qlq_pan26: Score the EORTC QLQ-PAN26 Quality of Life Questionnaire

In raybaser/PROscorer: Functions to Score Commonly-Used Patient-Reported Outcome (PRO) Measures and Other Psychometric Instruments

Score the EORTC QLQ-PAN26 Quality of Life Questionnaire

Description

Scores the European Organization for Research and Treatment of Cancer (EORTC) QLQ-PAN26 Pancreatic Cancer Module. (Experimental: This function was written quickly... please hand score 1 or 2 patients and check for accuracy)

Usage

qlq_pan26(df, items = NULL, keepNvalid = FALSE)

Arguments

df	A data frame containing responses to the 26 QLQ-PAN26 items, and possibly other variables.
items	A character vector with the QLQ-PAN26 item names, or a numeric vector indicating the column numbers of the QLQ-PAN26 items in df. If items is omitted, then qlq_PAN26 will assume that df contains ONLY the QLQ-PAN26 items and no other variables. See Details for more information.
keepNvalid	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.

Details

This function returns a total of 17 different scores from the EORTC QLQ-PAN26. Scores are calculated according to the official scoring algorithms from the EORTC. At the time this scoring function was written (April 2022), the QLQ-PAN26 had completed Phase 3 testing; however, the official scoring instructions from the EORTC warned that this scaling structure is still preliminary and may change in the future.

In addition to the name of your data frame containing the QLQ-PAN26 item responses (df), you need to tell the function how to find the variables that correspond to the QLQ-PAN26 items in df. You can do this in 1 of 2 ways:

1. 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 26 QLQ-PAN26 items in order starting with the 11th variable, then you could use items = 11:36.

2. The second way only applies if your data frame (df) contains ONLY the 26 variables corresponding to the 26 QLQ-PAN26 items, in order, with no other non-QLQ-PAN26 variables. In this case, you can just use the df argument and omit items.

Value

A data frame with all 17 of the QLQ-PAN26 scores is returned. Of the 17 scores, 15 are Symptom Scales and 2 are Functional Scales (see below). Of the 15 Symptom Scales, 10 are based on a single item each. 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)

• PAN_PP - Pancreatic pain (from 4 items)

• PAN_BF - Bloating (from 1 item)

• PAN_DS - Digestive symptoms (from 2 items)

• PAN_TA - Taste (from 1 item)

• PAN_ID - Indigestion (from 1 item)

• PAN_FL - Flatulence (from 1 item)

• PAN_WL - Weight loss (from 1 item)

• PAN_WE - Weakness arms and legs (from 1 item)

• PAN_DM - Dry mouth (from 1 item)

• PAN_LI - Hepatic symptoms (from 2 items)

• PAN_BO - Altered bowel habit (from 2 items)

• PAN_BI - Body image (from 2 item)

• PAN_SE - Troubled with side-effects(from 1 item)

• PAN_FU - Future Worries (from 1 item)

• PAN_PL - Planning of activities (from 1 item)

Functional Scales (higher is better functioning)

• PAN_SA - Satisfaction with health care (from 2 items)

• PAN_SX - Sexuality (from 2 items)

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).

How Missing Data is Handled

The qlq_PAN26 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.

Note

As of April 15, 2022, there is an error in the official PAN26 scoring instructions from the EORTC. The first page of the official PAN26 scoring instructions from the EORTC indicates that the two items comprising the SA (Satisfaction with health care) functional scale should be reverse scored. In the instructions, these two items are numbered as 53 and 54. However, the second page of the instructions indicates items 55 and 56 should be reversed (see bullet, "(1) Raw score" in the "Principle for scoring" subsection). Items 55 and 56 comprise the SX (Sexuality) functional scale. The items that need to be reversed are the SX items (55 and 56), NOT the SA items (not 53 and 54). This function correctly reverses the SX items instead of the SA items.

References

Fitzsimmons D, Johnson CD, George S, et al. Development of a disease specific quality of life (QoL) questionnaire module to supplement the EORTC core cancer QoL questionnaire, the QLQ-PAN26 in patients with pancreatic cancer. Eur. J. Cancer 35: 939-941, 1999.

Examples

## Not run: 
dat <- PROscorerTools::makeFakeData(n = 10, nitems = 26, prefix = "pan", values = 1:4)
qlq_pan26(dat, items = 1:26)

## End(Not run)

raybaser/PROscorer documentation built on Oct. 17, 2023, 8:48 p.m.