Bias Due to Confounders for the Exposure-Competing Risk Relationship

Approximate reciprocal relationship between two cause-specific hazard ratios in COVID-19 data with mutually exclusive events

COVID-19 survival data presents a special situation where not only the time-to-event period is short, but also the two events or outcome types, death and release from hospital, are mutually exclusive, leading to two cause-specific hazard ratios (csHR d and csHR r ). The eventual mortality/release outcome is also analyzed by logistic regression to obtain odds-ratio (OR). We have the following three empirical observations: (1) The magnitude of OR is an upper limit of the csHR d : |log(OR)| ≥ |log(csHR d )|. This relationship between OR and HR might be understood from the definition of the two quantities; (2) csHR d and csHR r point in opposite directions: log(csHR d ) ⋅ log(csHR r ) < 0; This relation is a direct consequence of the nature of the two events; and (3) there is a tendency for a reciprocal relation between csHR d and csHR r : csHR d ∼ 1/csHR r . Though an approximate reciprocal trend between the two hazard ratios is in indication that the same factor causing faster death also lead to slow recovery by a similar mechanism, and vice versa, a quantitative relation between csHR d and csHR r in this context is not obvious. These results may help future analyses of data from COVID-19 or other similar diseases, in particular if the deceased patients are lacking, whereas surviving patients are abundant.

Accounting for Competing Events When Evaluating Long-Term Outcomes in Survivors of Critical Illness

The clinical trajectory of survivors of critical illness after hospital discharge can be complex and highly unpredictable. Assessing long-term outcomes after critical illness can be challenging because of possible competing events, such as all-cause death during follow-up (which precludes the occurrence of an event of particular interest). In this perspective, we explore challenges and methodological implications of competing events during the assessment of long-term outcomes in survivors of critical illness. In the absence of competing events, researchers evaluating long-term outcomes commonly use the Kaplan-Meier method and the Cox proportional hazards model to analyze time-to-event (survival) data. However, traditional analytical and modeling techniques can yield biased estimates in the presence of competing events. We present different estimands of interest and the use of different analytical approaches, including changes to the outcome of interest, Fine and Gray regression models, cause-specific Cox proportional hazards models, and generalized methods (such as inverse probability weighting). Finally, we provide code and a simulated dataset to exemplify the application of the different analytical strategies in addition to overall reporting recommendations.

Predictors of frequent emergency department visits among hospitalized cancer patients: a comparative cohort study using integrated clinical and administrative data to improve care delivery

BACKGROUND

Frequent emergency department (FED) visits by cancer patients represent a significant burden to the health system. This study identified determinants of FED in recently hospitalized cancer patients, with a particular focus on opioid use.

METHODS

A prospective cohort discharged from surgical/medical units of the McGill University Health Centre was assembled. The outcome was FED use (≥ 4 ED visits) within one year of discharge. Data retrieved from the universal health insurance system was analyzed using Cox Proportional Hazards (PH) model, adopting the Lunn-McNeil approach for competing risk of death.

RESULTS

Of 1253 patients, 14.5% became FED users. FED use was associated with chemotherapy one-year pre-admission (adjusted hazard ratio (aHR) 2.60, 95% CI: 1.80-3.70), ≥1 ED visit in the previous year (aHR: 1.80, 95% CI 1.20-2.80), ≥15 pre-admission ambulatory visits (aHR 1.54, 95% CI 1.06-2.34), previous opioid and benzodiazepine use (aHR: 1.40, 95% CI: 1.10-1.90 and aHR: 1.70, 95% CI: 1.10-2.40), Charlson Comorbidity Index ≥ 3 (aHR: 2.0, 95% CI: 1.2-3.4), diabetes (aHR: 1.60, 95% CI: 1.10-2.20), heart disease (aHR: 1.50, 95% CI: 1.10-2.20) and lung cancer (aHR: 1.70, 95% CI: 1.10-2.40). Surgery (cardiac (aHR: 0.33, 95% CI: 0.16-0.66), gastrointestinal (aHR: 0.34, 95% CI: 0.14-0.82) and thoracic (aHR: 0.45, 95% CI: 0.30-0.67) led to a decreased risk of FED use.

CONCLUSIONS

Cancer patients with higher co-morbidity, frequent use of the healthcare system, and opioid use were at increased risk of FED use. High-risk patients should be flagged for preventive intervention.

The Lung Allocation Score Remains Inequitable for Patients with Pulmonary Arterial Hypertension, Even after the 2015 Revision

Rationale: The lung allocation score (LAS) was revised in 2015 to improve waiting list mortality and rate of transplant for patients with pulmonary arterial hypertension (PAH). Objectives: We sought to determine if the 2015 revision achieved its intended goals. Methods: Using the Standard Transplant Analysis and Research file, we assessed the impact of the 2015 LAS revision by comparing the pre- and postrevision eras. Registrants were divided into the LAS diagnostic categories: group A-chronic obstructive pulmonary disease; group B-pulmonary arterial hypertension; group C-cystic fibrosis; and group D-interstitial lung disease. Competing risk regressions were used to assess the two mutually exclusive competing risks of waiting list death and transplant. Cumulative incidence plots were created to visually inspect risks. Measurements and Main Results: The LAS at organ matching increased by 14.2 points for registrants with PAH after the 2015 LAS revision, the greatest increase among diagnostic categories (other LAS categories: Δ, -0.9 to +2.8 points). Before the revision, registrants with PAH had the highest risk of death and lowest likelihood of transplant. After the 2015 revision, registrants with PAH still had the highest risk of death, now similar to those with interstitial lung disease, and the lowest rate of transplant, now similar to those with chronic obstructive pulmonary disease. Conclusions: Although the 2015 LAS revision improved access to transplant and reduced the risk of waitlist death for patients with PAH, it did not go far enough. Significant differences in waitlist mortality and likelihood of transplant persist.

Causal inference in medical records and complementary systems pharmacology for metformin drug repurposing towards dementia

Metformin, a diabetes drug with anti-aging cellular responses, has complex actions that may alter dementia onset. Mixed results are emerging from prior observational studies. To address this complexity, we deploy a causal inference approach accounting for the competing risk of death in emulated clinical trials using two distinct electronic health record systems. In intention-to-treat analyses, metformin use associates with lower hazard of all-cause mortality and lower cause-specific hazard of dementia onset, after accounting for prolonged survival, relative to sulfonylureas. In parallel systems pharmacology studies, the expression of two AD-related proteins, APOE and SPP1, was suppressed by pharmacologic concentrations of metformin in differentiated human neural cells, relative to a sulfonylurea. Together, our findings suggest that metformin might reduce the risk of dementia in diabetes patients through mechanisms beyond glycemic control, and that SPP1 is a candidate biomarker for metformin's action in the brain.

A practical guide to handling competing events in etiologic time-to-event studies

Competing events are events that preclude the occurrence of the primary outcome. Much has been written on mainly the statistics behind competing events analyses. However, many of these publications and tutorials have a strong statistical tone and might fall short in providing a practical guide to clinician researchers as to when to use a competing event analysis and more importantly which method to use and why. Here we discuss the different target effects in the Fine-Gray and cause-specific methods using simple causal diagrams and provide strengths and limitations of both approaches for addressing etiologic questions. We argue why the Fine-Gray method might not be the best approach for handling competing events in etiological time-to-event studies.

Rate and Risk Factors of Acute Myocardial Infarction after Debut of Chronic Kidney Disease-Results from the KidDiCo

Chronic kidney disease (CKD) is a known risk factor for cardiovascular disease, including acute myocardial infarction. However, whether this risk is only associated with severe kidney disease or is also related to mildly impaired kidney function is still under debate. The incidence rate and risk factors of incident acute myocardial infarction (AMI) in patients with CKD are sparse. Potential differences in risk factor profiles between CKD patients with incident AMI and CKD patients with a prior AMI have not been sufficiently investigated. Furthermore, important factors such as albuminuria and socio-economic factors are often not included. The primary aim of this study was to establish the incidence rate of AMI after CKD debut. Secondly, to evaluate the importance of different CKD stages and the risk of having an AMI. Finally, to identify individuals at risk for AMI after CKD debut adjusted for prevalent AMI. Based on data from the kidney disease cohort of Southern Denmark (KidDiCo), including 66,486 CKD patients, we established incidence rates and characteristics of incident AMI among patients within a 5-year follow-up period after CKD debut. A Cox regression was performed to compute the cause-specific hazard ratios for the different risk factors. The incidence rate for CKD stage G3−5 patients suffering acute myocardial infarction is 2.5 cases/1000 people/year. In patients without a previous myocardial infarction, the risk of suffering a myocardial infarction after CKD debut was only significant in CKD stage G4 (HR = 1.402; (95% CI: 1.08−1.81); p-value = 0.010) and stage G5 (HR = 1.491; (95% CI: 1.01−2.19); p-value = 0.042). This was not the case in patients who had suffered an acute myocardial infarction prior to their CKD debut. In this group, a previous myocardial infarction was the most critical risk factor for an additional myocardial infarction after CKD debut (HR = 2.615; (95% CI: 2.241−3.05); p-value < 0.001). Irrespective of a previous myocardial infarction, age, male sex, hypertension, and a low educational level were significant risk factors associated with an acute myocardial infarction after CKD debut. The incidence rate of AMI in patients with CKD stage G3−5 was 2.5 cases/1000 people/year. Risk factors associated with incident AMI in CKD stage G3−5 patients were CKD stage, age, and hypertension. Female sex and higher educational levels were associated with a lower risk for AMI. Prior AMI was the most significant risk factor in patients with and without previous AMI before fulfilling CKD stage G3−5 criteria. Only age, sex, and a medium-long educational level were significant risk factors in this group.

Childhood adversity and cognitive impairment in later life

Objectives

This study examined the association between childhood adversity and cognitive impairment in later life and explored the potential moderation effect of gender and race.

Methods

The study sample included 15,133 participants of the Health and Retirement Study (1998-2016 surveys) who had complete data on key study measures and were more than 50. The outcome variable is a dichotomous indicator of cognitive impairment as assessed by the Telephone Interview for Cognitive Status for self-respondents and the 16-item Informant Questionnaire on Cognitive Decline in the Elderly for proxies. A total of six childhood adversity indicators included grade retention, parental substance abuse, physical abuse, trouble with the police, moving due to financial hardship, and receipt of help due to financial hardship in early life. The estimation of the association between childhood adversity and cognitive impairment involved Cox proportional hazards regression. Results: Grade retention had the largest effect on incident cognitive impairment (HR = 1.3, 95% CI = 1.23-1.38, p < 0.001), followed by physical abuse by a parent (HR = 1.10, 95% CI = 1.00-1.20, p = 0.001). The impact of grade retention was more detrimental to women than men (interaction term HR = 0.89, 95% CI = 0.80-1.00, p = 0.048, female as the reference). Parental substance abuse was associated with a lower risk of incident cognitive impairment for most racial groups (HR = 0.89, 95% CI = 0.83-0.95, p = 0.001), but this association was reversed in "non-Hispanic other" race, consisting mainly of Asians (HR = 1.54, 95% CI = 1.05-2.26, p = 0.025).

Discussion

Some aspects of childhood adversity continue to harm cognitive functioning in later life, while some events may have the opposite effect, with evidence of heterogeneity across gender and race.

Association of Psychiatric Services Referral and Attendance Following Treatment for Deliberate Self-harm With Prospective Mortality in Norwegian Patients

IMPORTANCE

Psychiatric care following somatic treatment for deliberate self-harm (DSH) is pivotal in patients' lives both in the short and long term, but evidence to guide such care is limited.

OBJECTIVE

To examine follow-up psychiatric care for patients treated for DSH (ie, intentional self-injury or self-poisoning, irrespective of motivation) at hospital emergency departments and to assess the association of psychiatric referral and treatment attendance with risk of subsequent mortality in these patients.

DESIGN, SETTING, AND PARTICIPANTS

Retrospective data from several Norwegian registries were interlinked to follow up a national cohort of all patients with hospital-treated DSH for up to 11 years from 2008 through 2018. Data were analyzed from March to October 2021.

EXPOSURES

Socioeconomic characteristics, psychiatric history, and clinical features of DSH.

MAIN OUTCOMES AND MEASURES

Referral to psychiatric services, attendance in psychiatric treatment, and prospective mortality were the 3-stage outcomes during follow-up. Logistic regression with odds ratios and cause-specific survival analysis with hazard ratios were used to examine associations between exposures and outcomes.

RESULTS

The study identified 43 153 patients (24 286 [56.3%] female; median [IQR] age at index DSH, 39.0 [23.0-56.0] years) involving 69 569 DSH episodes. Of these patients, 6762 (15.7%) were referred to psychiatric services after somatic treatment for DSH, and 22 008 patients (51.0%) attended psychiatric treatment within 3 months of discharge following somatic treatment for DSH. Prior psychiatric history and psychiatric disorders comorbid with DSH were associated with both referral to and attendance in psychiatric care. During follow-up, 7041 patients died by suicide (n = 911) or other causes (n = 6130). While suicide risk was associated with male sex, age 35 to 64 years, and particularly prior and coexisting psychopathologies, other-cause mortality was associated with age 65 years and older and socioeconomic disadvantage. Patients with psychiatric referrals generally had an increased risk of suicide, but the risk was particularly high among patients who received a referral but did not subsequently attend psychiatric treatment (adjusted hazard ratio, 3.07; 95% CI, 2.28-4.12). The observed association was more pronounced during the first years of follow-up and in patients aged 10 to 34 years or 35 to 64 years and those with a clear intent of self-harm.

CONCLUSIONS AND RELEVANCE

This national cohort study found an association between psychiatric care attendance following treatment for DSH and prospective mortality, highlighting the importance of patient engagement in psychiatric treatment.

Do P2Y12 receptor inhibitors prescribed poststroke modify the risk of cognitive disorder or dementia? Protocol for a target trial using multiple national Swedish registries

INTRODUCTION

The target of a class of antiplatelet medicines, P2Y12R inhibitors, exists both on platelets and on brain immune cells (microglia). This protocol aims to describe a causal (based on a counterfactual model) approach for analysing whether P2Y12R inhibitors prescribed for secondary prevention poststroke may increase the risk of cognitive disorder or dementia via their actions on microglia, using real-world evidence.

METHODS AND ANALYSIS

This will be a cohort study nested within the Swedish National Health and Medical Registers, including all people with incident stroke from 2006 to 2016. We developed directed acyclic graphs to operationalise the causal research question considering potential time-independent and time-dependent confounding, using input from several experts. We developed a study protocol following the components of the target trial approach described by Hernan et al and describe the data structure that would be required in order to make a causal inference. We also describe the statistical approach required to derive the causal estimand associated with this important clinical question; that is, a time-to-event analysis for the development of cognitive disorder or dementia at 1, 2 and 5-year follow-up, based on approaches for competing events to account for the risk of all-cause mortality. Causal effect estimates and the precision in these estimates will be quantified.

ETHICS AND DISSEMINATION

This study has been approved by the Ethics Committee of the University of Gothenburg and Confidentiality Clearance at Statistics Sweden with Dnr 937-18, and an approved addendum with Dnr 2019-0157. The analysis and interpretation of the results will be heavily reliant on the structure, quality and potential for bias of the databases used. When we implement the protocol, we will consider and document any biases specific to the dataset and conduct appropriate sensitivity analyses. Findings will be disseminated to local stakeholders via conferences, and published in appropriate scientific journals.

Long-term oncological outcomes in patients undergoing laparoscopic versus open surgery for colon cancer: A nationwide cohort study

AIM

To estimate the effect of laparoscopy versus laparotomy on recurrence status in patients undergoing intended curative resection for stage I-III colon cancer using nationwide data.

METHOD

A retrospective cohort study using prospectively collected nationwide quality assurance data on all patients undergoing elective, intended curative surgery for UICC stage I-III colon cancer in Denmark from 1 January 2010, through 31 December 2013. The association between laparoscopic versus open surgery and recurrence status was investigated using cause-specific hazard and subdistribution hazard models with death from any cause as a competing event.

RESULTS

In total, 4369 patients undergoing elective intended curative surgery for colon cancer were included in the analysis. Overall, 3243 (74.2%) patients underwent laparoscopic surgery. During a median follow-up time of 84 months, 1191 (27.2%) patients experienced recurrence, and 1304 (29.8%) patients died. The cause-specific hazard of recurrence following laparoscopic versus open surgery was HR_CS  = 1.08, 95% CI: 0.90-1.28, p = 0.422. The subdistribution hazard of recurrence following laparoscopic versus open surgery was HR_SD =0.99, 95% CI: 0.84-1.16, p = 0.880.

CONCLUSION

Elective laparoscopic resection for UICC stage I-III colon cancer is oncologically safe and comparable with open resection. These results confirm the external validity of previous RCTs in everyday clinical settings.

Outcome after intubation for septic shock with respiratory distress and hemodynamic compromise: an observational study

BACKGROUND

Acute respiratory failure in septic patients contributes to higher in-hospital mortality. Intubation may improve outcome but there are no specific criteria for intubation. Intubation of septic patients with respiratory distress and hemodynamic compromise may result in clinical deterioration and precipitate cardiovascular failure. The decision to intubate is complex and multifactorial. The purpose of this study was to evaluate the impact of intubation in patients with respiratory distress and predominant hemodynamic instability within 24 h after ICU admission for septic shock.

METHODS

We conducted a retrospective analysis of a prospective registry of adult patients with septic shock admitted to the medical ICU at Mayo Clinic, between April 30, 2014 and December 31, 2017. Septic shock was defined by persistent lactate > 4 mmol/L, mean arterial pressure < 65 mmHg, or vasopressor use after 30 mL/kg fluid boluses and suspected or confirmed infection. Patients who remained hospitalized in the ICU at 24 h were separated into intubated while in the ICU and non-intubated groups. The primary outcome was hospital mortality. The first analysis used linear regression models and the second analysis used time-dependent propensity score matching to match intubated to non-intubated patients.

RESULTS

Overall, 358 (33%) ICU patients were eventually intubated after their ICU admission and 738 (67%) were not. Intubated patients were younger, transferred more often from an outside facility, more critically ill, had more lung infection, and achieved blood pressure goals more often, but lactate normalization within 6 h occurred less often. Among those who remained hospitalized in the ICU 24 h after sepsis diagnosis, the crude in-hospital mortality was higher in intubated than non-intubated patients, 89 (26%) vs. 82 (12%), p < 0.001, as was the ICU mortality and ICU and hospital length of stay. After adjustment, intubation showed no effect on hospital mortality but resulted in fewer hospital-free days through day 28. One-to-one propensity resulted in similar conclusion.

CONCLUSIONS

Intubation within 24 h of sepsis was not associated with hospital mortality but resulted in fewer 28-day hospital-free days. Although intubation remains a high-risk procedure, we did not identify an increased risk in mortality among septic shock patients with predominant hemodynamic compromise.

Effectiveness and safety of oral anticoagulants in elderly patients with atrial fibrillation

OBJECTIVES

To assess the risk of stroke/systemic embolism (SE) and major bleeding associated with the use of oral anticoagulants in elderly patients with atrial fibrillation (AF) in a real-world population.

METHODS

We identified all anticoagulant-naive initiators of warfarin, dabigatran, rivaroxaban and apixaban for the indication AF in Norway between January 2013 and December 2017. Multivariate competing risk regression was used to calculate subhazard ratios (SHRs) describing associations between non-vitamin K antagonist oral anticoagulants (NOACs) compared with warfarin for risk of stroke/SE and major bleeding.

RESULTS

Among 30 401 patients ≥75 years identified (median age 82 years, 53% women, mean CHA₂DS₂-VaSc score 4.5), 3857 initiated dabigatran, 6108 rivaroxaban, 13 786 apixaban and 6650 warfarin. Reduced dose was initiated in 11 559 (49%) of the NOAC-treated patients. For stroke, the SHRs for standard dose NOAC against warfarin were 0.80 (95% CI 0.57 to 1.13) for dabigatran; 1.07 (95% CI 0.89 to 1.30) for rivaroxaban and 0.95 (95% CI 0.78 to 1.15) for apixaban. For major bleeding, the SHRs against warfarin were 0.75 (95% CI 0.52 to 1.08) for dabigatran; 0.96 (95% CI 0.78 to 1.16) for rivaroxaban and 0.74 (95% CI 0.60 to 0.91) for apixaban. Comparing reduced doses of NOACs with warfarin yielded similar results. Sensitivity analyses were in accordance with the main results.

CONCLUSION

In this nationwide cohort study of patients ≥75 years initiating oral anticoagulation for AF, standard and reduced dose NOACs were associated with similar risks of stroke/SE as warfarin and lower or similar risks of bleeding. The NOACs seem to be a safe option also in elderly patients.

Time to health-related quality of life improvement analysis was developed to enhance evaluation of modern anticancer therapies

OBJECTIVES

Major advances have recently been made in the treatments of cancer, which now also have the potential to improve patients' health-related quality of life (HRQOL). We propose the time to HRQOL improvement (TTI) and the time to sustained HRQOL improvement (TTSI) as potentially important cancer outcomes to be used in longitudinal HRQOL analyses.

STUDY DESIGN AND SETTING

As proof of principle, we defined TTI and TTSI, using the Fine-Gray model to include competing risks in estimates, in a case study in real life of a cohort of newly diagnosed patients with cancer receiving a targeted therapy. HRQOL was evaluated before and during therapy with six assessments over a 24-month period, using the well-validated European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30.

RESULTS

For each assessed HRQOL domain, we assessed TTI and TTSI and estimated the cumulative incidence of patients' clinically meaningful improvements, also accounting for the occurrence of competing events.

CONCLUSION

TTI and TTSI are potentially important outcomes in the era of modern anticancer therapies. The analysis of TTI and TTSI by competing risks approach will further add to the statistical methods that can be used to inform on the impact of cancer therapies on patients' HRQOL.

Remnant cholesterol as a risk factor for cardiovascular, cancer or other causes mortality: A competing risks analysis

BACKGROUND AND AIMS

Cardiovascular diseases (CVDis) are leading causes of morbidity and mortality. Even after the introduction of pharmacological therapy to lower Cholesterol, there is still a residual risk that may be ascribed to remnant cholesterol (RC). We aimed, by analyzing two prospective cohort studies, to estimate the effect of RC on risk and hazard of cardiovascular deaths (CVDs), while accounting for competing risks such as cancer (CDs) and other-causes deaths (OCDs).

METHODS AND RESULTS

Cohorts were enrolled in 1992 and 2005. Personal data history was recorded. A fasting venous blood sample was obtained, and RC was calculated at baseline. Cause of Death was coded by using ICD-10th version. Follow-up ended on December 31, 2017. Flexible parametric competing-risks models were applied, with age at death as time-axis. In total, 5729 subjects were enrolled. There were 861 (15.1%) deaths: 234 CVDs (27.2%), 245 CDs (28.5%), 271 OCDs (31.5%) and 111 unknown causes of death (12.8%). RC exposure was a strong risk factor only for CVDs (Risk 2.54, 95% Confidence Interval 1.21; 5.34; Trend 1.26 (1.00; 1.58) for ≥1.29 mmol/L).

CONCLUSIONS

RC is a strong independent risk factor for cardiovascular mortality. Competing risk analysis is demonstrably a useful tool to disentangle associations among different competing events with a common risk factor.

Causal inference in the face of competing events

Purpose of review

Epidemiologists frequently must handle competing events, which prevent the event of interest from occurring. We review considerations for handling competing events when interpreting results causally.

Recent findings

When interpreting statistical associations as causal effects, we recommend following a causal inference "roadmap" as one would in an analysis without competing events. There are, however, special considerations to be made for competing events when choosing the causal estimand that best answers the question of interest, selecting the statistical estimand (e.g. the cause-specific or subdistribution) that will target that causal estimand, and assessing whether causal identification conditions (e.g., conditional exchangeability, positivity, and consistency) have been sufficiently met.

Summary

When doing causal inference in the competing events setting, it is critical to first ascertain the relevant question and the causal estimand that best answers it, with the choice often being between estimands that do and do not eliminate competing events.

Incorporating competing risk theory into evaluations of changes in cancer survival: making the most of cause of death and routinely linked sociodemographic data

Background

Relative survival is the most common method used for measuring survival from population-based registries. However, the relative survival concept of ‘survival as far as the cancer is concerned’ can be biased due to differing non-cancer risk of death in the population with cancer (competing risks). Furthermore, while relative survival can be stratified or standardised, for example by sex or age, adjustment for a broad range of sociodemographic variables potentially influencing survival is not possible. In this paper we propose Fine and Gray competing risks multivariable regression as a method that can assess the probability of death from cancer, incorporating competing risks and adjusting for sociodemographic confounders.

Methods

We used whole of population, person-level routinely linked Western Australian cancer registry and mortality data for individuals diagnosed from 1983 to 2011 for major cancer types combined, female breast, colorectal, prostate, lung and pancreatic cancers, and grade IV glioma. The probability of death from the index cancer (cancer death) was evaluated using Fine and Gray competing risks regression, adjusting for age, sex, Indigenous status, socio-economic status, accessibility to services, time sub-period and (for all cancers combined) cancer type.

Results

When comparing diagnoses in 2008–2011 to 1983–1987, we observed substantial decreases in the rate of cancer death for major cancer types combined (N = 192,641, − 31%), female breast (− 37%), prostate (− 76%) and colorectal cancers (− 37%). In contrast, improvements in pancreatic (− 15%) and lung cancers (− 9%), and grade IV glioma (− 24%) were less and the cumulative probability of cancer death for these cancer types remained high.

Conclusion

Considering the justifiable expectation for confounder adjustment in observational epidemiological studies, standard methods for tracking population-level changes in cancer survival are simplistic. This study demonstrates how competing risks and sociodemographic covariates can be incorporated using readily available software. While cancer has been focused on here, this technique has potential utility in survival analysis for other disease states.

A causal framework for classical statistical estimands in failure-time settings with competing events

In failure-time settings, a competing event is any event that makes it impossible for the event of interest to occur. For example, cardiovascular disease death is a competing event for prostate cancer death because an individual cannot die of prostate cancer once he has died of cardiovascular disease. Various statistical estimands have been defined as possible targets of inference in the classical competing risks literature. Many reviews have described these statistical estimands and their estimating procedures with recommendations about their use. However, this previous work has not used a formal framework for characterizing causal effects and their identifying conditions, which makes it difficult to interpret effect estimates and assess recommendations regarding analytic choices. Here we use a counterfactual framework to explicitly define each of these classical estimands. We clarify that, depending on whether competing events are defined as censoring events, contrasts of risks can define a total effect of the treatment on the event of interest or a direct effect of the treatment on the event of interest not mediated by the competing event. In contrast, regardless of whether competing events are defined as censoring events, counterfactual hazard contrasts cannot generally be interpreted as causal effects. We illustrate how identifying assumptions for all of these counterfactual estimands can be represented in causal diagrams, in which competing events are depicted as time-varying covariates. We present an application of these ideas to data from a randomized trial designed to estimate the effect of estrogen therapy on prostate cancer mortality.

Estimation of the adjusted cause-specific cumulative probability using flexible regression models for the cause-specific hazards

In competing risks setting, we account for death according to a specific cause and the quantities of interest are usually the cause-specific hazards (CSHs) and the cause-specific cumulative probabilities. A cause-specific cumulative probability can be obtained with a combination of the CSHs or via the subdistribution hazard. Here, we modeled the CSH with flexible hazard-based regression models using B-splines for the baseline hazard and time-dependent (TD) effects. We derived the variance of the cause-specific cumulative probabilities at the population level using the multivariate delta method and showed how we could easily quantify the impact of a covariate on the cumulative probability scale using covariate-adjusted cause-specific cumulative probabilities and their difference. We conducted a simulation study to evaluate the performance of this approach in its ability to estimate the cumulative probabilities using different functions for the cause-specific log baseline hazard and with or without a TD effect. In the scenario with TD effect, we tested both well-specified and misspecified models. We showed that the flexible regression models perform nearly as well as the nonparametric method, if we allow enough flexibility for the baseline hazards. Moreover, neglecting the TD effect hardly affects the cumulative probabilities estimates of the whole population but impacts them in the various subgroups. We illustrated our approach using data from people diagnosed with monoclonal gammopathy of undetermined significance and provided the R-code to derive those quantities, as an extension of the R-package mexhaz.

How unmeasured confounding in a competing risks setting can affect treatment effect estimates in observational studies

Background

Analysis of competing risks is commonly achieved through a cause specific or a subdistribution framework using Cox or Fine & Gray models, respectively. The estimation of treatment effects in observational data is prone to unmeasured confounding which causes bias. There has been limited research into such biases in a competing risks framework.

Methods

We designed simulations to examine bias in the estimated treatment effect under Cox and Fine & Gray models with unmeasured confounding present. We varied the strength of the unmeasured confounding (i.e. the unmeasured variable’s effect on the probability of treatment and both outcome events) in different scenarios.

Results

In both the Cox and Fine & Gray models, correlation between the unmeasured confounder and the probability of treatment created biases in the same direction (upward/downward) as the effect of the unmeasured confounder on the event-of-interest. The association between correlation and bias is reversed if the unmeasured confounder affects the competing event. These effects are reversed for the bias on the treatment effect of the competing event and are amplified when there are uneven treatment arms.

Conclusion

The effect of unmeasured confounding on an event-of-interest or a competing event should not be overlooked in observational studies as strong correlations can lead to bias in treatment effect estimates and therefore cause inaccurate results to lead to false conclusions. This is true for cause specific perspective, but moreso for a subdistribution perspective. This can have ramifications if real-world treatment decisions rely on conclusions from these biased results. Graphical visualisation to aid in understanding the systems involved and potential confounders/events leading to sensitivity analyses that assumes unmeasured confounders exists should be performed to assess the robustness of results.

Electronic supplementary material

The online version of this article (10.1186/s12874-019-0808-7) contains supplementary material, which is available to authorized users.

Association between blood lead level and subsequent Alzheimer's disease mortality

Background:

Previous studies suggest that cumulative lead exposure is associated with cognitive decline, but its relation with Alzheimer’s disease (AD) remains unclear. Therefore, this study investigated the longitudinal association between blood lead level (BLL) and AD mortality.

Methods:

This study included 8,080 elders (60 years or older) with BLL data from the 1999 to 2008 US National Health and Nutrition Examination Survey. Mortality was determined from linked 1999–2014 National Death Index data. A causal diagram presented causal assumptions and identified a sufficient set of confounders: age, sex, poverty, race/ethnicity, and smoking. Cox proportional hazard models were used to determine the association between BLL and subsequent AD mortality. Impacts of competing risks and design effect were also assessed. Adjusted hazard rate ratio (HRR) and 95% confidence interval (CI) were reported.

Results:

Follow-up ranged from <1 to 152 months (median, 74). Eighty-one participants died from AD over 632,075 total person-months at risk. An increase in BLL was associated with an increase in AD mortality after adjusting for identified confounders. We estimated that those with BLL of 1.5 and 5 μg/dl had 1.2 (95% CI = 0.70, 2.1) and 1.4 (95% CI = 0.54, 3.8) times the rate of AD mortality compared to those with BLL of 0.3 μg/dl, respectively, after accounting for competing risks. Adjusted HRRs were 1.5 (95% CI = 0.81, 2.9) and 2.1 (95% CI = 0.70, 6.3), respectively, after considering design effect.

Conclusions:

This longitudinal study demonstrated a positive, albeit not statistically significant, association between BLL and AD mortality after adjustment for competing risks or design effect.

Exposure to Total Hydrocarbons During Cleanup of the Deepwater Horizon Oil Spill and Risk of Heart Attack Across 5 Years of Follow-up

Exposure to total hydrocarbons (THC) and volatile organic compounds from air pollution is associated with risk of coronary heart disease. THC exposure from oil spills might be similarly associated, but no research has examined this. We assessed the relationship between THC exposure during the response and cleanup of the Deepwater Horizon oil spill (Gulf of Mexico) and heart attack risk among 24,375 oil spill workers enrolled in the Gulf Long-Term Follow-up Study. There were 312 first heart attacks (self-reported physician-diagnosed myocardial infarction, or fatal coronary heart disease) ascertained during the study period (2010-2016). THC exposures were estimated using a job-exposure matrix incorporating self-reported activities and personal air measurements. We used Cox proportional hazards regression to estimate hazard ratios, with inverse-probability weights to account for confounding and censoring. Maximum THC levels of ≥0.30 parts per million (ppm) were associated with heart attack risk, with a 1.8-fold risk for exposure of ≥3.00 ppm versus <0.30 ppm (hazard ratio = 1.81, 95% confidence interval: 1.11, 2.95). The risk difference for highest versus lowest THC level was 10 excess cases per 1,000 workers. This is the first study of the persistent health impacts of THC exposure during oil spill work, and results support increased protection against oil exposure during cleanup of future spills.

Self-reported myocardial infarction and fatal coronary heart disease among oil spill workers and community members 5 years after Deepwater Horizon

BACKGROUND

Chemical, physical and psychological stressors due to the 2010 Deepwater Horizon oil spill may impact coronary heart disease (CHD) among exposed populations. Using longitudinal information from two interviews in the Gulf Long Term Follow-up (GuLF) STUDY, we assessed CHD among oil spill workers and community members.

OBJECTIVE

To assess the associations between duration of oil spill clean-up work, residential proximity to the oil spill, and incidence of self-reported myocardial infarction or fatal CHD.

METHODS

Among respondents with two GuLF STUDY interviews (n = 21,256), there were 395 first incident heart disease events (self-reported myocardial infarction or fatal CHD) across 5 years. We estimated hazard ratios (HR) and 95% confidence intervals (95%CI) for associations with duration of oil spill clean-up work and residential proximity to the oil spill. To assess potential impacts of non-response, we compared covariate distributions for those who did (n = 21,256) and did not (n = 10,353) complete the second interview and used inverse probability (IP) of censoring weights to correct for potential non-response bias.

RESULTS

Living in proximity to the oil spill (vs. living further away) was associated with heart disease, with [HR(95%CI) = 1.30(1.01-1.67)] and without [1.29(1.00-1.65)] censoring weights. For work duration, hazard of heart disease appeared to be higher for those who worked > 180 days (vs. 1-30 days), with and without censoring weights [1.43(0.91-2.25) and 1.36(0.88-2.11), respectively]. Associations persisted throughout the 5-year follow-up.

CONCLUSIONS

Residential proximity to the spill and duration of clean-up work were associated with a suggested 29-43% higher hazard of heart disease events. Associations were robust to censoring.

Missingness in the Setting of Competing Risks: from missing values to missing potential outcomes

Purpose of review

The setting of competing risks in which there is an event that precludes the event of interest from occurring is prevalent in epidemiological research. Unless studying all-cause mortality, any study following up individuals is subject to having a competing risk should individuals die during time period that the study covers. While there are prior papers discussing the need for competing risk methods in epidemiologic research, we are not aware of any review that discusses issues of missing data in a competing risk setting.

Recent Findings

We provide an overview of causal inference in competing risks as potential outcomes are missing, provide some strategies in dealing with missing (or misclassified) event type, and missing covariate data in competing risks. The strategies presented are specifically focused on those that may easily be implemented in standard statistical packages. There is ongoing work in terms of causal analyses, dealing with missing event type information, and missing covariate values specific to competing risk analyses.

Summary

Competing events are common in epidemiologic research. While there has been a focus on why one should conduct a proper competing risk analysis, a perhaps unrecognized issue is in terms of missingness. Strategies exist to minimize the impact of missingness in analyses of competing risks.

When to Censor?

Loss to follow-up is an endemic feature of time-to-event analyses that precludes observation of the event of interest. To our knowledge, in typical cohort studies with encounters occurring at regular or irregular intervals, there is no consensus on how to handle person-time between participants' last study encounter and the point at which they meet a definition of loss to follow-up. We demonstrate, using simulation and an example, that when the event of interest is captured outside of a study encounter (e.g., in a registry), person-time should be censored when the study-defined criterion for loss to follow-up is met (e.g., 1 year after last encounter), rather than at the last study encounter. Conversely, when the event of interest must be measured within the context of a study encounter (e.g., a biomarker value), person-time should be censored at the last study encounter. An inappropriate censoring scheme has the potential to result in substantial bias that may not be easily corrected.

Type 2 diabetes, adiposity and cancer morbidity and mortality risk taking into account competing risk of noncancer deaths in a prospective cohort setting

Type 2 diabetes (T2D) and adiposity associate with increased risk of several cancers, but the impact of competing risk of noncancer deaths on these associations is not known. We prospectively examined participants in the Malmö Diet and Cancer Study aged 44-73 years with no history of cancer at baseline (n = 26,953, 43% men). T2D was ascertained at baseline and during follow-up, and body mass index (BMI) and waist circumference (WC) at baseline. Multivariable cause-specific hazard ratios (HR) and subdistribution hazard ratios (sHR), taking into account noncancer deaths, were estimated using Cox- and competing risk regression. During follow-up (mean 17 years), 7,061 incident cancers (3,220 obesity-related cancer types) and 2,848 cancer deaths occurred. BMI and WC were associated with increased risk of obesity-related cancer incidence and cancer mortality. In T2D subjects, risk of obesity-related cancer was elevated among men (HR = 1.31, 95% CI: 1.12-1.54; sHR = 1.29, 95% CI: 1.10-1.52), and cancer mortality among both men and women (HR = 1.34, 95% CI: 1.20-1.49; sHR = 1.30, 95% CI: 1.16-1.45). There was no elevated actual risk of cancer death in T2D patients with long disease duration (sHR = 1.00, 95% CI: 0.83-1.20). There was a significant additive effect of T2D and adiposity on risk of obesity-related cancer and cancer mortality. In conclusion, detection bias may partially explain the increased risk of cancer morbidity among T2D patients. Both excess risk of competing events among patients with T2D and depletion of susceptibles due to earlier cancer detection will lower the actual risk of cancer, particularly with longer diabetes duration and at older ages.

Methodologic Issues When Estimating Risks in Pharmacoepidemiology

Risk is an important parameter to describe the occurrence of health outcomes over time. However, many outcomes of interest in healthcare settings, such as disease incidence, treatment initiation, and cause-specific mortality, may be precluded from occurring by other events, often referred to as competing events. Here, we review straightforward approaches to estimate risk in the presence of competing events. We illustrate the application of these methods using timely examples in pharmacoepidemiologic research and compare results to those obtained using analytic simplifications commonly used to handle competing events. These examples demonstrate how the analytic methods used to account for competing events affect the interpretation of results from pharmacoepidemiologic studies.