Scores the European Organization for Research and Treatment of Cancer (EORTC) QLQ-CX24 Cervical Cancer Module.
qlq_cx24(df, items = NULL, keepNvalid = FALSE)A data frame with all 9 of the QLQ-CX24 scores is returned. Of the 9 scores, 7 are Symptom Scales and 2 are Functional Scales (see below). Of the 9 scores, only 3 are based on multiple items (the first 3 Symptom Scales), and the other 6 scores are each based on a single item. All scores are scaled to range from 0-100, even scores based on single items. Be aware that these single-item scales still have only 4 possible values, even though they are transformed to range from 0-100. The scale names and numbers of items are listed below.
Symptom Scales (higher is more symptoms, worse functioning)
CX_SE - Symptom Experience (from 11 items)
CX_BI - Body Image (from 3 items)
CX_SV - Sexual/Vaginal Functioning (from 4 items)
CX_LY - Lymphoedema (from 1 item)
CX_PN - Peripheral Neuropathy (from 1 item)
CX_MS - Menopausal Symptoms (from 1 item)
CX_SXW - Sexual Worry (from 1 item)
Functional Scales (higher is better functioning)
CX_SXA - Sexual Activity (from 1 item)
CX_SXE - Sexual Enjoyment (from 1 item)
Optionally, the data frame can additionally have variables containing the
number of valid item responses on each scale for each respondent (if
keepNvalid = TRUE, but this option might be removed in future package
updates).
A data frame containing responses to the 24 QLQ-CX24 items, and possibly other variables.
A character vector with the QLQ-CX24 item names, or a numeric
vector indicating the column numbers of the QLQ-CX24 items in df.
If items is omitted, then qlq_cx24 will assume that
df contains ONLY the QLQ-CX24 items and no other variables.
See Details for more information.
Logical, whether to return variables containing the
number of valid, non-missing items on each scale for each respondent should
be returned in the data frame with the scale scores. The default is
FALSE. Set to TRUE to return these variables, which will be
named "scalename_N" (e.g., QL_N). Most users should omit
this argument entirely. This argument might be removed from future
versions of the package, so please let me know if you think this argument
useful and would rather it remain a part of the function.
The qlq_cx24 function will calculate the scale scores as long as at
least half of the items on the given scale have valid, non-missing item
responses. Scores calculated in the presence of missing
items are pro-rated so that their theoretical minimum and maximum values
are identical to those from scores calculated from complete data.
This function returns a total of 9 different scores from the EORTC QLQ-CX24. Scores are calculated according to the official scoring algorithms from the EORTC.
In addition to the name of your data frame containing the QLQ-CX24 item
responses (df), you need to tell the function how to find the
variables that correspond to the QLQ-CX24 items in df. You can do this
in 1 of 2 ways:
The first way is to manually provide the item names or locations
using the items argument. For example, if your first 10
variables in df contain demographics, followed by the 24 QLQ-CX24
items in order starting with the 11th variable, then you could
use items = 11:34.
The second way only applies if your data frame (df) contains
ONLY the 24 variables corresponding to the 24 QLQ-CX24 items,
in order, with no other non-QLQ-CX24 variables. In this case, you can
just use the df argument and omit items.
Greimel E, Kuljanic Vlasic K, Waldenstrom AC et al. on behalf of the EORTC Quality of Life Group. The European Organization for Research and Treatment of Cancer (EORTC) Quality-of-Life questionnaire cervical cancer module - EORTC QLQ-CX24. Cancer 107 (8): 1812-1822, 2006.
if (FALSE) {
dat <- PROscorerTools::makeFakeData(n = 10, nitems = 24, prefix = "cx", values = 1:4)
qlq_cx24(dat, items = 1:24)
}
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