Apparently the one that is in the EORTC manual is not working in SPSS 22. and I could not find any solution in internet. I would appreciate if you help me to deal with it.
Hi Everyone,
Below is an SPSS SYNTAX for computing the QLQ-C30 And the QLQ-BR23 quality of life questionnaires that look at general and breast cancer patients specific quality of life , with an demo for functional and symptom sub-scales with an SPSS COMMAND .
Ahead of the time, use the same names for variables we had used to grantee you get correct results that fit with the syntax, otherwise you could get hair pulling experience like we had . They are a truly complicated two scales-with regards to scaling and re-scaling, Rasch modelling should make it simpler using weighting rather scaling and re-scaling .
The steps for each sub-domain follows two steps:-
1-Step-1: firstly estimate the mean raw scores according to the scoring manual of either QLQ-C30 or QLQ-BR23. Use the means command in the SPSS PROGRAM to achieve all the means of those sub-scales.
2-Step-2: Do the re-scaling into a linearized score ( between 0-100 points) using the formulas dictated by the authors of the scale, below is a demo computation for one functional score, which is physical functioning, and another for the symptoms scores- i did the fatigue score as a demo.
Here we go starting with the Physical functioning score:-
**COMPUTING THE MEAN RAW SCORES FOR PHYSICAL FUNCTIONING SCALE *.
*Note this is a functional scale and is comprised of items 1-5 in QLQ-C30* .
COMPUTE PF2=mean.1(QLQ30_1 TO QLQ30_5).
VARIABLE LABELS PF2 'QOL Physical functioning scale '.
EXECUTE.
***** NOW , WE WILL COMPUTE THE RE-SCALED LINEARIZED VALUE FOR MEAN PHYSICAL FUNCTIONING SCALE INTO A SCORE BETWEEN 0-100 POINTS*.
COMPUTE PF1_RSC1=(1-((PF2-1)/3)) * 100..
VARIABLE LABELS PF1_RSC1 'Re-scaled Physical functioning 1'.
EXECUTE.
******* ==========To compute the Physical symptoms scale, we show A DEMO below for the computation of the mean FATIGUE RAW SCORE, made from items ( 10,12 and 18) , which is a symptom score Not a functional score anyways *** .
COMPUTE FA=mean.2(QLQ30_10 ,QLQ30_12 , QLQ30_18).
VARIABLE LABELS FA ' QOL Fatigue scale-1'.
EXECUTE.
*****Now we're re-scaling the Fatigue score into an linearized 0-100 score*. *Note the formula here is different from functional score estimation method*.
COMPUTE FA_RSC1=((FA-1)/3) * 100.
VARIABLE LABELS FA_RSC1 'Re-scaled fatigue function score'.
EXECUTE.
****copy the formulas for mean scores and for computing the re-scaled scores and apply it to your remaining sub-domains, accounting for the user scoring manual and naming of the variables, the formulas are the same. Keep in mind: functional scales use different formulas than the symptom scales, see above.*
**To compute the overall QOL scores use this formula and apply it to the re-scaled linearized product score Not the raw scores ****.
********************************OVERALL QLQ-30 SCORE BASELINE*.+++++++++++++++++++++++++++++*.
COMPUTE QLQ30_1=(PF1_RSC1+ RF1_RSC1+ SF1_RSC1+ EF1_RSC1+ CF1_RSC1+ 100-fatigue_RSC1+ 100-PA_RSC1+
100-NV_RSC1+ 100-DA_RSC1+ 100-SL_RSC1+ 100-AP2_RSC1+ 100-CO2_RSC1+ 100-DI2_RSC1)/13.
VARIABLE LABELS QLQ30_1 'The overall QLQ-30 Score'.
EXECUTE.
Mohammad
www.hodhodata.com
Dear Mr. Parivash Jamrasi ,
http://www.eortc.be/qol/files/SCManualQLQ-C15-PAL.pdf, in the article there is an email address, maybe they can help you, by contacting him via email, thank you.
Dear Mr. Parivash Jamrasi, I am struggling with the same issue (SPSS 25). Have you been able to find a solution? Thank you very much.
Hi Everyone,
Below is an SPSS SYNTAX for computing the QLQ-C30 And the QLQ-BR23 quality of life questionnaires that look at general and breast cancer patients specific quality of life , with an demo for functional and symptom sub-scales with an SPSS COMMAND .
Ahead of the time, use the same names for variables we had used to grantee you get correct results that fit with the syntax, otherwise you could get hair pulling experience like we had . They are a truly complicated two scales-with regards to scaling and re-scaling, Rasch modelling should make it simpler using weighting rather scaling and re-scaling .
The steps for each sub-domain follows two steps:-
1-Step-1: firstly estimate the mean raw scores according to the scoring manual of either QLQ-C30 or QLQ-BR23. Use the means command in the SPSS PROGRAM to achieve all the means of those sub-scales.
2-Step-2: Do the re-scaling into a linearized score ( between 0-100 points) using the formulas dictated by the authors of the scale, below is a demo computation for one functional score, which is physical functioning, and another for the symptoms scores- i did the fatigue score as a demo.
Here we go starting with the Physical functioning score:-
**COMPUTING THE MEAN RAW SCORES FOR PHYSICAL FUNCTIONING SCALE *.
*Note this is a functional scale and is comprised of items 1-5 in QLQ-C30* .
COMPUTE PF2=mean.1(QLQ30_1 TO QLQ30_5).
VARIABLE LABELS PF2 'QOL Physical functioning scale '.
EXECUTE.
***** NOW , WE WILL COMPUTE THE RE-SCALED LINEARIZED VALUE FOR MEAN PHYSICAL FUNCTIONING SCALE INTO A SCORE BETWEEN 0-100 POINTS*.
COMPUTE PF1_RSC1=(1-((PF2-1)/3)) * 100..
VARIABLE LABELS PF1_RSC1 'Re-scaled Physical functioning 1'.
EXECUTE.
******* ==========To compute the Physical symptoms scale, we show A DEMO below for the computation of the mean FATIGUE RAW SCORE, made from items ( 10,12 and 18) , which is a symptom score Not a functional score anyways *** .
COMPUTE FA=mean.2(QLQ30_10 ,QLQ30_12 , QLQ30_18).
VARIABLE LABELS FA ' QOL Fatigue scale-1'.
EXECUTE.
*****Now we're re-scaling the Fatigue score into an linearized 0-100 score*. *Note the formula here is different from functional score estimation method*.
COMPUTE FA_RSC1=((FA-1)/3) * 100.
VARIABLE LABELS FA_RSC1 'Re-scaled fatigue function score'.
EXECUTE.
****copy the formulas for mean scores and for computing the re-scaled scores and apply it to your remaining sub-domains, accounting for the user scoring manual and naming of the variables, the formulas are the same. Keep in mind: functional scales use different formulas than the symptom scales, see above.*
**To compute the overall QOL scores use this formula and apply it to the re-scaled linearized product score Not the raw scores ****.
********************************OVERALL QLQ-30 SCORE BASELINE*.+++++++++++++++++++++++++++++*.
COMPUTE QLQ30_1=(PF1_RSC1+ RF1_RSC1+ SF1_RSC1+ EF1_RSC1+ CF1_RSC1+ 100-fatigue_RSC1+ 100-PA_RSC1+
100-NV_RSC1+ 100-DA_RSC1+ 100-SL_RSC1+ 100-AP2_RSC1+ 100-CO2_RSC1+ 100-DI2_RSC1)/13.
VARIABLE LABELS QLQ30_1 'The overall QLQ-30 Score'.
EXECUTE.
Mohammad
www.hodhodata.com
One more Notes, if breast cancer patients are subjected to psycological distress and burden from the disease, why waste their time measuring two LONG questionnaires. Many studies have collected the two questionnaires from cancer diagnosed women for the purpose of testing the psychometric properties and validity properties of translated versions or to shorten them , people are following their steps by applying BOTH Scales with out clear point sometimes , when one of the scales could DOES the job of the your specific study aims then use the one that is suitable and useful Not both unless both is what you need , since they are supplementing each other . Many thanks and god bless-My point is to economize with using those measures when they're NOT required.
Mohammad
A third point Not addressed clearly by literature : The QLQ-30 had been subject to many modifications and upgrades to address gaps by its authors ,in particular if we look at QLQ-C30 Items in general they are an echo of the QLQ-BR23 but the QLQ-BR23 is specific to breast cancer affected women , this latter scale however is nominated more often for longitudinal studies as well as RCT's , little is hinted whether the QLQ-C30 is suited for Longitudinal studies however, Not even the authors manual show any CLEAR DETAILS AND DIRECTIONS. see the attached systematic review, clearer information however.
My whole experience is = Confusion machine!
best
Mohammad
Patricia Hamers I ended up with writing the formula in Excel for each category under QLQ-30
Dearest Parivash Jamrasi , Thank you too for your kindness. Parivash Jamrasi
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