based cancer survival studies and standardized mortality ratios. These expected rates are usually presented according to age, sex, and calendar year. In certain situations, stratification of expected rates by other factors is required to avoid potential bias if interest lies in quantifying measures according to such factors as, for example, socioeconomic status. If data are not available on a population level, information from a control population could be used to adjust expected rates. We have presented two approaches for adjusting expected mortality rates using information from a control population: a Poisson generalized linear model and a flexible parametric survival model. We used a control group from BCBaSe--a register-based, matched breast cancer cohort in Sweden with diagnoses between 1992 and 2012--to illustrate the two methods using socioeconomic status as a risk factor of interest. Results showed that Poisson and flexible parametric survival approaches estimate similar adjusted mortality rates according to socioeconomic status. Additional uncertainty involved in the methods to estimate stratified, expected mortality rates described in this study can be accounted for using a parametric bootstrap, but this might make little difference if using a large control population. [ABSTRACT FROM AUTHOR]

Background: The aggregation of misfolded proteins in the brain occurs in several neurodegenerative disorders. Aberrant protein aggregation is inducible in rodents and primates by intracerebral inoculation. Possible transfusion transmission of neurodegenerative diseases has important public health implications.Objective: To investigate possible transfusion transmission of neurodegenerative disorders.Design: Retrospective cohort study.Setting: Nationwide registers of transfusions in Sweden and Denmark.Participants: 1 465 845 patients who received transfusions between 1968 and 2012.Measurements: Multivariable Cox regression models were used to estimate hazard ratios for dementia of any type, Alzheimer disease, and Parkinson disease in patients receiving blood transfusions from donors who were later diagnosed with any of these diseases versus patients who received blood from healthy donors. Whether excess occurrence of neurodegenerative disease occurred among recipients of blood from a subset of donors was also investigated. As a positive control, transmission of chronic hepatitis before and after implementation of hepatitis C virus screening was assessed.Results: Among included patients, 2.9% received a transfusion from a donor diagnosed with one of the studied neurodegenerative diseases. No evidence of transmission of any of these diseases was found, regardless of approach. The hazard ratio for dementia in recipients of blood from donors with dementia versus recipients of blood from healthy donors was 1.04 (95% CI, 0.99 to 1.09). Corresponding estimates for Alzheimer disease and Parkinson disease were 0.99 (CI, 0.85 to 1.15) and 0.94 (CI, 0.78 to 1.14), respectively. Hepatitis transmission was detected before but not after implementation of hepatitis C virus screening.Limitation: Observational study design, underascertainment of the outcome, and possible insufficient statistical power.Conclusion: The data provide no evidence for the transmission of neurodegenerative diseases and suggest that if transmission does occur, it is rare.Primary Funding Source: Swedish Research Council, Swedish Heart-Lung Foundation, Swedish Society for Medical Research, and Danish Council for Independent Research. [ABSTRACT FROM AUTHOR]

Background: To demonstrate how assessment of life expectancy and loss in expectation of life can be used to address a wide range of research questions of public health interest pertaining to the prognosis of cancer patients. Methods: We identified 135,092 cases of colon adenocarcinoma diagnosed during 1961-2011 from the population-based Swedish Cancer Register. Flexible parametric survival models for relative survival were used to estimate the life expectancy and the loss in expectation of life. Results: The loss in expectation of life for males aged 55 at diagnosis was 13.5 years (95 % CI 13.2-13.8) in 1965 and 12.8 (12.4-13.3) in 2005. For males aged 85 the corresponding figures were 3.21 (3.15-3.28) and 2.10 (2.04-2.17). The pattern was similar for females, but slightly greater loss in expectation of life. The loss in expectation of life is reduced given survival up to a certain time point post diagnosis. Among patients diagnosed in 2011, 945 life years could potentially be saved if the colon cancer survival among males could be brought to the same level as for females. Conclusion: Assessment of loss in expectation of life facilitates the understanding of the impact of cancer, both on individual and population level. Clear improvements in survival among colon cancer patients have led to a gain in life expectancy, partly due to a general increase in survival from all causes. [ABSTRACT FROM AUTHOR]

The article offers information on the study conducted by the authors related to the screening and treatment for cervical cancer. It states that the study revealed that women who receive a diagnosis of cervical cancer based on a smear test have a substantially better prognosis than women whose cancers are detected as a result of symptoms.

Background: Breast cancer can negatively influence working life, but it is unclear how many working years women with breast cancer can expect to lose.Methods: Women diagnosed with breast cancer between 1997 and 2012 were identified in the Breast Cancer Data Base Sweden (N=19 661), together with breast cancer-free comparison women (N=81 303). Using flexible parametric survival modelling, the loss in working years was calculated as the difference in the remaining years in the work force between women with and without breast cancer.Results: Women aged 50 years at diagnosis with stage I disease lost on average 0.5 years (95% CI, 0.2-0.7) of their remaining working time; the corresponding estimates were 0.9 years (0.5-1.2) in stage II, 2.5 years (1.9-3.1) in stage III and 8.1 years (6.5-9.7) in stage IV. Women with in situ breast cancer did not lose any working years. The strongest treatment determinant was axillary lymph node dissection.Conclusions: We found a loss in working years not only in late but also in early-stage breast cancer. Although it is reassuring that some groups had no or only a modest work loss, the economic consequences for society are considerable given the large number of women annually diagnosed with breast cancer. [ABSTRACT FROM AUTHOR]