Special issue dedicated to Odd O. Aalen

Borgan, Ørnulf; Gjessing, Håkon K.

doi:10.1007/s10985-019-09483-z

Cited by 2 publications

(6 citation statements)

References 30 publications

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“…Briefly, we implemented and extended a previously published construction of the longitudinal care continuum [18] to accommodate late entries to the analysis (patients who transferred care having already initiated ART elsewhere) under the assumption that late entries are not informative [23,24]. We estimated the cumulative incidence of the following nine events (different from the seven stages) nonparametrically using the Aalen-Johansen estimator [25][26][27]. Events were not of interest in and of themselves, but represent transitions between the stages.…”

Section: Discussionmentioning

confidence: 99%

Longitudinal HIV care outcomes by gender identity in the United States

Lesko

Edwards

Hanna

et al. 2022

Aids

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Objective:Describe engagement in HIV care over time after initial engagement in HIV care, by gender identity.Design:Observational, clinical cohort study of people with HIV engaged in routine HIV care across the United States.Methods:We followed people with HIV who linked to and engaged in clinical care (attending ≥2 visits in 12 months) in cohorts in the North American Transgender Cohort Collaboration, 2000–2018. Within strata of gender identity, we estimated the 7-year (84-month) restricted mean time spent: lost-to-clinic (stratified by pre/postantiretroviral therapy (ART) initiation); in care prior to ART initiation; on ART but not virally suppressed; virally suppressed (≤200 copies/ml); or dead (pre/post-ART initiation).Results:Transgender women (N = 482/101 841) spent an average of 35.5 out of 84 months virally suppressed (this was 30.5 months for cisgender women and 34.4 months for cisgender men). After adjustment for age, race, ethnicity, history of injection drug use, cohort, and calendar year, transgender women were significantly less likely to die than cisgender people. Cisgender women spent more time in care not yet on ART, and less time on ART and virally suppressed, but were less likely to die compared with cisgender men. Other differences were not clinically meaningful.Conclusions:In this sample, transgender women and cisgender people spent similar amounts of time in care and virally suppressed. Additional efforts to improve retention in care and viral suppression are needed for all people with HIV, regardless of gender identity.

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Section: Discussionmentioning

confidence: 99%

Longitudinal HIV care outcomes by gender identity in the United States

Lesko

Edwards

Hanna

et al. 2022

Aids

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“…A number of works in this field have focused on the predictions task and provided equations to calculate (conditional or not) probabilities of interest from the (estimated) transition hazards. [23][24][25][26][27] Let us denote the time to enter the intermediate event D as T Ã D and the time of the clinical event of interest as T Ã E . We are interested in estimating the marginal survival function of T Ã E , that we will express as S T Ã E tjarm ð Þ, as this function characterizes the probability distribution of T Ã E regardless of whether or not the subject has stopped by state D along the way.…”

Section: Calculating the Survival Function Of Interestmentioning

confidence: 99%

“…E as a valid hazard function as defined in survival analysis without competing events. We can do that because, when a subject is at state D, there are no future transitions competing with the transition to E. 27 We note that Equations (3), ( 5), and ( 6) are particular cases of eqs. ( 34), (31), and (29), respectively, from the work of Putter, Fiocco, and Geskus, as here we do not condition on results up to an interim data point s (with 0 ≤ s < t) but set s ¼ 0.…”

Section: Calculating the Survival Function Of Interestmentioning

confidence: 99%

“…To identify these two transitions, we could use either nonparametric, semiparametric, or fully parametric methods. 23,27,36,44 In this paper, we will use flexible (possibly stratified) parametric models. We have chosen this approach as it allows us to adjust for baseline covariates using either the PH assumption or stratification.…”

Section: Modeling Transitions I ! E and I ! Dmentioning

confidence: 99%

“…The estimator proposed in Sections 3.1 and 3.2 is one among the many options available in the literature to fit an illness-death model. 23,27,36,44,45 In this section, we will consider a few alternatives.…”

Section: Other Modeling Optionsmentioning

confidence: 99%

See 2 more Smart Citations

An illness–death multistate model to implement delta adjustment and reference‐based imputation with time‐to‐event endpoints

García‐Hernandez,

Pérez,

del Carmen Pardo

et al. 2023

Pharmaceutical Statistics

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With a treatment policy strategy, therapies are evaluated regardless of the disturbance caused by intercurrent events (ICEs). Implementing this estimand is challenging if subjects are not followed up after the ICE. This circumstance can be dealt with using delta adjustment (DA) or reference‐based (RB) imputation. In the survival field, DA and RB imputation have been researched so far using multiple imputation (MI). Here, we present a fully analytical solution. We use the illness–death multistate model with the following transitions: (a) from the initial state to the event of interest, (b) from the initial state to the ICE, and (c) from the ICE to the event. We estimate the intensity function of transitions (a) and (b) using flexible parametric survival models. Transition (c) is assumed unobserved but identifiable using DA or RB imputation assumptions. Various rules have been considered: no ICE effect, DA under proportional hazards (PH) or additive hazards (AH), jump to reference (J2R), and (either PH or AH) copy increment from reference. We obtain the marginal survival curve of interest by calculating, via numerical integration, the probability of transitioning from the initial state to the event of interest regardless of having passed or not by the ICE state. We use the delta method to obtain standard errors (SEs). Finally, we quantify the performance of the proposed estimator through simulations and compare it against MI. Our analytical solution is more efficient than MI and avoids SE misestimation—a known phenomenon associated with Rubin's variance equation.

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Special issue dedicated to Odd O. Aalen

Cited by 2 publications

References 30 publications

Longitudinal HIV care outcomes by gender identity in the United States

Longitudinal HIV care outcomes by gender identity in the United States

An illness–death multistate model to implement delta adjustment and reference‐based imputation with time‐to‐event endpoints

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