Using Relative Survival to Estimate the Burden of Kidney Failure.

RATIONALE & OBJECTIVE: Estimates of mortality from kidney failure are misleading because the mortality from kidney failure is inseparable from the mortality attributed to comorbid conditions. We sought to develop an alternative method to reduce the bias in estimating mortality due to kidney failure using life table methods. STUDY DESIGN: Longitudinal cohort study. SETTING & PARTICIPANTS: Using data from the US Renal Data System and the Medicare 5% sample, we identified an incident cohort of patients, age 66+, who first had kidney failure in 2009 and a similar general population cohort without kidney failure. EXPOSURE: Kidney failure. OUTCOME: Death. ANALYTICAL APPROACH: We created comorbidity, age, sex, race, and year-specific life tables to estimate relative survival of patients with incident kidney failure and to attain an estimate of excess kidney failure-related deaths. Estimates were compared with those based on standard life tables (not adjusted for comorbidity). RESULTS: The analysis included 31,944 adults with kidney failure with a mean age of 77±7 years. The 5-year relative survival was 31% using standard life tables (adjusted for age, sex, race, and year) versus 36% using life tables also adjusted for comorbidities. Compared with other chronic diseases, patients with kidney failure have among the lowest relative survival. Patients with incident kidney failure ages 66-70 and 76-80 have a survival comparable to adults without kidney failure roughly 86-90 and 91-95 years old, respectively. LIMITATIONS: Relative survival estimates can be improved by narrowing the specificity of the covariates collected (eg, disease severity and ethnicity). CONCLUSIONS: Estimates of survival relative to a matched general population partition the mortality due to kidney failure from other causes of death. Results highlight the immense burden of kidney failure on mortality and the importance of disease prevention efforts among older adults. PLAIN-LANGUAGE SUMMARY: Estimates of death due to kidney failure can be misleading because death information from kidney failure is intertwined with death due to aging and other chronic diseases. Life tables are an old method, commonly used by actuaries and demographers to describe the life expectancy of a population. We developed life tables specific to a patient's age, sex, year, race, and comorbidity. Survival is derived from the life tables as the percentage of patients who are still alive in a specified period. By comparing survival of patients with kidney failure to the survival of people from the general population, we estimate that patients with kidney failure have one-third the chance of survival in 5 years compared with people with similar demographics and comorbidity but without kidney failure. The importance of this measure is that it provides a quantifiable estimate of the immense mortality burden of kidney failure.

The lifetime risk of surgery in England: a nationwide observational cohort study.

BACKGROUND: The average number of times a person will have surgery in their lifetime, and the amount of surgical healthcare resources they use, is unknown. Lifetime risk is a measure of the risk of an average person having a specific event within their lifetime. We report the lifetime risk of surgery and the change observed during the first year of the COVID-19 pandemic. METHODS: We conducted a population cohort study using hospital episode statistics to identify all patients undergoing surgery between January 1, 2016, and December 31, 2020, in England. We calculated age- and sex-specific incidence rates of surgery and combined these with routinely available population and mortality data from the Office for National Statistics. We computed the probability of requiring surgery stratified by 5-yr epochs (age 0-4 to ≥90 yr). Our primary analysis calculated lifetime risk for all surgery using the life table method. We assessed the impact of the COVID-19 pandemic, comparing a pre-pandemic and a pandemic period. RESULTS: Between 2016 and 2020, 23 427 531 patients underwent surgery, of which 11 937 062 were first surgeries. The average denominator population for England was 55.9 million. The lifetime risk of first surgery was 60.2% (95% confidence interval 55.1-65.4%) for women and 59.1% (95% confidence interval 54.2-64.1%) for men. The COVID-19 pandemic decreased the lifetime risk of first surgery by 32.3% for women and by 31.7% for men. This estimated lifetime risk should only be applied to the English population. CONCLUSIONS: This population epidemiological analysis suggests that approximately 60% of people in England will undergo surgery in their lifetime.

Age- and cause-specific contributions to increase in life expectancy at birth in Korea, 2000-2019: a descriptive study.

BACKGROUND: Korea's life expectancy at birth has consistently increased in the 21st century. This study compared the age and cause-specific contribution to the increase in life expectancy at birth in Korea before and after 2010. METHODS: The population and death numbers by year, sex, 5-year age group, and cause of death from 2000 to 2019 were acquired. Life expectancy at birth was calculated using an abridged life table by sex and year. The annual age-standardized and age-specific mortality by cause of death was also estimated. Lastly, the age and cause-specific contribution to the increase in life expectancy at birth in the two periods were compared using a stepwise replacement algorithm. RESULTS: Life expectancy at birth in Korea increased consistently from 2010 to 2019, though slightly slower than from 2000 to 2009. The cause-specific mortality and life expectancy decomposition analysis showed a significant decrease in mortality in chronic diseases, such as neoplasms and diseases of the circulatory system, in the middle and old-aged groups. External causes, such as transport injuries and suicide, mortality in younger age groups also increased life expectancy. However, mortality from diseases of the respiratory system increased in the very old age group during 2010-2019. CONCLUSIONS: Life expectancy at birth in Korea continued to increase mainly due to decreased mortality from chronic diseases and external causes during the study period. However, the aging of the population structure increased vulnerability to respiratory diseases. The factors behind the higher death rate from respiratory disease should be studied in the future.

Sublethal effects of a spiromesifen and abamectin combination on Tetranychus urticae (Acari: Tetranychidae) and its predators Phytoseiulus persimilis and Amblyseius swirskii (Acari: Phytoseiiidae).

The two-spotted spider mite, Tetranychus urticae Koch (TSSM), is an important cosmopolitan pest of agricultural crops that is often managed in greenhouses by augmentation of predatory mites in combination with acaricides. Here we examined the transgenerational effects of low lethal concentrations of a widely-used acaricide, Oberon Speed® (a combination of spiromesifen and abamectin), on the life history traits and population growth of T. urticae and two of its predators, Phytoseiulus persimilis Athias-Henriot and Amblyseius swirskii Athias-Henriot (Acari: Phytoseiidae). The concentrations employed corresponded to the LC10, LC20 and LC30 values estimated for TSSM protonymphs 48 h post-exposure in a topical bioassay, which yielded an LC50 value of 207.2 ppm. Parental exposure of TSSM to all three low concentrations increased the total developmental time of progeny; both the LC20 and LC30 treatments reduced adult longevity and number of oviposition days, but only the LC30 treatment increased the preoviposition period. Similarly, both the LC20 and LC30 treatments significantly reduced life table parameters (r, R0, λ, and GRR), and increased generation time (T) and population doubling time (DT). Although maternal exposure to the acaricide had various impacts on progeny life history, A. swirskii was less affected than P. persimilis, suggesting the former species would be more compatible for integration with Oberon Speed® for control of T. urticae in greenhouse vegetable production.

A new cure model that corrects for increased risk of non-cancer death: analysis of reliability and robustness, and application to real-life data.

BACKGROUND: Non-cancer mortality in cancer patients may be higher than overall mortality in the general population due to a combination of factors, such as long-term adverse effects of treatments, and genetic, environmental or lifestyle-related factors. If so, conventional indicators may underestimate net survival and cure fraction. Our aim was to propose and evaluate a mixture cure survival model that takes into account the increased risk of non-cancer death for cancer patients. METHODS: We assessed the performance of a corrected mixture cure survival model derived from a conventional mixture cure model to estimate the cure fraction, the survival of uncured patients, and the increased risk of non-cancer death in two settings of net survival estimation, grouped life-table data and individual patients' data. We measured the model's performance in terms of bias, standard deviation of the estimates and coverage rate, using an extensive simulation study. This study included reliability assessments through violation of some of the model's assumptions. We also applied the models to colon cancer data from the FRANCIM network. RESULTS: When the assumptions were satisfied, the corrected cure model provided unbiased estimates of parameters expressing the increased risk of non-cancer death, the cure fraction, and net survival in uncured patients. No major difference was found when the model was applied to individual or grouped data. The absolute bias was < 1% for all parameters, while coverage ranged from 89 to 97%. When some of the assumptions were violated, parameter estimates appeared more robust when obtained from grouped than from individual data. As expected, the uncorrected cure model performed poorly and underestimated net survival and cure fractions in the simulation study. When applied to colon cancer real-life data, cure fractions estimated using the proposed model were higher than those in the conventional model, e.g. 5% higher in males at age 60 (57% vs. 52%). CONCLUSIONS: The present analysis supports the use of the corrected mixture cure model, with the inclusion of increased risk of non-cancer death for cancer patients to provide better estimates of indicators based on cancer survival. These are important to public health decision-making; they improve patients' awareness and facilitate their return to normal life.

Life expectancy and healthy life expectancy of Korean registered disabled by disability type in 2014-2018: Korea National Rehabilitation Center database.

BACKGROUND: Conducting a distinct comparison between the life expectancy (LE) and healthy life expectancy (HALE) of people with disabilities (PWDs) and the general population is necessary due to the various environmental and health conditions they encounter. Therefore, this study aimed to develop the life table for PWDs and calculate those of LE and HALE based on sex, severity, and disability types among the registered Korean PWDs. METHODS: We used aggregated data of registered PWDs from the Korea National Rehabilitation Center database between 2014 and 2018. Overall, 345,595 deaths were included among 12,627,428 registered PWDs. First, we calculated the LE for total PWDs and non-disabled people using a standard life table, extending the old age mortality among nine models. Subsequently, we calculated the LE for each type of disability using the relationship between the mortality of total PWDs and those of each type of disability. Finally, HALE was calculated using the Sullivan method for three types as follows: disability-free and perceived health (PH) using the National Survey, and hospitalized for ≥ 7 days using the Korea National Health Insurance System (NHIS) database. RESULTS: The calculated LE/HALE-NHIS (years) at registration in males and females were 81.32/73.32 and 87.38/75.58, 68.54/58.98 and 71.43/59.24, 73.87/65.43 and 78.25/67.51, and 61.53/50.48 and 62.41/49.72 years among non-disabled, total PWDs, mild disabled, and severe disabled, respectively. LE/HALE-NHIS was lowest and highest in respiratory dysfunction and hearing disabilities, respectively. CONCLUSIONS: Males with disabilities had shorter LE and HALE at registration than females, except for those with severe disabilities, and there were variabilities in the LE based on the disability types.

Flexible transition timing in discrete-time multistate life tables using Markov chains with rewards.

Discrete-time multistate life tables are attractive because they are easier to understand and apply in comparison with their continuous-time counterparts. While such models are based on a discrete time grid, it is often useful to calculate derived magnitudes (e.g. state occupation times), under assumptions which posit that transitions take place at other times, such as mid-period. Unfortunately, currently available models allow very few choices about transition timing. We propose the use of Markov chains with rewards as a general way of incorporating information on the timing of transitions into the model. We illustrate the usefulness of rewards-based multistate life tables by estimating working life expectancies using different retirement transition timings. We also demonstrate that for the single-state case, the rewards approach matches traditional life-table methods exactly. Finally, we provide code to replicate all results from the paper plus R and Stata packages for general use of the method proposed.

Correcting for heterogeneity and non-comparability bias in multicenter clinical trials with a rescaled random-effect excess hazard model.

In the presence of competing causes of event occurrence (e.g., death), the interest might not only be in the overall survival but also in the so-called net survival, that is, the hypothetical survival that would be observed if the disease under study were the only possible cause of death. Net survival estimation is commonly based on the excess hazard approach in which the hazard rate of individuals is assumed to be the sum of a disease-specific and expected hazard rate, supposed to be correctly approximated by the mortality rates obtained from general population life tables. However, this assumption might not be realistic if the study participants are not comparable with the general population. Also, the hierarchical structure of the data can induces a correlation between the outcomes of individuals coming from the same clusters (e.g., hospital, registry). We proposed an excess hazard model that corrects simultaneously for these two sources of bias, instead of dealing with them independently as before. We assessed the performance of this new model and compared it with three similar models, using extensive simulation study, as well as an application to breast cancer data from a multicenter clinical trial. The new model performed better than the others in terms of bias, root mean square error, and empirical coverage rate. The proposed approach might be useful to account simultaneously for the hierarchical structure of the data and the non-comparability bias in studies such as long-term multicenter clinical trials, when there is interest in the estimation of net survival.

A censored quantile regression approach for relative survival analysis: Relative survival quantile regression.

We propose a censored quantile regression model for the analysis of relative survival data. We create a hybrid data set consisting of the study observations and counterpart randomly sampled pseudopopulation observations imputed from population life tables that adjust for expected mortality. We then fit a censored quantile regression model to the hybrid data incorporating demographic variables (e.g., age, biologic sex, calendar time) corresponding to the population life tables of demographically-similar individuals, a population versus study covariate, and its interactions with the variables of interest. These latter variables can be interpreted as relative survival parameters that depict the differences in failure quantiles between the study participants and their population counterparts.

Wheat as a new host for potato aphid Macrosiphum euphorbiae Thomas (Hemiptera: Aphididae) and construction of its age-stage two-sex life tables.

Wheat (Triticum aestivum L.) is the major global staple food crop that meets the food security demands of various nations across the continents. The recent reduction in wheat production is attributed to several biotic and abiotic factors especially, temperature and rainfall patterns, and pest occurrence. Among insect pests, aphid species are emerging as new pests of economic importance in India and elsewhere. The present investigation identified a new association of Macrosiphum euphorbiae Thomas with the wheat crop. Life table parameters were studied for M. euphorbiae and Rhopalosiphum padi fed on wheat foliage. The total nymphal duration and life cycle duration, respectively, of R. padi (4.76 ± 0.54 and 9.71 ± 1.38 days) and M. euphorbiae (5.84 ± 0.69 and 9.96 ± 1.31 days) were significantly different for these species. The fecundity of the two aphid species was 23.95 ± 8.67 and 11.6 ± 4.10 progeny/female, respectively. Age-specific survival rate (lx), age-specific fecundity (fx), and population age-specific fecundity (mx) were higher in R. Padi compared to M. euphorbiae. Reproductive value (Vxj) was high in R. padi and the duration of reproduction was less, while these parameters showed an opposite trend in M. euphorbiae. The gross reproduction rate (GRR) was found higher in R. Padi (29.17 offspring/adult lifetime) compared to M. euphorbiae (19.58 offspring/adult lifetime). The M. euphorbiae being a pest of solanaceous crops seems to have shifted to a new host, i.e., wheat. This new adaptation strategy to survive for long periods on a wheat crop might pose a serious threat to wheat crop cultivation in near future.

Impact of including second and later cancers in cause-specific survival estimates using population-based registry data.

BACKGROUND: Second or later primary cancers account for approximately 20% of incident cases in the United States. Currently, cause-specific survival (CSS) analyses exclude these cancers because the cause of death (COD) classification algorithm was available only for first cancers. The authors added rules for later cancers to the Surveillance, Epidemiology, and End Results cause-specific death classification algorithm and evaluated CSS to include individuals with prior tumors. METHODS: The authors constructed 2 cohorts: 1) the first ever primary cohort, including patients whose first cancer was diagnosed during 2000 through 2016) and 2) the earliest matching primary cohort, including patients with any cancer who matched the selection criteria irrespective of whether it was the first or a later cancer diagnosed during 2000 through 2016. The cohorts' CSS estimates were compared using follow-up through December 31, 2017. The new rules were used in the second cohort for patients whose first cancers during 2000 through 2016 were their second or later cancers. RESULTS: Overall, there were no statistically significant differences in CSS estimates between the 2 cohorts. Estimates were similar by age, stage, race, and time since diagnosis, except for patients with leukemia and those aged 65 to 74 years (3.4 percentage point absolute difference). CONCLUSIONS: The absolute difference in CSS estimates for the first cancer ever cohort versus earliest of any cancers cohort in the study period was small for most cancer types. As the number of newly diagnosed patients with prior cancers increases, the algorithm will make CSS more inclusive and enable estimating survival for a group of patients with cancer for whom life tables are not available or life tables are available but do not capture other-cause mortality appropriately.

On models for the estimation of the excess mortality hazard in case of insufficiently stratified life tables.

In cancer epidemiology using population-based data, regression models for the excess mortality hazard is a useful method to estimate cancer survival and to describe the association between prognosis factors and excess mortality. This method requires expected mortality rates from general population life tables: each cancer patient is assigned an expected (background) mortality rate obtained from the life tables, typically at least according to their age and sex, from the population they belong to. However, those life tables may be insufficiently stratified, as some characteristics such as deprivation, ethnicity, and comorbidities, are not available in the life tables for a number of countries. This may affect the background mortality rate allocated to each patient, and it has been shown that not including relevant information for assigning an expected mortality rate to each patient induces a bias in the estimation of the regression parameters of the excess hazard model. We propose two parametric corrections in excess hazard regression models, including a single-parameter or a random effect (frailty), to account for possible mismatches in the life table and thus misspecification of the background mortality rate. In an extensive simulation study, the good statistical performance of the proposed approach is demonstrated, and we illustrate their use on real population-based data of lung cancer patients. We present conditions and limitations of these methods and provide some recommendations for their use in practice.

Healthy lifestyle in older adults and life expectancy with and without heart failure.

Several lifestyle factors have been linked to risk for heart failure (HF) and premature mortality. The aim of this study was to estimate the impact of a healthy lifestyle on life expectancy with and without HF among men and women from a general population. This study was performed among 6113 participants (mean age 65.8 ± 9.7 years; 58.9% women) from the Rotterdam Study, a large prospective population-based cohort study. A continuous lifestyle score was created based on five lifestyle factors: smoking status, alcohol consumption, diet quality, physical activity and weight status (assessed 1995-2008). The lifestyle score was categorized into three levels: unhealthy (reference), intermediate and healthy. Gompertz regression and multistate life tables were used to estimate the effects of lifestyle on life expectancy with and without HF in men and women separately at ages 45, 65 and 85 years (follow-up until 2016). During an average follow-up of 11.3 years, 699 incident HF events and 2146 deaths occurred. At the age of 45 years, men in the healthy lifestyle category had a 4.4 (95% CI: 4.1-4.7) years longer total life expectancy than men in the unhealthy lifestyle category, and a 4.8 (95% CI: 4.4-5.1) years longer life expectancy free of HF. Among women, the difference in total life-expectancy at the age of 45 years was 3.4 (95% CI: 3.2-3.5) years and was 3.4 (95% CI: 3.3-3.6) years longer for life expectancy without HF. This effect persisted also at older ages. An overall healthy lifestyle can have a positive impact on total life expectancy and life expectancy free of HF.

Modeling Age Patterns of Under-5 Mortality: Results From a Log-Quadratic Model Applied to High-Quality Vital Registration Data.

Information about how the risk of death varies with age within the 0-5 age range represents critical evidence for guiding health policy. This study proposes a new model for summarizing regularities about how under-5 mortality is distributed by detailed age. The model is based on a newly compiled database that contains under-5 mortality information by detailed age in countries with high-quality vital registration systems, covering a wide array of mortality levels and patterns. It uses a log-quadratic approach in predicting a full mortality schedule between ages 0 and 5 on the basis of only one or two parameters. With its larger number of age-groups, the proposed model offers greater flexibility than existing models in terms of both entry parameters and model outcomes. We present applications of this model for evaluating and correcting under-5 mortality information by detailed age in countries with problematic mortality data.

Transovarial toxicity matters: lethal and sublethal effects of hexythiazox on the two-spotted spider mite (Acari: Tetranychidae).

The effects of hexythiazox on life-history traits and demographic parameters of Tetranychus urticae Koch (Acari: Tetranychidae) were evaluated using the age-stage two-sex life table (in fecundity-based and fertility-based variants), with emphasis on its transovarial toxicity. Hexythiazox was applied when T. urticae females were either in the preovipositional period or in the first day of oviposition. In the F0 generation bioassay, treatments with concentrations of 50, 12.5 and 3.125 mg/l significantly reduced the longevity of females and their fecundity. These effects were mostly the result of mortality of treated females (18-23%) over the 24-h exposure period. Even though the net reproductive rate (R0) decreased significantly, the intrinsic rate of increase (r), finite rate of increase (λ) and doubling time (D) were not significantly different from the control. The strongest transovarial toxic effect occurred within the first 4 days following treatment, when 52-89% of the eggs laid by treated females (96% in control) hatched. Fertility was significantly reduced by concentrations of 50, 12.5, 3.125, 0.781 and 0.195 mg/l. These concentrations caused significant reductions in R0 (34-54%), r (12-24%) and λ (3-5%), whereas D was extended for 0.4-0.7 days. In the F1 generation bioassay, 50, 12.5, 3.125, 0.781, 0.049 and 0.012 mg/l caused significant reductions in R0 (34-92%), r (10-68%) and λ (3-17%), whereas extending D for 0.3-5.6 days. These effects were mostly the consequence of transovarial toxicity. Application of the fecundity-based life table underestimated population-level effects of hexythiazox on T. urticae.

Projection of Impaired Life Expectancy for Individuals in the United Kingdom Using Estimated Excess Death Rates.

We have recently constructed tables of the estimated life expectancies of impaired lives on the basis of mortality ratios and the cohort life expectancy tables given in the 8th edition of the Ogden Tables, which are derived from the ONS 2018-based population projections for the United Kingdom.1,2 The life expectancy of impaired lives may also be estimated using excess death rates. In this paper, we give tables of life expectancies for impaired lives using a range of excess death rates for males and females from age 0 to age 100. As both mortality ratios and excess death rates are widely used in medical and legal settings, it is hoped that these additional tables of life expectancies will be of practical value.

Projection of Impaired Life Expectancy in Individuals in the United Kingdom Using Mortality Ratios.

Projections of life expectancy are widely used in medicine, actuarial practice, and in the medicolegal and insurance fields. For individuals considered to have average future survival, nationally-derived life expectancy tables are available, referred to as the Ogden Tables. In the United Kingdom, updated tables (the 8th edition) were published in July 2020. We have calculated impaired projected life expectancies for the United Kingdom based on age and gender, derived from the 8th edition of the Ogden Tables together with various assumed lifelong mortality ratios.

Estimating (quality-adjusted) life-year losses associated with deaths: With application to COVID-19.

Many epidemiological models of the COVID-19 pandemic have focused on preventing deaths. Questions have been raised as to the frailty of those succumbing to the COVID-19 infection. In this paper we employ standard life table methods to illustrate how the potential quality-adjusted life-year (QALY) losses associated with COVID-19 fatalities could be estimated, while adjusting for comorbidities in terms of impact on both mortality and quality of life. Contrary to some suggestions in the media, we find that even relatively elderly patients with high levels of comorbidity can still lose substantial life years and QALYs. The simplicity of the method facilitates straightforward international comparisons as the pandemic evolves. In particular, we compare five different countries and show that differences in the average QALY losses for each COVID-19 fatality is driven mainly by differing age distributions for those dying of the disease.

[Survival analysis of silicosis patients in Wuxi City].

Objective: To analyze the living condition and influencing factors of silicosis patients in Wuxi City form 1975 to 2019. Methods: Through the monitoring of death causes of residents, the paper-based materials and online report system of diagnosis over the years, and the combination of public security and human social system to obtain 3721 cases of silicosis patients as subjects form August to December 2019. And the combination of Kaplan Meier method and life table method were used to carry out single factor survival analysis. Through Cox regression model to analyze the factors affecting the survival time of patients. Results: From 1975 to 2019, 3721 cases of silicosis and 1274 deaths have been reported in Wuxi City, with a mortality rate of 34.24% and a median survival time of 30.9 years. With the development of diagnosis time, the mortality decreased significantly (χ(2)=747.75, P<0.05) . Compared with the first stage silicosis patients, the risk of decreased survival time of the third stage silicosis patients increased (HR=1.486, P<0.05) . Compared with the non-smoking patients, the risk of decreased survival time of the smoking patients increased (HR=1.136, P<0.05) . Compared with the patients who were less than 30 years old, the risk of decreased survival time of patients with 40-49 years old, 50-59 years old and more than 60 years old were increased (HR=9.641, 13.650, 26.794, P<0.05) . Compared with the patients who received industrial and commercial insurance, the risk of decreased survival time of patients who received compensation from employers, basic medical insurance for urban and rural residents, other social compensation and no compensation were increased (HR=3.137, 3.119, 5.129, 8.442, P<0.05) . Conclusion: The survival time of silicosis patients is related to the stage of silicosis, smoking condition, age of onset and social compensation. We should focus on controlling the above risk factors so as to improve the quality of life of patients and prolong their lives.

Pre-injury health status and excess mortality in persons with traumatic brain injury: A decade-long historical cohort study.

An increasing number of patients are able to survive traumatic brain injuries (TBIs) with advanced resuscitation. However, the role of their pre-injury health status in mortality in the following years is not known. Here, we followed 77,088 consecutive patients (59% male) who survived the TBI event in Ontario, Canada for more than a decade, and examined the relationships between their pre-injury health status and mortality rates in excess to the expected mortality calculated using sex- and age-specific life tables. There were 5792 deaths over the studied period, 3163 (6.95%) deaths in male and 2629 (8.33%) in female patients. The average excess mortality rate over the follow-up period of 14 years was 1.81 (95% confidence interval = 1.76-1.86). Analyses of follow-up time windows showed different patterns for the average excess rate of mortality following TBI, with the greatest rates observed in year one after injury. Among identified pre-injury comorbidity factors, 33 were associated with excess mortality rates. These rates were comparable between sexes. Additional analyses in the validation dataset confirmed that these findings were unlikely a result of TBI misclassification or unmeasured confounding. Thus, detection and subsequent management of pre-injury health status should be an integral component of any strategy to reduce excess mortality in TBI patients. The complexity of pre-injury comorbidity calls for integration of multidisciplinary health services to meet TBI patients' needs and prevent adverse outcomes.