scholarly journals Strongly reduced alloreactivity and long-term survival times of cardiac allografts in Vav1- and Vav1/Vav2-knockout mice

2007 ◽  
Vol 20 (4) ◽  
pp. 353-364 ◽  
Author(s):  
Gisbert Weckbecker ◽  
Christian Bruns ◽  
Klaus-Dieter Fischer ◽  
Christoph Heusser ◽  
Jianping Li ◽  
...  
Keyword(s):  
Knockout Mice ◽  
Survival Times ◽  
Term Survival ◽  
Long Term Survival ◽  
Cardiac Allografts

Oxygen treatment after perinatal hypoxia-ischemia reduces neuronal damage at short survival times, but worsens injury with long-term survival

2005 ◽  
Vol 25 (1_suppl) ◽  
pp. S444-S444 ◽  
Author(s):  
Kristin M Noppens ◽  
J Regino Perez-Polo ◽  
David K Rassin ◽  
Karin N Westlund ◽  
Roderic Fabian ◽  
...  
Keyword(s):  
Neuronal Damage ◽  
Perinatal Hypoxia ◽  
Survival Times ◽  
Term Survival ◽  
Long Term Survival ◽  
Short Survival ◽  
Oxygen Treatment ◽  
Hypoxia Ischemia

scholarly journals Long-term survival benefit of ramipril in patients with acute myocardial infarction complicated by heart failure

Heart ◽  
2021 ◽  
Vol 107 (5) ◽  
pp. 389-395
Author(s):  
Jianhua Wu ◽  
Alistair S Hall ◽  
Chris P Gale
Keyword(s):  
Myocardial Infarction ◽  
Heart Failure ◽  
Acute Myocardial Infarction ◽  
Life Expectancy ◽  
Survival Benefit ◽  
Ace Inhibition ◽  
Survival Times ◽  
Term Survival ◽  
Long Term Survival

AimsACE inhibition reduces mortality and morbidity in patients with heart failure after acute myocardial infarction (AMI). However, there are limited randomised data about the long-term survival benefits of ACE inhibition in this population.MethodsIn 1993, the Acute Infarction Ramipril Efficacy (AIRE) study randomly allocated patients with AMI and clinical heart failure to ramipril or placebo. The duration of masked trial therapy in the UK cohort (603 patients, mean age=64.7 years, 455 male patients) was 12.4 and 13.4 months for ramipril (n=302) and placebo (n=301), respectively. We estimated life expectancy and extensions of life (difference in median survival times) according to duration of follow-up (range 0–29.6 years).ResultsBy 9 April 2019, death from all causes occurred in 266 (88.4%) patients in placebo arm and 275 (91.1%) patients in ramipril arm. The extension of life between ramipril and placebo groups was 14.5 months (95% CI 13.2 to 15.8). Ramipril increased life expectancy more for patients with than without diabetes (life expectancy difference 32.1 vs 5.0 months), previous AMI (20.1 vs 4.9 months), previous heart failure (19.5 vs 4.9 months), hypertension (16.6 vs 8.3 months), angina (16.2 vs 5.0 months) and age >65 years (11.3 vs 5.7 months). Given potential treatment switching, the true absolute treatment effect could be underestimated by 28%.ConclusionFor patients with clinically defined heart failure following AMI, ramipril results in a sustained survival benefit, and is associated with an extension of life of up to 14.5 months for, on average, 13 months treatment duration.

ICOS-Ig combined with CsA induces long term survival of cardiac allografts in mouse

2009 ◽  
Vol 24 (5) ◽  
pp. 249-258
Author(s):  
Zhang Peng ◽  
Wang Zhenmeng ◽  
Qin Qin ◽  
Tang Yi ◽  
Wang Quanxing ◽  
...  
Keyword(s):  
Term Survival ◽  
Long Term Survival ◽  
Cardiac Allografts

scholarly journals Renal Replacement Therapy in Patients With Stage IV Cancer Admitted to the Intensive Care Unit With Acute Kidney Injury at a Comprehensive Cancer Center Was Not Associated With Survival

2020 ◽  
Vol 37 (9) ◽  
pp. 707-715
Author(s):  
Ala Abudayyeh ◽  
Juhee Song ◽  
Maen Abdelrahim ◽  
Ibrahim Dahbour ◽  
Valda D. Page ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Kidney Injury ◽  
Stage Iv ◽  
Inpatient Mortality ◽  
Survival Times ◽  
Term Survival ◽  
Long Term Survival ◽  
Time Points ◽  
Stage Iv Cancer

Introduction: In patients with advanced cancer, prolongation of life with treatment often incurs substantial emotional and financial expense. Among hospitalized patients with cancer since acute kidney injury (AKI) is known to be associated with much higher odds for hospital mortality, we investigated whether renal replacement therapy (RRT) use in the intensive care unit (ICU) was a significant independent predictor of worse outcomes. Methods: We retrospectively reviewed patients admitted in 2005 to 2014 who were diagnosed with stage IV solid tumors, had AKI, and a nephrology consult. The main outcomes were survival times from the landmark time points, inpatient mortality, and longer term survival after hospital discharge. Logistic regression and Cox proportional regression were used to compare inpatient mortality and longer term survival between RRT and non-RRT groups. Propensity score-matched landmark survival analyses were performed with 2 landmark time points chosen at day 2 and at day 7 from ICU admission. Results: Of the 465 patients with stage IV cancer admitted to the ICU with AKI, 176 needed RRT. In the multivariate logistic regression model after adjusting for baseline serum albumin and baseline maximum Sequential Organ Failure Assessment (SOFA), the patients who received RRT were not significantly different from non-RRT patients in inpatient mortality (odds ratio: 1.004 [95% confidence interval: 0.598-1.684], P = .9892). In total, 189 patients were evaluated for the impact of RRT on long-term survival and concluded that RRT was not significantly associated with long-term survival after discharge for patients who discharged alive. Landmark analyses at day 2 and day 7 confirmed the same findings. Conclusions: Our study found that receiving RRT in the ICU was not significantly associated with inpatient mortality, survival times from the landmark time points, and long-term survival after discharge for patients with stage IV cancer with AKI.

scholarly journals Causal inference for long-term survival in randomised trials with treatment switching: Should re-censoring be applied when estimating counterfactual survival times?

2018 ◽  
Vol 28 (8) ◽  
pp. 2475-2493 ◽  
Author(s):  
NR Latimer ◽  
IR White ◽  
KR Abrams ◽  
U Siebert
Keyword(s):  
Treatment Effect ◽  
Failure Time ◽  
Survival Function ◽  
Experimental Treatment ◽  
Control Group ◽  
Survival Times ◽  
Term Survival ◽  
Long Term Survival ◽  
Treatment Switching

Treatment switching often has a crucial impact on estimates of effectiveness and cost-effectiveness of new oncology treatments. Rank preserving structural failure time models (RPSFTM) and two-stage estimation (TSE) methods estimate ‘counterfactual’ (i.e. had there been no switching) survival times and incorporate re-censoring to guard against informative censoring in the counterfactual dataset. However, re-censoring causes a loss of longer term survival information which is problematic when estimates of long-term survival effects are required, as is often the case for health technology assessment decision making. We present a simulation study designed to investigate applications of the RPSFTM and TSE with and without re-censoring, to determine whether re-censoring should always be recommended within adjustment analyses. We investigate a context where switching is from the control group onto the experimental treatment in scenarios with varying switch proportions, treatment effect sizes, treatment effect changes over time, survival function shapes, disease severity and switcher prognosis. Methods were assessed according to their estimation of control group restricted mean survival that would be observed in the absence of switching, up to the end of trial follow-up. We found that analyses which re-censored usually produced negative bias (i.e. underestimating control group restricted mean survival and overestimating the treatment effect), whereas analyses that did not re-censor consistently produced positive bias which was often smaller in magnitude than the bias associated with re-censored analyses, particularly when the treatment effect was high and the switching proportion was low. The RPSFTM with re-censoring generally resulted in increased bias compared to the other methods. We believe that analyses should be conducted with and without re-censoring, as this may provide decision-makers with useful information on where the true treatment effect is likely to lie. Incorporating re-censoring should not always represent the default approach when the objective is to estimate long-term survival times and treatment effects.

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