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Comparing longitudinal assessments of quality of life by patient and parent in newly diagnosed children with cancer: the value of both raters’ perspectives

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Abstract

Purpose

Health-related quality of life (HRQoL) information from children facing rare and/or life-threatening disease serves important clinical functions. Longitudinal HRQoL ratings from 222 child–parent dyads collected at four time points during the first 16 weeks of cancer treatment are presented. Patient and parent HRQoL reports at the domain level, based on the Pediatric Quality of Life Inventory™ 4.0 Generic Core Scales, were compared over time, and variation in child/parent agreement by age, treatment intensity, and time on treatment was explored.

Patients and methods

Analyses included consideration of missingness, differences between child and parent group mean domain scores averaged over assessments, agreement between individual child and parent, compared to group averages, and within-subject changes between assessments.

Results

Children consistently reported higher functioning than their parents with differences varying by child age and HRQoL domain and diminishing over time. No differences were found by intensity of treatment. The between-subject correlation ranged from 0.61 (social functioning) to 0.86 (physical functioning) across time. Agreement within groups, defined by age, treatment intensity, and time were generally similar.

Conclusions

Results indicate moderate-to-good child/parent agreement with variability by domain of HRQoL. Findings underscore the complexity of self- and proxy-based report and support the use of information from both raters.

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Acknowledgments

The authors express sincere appreciation to the patients, their parents, and the investigators of the parent trial; Drs. Bassem I. Razzouk, Jeffrey D. Hord, Marilyn Hockenberry, James Feusner, Denise Williams, and Wayne R. Rackoff; as well to Helen Varsos, MS, RPh, Ortho Biotech Clinical Affairs LLC. We also appreciate the permission from Ortho Biotech Clinical Affairs LLC for granting us access to the data set used for this study. This work was funded in part by Ortho Biotech.

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Correspondence to Susan K. Parsons.

Appendix

Appendix

The longitudinal data for each domain were modeled as follows: \( Y_{oit} = \mu_{ot} + \delta_{oi} + \varepsilon_{oit} \) where i indicates the ith child, o indicates whether the observer is the child (c) or parent (p), and t indicates the tth assessment. The between-subject random effects and within-subject residual errors were allowed to be correlated between the child and parent, \( {\text{Cov}}(\delta_{ci} ,\delta_{pi} ) = \varsigma_{cp} \)and\( {\text{Cov}}(\varepsilon_{cit} ,\varepsilon_{pit} ) = \sigma_{cp} \)but otherwise the errors were independent, \( {\text{Cov}}(\delta_{oi} ,\varepsilon_{oit} ) = 0. \)

The SAS code to generate the means and variance parameters is as follows:

proc mixed data=work.mixed method=ml covtest;

  class pid observer visit;

  model (outcome_specified_here)=observer*visit/noint solution;

  random observer/subject=pid type=un;

  repeated observer/subject=pid (visit) type=un;

  where (specifics_for_subgroups);

run;

This will generate 6 variance parameters that correspond to the output as:

 

\( \varsigma_{c}^{2} \)

UN (1,1)

PID

\( \varsigma_{cp} \)

UN (2,1)

PID

\( \varsigma_{p}^{2} \)

UN (2,2)

PID

\( \sigma_{c}^{2} \)

UN (1,1)

PID (visit)

\( \sigma_{cp} \)

UN (2,1)

PID (visit)

\( \sigma_{p}^{2} \)

UN (2,2)

PID (visit)

The correlation of the two between-observer components are calculated as \( \varsigma_{cp} /\sqrt {\varsigma_{c}^{2} \varsigma_{p}^{2} } \) for between-subject variation and \( \sigma_{cp} /\sqrt {\sigma_{c}^{2} \sigma_{p}^{2} } \) for within-subject variation.

The interclass correlations are calculated as \( \varsigma_{o}^{2} /\left( {\varsigma_{o}^{2} + \sigma_{o}^{2} } \right). \)

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Parsons, S.K., Fairclough, D.L., Wang, J. et al. Comparing longitudinal assessments of quality of life by patient and parent in newly diagnosed children with cancer: the value of both raters’ perspectives. Qual Life Res 21, 915–923 (2012). https://doi.org/10.1007/s11136-011-9986-4

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  • DOI: https://doi.org/10.1007/s11136-011-9986-4

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