bos: Bronchiolitis obliterans syndrome after lung transplants
In flexsurv: Flexible Parametric Survival and Multi-State Models
bos R Documentation
Bronchiolitis obliterans syndrome after lung transplants
Description
A dataset containing histories of bronchiolitis obliterans syndrome (BOS)
from lung transplant recipients. BOS is a chronic decline in lung function,
often observed after lung transplantation.
Format
A data frame containing a sequence of observed or censored
transitions to the next stage of severity or death. It is grouped
by patient and includes histories of 204 patients. All patients
start in state 1 (no BOS) at six months after transplant, and may
subsequently develop BOS or die.
bosms3 contains the data for a three-state model: no BOS, BOS or
death. bosms4 uses a four-state representation: no BOS, mild BOS,
moderate/severe BOS or death.
id (numeric)
Patient identification number
from (numeric) Observed
starting state of the transition
to (numeric) Observed
or potential ending state of the transition
Tstart
(numeric) Time at the start of the interval
Tstop
(numeric) Time at the end of the interval
time
(numeric) Time difference Tstart-Tstop
status
(numeric) 1 if the transition to state to was observed, or
0 if the transition to state to was censored (for example, if the
patient was observed to move to a competing state)
trans
(factor) Number of the transition from-to in the set of
all ntrans allowed transitions, numbered from 1 to ntrans.
Details
The entry time of each patient into each stage of BOS was estimated by
clinicians, based on their history of lung function measurements and acute
rejection and infection episodes. BOS is only assumed to occur beyond six
months after transplant. In the first six months the function of each
patient's new lung stabilises. Subsequently BOS is diagnosed by comparing
the lung function against the "baseline" value.
The same data are provided in the msm package, but in the
native format of msm to allow Markov models to be fitted.
In flexsurv, much more flexible models can be fitted.
Source
Papworth Hospital, U.K.
References
Heng. D. et al. (1998). Bronchiolitis Obliterans Syndrome:
Incidence, Natural History, Prognosis, and Risk Factors. Journal of Heart
and Lung Transplantation 17(12)1255–1263.
flexsurv documentation built on Feb. 16, 2023, 5:07 p.m.
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| bos | R Documentation |
Bronchiolitis obliterans syndrome after lung transplants
Description
A dataset containing histories of bronchiolitis obliterans syndrome (BOS) from lung transplant recipients. BOS is a chronic decline in lung function, often observed after lung transplantation.
Format
A data frame containing a sequence of observed or censored transitions to the next stage of severity or death. It is grouped by patient and includes histories of 204 patients. All patients start in state 1 (no BOS) at six months after transplant, and may subsequently develop BOS or die.
bosms3 contains the data for a three-state model: no BOS, BOS or
death. bosms4 uses a four-state representation: no BOS, mild BOS,
moderate/severe BOS or death.
id | (numeric) | Patient identification number |
from | (numeric) | Observed starting state of the transition |
to | (numeric) | Observed or potential ending state of the transition |
Tstart | (numeric) | Time at the start of the interval |
Tstop | (numeric) | Time at the end of the interval |
time | (numeric) | Time difference Tstart-Tstop |
status
| (numeric) | 1 if the transition to state to was observed, or
0 if the transition to state to was censored (for example, if the
patient was observed to move to a competing state) |
trans | (factor) | Number of the transition from-to in the set of
all ntrans allowed transitions, numbered from 1 to ntrans. |
Details
The entry time of each patient into each stage of BOS was estimated by clinicians, based on their history of lung function measurements and acute rejection and infection episodes. BOS is only assumed to occur beyond six months after transplant. In the first six months the function of each patient's new lung stabilises. Subsequently BOS is diagnosed by comparing the lung function against the "baseline" value.
The same data are provided in the msm package, but in the native format of msm to allow Markov models to be fitted. In flexsurv, much more flexible models can be fitted.
Source
Papworth Hospital, U.K.
References
Heng. D. et al. (1998). Bronchiolitis Obliterans Syndrome: Incidence, Natural History, Prognosis, and Risk Factors. Journal of Heart and Lung Transplantation 17(12)1255–1263.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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