Mats Julius Stensrud

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In response to the coronavirus disease (COVID-19) pandemic, public health scientists have produced a large and rapidly expanding body of literature that aims to answer critical questions, such as the proportion of the population in a geographic area that h ...

Observational studies reporting on adjusted associations between childhood body mass index (BMI; weight (kg)/height (m)(2)) rebound and subsequent cardiometabolic outcomes have often not paid explicit attention to causal inference, including definition of ...

Sometimes treatment effects are absent in a subgroup of the population. For example, penicillin has no effect on severe symptoms in individuals infected by resistant Staphylococcus aureus, and codeine has no effect on pain in individuals with certain polym ...

We present a method for estimating several prognosis parameters for cancer survivors. The method utilizes the fact that these parameters solve differential equations driven by cumulative hazards. By expressing the parameters as solutions to differential eq ...

Knowing whether vaccine protection wanes over time is important for health policy and drug development. However, quantifying waning effects is difficult. A simple contrast of vaccine efficacy at two different times compares different populations of individ ...

Avoiding harm is an uncontroversial aim of personalized medicine and other epidemiologic initiatives. However, the precise mathematical translation of "harm"is disputable. Here, we use a formal causal language to study common, but distinct, definitions of ...

The interpretation of vaccine efficacy estimands is subtle, even in randomized trials designed to quantify the immunologic effects of vaccination. In this article, we introduce terminology to distinguish between different vaccine efficacy estimands and cla ...

Hazard ratios are routinely reported as effect measures in clinical trials and observational studies. However, many methodological works have raised concerns about the interpretation of hazard ratios as causal effects. These concerns are often related to t ...

In studies of medical treatments, individuals often experience post-treatment events that predict their future outcomes. In this work, we study how to use initial observations of a recurrent event - a type of post-treatment event - to offer updated treatme ...

Point identification of causal effects requires strong assumptions that are unreasonable in many practical settings. However, bounds on these effects can often be derived under plausible assumptions. Even when these bounds are wide or cover null effects, t ...

In our original article, we examine twin definitions of "harm" in personalized medicine: a first based on predictions of individuals' unmeasurable response types (counterfactual harm), and a second based solely on the observations of experiments (intervent ...

Risk ratios are one of the most commonly used effect measures in epidemiology. Yet their properties and transportability across different populations remain debated. In this article, we show that the causal risk ratio is stable to selection based on immune ...

Young age is associated with increased risk of recurrence in hormone receptor (HR)–positive early-stage breast cancer (eBC). Lack of adherence to endocrine therapy (ET) is a potential reason for the lower survival proportions observed in younger patients, ...

Many research questions involve time-to-event outcomes that can be prevented from occurring due to competing events. In these settings, we must be careful about the causal interpretation of classical statistical estimands. In particular, estimands on the h ...

Researchers are often interested in treatment effects on outcomes that are only defined conditional on posttreatment events. For example, in a study of the effect of different cancer treatments on quality of life at end of follow-up, the quality of life of ...

Intercurrent (post-treatment) events occur frequently in randomized trials, and investigators often express interest in treatment effects that suitably take account of these events. Contrasts that naively condition on intercurrent events do not have a stra ...

Pathogens usually exist in heterogeneous variants, like subtypes and strains. Quantifying treatment effects on the different variants is important for guiding prevention policies and vaccine development. Here, we ground analyses of variant-specific effects ...

We recently questioned the utility of testing for proportional hazards in survival analysis. Here, we expand on why the proportional hazards assumption is both implausible and unnecessary in most medical studies, particularly in randomized trials. We concl ...

Mats Julius Stensrud

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How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19

Separating Algorithms From Questions and Causal Inference With Unmeasured Exposures: An Application to Birth Cohort Studies of Early Body Mass Index Rebound

Using Negative Control Populations to Assess Unmeasured Confounding and Direct Effects

Prognosis of cancer survivors: estimation based on differential equations

Quantification of Vaccine Waning as a Challenge Effect

Perspectives on "harm" in personalized medicine

Distinguishing Immunologic and Behavioral Effects of Vaccination

How hazard ratios can mislead and why it matters in practice

A positivity robust strategy to study effects of switching treatment

Improved bounds and inference on optimal regimes

Rejoinder to "'Harm' in personalized medicine-an alternative perspective"

Immune-selection stability is a neglected property of the causal risk ratio

Explaining the Relationships Between Age, Endocrine Therapy Persistence, and Risk of Recurrence in Hormone Receptor–Positive Early Breast Cancer: A Nationwide Cohort Study

Estimation of separable direct and indirect effects in continuous time

Conditional Separable Effects

Translating questions to estimands in randomized clinical trials with intercurrent events

Variant Specific Treatment Effects with Applications in Vaccine Studies

Why use methods that require proportional hazards?

On the logic of collapsibility for causal effect measures

Discussion on "Causal mediation of semicompeting risks" by Yen-Tsung Huang