Methodological Issues in the Study of the Effects of Hemoglobin Variability

We consider estimating the effect of hemoglobin variability on mortality in hemodialysis patients. Causal effects can be defined as comparisons of outcomes under different hypothetical interventions. Defining measures of the effect of hemoglobin variability and clinical outcomes is complicated by the fact that hypothetical interventions on variability used to define its effect inevitably involve manipulation of related variables. We propose a model-based definition of the effect of the hemoglobin variability as a parameter for variability in a causal model for the effect of an overall intervention on hemoglobin levels over time. We consider this problem using history-adjusted marginal structural models, and apply this approach to data from a large observational database. We consider issues arising when the variable of interest is endogenous, and consider in principle alternate estimands

Observational cohort study of the safety of digoxin use in women with heart failure

Objectives: This study aims to assess whether digoxin has a different effect on mortality risk for women than it does for men in patients with heart failure (HF). Design This study uses the UK-based The Health Information Network population database in a cohort study of the impact of digoxin exposure on mortality for men and women who carry the diagnosis of HF. Digoxin exposure was assessed based on prescribing data. Multivariable Cox proportional hazards models were used to assess whether there was an interaction between sex and digoxin affecting mortality hazard. Setting The setting was primary care outpatient practices. Participants The study cohort consisted of 17 707 men and 19 227 women with the diagnosis of HF who contributed only time without digoxin exposure and 9487 men and 10 808 women with the diagnosis of HF who contributed time with digoxin exposure. Main outcome measures The main outcome measure was all-cause mortality. Results: The primary outcome of this study was the absence of a large interaction between digoxin use and sex affecting mortality. For men, digoxin use was associated with a HR for mortality of 1.00, while for women, the HR was also 1.00 (p value for interaction 0.65). The results of sensitivity analyses were consistent with those of the primary analysis. Conclusion: Observational data do not support the concern that there is a substantial increased risk of mortality due to the use of digoxin in women. This finding is consistent with previous observational studies but discordant with results from a post hoc analysis of a randomised controlled trial of digoxin versus placebo

The impact of surgical delay on resectability of colorectal cancer: An international prospective cohort study

AIM: The SARS-CoV-2 pandemic has provided a unique opportunity to explore the impact of surgical delays on cancer resectability. This study aimed to compare resectability for colorectal cancer patients undergoing delayed versus non-delayed surgery. METHODS: This was an international prospective cohort study of consecutive colorectal cancer patients with a decision for curative surgery (January-April 2020). Surgical delay was defined as an operation taking place more than 4 weeks after treatment decision, in a patient who did not receive neoadjuvant therapy. A subgroup analysis explored the effects of delay in elective patients only. The impact of longer delays was explored in a sensitivity analysis. The primary outcome was complete resection, defined as curative resection with an R0 margin. RESULTS: Overall, 5453 patients from 304 hospitals in 47 countries were included, of whom 6.6% (358/5453) did not receive their planned operation. Of the 4304 operated patients without neoadjuvant therapy, 40.5% (1744/4304) were delayed beyond 4 weeks. Delayed patients were more likely to be older, men, more comorbid, have higher body mass index and have rectal cancer and early stage disease. Delayed patients had higher unadjusted rates of complete resection (93.7% vs. 91.9%, P = 0.032) and lower rates of emergency surgery (4.5% vs. 22.5%, P < 0.001). After adjustment, delay was not associated with a lower rate of complete resection (OR 1.18, 95% CI 0.90-1.55, P = 0.224), which was consistent in elective patients only (OR 0.94, 95% CI 0.69-1.27, P = 0.672). Longer delays were not associated with poorer outcomes. CONCLUSION: One in 15 colorectal cancer patients did not receive their planned operation during the first wave of COVID-19. Surgical delay did not appear to compromise resectability, raising the hypothesis that any reduction in long-term survival attributable to delays is likely to be due to micro-metastatic disease

Extended Instrumental Variables Estimation for Overall Effects

We consider a method for extending instrumental variables methods in order to estimate the overall effect of a treatment or exposure. The approach is designed for settings in which the instrument influences both the treatment of interest and a secondary treatment also influenced by the primary treatment. We demonstrate that, while instrumental variables methods may be used to estimate the joint effects of the primary and secondary treatments, they cannot by themselves be used to estimate the overall effect of the primary treatment. However, instrumental variables methods may be used in conjunction with approaches for estimating the effect of the primary on the secondary treatment to estimate the overall effect of the primary treatment. We consider extending the proposed methods to deal with confounding of the effect of the instrument, mediation of the effect of the instrument by other variables, failure-time outcomes, and time-varying secondary treatments. We motivate our discussion by considering estimation of the overall effect of the type of vascular access among hemodialysis patients

Extended Instrumental Variables Estimation for Overall Effects

We consider a method for extending instrumental variables methods in order to estimate the overall effect of a treatment or exposure. The approach is designed for settings in which the instrument influences both the treatment of interest and a secondary treatment also influenced by the primary treatment. We demonstrate that, while instrumental variables methods may be used to estimate the joint effects of the primary and secondary treatments, they cannot by themselves be used to estimate the overall effect of the primary treatment. However, instrumental variables methods may be used in conjunction with approaches for estimating the effect of the primary on the secondary treatment to estimate the overall effect of the primary treatment. We consider extending the proposed methods to deal with confounding of the effect of the instrument, mediation of the effect of the instrument by other variables, failure-time outcomes, and time-varying secondary treatments. We motivate our discussion by considering estimation of the overall effect of the type of vascular access among hemodialysis patients.

Predictors of treatment with dialysis modalities in observational studies for comparative effectiveness research

BACKGROUND: The Institute of Medicine has identified the comparative effectiveness of renal replacement therapies as a kidney-related topic among the top 100 national priorities. Given the importance of ensuring internal and external validity, the goal of this study was to identify potential sources of bias in observational studies that compare outcomes with different dialysis modalities. METHODS: This observational cohort study used data from the electronic medical records of all patients that started maintenance dialysis in the calendar years 2007–2011 and underwent treatment for at least 60 days in any of the 2217 facilities operated by DaVita Inc. Each patient was assigned one of six dialysis modalities for each 91-day period from the date of first dialysis (thrice weekly in-center hemodialysis (HD), peritoneal dialysis (PD), less-frequent HD, home HD, frequent HD and nocturnal in-center HD). RESULTS: Of the 162 644 patients, 18% underwent treatment with a modality other than HD for at least one 91-day period. Except for PD, patients started treatment with alternative modalities after variable lengths of treatment with HD; the time until a change in modality was shortest for less-frequent HD (median time = 6 months) and longest for frequent HD (median time = 15 months). Between 30 and 78% of patients transferred to another dialysis facility prior to change in modality. Finally, there were significant differences in baseline and time-varying clinical characteristics associated with dialysis modality. CONCLUSIONS: This analysis identified numerous potential sources of bias in studies of the comparative effectiveness of dialysis modalities

Predictors of treatment with dialysis modalities in observational studies for comparative effectiveness research

BACKGROUND: The Institute of Medicine has identified the comparative effectiveness of renal replacement therapies as a kidney-related topic among the top 100 national priorities. Given the importance of ensuring internal and external validity, the goal of this study was to identify potential sources of bias in observational studies that compare outcomes with different dialysis modalities. METHODS: This observational cohort study used data from the electronic medical records of all patients that started maintenance dialysis in the calendar years 2007–2011 and underwent treatment for at least 60 days in any of the 2217 facilities operated by DaVita Inc. Each patient was assigned one of six dialysis modalities for each 91-day period from the date of first dialysis (thrice weekly in-center hemodialysis (HD), peritoneal dialysis (PD), less-frequent HD, home HD, frequent HD and nocturnal in-center HD). RESULTS: Of the 162 644 patients, 18% underwent treatment with a modality other than HD for at least one 91-day period. Except for PD, patients started treatment with alternative modalities after variable lengths of treatment with HD; the time until a change in modality was shortest for less-frequent HD (median time = 6 months) and longest for frequent HD (median time = 15 months). Between 30 and 78% of patients transferred to another dialysis facility prior to change in modality. Finally, there were significant differences in baseline and time-varying clinical characteristics associated with dialysis modality. CONCLUSIONS: This analysis identified numerous potential sources of bias in studies of the comparative effectiveness of dialysis modalities