A potential outcomes approach to defining and estimating gestational age-specific exposure effects during pregnancy

Many studies seek to evaluate the effects of potentially harmful pregnancy exposures during specific gestational periods. We consider an observational pregnancy cohort where pregnant individuals can initiate medication usage or become exposed to a drug at various times during their pregnancy. An important statistical challenge involves how to define and estimate exposure effects when pregnancy loss or delivery can occur over time. Without proper consideration, the results of standard analysis may be vulnerable to selection bias, immortal time-bias, and time-dependent confounding. In this study, we apply the “target trials” framework of Hernán and Robins in order to define effects based on the counterfactual approach often used in causal inference. This effect is defined relative to a hypothetical randomized trial of timed pregnancy exposures where delivery may precede and thus potentially interrupt exposure initiation. We describe specific implementations of inverse probability weighting, G-computation, and Targeted Maximum Likelihood Estimation to estimate the effects of interest. We demonstrate the performance of all estimators using simulated data and show that a standard implementation of inverse probability weighting is biased. We then apply our proposed methods to a pharmacoepidemiology study to evaluate the potentially time-dependent effect of exposure to inhaled corticosteroids on birthweight in pregnant people with mild asthma.

Risk of bias in observational studies using routinely collected data of comparative effectiveness research: a meta-research study

Background To assess the completeness of reporting, research transparency practices, and risk of selection and immortal bias in observational studies using routinely collected data for comparative effectiveness research. Method We performed a meta-research study by searching PubMed for comparative effectiveness observational studies evaluating therapeutic interventions using routinely collected data published in high impact factor journals from 01/06/2018 to 30/06/2020. We assessed the reporting of the study design (i.e., eligibility, treatment assignment, and the start of follow-up). The risk of selection bias and immortal time bias was determined by assessing if the time of eligibility, the treatment assignment, and the start of follow-up were synchronized to mimic the randomization following the target trial emulation framework. Result Seventy-seven articles were identified. Most studies evaluated pharmacological treatments (69%) with a median sample size of 24,000 individuals. In total, 20% of articles inadequately reported essential information of the study design. One-third of the articles (n = 25, 33%) raised some concerns because of unclear reporting (n = 6, 8%) or were at high risk of selection bias and/or immortal time bias (n = 19, 25%). Only five articles (25%) described a solution to mitigate these biases. Six articles (31%) discussed these biases in the limitations section. Conclusion Reporting of essential information of study design in observational studies remained suboptimal. Selection bias and immortal time bias were common methodological issues that researchers and physicians should be aware of when interpreting the results of observational studies using routinely collected data.

Immortal time bias for life-long conditions in retrospective observational studies using electronic health records

Background Immortal time bias is common in observational studies but is typically described for pharmacoepidemiology studies where there is a delay between cohort entry and treatment initiation. Methods This study used the Clinical Practice Research Datalink (CPRD) and linked national mortality data in England from 2000–2019 to investigate immortal time bias for a specific life-long condition, intellectual disability. Life expectancy (Chiang’s abridged life table approach) was compared for 33,867 exposed and 980,586 unexposed individuals aged 10+ years using five methods: (1) treating immortal time as observation time; (2) excluding time before date of first exposure diagnosis; (3) matching cohort entry to first exposure diagnosis; (4) excluding time before proxy date of entering first exposure diagnosis (by the physician); and (5) treating exposure as a time-dependent measure. Results When not considered in the design or analysis (Method 1), immortal time bias led to disproportionately high life expectancy for the exposed population during earlier calendar periods (additional years expected to live: 2000–2004: 65.6 [95% CI: 63.6,67.6]; 2005–2009: 59.9 [58.8,60.9]; 2010–2014: 58.0 [57.1,58.9]; 2015–2019: 58.2 [56.8,59.7]). Date of entry of diagnosis (Method 4) was unreliable in this CPRD cohort. The final methods (Method 2, 3 and 5) appeared to solve the main theoretical problem but residual bias may have remained. Conclusions We conclude that immortal time bias is a significant issue for studies of life-long conditions that use electronic health record data and requires careful consideration of how clinical diagnoses are entered onto electronic health record systems.

Oral Anticoagulation Timing in Patients with Acute Ischaemic Stroke and Atrial Fibrillation

Background and Purpose: Oral anticoagulants (OACs) prevent stroke recurrence and vascular embolism in patients with acute ischaemic stroke (AIS) and atrial fibrillation (AF). Current guidance recommends a “1-3-6-12 day”’ rule to resume OACs after AIS, based mainly on empirical consensus. This study investigated the suitability of guideline-recommended timing for OAC initiation. Methods: To overcome immortal time bias, we emulated a sequence of randomized placebo-controlled trials and constructed 90 propensity score-matched cohorts of 12,307 patients with AF and AIS from 2012 to 2016. We compared the risk of composite effectiveness and safety outcome in the early vs no OAC use group and in the delayed vs no OAC use. Indirect comparison between early and delayed use was conducted using a network meta-analysis. Results: Across the groups of AIS severity, the risks of composite outcome or effectiveness outcome were lower in the OAC use group than the no use group and the risks were similar between the early and delayed use groups. In patients with severe AIS, those receiving early OACs use had an increased risk of safety outcome, with HR of 2.10 (CI: 1.13-3.92) compared with those without OAC use, and HR of 1·44 (CI: 0·99-2·09) compared with those receiving delayed use. Conclusions: In AF patients with severe AIS, early OAC use before the guideline-recommended days appeared to increase the risk of bleeding events, although the OAC initiation time seemed not to affect the risk of serious vascular events. The optimal severity-specific timing for OAC initiation after AIS requires further evaluation

Analytical challenges in estimating the effect of exposures that are bounded by follow-up time: experiences from the Blood Stream Infection—Focus on Outcomes study

Objective To illustrate the challenges of estimating the effect of an exposure that is bounded by duration of follow-up on all-cause 28-day mortality, whilst simultaneously addressing missing data and time-varying covariates. Study design and methods BSI-FOO is a multicentre cohort study with the primary aim of quantifying the effect of modifiable risk factors, including time to initiation of therapy, on all-cause 28-day mortality in patients with bloodstream infection. The primary analysis involved two Cox proportional hazard models, first one for non-modifiable risk factors and second one for modifiable risk factors, with a risk score calculated from the first model included as a covariate in the second model. Modifiable risk factors considered in this study were recorded daily for a maximum of 28 days after infection. Follow-up was split at daily intervals from day 0 to 28 with values of daily collected data updated at each interval (i.e., one row per patient per day). Analytical challenges Estimating the effect of time to initiation of treatment on survival is analytically challenging since only those who survive to time t can wait until time t to start treatment, introducing immortal time bias. Time-varying covariates representing cumulative counts were used for variables bounded by survival time e.g. the cumulative count of days before first receipt of treatment. Multiple imputation using chained equations was used to impute missing data, using conditional imputation to avoid imputing non-applicable data e.g. ward data after discharge. Conclusion Using time-varying covariates represented by cumulative counts within a one row per day per patient framework can reduce the risk of bias in effect estimates. The approach followed uses established methodology and is easily implemented in standard statistical packages.

Beta-Blocker Treatment in Ventilated COVID-19 patients – A Cox Regression with Time Dependent Covariate Analysis

Background: Patients with co-morbidities are particularly vulnerable to severe COVID-19 disease. Critically ill patients with COVID-19 frequently experience severe tachycardias and avoidance of these is important in some co-morbidities, for instance cardiovascular disease. There is growing interest in beta blockade in critical illness as their use been associated with improved outcomes in a variety of conditions. We report the real-world use of heart rate management in patients during the first wave of the COVID-19 pandemic. As retrospective data are prone to an Immortal Time Bias, we created a Cohort Trial such as might be used for a future prospective trial and used Time Dependent Covariate Analysis for its analysis. Methods: Data for all PCR-proven COVID-19 patients ventilated in the Intensive Care Unit (ICU) were extracted from the hospital databases. To compensate for the risk of immortal time bias, we restricted analysis to 144 patients who achieved a heart rate (HR) of 90 beats per minute for more than 12 hours and were treated with norepinephrine. We recorded time from these ‘entry criteria’ to first beta blocker dose. Those patients who did not receive a beta blocker were given a nominal time to beta blocker beyond the censor day. Outcome was mortality censored at 28 days.Results: In the study group, 83/144 patients (57.6%) received a beta blocker. The median interval from entry criteria to beta blocker was 7.91 days (IQR 3.89, 13.15) and median duration of treatment was 7.00 days (IQR 4.00, 14.00). Twenty-four beta blocker patients (28.9%) died within 28 days compared with 29 (47.5%) who did not (adjusted OR 0.43; 95% CI 0.20-0.95, P=0.036). Cox Regression with time-dependent covariate analysis revealed there was an increased, but not significant, risk of death with beta blocker delay (Hazard Ratio 1.42 p=0.264). Mortality was also reduced for each day treated with beta blockade (adjusted Odds Ratio 0.76, 95% CI 0.64-0.91; P=0.002).Conclusions: In a retrospective analysis of critically ill ventilated patients with COVID-19 who developed a tachycardia >90 beats per minute and were treated with norepinephrine, beta blockade was associated with reduced mortality.

Adjuvant platinum-based chemotherapy in radically resected adrenocortical carcinoma: a cohort study

Background After radical resection, patients with adrenocortical carcinoma (ACC) frequently experience recurrence and, therefore, effective adjuvant treatment is urgently needed. The aim of the study was to investigate the role of adjuvant platinum-based therapy. Methods In this retrospective multicentre cohort study, we identified patients treated with adjuvant platinum-based chemotherapy after radical resection and compared them with patients without adjuvant chemotherapy. Recurrence-free and overall survival (RFS/OS) were investigated in a matched group analysis and by applying a propensity score matching using the full control cohort (n = 268). For both approaches, we accounted for immortal time bias. Results Of the 31 patients in the platinum cohort (R0 n = 25, RX n = 4, R1 n = 2; ENSAT Stage II n = 11, III n = 16, IV n = 4, median Ki67 30%, mitotane n = 28), 14 experienced recurrence compared to 29 of 31 matched controls (median RFS after the landmark at 3 months 17.3 vs. 7.3 months; adjusted HR 0.19 (95% CI 0.09–0.42; P < 0.001). Using propensity score matching, the HR for RFS was 0.45 (0.29–0.89, P = 0.021) and for OS 0.25 (0.09–0.69; P = 0.007). Conclusions Our study provides the first evidence that adjuvant platinum-based chemotherapy may be associated with prolonged recurrence-free and overall survival in patients with ACC and a very high risk for recurrence.