| Literature DB >> 35721046 |
Nikolaus Kneidinger1, Alessandro Ghiani2, Katrin Milger1, Víctor Monforte3, Christiane Knoop4, Peter Jaksch5, Jasvir Parmar6, Piedad Ussetti7, Amparo Solé8, Joachim Müller-Quernheim9, Andreas Voelp10, Juergen Behr1, Claus Neurohr2.
Abstract
Background: Chronic lung allograft dysfunction (CLAD) is defined by a progressive loss of FEV1 and is associated with premature mortality. The aim of this study was to investigate the direct association between FEV1 decline and risk of mortality in patients after lung transplantation (LTx).Entities:
Keywords: BOS; CLAD; Cyclosporine (CsA); chronic rejection; lung transplantation
Year: 2022 PMID: 35721046 PMCID: PMC9201567 DOI: 10.3389/fmed.2022.897581
Source DB: PubMed Journal: Front Med (Lausanne) ISSN: 2296-858X
Baseline characteristics of study participants.
|
|
|
| ||
|---|---|---|---|---|
| Sex: number (%) female | 29 (39.2%) | 25 (44.6%) | 54 (41.5%) | |
| Age at screening (years) | 51.4 ± 12.8 | 52.1 ± 10.1 | 51.7 ± 11.7 | |
| Range 20–68 | Range 24–67 | Range 20–68 | ||
| Type of lung transplantation | Single | 23 (31.1%) | 17 (30.4%) | 40 (38.8%) |
| Double | 51 (68.9%) | 39 (69.6%) | 90 (69.2%) | |
| Time between lung transplantation and baseline (weeks) | 15.0 ± 7.8 | 18.5 ± 6.3 | 16.5 ± 7.4 | |
| Range 1.6–28.9 | Range 2.4–28.4 | Range 1.6–28.9 | ||
| FEV1 at baseline (L) | 2.32 ± 0.80 | 2.44 ± 0.70 | 2.37 ± 0.76 | |
| Range 0.96–4.93 | Range 1.12–4.17 | Range 0.96–4.93 | ||
| Maximum FEV1 after lung transplantation (personal best, L) | 2.67 ± 0.84 | 2.73 ± 0.81 | 2.70 ± 0.82 | |
| Range 0.96–5.08 | Range 1.21–4.50 | Range 0.96–5.08 |
Data are presented as mean ± SD and range or number and %.
FEV1, forced expiratory volume in 1 s; L-CsA-i, liposomal Cyclosporine A for inhalation.
Figure 1Individual subject trajectories of FEV1baseline% from baseline to end of follow-up. FEV1baseline% of intraindividual baseline value—individual subject trajectories (Month 0 corresponds to the baseline assessment of study 12011.201). Gray lines represent LOWESS regression lines.
Association between FEV1 % of baseline value time course and various predictors—linear mixed model main results.
|
|
|
|
|
|---|---|---|---|
| Treatment: placebo | −1.431 | −5.179, 2.318 | 0.454 |
| Time, linear association (months) | 0.149 | 0.007, 0.290 | 0.039 |
| Time, quadric association (months2) | −0.005 | −0.006, −0.004 | <0.001 |
| Treatment (placebo) by time interaction, linear (months) | −0.420 | −0.660, −0.180 | 0.001 |
| Treatment (placebo) by time interaction, quadric (months2) | 0.002 | 0.000, 0.003 | 0.009 |
| FEV1 at baseline (L) | −6.222 | −9.333, −3.112 | <0.001 |
| Type of LTx: single | −4.714 | −9.442, 0.124 | 0.056 |
| Age at baseline (years) | −0.079 | −0.236, 0.079 | 0.326 |
| Sex: male | 5.959 | 1.679, 10.239 | 0.006 |
The model represents the longitudinal process of the joint model assessing the association between FEV1 % of baseline time course and patient mortality.
FEV1, forced expiratory volume in 1 s; LTx, lung transplantation.
Figure 2Association between FEV1baseline% of the baseline value and survival (joint model analysis). The predicted association between FEV1% of baseline value and mortality risk is illustrated graphically.
Cox regression model with progression to FEV1baseline% ≥ 20% or below as the dependent variable and parameter estimates for covariates in the equation.
|
|
|
|
|
|
| ||||
|---|---|---|---|---|---|---|---|---|---|
|
|
| ||||||||
| First step | Treatment: L-CsA-i | −0.661 | 0.304 | 4.715 | 1 | 0.030 | 0.517 | 0.285 | 0.938 |
| Type of transplantation: double LTx | −0.787 | 0.351 | 5.021 | 1 | 0.025 | 0.455 | 0.229 | 0.906 | |
| Sex: female | −0.303 | 0.361 | 0.703 | 1 | 0.402 | 0.739 | 0.364 | 1.499 | |
| Age at baseline (years) | −0.009 | 0.014 | 0.395 | 1 | 0.530 | 0.991 | 0.964 | 1.019 | |
| FEV1 at randomization (L) | −0.083 | 0.272 | 0.092 | 1 | 0.761 | 0.921 | 0.541 | 1.568 | |
| Last step | Treatment: L-CsA-i | −0.629 | 0.296 | 4.504 | 1 | 0.034 | 0.533 | 0.298 | 0.953 |
| Type of transplantation: double LTx | −0.795 | 0.302 | 6.932 | 1 | 0.008 | 0.452 | 0.250 | 0.816 | |
While the upper part of the table shows the initial step that includes all specified covariates, the lower part shows the final step after removal of the covariates that did not have a statistically importance, predictive effect for lung function progression.
FEV1, forced expiratory volume in 1 s; LTx, lung transplantation; L-CsA-i, liposomal Cyclosporine A for inhalation.
Figure 3Graphical illustration of estimated cumulative non-progression to a loss in FEV1 by ≥20% of the baseline value—Cox regression analysis plotted for type of transplantation (A) and treatment (B). The “steps” in the curves of the subsets represent predicted events resulting from the regression model.
Cox regression model with all-cause mortality as the dependent variable and parameter estimates for covariates in the final equation.
|
|
|
|
|
|
| ||||
|---|---|---|---|---|---|---|---|---|---|
|
|
| ||||||||
| First step | Treatment: L-CsA-i | −0.055 | 0.304 | 0.032 | 1 | 0.857 | 0.947 | 0.522 | 1.717 |
| Type of transplantation: double LTx | −0.719 | 0.362 | 3.939 | 1 | 0.047 | 0.487 | 0.240 | 0.991 | |
| Sex: female | −0.249 | 0.352 | 0.501 | 1 | 0.479 | 0.780 | 0.391 | 1.553 | |
| Age at baseline (years) | 0.003 | 0.014 | 0.053 | 1 | 0.817 | 1.003 | 0.976 | 1.031 | |
| FEV1 at randomization (L) | −0.128 | 0.285 | 0.202 | 1 | 0.653 | 0.880 | 0.504 | 1.537 | |
| Last step | Treatment: L-CsA-i | −0.021 | 0.296 | 0.005 | 1 | 0.945 | 0.980 | 0.549 | 1.748 |
| Type of transplantation: double LTx | −0.831 | 0.299 | 7.723 | 1 | 0.005 | 0.436 | 0.242 | 0.783 | |
While the upper part of the table shows the initial step that includes all specified covariates, the lower part shows the final step after removal of the covariates that did not have a statistically importance, predictive effect for lung function progression.
FEV1, forced expiratory volume in 1 s; LTx, lung transplantation; L-CsA-i, liposomal Cyclosporine A for inhalation.
Figure 4Graphical illustration of estimated cumulative survival for subjects with different types of LTx—Cox regression analysis. The “steps” in the curves of the subsets represent predicted events resulting from the regression model.