Search results for "competing risks"

Mortality in early-stage, surgically resected non-small cell lung cancer less than 3cm of size: Competing risk analysis

2015

Abstract Background and objective Survival studies of non-small cell lung cancer (NSCLC) are usually based on the Kaplan–Meier method. However, other factors not covered by this method may modify the observation of the event of interest. There are models of cumulative incidence (CI), that take into account these competing risks, enabling more accurate survival estimates and evaluation of the risk of death from other causes. We aimed to evaluate these models in resected early-stage NSCLC patients. Patients and method This study included 263 patients with resected NSCLC whose diameter was ≤3 cm without node involvement (N0). Demographic, clinical, morphopathological and surgical variables, TN…

Advances in survival analysis: applications and extensions of the "standard" competing risks model

2023

Bayesian joint modeling of bivariate longitudinal and competing risks data: An application to study patient-ventilator asynchronies in critical care …

2017

Mechanical ventilation is a common procedure of life support in intensive care. Patient-ventilator asynchronies (PVAs) occur when the timing of the ventilator cycle is not simultaneous with the timing of the patient respiratory cycle. The association between severity markers and the events death or alive discharge has been acknowledged before, however, little is known about the addition of PVAs data to the analyses. We used an index of asynchronies (AI) to measure PVAs and the SOFA (sequential organ failure assessment) score to assess overall severity. To investigate the added value of including the AI, we propose a Bayesian joint model of bivariate longitudinal and competing risks data. Th…

Elastīgais parametriskais modelis izdzīvošanas datiem ar konkurējošiem riskiem

2015

Konkurējošie riski ir izplatīta parādība izdzīvošanas analīzē. Tie rodas, kad subjekts atrodas vairāku savstarpēji izslēdzošu notikumu riska zonā. Populārākā metode, pētot šāda veida datus, ir Deivida Koksa semi-parametriskā modeļa izmantošana. Darbā ir aplūkots alternatīvais variants izdzīvošanas datiem ar konkurējošiem riskiem – elastīgais parametriskais modelis, kas sniedz gludus novērtējumus galvenajiem raksturlielumiem – konkrēto cēloņu riskam un kumulatīvo biežumu funkcijai. Turklāt, izmantojot šo modeli, ir viegli iekļaut no laika atkarīgus ietekmējošos mainīgos. Darbā tiek aprakstīta konkurējošo risku elastīgā parametriskā modeļa būtība, un metode ir salīdzināta ar Koksa modeli. Ir …

Repeated kidney re-transplantation—the Eurotransplant experience: a retrospective multicenter outcome analysis

2020

Transplant international (2020). doi:10.1111/tri.13569