Description Usage Arguments Details Value Author(s) References See Also Examples
A program that computes the time until definitive deterioration in quality of score.
1 2 |
X |
input data matrix or data frame with a quality of life score. Missing values are inserted as NA. |
score |
vector with the name of the quality of life scores of interest |
MCID |
a vector equals to the minimal clinically important difference (MCID). Several MCID can be specified |
ref.init |
the reference score to qualify the deterioration.
By default, |
ref.def |
the deterioration is definitive 1: if there is no clinically significant improvement as compared to the reference score ( |
order |
a vector equals to 1 if the deterioration corresponds to a decrease of the score, 2 otherwise |
no_baseline |
By default, |
no_follow |
By default, |
death |
missing if patients who died without experienced a deterioration are censored at the time of the last quality of life assessment, equals to the name of the death date in the dataframe |
sensitivity |
Boolean equal to |
To apply this function, the dataset must respect a general structure.
The dataset X
must be in long format with the following variables in the following order:
Patient identification number
Variable identify the quality of life assessment, i.e. the visit number
Date of quality of life measure
quality of life scores
Other variables such as the date of death or the treatment arm.
The dataset must also be sorted by patient identification number and quality of life measurement time.
Dates must be in Julian format (i.e. number of days since a reference time point).
All these definitions are extensively described in the referenced papers below.
The result is a dataframe with the id
variable of the dataframe X
and the results of the time to deterioration analyses performed.
For each score and each time to deterioration analysis, two variables are created called event
and time
with the value of the MCID
and the name of the corresponding score as a suffix.
Moreover, if sensitivity
is TRUE
, a suffix is added to each result of this function reflecting the sensitivity analysis corresponding (SA1, SA2 or SA3).
The first variable event
is a dummy vector equal to 1 if the patient is deteriorated and 0 if not.
The second variable time
equal to the time in months to deterioration since baseline if the patient is deteriorated or the time to censoring.
As example, for a given score "qol", MCID = 5
and one analyse performed (i.e. sensitivity
is FALSE
), then two variables are created called event.5.qol
and time.5.qol
.
Amelie Anota
Maintainer: Amelie Anota <aanota@chu-besancon.fr>
Anota A., et al. Time to Health-related Quality of Life score deterioration as a modality of longitudinal analysis for health-related quality of life studies in oncology: do we need RECIST for quality of life to achieve standardization? Qual Life Res. 2013 Nov 26.
Bonnetain F., et al. Time until definitive deterioration as a means of longitudinal analysis for treatment trials in patients with metastatic pancreatic adenocarcinoma. Eur J Cancer 2010, 46(5): 2753-2762.
1 2 3 4 5 6 | data(dataqol2)
# Time to definitive deterioration of at least 5 points of the "QoL" score
# as compared to the best previous score with no further improvement of more
# than 5 points as compared to the best previous score:
tudd=TUDD(dataqol2,score=c("QoL","pain"),ref.init="best",order=1,MCID=5)
head(tudd)
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