Naive hypothesis testing for case series analysis with time-varying exposure onset measurement error: inference for infection-cardiovascular risk in patients on dialysis.

The case series method is useful in studying the relationship between time-varying exposures, such as infections, and acute events observed during the observation periods of individuals. It provides estimates of the relative incidences of events in risk periods (e.g.

Measurement Error Case Series Models with Application to Infection-Cardiovascular Risk in OlderPatients on Dialysis.

Infection and cardiovascular disease are leading causes of hospitalization and death in older patients on dialysis. Our recent work found an increase in the relative incidence of cardiovascular outcomes during the ~ 30 days after infection-related hospitalizations using the case series model, which adjusts for measured and unmeasured baseline confounders. However, a major challenge in modeling/assessing the infection-cardiovascular risk hypothesis is that the exact time of infection, or more generally "exposure," onsets cannot be ascertained based on hospitalization data.

Modeling time-varying effects with generalized and unsynchronized longitudinal data.

We propose novel estimation approaches for generalized varying coefficient models that are tailored for unsynchronized, irregular and infrequent longitudinal designs/data. Unsynchronized longitudinal data refer to the time-dependent response and covariate measurements for each individual measured at distinct time points. Data from the Comprehensive Dialysis Study motivate the proposed methods.

Design considerations for case series models with exposure onset measurement error.

The case series model allows for estimation of the relative incidence of events, such as cardiovascular events, within a pre-specified time window after an exposure, such as an infection. The method requires only cases (individuals with events) and controls for all fixed/time-invariant confounders. The measurement error case series model extends the original case series model to handle imperfect data, where the timing of an infection (exposure) is not known precisely.

Risk of cardiovascular events after infection-related hospitalizations in older patients on dialysis.

Background And Objectives: Infection and cardiovascular disease are leading causes of hospitalization and death in patients on dialysis. The objective of this study was to determine whether an infection-related hospitalization increased the short-term risk of a cardiovascular event in older patients on dialysis.

Design, Setting, Participants, & Measurements: With use of the United States Renal Data System, patients aged 65 to 100 years who started dialysis between January 1, 2000, and December 31, 2002, were examined.

Racial disparities on the use of invasive and noninvasive staging in patients with non-small cell lung cancer.

Introduction: Racial disparities have been reported in non-small cell lung cancer (NSCLC) staging and therapeutic outcomes. We investigated whether such disparities exist in the era of modern noninvasive staging modalities, including positron emission tomography scan use.

Methods: NSCLC patients from the California Cancer Registry diagnosed between January 1, 1994, and December 31, 2004, were included.