Sharp Bounds on Survivor Average Causal Effects When the Outcome Is Binary and Truncated by Death

Patient-centered outcomes, such as quality of life and length of hospital stay, are the focus in a wide array of clinical studies. However, participants in randomized trials for elderly or critically and severely ill patient populations may have truncated or undefined non-mortality outcomes if they do not survive through the measurement time point. To address truncation by death, the survivor average causal effect has been proposed as a causally interpretable subgroup treatment effect defined under the principal stratification framework. However, the majority of methods for estimatingthe survivor average causal effect have been developed in the context of individually randomized trials. Only limited discussions have been centered around cluster-randomized trials, where methods typically involve strong distributional assumptions for outcome modeling. In this article, we propose two weighting methods to estimatethe survivor average causal effect in cluster-randomized trials that obviate the need for potentially complicated outcome distribution modeling. We establish the requisite assumptions that address latent clustering effects to enable point identification of thesurvivor average causal effect, and we provide computationally efficient asymptotic variance estimators for each weighting estimator. In simulations, we evaluate our weighting estimators, demonstrating their finite-sample operating characteristics and robustness to certain departures from the identification assumptions. We illustrate our methods using data from a cluster-randomized trial to assess the impact of a sedation protocol on mechanical ventilation among children with acute respiratory failure.

While the HVTN 505 trial showed no overall efficacy of the tested vaccine to prevent HIV infection over placebo, markers measuring immune response to vaccination were strongly correlated with infection. This finding generated the hypothesis that some marker-defined vaccinated subgroups were partially protected whereas others had their risk increased. This hypothesis can be assessed using the principal stratification framework (Frangakis and Rubin, 2002) for studying treatment effect modification by an intermediate response variable, using methods in the sub-field of principal surrogate (PS) analysis that studies multiple principal strata. Unfortunately, available methods for PS analysis require an augmented study design not available in HVTN 505, and make untestable structural risk assumptions, motivating a need for more robust PS methods. Fortunately, another sub-field of principal stratification, survivor average causal effect (SACE) analysis (Rubin, 2006) - which studies effects in a single principal stratum - provides many methods not requiring an augmented design and making fewer assumptions. We show how, for a binary intermediate response variable, methods developed for SACE analysis can be adapted to PS analysis, providing new and more robust PS methods. Application to HVTN 505 supports that the vaccine partially protected individuals with vaccine-induced T-cells expressing certain combinations of functions.

In randomized trials in which the outcome requires considerable follow-up, participants may die before the trial is complete. In such cases, for the individuals who die before follow-up is complete, the outcome is not simply missing, but is undefined. Some authors refer to this situation as one in which the outcome is “truncated by death� [1,2], to distinguish this scenario from cases in which the outcome is merely missing because of inadequate data collection. In these settings, a crude comparison of the outcome between those who survived in each treatment arm may give misleading results, because we no longer preserve randomization by conditioning on a post-treatment event (survival) and thus the crude comparison is not a comparison for the same population comparing different treatments, but a comparison of different populations.

The HiLo Trial: a Multicentre Randomised Trial of High- versus Low-dose Radioiodine, with or without Recombinant Human Thyroid Stimulating Hormone, for Remnant Ablation after Surgery for Differentiated Thyroid Cancer

Convalescent Plasma and Coronavirus Disease 2019: Time for Reassessment.

Assessing the causal effects of interventions on ordinal outcomes is an important objective of many educational and behavioral studies. Under the potential outcomes framework, we can define causal effects as comparisons between the potential outcomes under treatment and control. However, unfortunately, the average causal effect, often the parameter of interest, is difficult to interpret for ordinal outcomes. To address this challenge, we propose to use two causal parameters, which are defined as the probabilities that the treatment is beneficial and strictly beneficial for the experimental units. However, although well-defined for any outcomes and of particular interest for ordinal outcomes, the two aforementioned parameters depend on the association between the potential outcomes and are therefore not identifiable from the observed data without additional assumptions. Echoing recent advances in the econometrics and biostatistics literature, we present the sharp bounds of the aforementioned causal parameters for ordinal outcomes, under fixed marginal distributions of the potential outcomes. Because the causal estimands and their corresponding sharp bounds are based on the potential outcomes themselves, the proposed framework can be flexibly incorporated into any chosen models of the potential outcomes and is directly applicable to randomized experiments, unconfounded observational studies, and randomized experiments with noncompliance. We illustrate our methodology via numerical examples and three real-life applications related to educational and behavioral research.

First-Cycle Pegfilgrastim Reduces Chemotherapy-Induced Febrile Neutropenia among Older Patients with NHL Treated in Community Practice: Results from a Large, Randomized, Controlled Trial.

Effect of multicomponent intervention on malnutrition in older adults: A multicenter randomized clinical trial

Background : Kotase ® is a combination systemic enzyme therapy that contains bromelain and trypsin. Bromelain is a crude extract of pineapple plant that contains mainly plant proteases. A multitude of actions have been ascribed to it including anti inflammatory properties. Aim : To evaluate the efficacy of bromelain/trypsin combination (Kotase ® ) in resolution of post laparotomy wound inflammation. Materials and Methods : The study is an open labeled study in which 111 patients were randomized in a 1:1 ratio to receive either Kotase ® or no kotase in their post op treatment. All the patients had major laparotomy wounds and were able to resume oral intake within 72 hours of surgery. The two groups of patients received all treatment necessary for their condition except with regards to analgesic and anti-inflammatory treatment. After commencement of oral intake, patients for Kotase treatment had two tablet of Kotase ® qid added to their post op drugs for a maximum of ten days or until the patient was discharged. Patients were assessed every day for operative wound pain, and inflammatory oedema. Also, the analgesic requirements and wound failure rates were assessed. Results : The two groups were matched with respect to demographic characteristics and case distribution. In the no treatment arm, the average post op inflammatory oedema decreased from 1.969mm on commencement of oral intake to 1.827mm on the 5 th day of measurement and 1.631mm by the time the patients were discharged. In the Kotase ® treatment group, the inflammatory oedema decreased from 1.959mm on the first day of drug treatment to 1.389mm by the 5 th day and 1.018mm by the time the patients were discharged. There was significant difference in the size of the oedema of the two groups on the 5 th day and by the time of discharge. The average visual analogue pain score of patients without Kotase ® decreased from 6.27 on the first day of oral intake to 3.65 by the 5 th day and 1.84 by the time the patients were discharged. The patients that had Kotase ® had an average pain score of 6.32 on the 1 st day and 2.45 on the 5 th day and 0.68 by the time of discharge. Again the drop in pain score was significantly more in the patients that had Kotase ® . Ten patients in the no Kotase ® arm needed extra doses of dipyrone in addition to the set down analgesics to control their pain while only one in the Kotase ® arm needed extra doses of analgesics to control his pain. There were 6 minor wound infections in each treatment arm and one wound breakdown in the no Kotase ® treatment group. There was no unexpected adverse reaction due to the use of Kotase ® . Conclusion : The results show the effectiveness of combination of bromelain and trypsin in reducing post operative inflammatory oedema and operation wound pain that accompany major laparotomy wounds. Keywords : bromelain, trypsin, post op inflammation, systemic enzyme therapy (SET) Journal of College of Medicine Vol. 10(2) 2005: 61-66

Objective:To examine the effect of selenium supplementation on CD4+ T-cell counts, viral suppression, and time to antiretroviral therapy (ART) initiation in ART-naive HIV-infected patients in Rwanda.Methods:A multicenter, double-blinded, placebo-controlled, randomized clinical trial was conducted. Eligible patients were HIV-infected adults (≥21 years) who had a CD4+ cell count between 400 and 650 cells/μl (ART eligibility was ≤350 cells/μl throughout the trial), and were willing to practice barrier methods of birth control. Patients were randomized to receive once-daily 200 μg selenium tablets or identical placebo. They were followed for 24 months with assessments every 6 months. Declines in CD4+ cell counts were modeled using linear regressions with generalized estimating equations and effect modification, and the composite outcome (ART eligible or ART initiation) using Cox proportional-hazards regression, both conducted with intention to treat.Results:Of the 300 participants, 149 received selenium, 202 (67%) were women, and median age was 33.5 years. The rate of CD4+ depletion was reduced by 43.8% [95% confidence interval (CI) 7.8–79.8% decrease] in the treatment arm – from mean 3.97 cells/μl per month to mean 2.23 cells/μl per month. We observed 96 composite outcome events – 45 (47%) in the treatment arm. We found no treatment effect for the composite outcome (hazard ratio 1.00, 95% CI 0.66–1.54) or viral suppression (odds ratio 1.18, 95% CI 0.71–1.94). The trial was underpowered for the composite outcome due to a lower-than-anticipated event rate. Adverse events were comparable throughout.Conclusions:This randomized clinical trial demonstrated that 24-month selenium supplementation significantly reduces the rate of CD4+ cell count decline among ART-naive patients.

Reply from Authors re: Ronald C. Chen. Decisions Regarding Whether to Use Androgen Deprivation Therapy with Radiotherapy in Prostate Cancer: Is Cardiovascular Mortality the Most Relevant Outcome? Eur Urol 2016;69:211–2: Outcomes for Favorable and Unfavorable Intermediate Risk Prostate Cancer Patients Receiving Radiation Therapy With or Without Short-term Androgen Deprivation Therapy

The Causal Effect of Fertility on Female Labor Supply: Evidence from Taiwanese Son Preference

In clinical trials with time-to-event outcomes, it is common to estimate the marginal hazard ratio from the proportional hazards model, even when the proportional hazards assumption is not valid. This is unavoidable from the perspective that the estimator must be specified a priori if probability statements about treatment effect estimates are desired. Marginal hazard ratio estimates under non-proportional hazards are still useful, as they can be considered to be average treatment effect estimates over the support of the data. However, as many have shown, under non-proportional hazard, the 'usual' unweighted marginal hazard ratio estimate is a function of the censoring distribution, which is not normally considered to be scientifically relevant when describing the treatment effect. In addition, in many practical settings, the censoring distribution is only conditionally independent (e.g., differing across treatment arms), which further complicates the interpretation. In this paper, we investigate an estimator of the hazard ratio that removes the influence of censoring and propose a consistent robust variance estimator. We compare the coverage probability of the estimator to both the usual Cox model estimator and an estimator proposed by Xu and O'Quigley (2000) when censoring is independent of the covariate. The new estimator should be used for inference that does not depend on the censoring distribution. It is particularly relevant to adaptive clinical trials where, by design, censoring distributions differ across treatment arms.

Efficacy and safety of therapeutic vs. prophylactic bemiparin in noncritically ill patients with COVID-19 pneumonia

To examine long-term and oncologic outcomes of broad-spectrum perioperative antimicrobial prophylaxis, compared with standard care antibiotics, in patients undergoing pancreatoduodenectomy. A registry-linked randomized clinical trial demonstrated a reduction in surgical site infection (SSI) in patients undergoing pancreatoduodenectomy who received piperacillin-tazobactam as perioperative prophylaxis compared to cefoxitin. However, long-term outcomes remain undefined. Participant records from the American College of Surgeons National Surgical Quality Improvement Program database were matched to the National Cancer Database. Associations between treatment arm, perioperative complications, and oncologic outcomes were assessed. Logistic regression models investigated associations with oncologic outcomes. Survival analyses used Kaplan Meier and Cox proportional hazard modeling. Of 778 patients, 471 (60.5%) were treated at Commission on Cancer accredited hospitals and eligible for linkage. Of those, 426 (90.4%) were matched in the NCDB including 203 (47.7%) treated with piperacillin-tazobactam and 223 (52.3%) with cefoxitin. Among patients with indications for chemotherapy, chemotherapy omission rates were similar between the treatment arms (9.4% in piperacillin-tazobactam vs 15.4% in cefoxitin; P=0.097). There was no association between the receipt of indicated adjuvant chemotherapy and receipt of piperacillin-tazobactam (OR 1.49; 95% CI 0.56-3.95) or presence of SSI (OR 0.58; 95% CI 0.21-1.65). Postoperative SSI was associated with poorer 3-year overall survival (HR 1.69, 95% CI 1.20-2.38). While patients experiencing an SSI had poorer survival, piperacillin-tazobactam prophylaxis did not significantly affect oncologic care delivery. These results cement the long-term implications of perioperative complications in patients with cancer and highlight leveraging cancer registries for clinical trial data analysis.