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Background: A lack of available data and statistical code being published alongside journal articles provides a significant barrier to open scientific discourse, and reproducibility of research. Information governance restrictions inhibit the active dissemination of individual level data to accompany published manuscripts. Realistic, high-fidelity time-to-event synthetic data can aid in the acceleration of methodological developments in survival analysis and beyond by enabling researchers to access and test published methods using data similar to that which they were developed on.Methods: We present methods to accurately emulate the covariate patterns and survival times found in real-world datasets using synthetic data techniques, without compromising patient privacy. We model the joint covariate distribution of the original data using covariate specific sequential conditional regression models, then fit a complex flexible parametric survival model from which to generate survival times conditional on individual covariate patterns. We recreate the administrative censoring mechanism using the last observed follow-up date information from the initial dataset. Metrics for evaluating the accuracy of the synthetic data, and the non-identifiability of individuals from the original dataset, are presented.Results: We successfully create a synthetic version of an example colon cancer dataset consisting of 9064 patients which aims to show good similarity to both covariate distributions and survival times from the original data, without containing any exact information from the original data, therefore allowing them to be published openly alongside research.Conclusions: We evaluate the effectiveness of the methods for constructing synthetic data, as well as providing evidence that there is minimal risk that a given patient from the original data could be identified from their individual unique patient information. Synthetic datasets using this methodology could be made available alongside published research without breaching data privacy protocols, and allow for data and code to be made available alongside methodological or applied manuscripts to greatly improve the transparency and accessibility of medical research. [ABSTRACT FROM AUTHOR]

Simulation studies are conducted to assess the performance of current and novel statistical models in pre-defined scenarios. It is often desirable that chosen simulation scenarios accurately reflect a biologically plausible underlying distribution. This is particularly important in the framework of survival analysis, where simulated distributions are chosen for both the event time and the censoring time. This paper develops methods for using complex distributions when generating survival times to assess methods in practice. We describe a general algorithm involving numerical integration and root-finding techniques to generate survival times from a variety of complex parametric distributions, incorporating any combination of time-dependent effects, time-varying covariates, delayed entry, random effects and covariates measured with error. User-friendly Stata software is provided. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: Background: Survival from breast cancer is lower in the UK than in some other European countries. We compared survival in England and Norway by age and time from diagnosis. Methods: We included 303,648 English and 24,919 Norwegian cases of breast cancer diagnosed 1996–2004 using flexible parametric relative survival models, enabling improved quantification of differences in survival. Crude probabilities were estimated to partition the probability of death due to all causes into that due to cancer and other causes and to estimate the number of “avoidable” deaths. Results: England had lower relative survival for all ages with the difference increasing with age. Much of the difference was due to higher excess mortality in England in the first few months after diagnosis. Older patients had a higher proportion of deaths due to other causes. At 5 years post diagnosis, a woman aged 85 in England had probabilities of 0.35 of dying of cancer and 0.32 of dying of other causes, whilst in Norway they were 0.26 and 0.35. By eight years the number of “avoidable” all-cause deaths in England was 1020 with the number of “avoidable” breast cancer related deaths 1488. Conclusion: Lower breast cancer survival in England is mainly due to higher mortality in the first year after diagnosis. Crude probabilities aid our understanding of the impact of disease on individual patients and help assess different treatment options. [Copyright &y& Elsevier]

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]

: ObjectiveStandard survival methods can yield out-of-date estimates of long-term survival. Period analysis, based on life-table methodology, provides more up-to-date survival estimates by exploring survival during a restricted recent period of interest. It excludes the short-term survival of patients recruited at the start of the study. We use statistical models to further develop the method of period analysis, providing more up-to-date estimates of survival and the ability to explore differences in survival by covariates and adjust for case mix.: MethodsWe use cancer registry data for colorectal cancer in Leicestershire, UK, to illustrate the use of Cox proportional hazards (CPH) models to estimate period and standard survival. We compare these estimates with those obtained using life-table methodology.: ResultsPeriod estimates were slightly higher than the standard estimates as they reflect recent improvements in short-term survival. The results for period analysis using the life-table approach and using CPH models were similar. However, CPH models allowed further investigation of other risk factors and the ability to control for potential confounding variables.: ConclusionUsing period survival estimates, more up-to-date information is available to clinicians and others with an interest in monitoring survival. Period CHP models offer all the advantages of statistical modeling, and are straightforward to fit in standard statistical packages. [Copyright &y& Elsevier]

When analyzing cohort data, we rarely consider potential simultaneous effects of multiple time-scales on estimated survival proportions and hazard ratios. Instead, often, only one time-scale, such as time-on-study or attained age, is taken as the main time-scale and the other time-scale(s) included in the model as time-fixed covariate(s). In this simulation study, we investigate the potential bias in estimated survival proportions and hazard ratios by not modeling multiple time-scales. We simulate data with two time-scales, under various scenarios, and a binary covariate as the exposure of interest. Flexible parametric models with one time-scale were fitted to the simulated data, including the exposure variable of interest and the other time-scale as a fixed covariate. For many of our simulated scenarios, the models with one time-scale showed small bias for the survival proportions. Bias in the log hazard ratios (for the covariate of interest) was observed when there were non-proportional hazards on the second time-scale. If one is modeling only one time-scale it is advisable to include non-proportional hazards and interactions with the time-scale. Exploration of approaches to modeling multiple time-scales is outside the scope of this study. [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]

Survival of patients with colon and rectal cancer has improved in all Nordic countries during the past decades. The aim of this study was to further assess survival trends in patients with colon and rectal cancer in the Nordic countries by age at diagnosis and to present additional survival measures. Data on colon and rectal cancer cases diagnosed in the Nordic countries between 1990 and 2016 were obtained from the NORDCAN database. Relative survival was estimated using flexible parametric models. Both age-standardized and age-specific measures for women and men were estimated from the models, as well as reference-adjusted crude probabilities of death and life-years lost. The five-year age-standardized relative survival of colon and rectal cancer patients continued to improve for women and men in all Nordic countries, from around 50% in 1990 to about 70% at the end of the study period. In general, survival was similar across age and sex. The largest improvement was seen for Danish men and women with rectal cancer, from 41% to 69% and from 43% to 71%, respectively. The age-standardized and reference-adjusted five-year crude probability of death in colon cancer ranged from 30% to 36% across countries, and for rectal cancer from 20% to 33%. The average number of age-standardized and reference-adjusted life-years lost ranged between six and nine years. There were substantial improvements in colon and rectal cancer survival in all Nordic countries 1990–2016. Of special note is that the previously observed survival disadvantage in Denmark is no longer present. • Substantial improvements in survival seen for patients with colon and rectal cancer. • Previously observed survival disadvantage in Denmark is no longer present. • Improvements in survival seen in both women and men and across age. • Age-standardized five-year relative survival around 70% at end of study period. [ABSTRACT FROM AUTHOR]

The survival in patients diagnosed with cutaneous malignant melanoma (CMM) has improved in the Nordic countries in the last decades. It is of interest to know if these improvements are observed in all ages and for both women and men. Patients diagnosed with CMM in the Nordic countries in 1990–2016 were identified in the NORDCAN database. Flexible parametric relative survival models were fitted, except for Iceland where a non-parametric Pohar-Perme approach was used. A range of survival metrics were estimated by sex, both age-standardised and age-specific. The 5-year relative survival improved in all countries, in both women and men and across age. While the improvement was more pronounced in men, women still had a higher survival at the end of the study period. The survival was generally high, with age-standardised estimates of 5-year relative survival towards the end of the study period ranging from 85% in Icelandic men to 95% in Danish women. The age-standardised and reference-adjusted 5-year crude probability of death due to CMM ranged from 5% in Danish and Swedish women to 13% in Icelandic men. Although survival following CMM was relatively high in the Nordic countries in 1990, continued improvements in survival were observed throughout the study period in both women and men and across age. • Survival following cutaneous malignant melanoma is high in the Nordic countries. • The survival has continuously improved between 1990 and 2016. • Survival improvements were observed across age and in both men and women. [ABSTRACT FROM AUTHOR]

Abstract: Background: The methods on how to calculate cumulative relative survival have been ambiguous and have given differences in empirical results. Methods: The gold standard for the cumulative relative survival ratio is the weighted average of age-specific cumulative relative survival ratios, with weights proportional to numbers of patients at diagnosis. Mathematics and representative empirical materials from the population-based Finnish Cancer Registry were studied for the different relative survival methods and compared with the gold standard. Results: The theoretical and empirical results show a good agreement between the method suggested in 1959 by Ederer and Heise (the so-called Ederer II method) and the gold standard. This result is in part due the fact that as follow-up time increases the conditional (annual) relative survival ratios become increasingly more independent of age. Moreover, the dependence between the excess mortality due to cancer and the baseline general mortality does not introduce an important enough selection in practice to cause a notable bias. Conclusion: The use of the method by Ederer and Heise, multiplication of the annual relative survival ratios, instead of direct standardisation, should be considered in future applications. This would be particularly important for the long-term follow-up when age-specific relative survival is not available in the oldest age categories. [Copyright &y& Elsevier]

Background: Data from population-based cancer registries are often used to compare cancer survival between countries or regions. The ICBP SURVMARK-2 study is an international partnership aiming to quantify and explore the reasons behind survival differences across high-income countries. However, the magnitude and relevance of differences in cancer survival between countries have been questioned, as it is argued that observed survival variations may be explained, at least in part, by differences in cancer registration practice, completeness and the availability and quality of the respective data sources.Methods: As part of the ICBP SURVMARK-2 study, we used a simulation approach to better understand how differences in completeness, the characteristics of those missed and inclusion of cases found from death certificates can impact on cancer survival estimates.Results: Bias in 1- and 5-year net survival estimates for 216 simulated scenarios is presented. Out of the investigated factors, the proportion of cases not registered through sources other than death certificates, had the largest impact on survival estimates.Conclusion: Our results show that the differences in registration practice between participating countries could in our most extreme scenarios explain only a part of the largest observed differences in cancer survival. [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]

Background: The life expectancy of cancer patients, and the loss in expectation of life as compared to the life expectancy without cancer, is a useful measure of cancer patient survival and complement the more commonly reported 5-year survival. The estimation of life expectancy and loss in expectation of life generally requires extrapolation of the survival function, since the follow-up is not long enough for the survival function to reach 0. We have previously shown that the survival of the cancer patients can be extrapolated by breaking down the all-cause survival into two component parts, the expected survival and the relative survival, and make assumptions for extrapolation of these functions independently. When extrapolating survival from a model including covariates such as calendar year, age at diagnosis and deprivation status, care has to be taken regarding the assumptions underlying the extrapolation. There are often different alternative ways for modelling covariate effects or for assumptions regarding the extrapolation.Methods: In this paper we describe and discuss different alternative approaches for extrapolation of survival when estimating life expectancy and loss in expectation of life for cancer patients. Flexible parametric models within a relative survival setting are used, and examples are presented using data on colon cancer in England.Results: Generally, the different modelling assumptions and approaches give small differences in the estimates of loss in expectation of life, however, the results can differ for younger ages and for conditional estimates.Conclusion: Sensitivity analyses should be performed to evaluate the effect of the assumptions made when modelling and extrapolating survival to estimate the loss in expectation of life. [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: 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]

Objectives: A large proportion of patients with cutaneous malignant melanoma (CMM) do not experience excess mortality due to their disease. This group of patients is referred to as the cure proportion. Few studies have examined the possibility of cure for CMM. The aim of this study was to estimate the cure proportion of patients with CMM in a Swedish population. Methods: We undertook a population-based study of 5850 CMM patients in two Swedish health care regions during 1996-2005. We used flexible parametric cure models to estimate cure proportions and median survival times (MSTs) of uncured by stage, sex, age and anatomical site. Results: Disease stage at diagnosis was the most important factor for the probability of cure, with a cure proportion of approximately 1.0 for stage IA. While the probability of cure decreased with older age, the influence of age was smaller on the MST of uncured. Differences in prognosis between males and females were mainly attributed to differences in cure as opposed to differences in MST of uncured. Conclusions: This population-based study showed approximately 100% cure among stage IA disease. Almost 50% of patients had stage IA disease and the high cure proportion for this large patient group is reassuring. [ABSTRACT FROM AUTHOR]

The 5-year relative survival of adults diagnosed with acute myeloid leukaemia ( AML) was less than 10% during the 1970s and 1980s in England. This population-based study estimated the 5-year relative survival and 'cure' for 48 380 adult patients diagnosed with AML in England during 1971-2006. Relative survival and cure mixture models were used to produce estimates of 5-year relative survival and the percentage 'cured'. 'Cure' was defined as the proportion of a group of survivors for whom there is no excess mortality compared with the general population. The 5-year relative survival and the percentage 'cured' increased for patients aged under 70 years at diagnosis during 1971-2006, but advancing age was associated with poorer outcome. During the study period a dramatic increase in 5-year relative survival occurred in those aged 15-24 years, from 7% to 53%. The percentage 'cured' was less than 10% for all ages in 1975, but increased to 45% for those aged 15-24 years in 2000. Cure could not be estimated for patients over 70 years, because survival was consistently low (<5%). The long-term outcome of patients with AML has improved substantially, particularly in younger patients. The potential exists for further increasing levels of 'cure'. [ABSTRACT FROM AUTHOR]

Abstract: The objective of this study was to examine differences in cancer survival between socioeconomic groups in England, with particular attention to survival in the short term of follow-up. Patients and methods: Individuals diagnosed with colorectal cancer between 1996 and 2004 in England were identified from cancer registry records. Five-year cumulative relative survival and excess death rates were computed. Results: For colon cancer there was a very high excess death rate in the first month of follow-up, and the excess death rate was highest in the socioeconomically deprived groups. In subsequent periods, excess mortality rates were much lower and there was less socioeconomic variation. The pattern of variation in excess death rates was generally similar in rectal cancer but the socioeconomic difference in death rates persisted several years longer. If the excess death rates in the entire colorectal cancer patient population were the same as those observed in the most affluent socioeconomic quintile, the annual reduction would be 360 deaths in colon cancer and 336 deaths in rectal cancer patients. These deaths occurred almost entirely in the first month and the first year after diagnosis. Conclusion: Recent developments in the national cancer control agenda have included an increasing emphasis on outcome measures, with short-term cancer survival an operational measure of variation and progress in cancer control. In providing clues to the nature of the survival differences between socioeconomic groups, the results presented here give strong support for this strategy. [Copyright &y& Elsevier]