Interpreting Within-Patient Changes on the EORTC QLQ-C30 and EORTC QLQ-LC13

Cheryl D Coon, Michael Schlichting, Xinke Zhang, Cheryl D Coon, Michael Schlichting, Xinke Zhang

Abstract

Introduction: When determining if changes on patient-reported outcome (PRO) scores in clinical trials convey a meaningful treatment benefit, statistical significance tests alone may not communicate the patient perspective. Appraising within-patient changes on PRO scores against established thresholds can determine if improvements or deteriorations experienced by individuals are meaningful. To evaluate the appropriateness of thresholds for interpreting meaningful improvements and deterioration within individuals on the European Organisation for Research and Treatment of Cancer (EORTC) 30-item core instrument (QLQ-C30) and 13-item lung cancer module (QLQ-LC13), a series of psychometric methods were applied to data from a phase III randomized controlled clinical trial in non-small cell lung cancer.

Methods: Anchor-based methods of empirical cumulative distribution functions and classification statistics were employed using change scores from Baseline to Week 7 using changes on the QLQ-C30 Global Health Status item as an anchor. Distribution-based methods of one-half standard deviation and standard error of measurement identified the minimum amount of change each domain score can reliably measure.

Results: While the correlations between the domain scores and the anchor item were modest in size (i.e., r ≥ 0.30 for only 5 of 24 domains), consideration of multiple methods along with the magnitude of possible step changes on the score allowed for patterns to emerge. The triangulation process planned a priori resulted in different methods being the source for different domain scores. Absolute values of the proposed thresholds ranged from 11.11 to 33.33, and all resulted in the same classifications for all EORTC domains, except QLQ-C30 Fatigue, as would the 10-point threshold that is traditionally used.

Conclusion: This study confirms the appropriateness of the 10-point EORTC score threshold generally used by the field for interpreting within-patient changes, but the thresholds proposed from this study enhance interpretability by corresponding to only observable locations along the domain score scale.

Trial registration: ClinicalTrials.gov NCT02395172.

Conflict of interest statement

Cheryl D. Coon is an employee of Outcometrix and received funding for this psychometric analysis from EMD Serono Research & Development Institute, Inc., Billerica, MA, USA, an affiliate of Merck KGaA (CrossRef Funder ID: 10.13039/100004755). Michael Schlichting is an employee of Merck Healthcare KGaA, Darmstadt, Germany. Xinke Zhang is an employee of EMD Serono Research & Development Institute, Inc., Billerica, MA, USA, an affiliate of Merck KGaA.

© 2022. The Author(s).

Figures

Fig. 1
Fig. 1
ECDFs of change on key EORTC domain scores and change on Global Health Status from Baseline to Week 7 (anchor group sample sizes indicated in parentheses). ECDF empirical cumulative distribution function, EORTC European Organisation for Research and Treatment of Cancer, QLQ-C30 30-item core instrument, QLQ-LC13 13-item lung cancer module
Fig. 2
Fig. 2
Classification statistics for improvement on key EORTC domain scores anchored on a two-category improvement on Global Health Status from Baseline to Week 7. EORTC European Organisation for Research and Treatment of Cancer, NPV negative predictive value, PPV positive predictive value, QLQ-C30 30-item core instrument, QLQ-LC13 13-item lung cancer module
Fig. 3
Fig. 3
Classification statistics for deterioration on key EORTC domain scores anchored on a two-category deterioration on Global Health Status from Baseline to Week 7. EORTC European Organisation for Research and Treatment of Cancer, NPV negative predictive value, PPV positive predictive value, QLQ-C30 30-item core instrument, QLQ-LC13 13-item lung cancer module

References

    1. US FDA Guidance for industry on patient-reported outcome measures: Use in medical product development to support labeling claims. Fed Reg. 2009;74(235):65132–65133.
    1. Fiero MH, Roydhouse JK, Vallejo J, King-Kallimanis BL, Kluetz PG, Sridhara R. US Food and Drug Administration review of statistical analysis of patient-reported outcomes in lung cancer clinical trials approved between January, 2008, and December, 2017. Lancet Oncol. 2019;20(10):e582–e589. doi: 10.1016/S1470-2045(19)30335-3.
    1. Xalkori [package insert]. New York, NY: Pfizer, Inc.; 2021.
    1. Aaronson NK, Ahmedzai S, Bergman B, Bullinger M, Cull A, Duez NJ, et al. The European Organisation for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst. 1993;85:365–376. doi: 10.1093/jnci/85.5.365.
    1. Bergman B, Aaronson NK, Ahmedzai S, Kaasa S, Sullivan M. The EORTC QLQ-LC13: a modular supplement to the EORTC core quality of life questionnaire (QLQ-C30) for use in lung cancer clinical trials. Euro J Cancer. 1994;30(5):635–642. doi: 10.1016/0959-8049(94)90535-5.
    1. Osoba D, Rodrigues G, Myles J, Zee B, Pater J. Interpreting the significance of changes in health-related quality-of-life scores. J Clin Oncol. 1998;16(1):139–144. doi: 10.1200/JCO.1998.16.1.139.
    1. Cocks K, King MT, Velikova G, Fayers PM, Brown JM. Quality, interpretation and presentation of European organization for research and treatment of cancer quality of life questionnaire core 30 data in randomized controlled trials. Eur J Cancer. 2008;44:1793–1798. doi: 10.1016/j.ejca.2008.05.008.
    1. King MT. The interpretation of scores from the EORTC quality of life questionnaire QLQ-C30. Qual Life Res. 1996;5:555–567. doi: 10.1007/BF00439229.
    1. Maringwa JT, Quinten C, King M, Ringash J, Osoba D, Coens C, et al. Minimal important differences for interpreting health-related quality of life scores from the EORTC QLQ-C30 in lung cancer patients participating in randomized controlled trials. Support Care Cancer. 2011;19(11):1753–1760. doi: 10.1007/s00520-010-1016-5.
    1. Koller M, Musoro JZ, Tomaszewski K, Coens C, King MT, Sprangers MAG, et al. Minimally important differences of EORTC QLQ-C30 scales in patients with lung cancer or malignant pleural mesothelioma - Interpretation guidance derived from two randomized EORTC trials. Lung Cancer. 2022;167:65–72. doi: 10.1016/j.lungcan.2022.03.018.
    1. Kluetz PG, Slagle A, Papadopoulos EJ, Johnson LL, Donoghue M, Kwitkowski VE, et al. Focusing on core patient-reported outcomes in cancer clinical trials: symptomatic adverse events, physical function, and disease-related symptoms. Clin Cancer Res. 2016;22:1553–1558. doi: 10.1158/1078-0432.CCR-15-2035.
    1. Roy UB, King-Kallimanis BL, Kluetz PG, Selig W, Ferris A. Learning from patients: reflections on use of patient-reported outcomes in lung cancer trials. J Thorac Oncol. 2018;13(12):1815–1817. doi: 10.1016/j.jtho.2018.09.003.
    1. US FDA. Voice of the patient. A series of reports from the U.S. Food and Drug Administration’s (FDA’s) Patient-Focused Drug Development Initiative. Lung Cancer. 2013. . Accessed 9 Nov 2021.
    1. Barlesi F, Vansteenkiste J, Spigel D, Ishii H, Garassino M, de Marinis F, et al. Avelumab versus docetaxel in patients with platinum-treated advanced non-small-cell lung cancer (JAVELIN Lung 200): an open-label, randomised, phase 3 study. Lancet Oncol. 2018;19(11):1468–1479. doi: 10.1016/S1470-2045(18)30673-9.
    1. Gralla RJ, Coon C, Taylor F, et al. Evaluation of disease-related symptoms in patients with advanced squamous non-small cell lung cancer treated with nivolumab or docetaxel. J Thorac Oncol. 2015;10(9):S233–S234.
    1. Barlesi F, Garon E, Kim DW, et al. Assessment of health-related quality of life (HRQoL) in KEYNOTE-010: a phase 2/3 study of pembrolizumab vs docetaxel in patients with previously treated advanced NSCLC. Ann Oncol. 2016;27(Suppl 6):1219P.
    1. Bedard G, Zeng L, Zhang L, Lauzon N, Holden L, Tsao M, et al. Minimal important differences in the EORTC QLQ-C30 in patients with advanced cancer. Asia-Pac J Clin Oncol. 2014;10(2):109–117. doi: 10.1111/ajco.12070.
    1. Revicki D, Hays RD, Cella D, Sloan J. Recommended methods for determining responsiveness and minimally important differences for patient-reported outcomes. J Clin Epidemiol. 2008;61(2):102–109. doi: 10.1016/j.jclinepi.2007.03.012.
    1. US Fda. Patient-focused drug development: select, develop or modify fit-for-purpose clinical outcome assessments. Fed Reg. 2018;83(156):40057–40059.
    1. Coon CD, Cook KF. Moving from significance to real-world meaning: methods for interpreting change in clinical outcome assessment scores. Qual Life Res. 2017;27:33–40. doi: 10.1007/s11136-017-1616-3.
    1. Norman GR, Sloan JA, Wyrwich KW. Interpretation of changes in health-related quality of life: the remarkable universality of half a standard deviation. Med Care. 2003;41(5):582–592. doi: 10.1097/01.MLR.0000062554.74615.4C.
    1. Wyrwich KW, Tierney WM, Wolinsky FD. Further evidence supporting an SEM-based criterion for identifying meaningful intra-individual changes in health-related quality of life. J Clin Epidemiol. 1999;52(9):861–873. doi: 10.1016/S0895-4356(99)00071-2.
    1. Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med. 2016;15(2):155–163. doi: 10.1016/j.jcm.2016.02.012.
    1. Beaumont J, Yu H, Lin HM, Goodman E, Hecht S, Le K, et al. Estimation of meaningful change thresholds for the EORTC QLQ-C30 and QLQ-LC13 inpatients with ALK+ non-small cell lung cancer (NSCLC). Poster presented at the 28th Annual Conference of the International Society for Quality of Life Research; October 2021.
    1. IQWiG. General Methods Version 6.0 of 5 November 2020. . Accessed 27 Jan 2022.

Source: PubMed

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