Important differences and meaningful changes for the Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog)

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Abstract

Background

We estimated clinically important, group-level differences in self-reported cognitive function for the Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog) instrument. We also investigated individual level change that could be considered meaningful for cancer survivors affected by cognitive impairment following chemotherapy, and that could be used for responder analyses. We used data from a multi-site randomized controlled trial in 242 participants that evaluated a web-based intervention for improving self-reported cognitive functioning in adult cancer survivors who reported cognitive impairment and who had adjuvant chemotherapy in the previous 6–60 months. We used anchor and distribution methods to estimate a range of clinically important differences (CIDs) and investigated meaningful change thresholds (MCTs) for the FACT-Cog and the Perceived Cognitive Impairments (PCI) subscale, post-intervention and at six-month follow-up with empirical cumulative distribution functions. Our primary anchor was the patient reported cognitive function subscale of the European Organization for Research and Treatment of Cancer Quality of Life-Cognitive Functioning Scale (EORTC-CF).

Results

Most participants were female (95%) breast cancer survivors (89%). Correlation of changes in the FACT-Cog and the EORTC-CF were 0.55 post-intervention and 0.61 at follow-up. Anchor-based CID estimates for the FACT-Cog using our primary anchor were 11.3 points (post) and 8.8 (follow-up), which corresponds to a standardized effect size of 0.49 and 0.38; 8.6% and 6.6% of the total scale’s range. Anchor-based CID estimates for the FACT-Cog PCI subscale were 7.4 (post) and 4.6 points (follow-up), which corresponds to a standardized effect size of 0.50 and 0.31; 10.3% and 6.4% of the PCI range). Empirical cumulative distribution functions of change in FACT-Cog demonstrating possible MCTs showed that anchor change of none, minimally better and much better were well separated.

Conclusions

The CID and MCT estimates from this manuscript can help in the design, analysis and interpretation of self-reported cognitive function in cancer patients and survivors.

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Most cited references 22

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Further evidence supporting an SEM-based criterion for identifying meaningful intra-individual changes in health-related quality of life.

K Wyrwich, W Tierney, F D Wolinsky (1999)

This study used the standard error of measurement (SEM) to evaluate intra-individual change on both the Chronic Respiratory Disease Questionnaire (CRQ) and the SF-36. After analyzing the reliability and validity of both instruments at baseline among 471 COPD outpatients, the SEM was compared to established minimal clinically important difference (MCID) standards for three CRQ dimensions. A value of one SEM closely approximated the MCID standards for all CRQ dimensions. This SEM-based criterion was then validated by cross-classifying the change status (improved, stable, or declined) of 393 follow-up outpatients using the one-SEM criterion and the MCID standard. Excellent agreement was achieved for all three CRQ dimensions. Although MCID standards have not been established for the SF-36, the one-SEM criterion was explored in these change scores. Among SF-36 scales demonstrating acceptable reliability and reasonable variance, the percent of individuals within each change category was consistent with those seen in the CRQ dimensions. These results replicate previous findings where a value of one SEM also closely approximated MCIDs for all dimensions of the Chronic Heart Disease Questionnaire among cardiovascular outpatients. The one-SEM criterion should be explored in other health-related quality of life instruments with established MCIDs.

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Handling missing data in RCTs; a review of the top medical journals

Melanie L Bell, Mallorie Fiero, Nicholas J Horton … (2014)

Background Missing outcome data is a threat to the validity of treatment effect estimates in randomized controlled trials. We aimed to evaluate the extent, handling, and sensitivity analysis of missing data and intention-to-treat (ITT) analysis of randomized controlled trials (RCTs) in top tier medical journals, and compare our findings with previous reviews related to missing data and ITT in RCTs. Methods Review of RCTs published between July and December 2013 in the BMJ, JAMA, Lancet, and New England Journal of Medicine, excluding cluster randomized trials and trials whose primary outcome was survival. Results Of the 77 identified eligible articles, 73 (95%) reported some missing outcome data. The median percentage of participants with a missing outcome was 9% (range 0 – 70%). The most commonly used method to handle missing data in the primary analysis was complete case analysis (33, 45%), while 20 (27%) performed simple imputation, 15 (19%) used model based methods, and 6 (8%) used multiple imputation. 27 (35%) trials with missing data reported a sensitivity analysis. However, most did not alter the assumptions of missing data from the primary analysis. Reports of ITT or modified ITT were found in 52 (85%) trials, with 21 (40%) of them including all randomized participants. A comparison to a review of trials reported in 2001 showed that missing data rates and approaches are similar, but the use of the term ITT has increased, as has the report of sensitivity analysis. Conclusions Missing outcome data continues to be a common problem in RCTs. Definitions of the ITT approach remain inconsistent across trials. A large gap is apparent between statistical methods research related to missing data and use of these methods in application settings, including RCTs in top medical journals. Electronic supplementary material The online version of this article (doi:10.1186/1471-2288-14-118) contains supplementary material, which is available to authorized users.

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Combining distribution- and anchor-based approaches to determine minimally important differences: the FACIT experience.

Kathleen Yost, David Eton (2005)

Health-related quality of life (HRQOL) is an important endpoint in cancer clinical trials and in cancer treatment in general; however, the meaningfulness of HRQOL scores may not be apparent to clinicians or researchers. Minimally important differences (MIDs) can enhance the interpretability of HRQOL scores by identifying differences likely to be meaningful to patients and clinicians. This article's objective is to describe and provide examples of approaches we have used to identify MIDs for instruments in the Functional Assessment of Chronic Illness Therapy (FACIT) measurement system. Distribution- and anchor-based approaches are described and illustrated. We also discuss the importance of assessing the appropriateness of anchors, and we provide suggestions for combining results into a single range of plausible MIDs. MIDs for FACIT instruments established to date are summarized, and general guidelines that can be used to estimate MIDs for other FACIT instruments are provided. Applications of MIDs in research are illustrated.

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Author and article information

Contributors

M L Bell:

ORCID: http://orcid.org/0000-0003-4821-4094

(520) 626-2795 , melaniebell@email.arizona.edu

H M Dhillon: haryana.dhillon@sydney.edu.au

V J Bray: victoria.bray@health.nsw.gov.au

J L Vardy: janette.vardy@sydney.edu.au

Journal

Journal ID (nlm-ta): J Patient Rep Outcomes

Journal ID (iso-abbrev): J Patient Rep Outcomes

Title: Journal of Patient-Reported Outcomes

Publisher: Springer International Publishing (Cham )

ISSN (Electronic): 2509-8020

Publication date (Electronic): 12 October 2018

Publication date PMC-release: 12 October 2018

Publication date Collection: December 2018

Volume: 2

Electronic Location Identifier: 48

Affiliations

[1 ]ISNI 0000 0001 2168 186X, GRID grid.134563.6, Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, , University of Arizona, ; 1295 N Martin Ave, Tucson, AZ 85724 USA

[2 ]ISNI 0000 0004 1936 834X, GRID grid.1013.3, Psycho-Oncology Co-operative Research Group, School of Psychology, , University of Sydney, ; Sydney, NSW Australia

[3 ]ISNI 0000 0004 1936 834X, GRID grid.1013.3, Centre for Medical Psychology & Evidence-based Decision-making, School of Psychology, , University of Sydney, ; Sydney, NSW Australia

[4 ]ISNI 0000 0004 1936 834X, GRID grid.1013.3, Department of Medical Oncology, , Liverpool Hospital and University of Sydney, ; Sydney, NSW Australia

[5 ]ISNI 0000 0004 1936 834X, GRID grid.1013.3, Concord Cancer Centre and Sydney Medical School, , University of Sydney, ; Sydney, NSW Australia

Author information

M L Bell http://orcid.org/0000-0003-4821-4094

Article

Publisher ID: 71

DOI: 10.1186/s41687-018-0071-4

PMC ID: 6185877

SO-VID: 692443c1-365f-44d2-b3d9-11b64d31fee9

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

History

Date received : 4 August 2017

Date accepted : 21 September 2018

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100000054, National Cancer Institute;

Award ID: P30 CA023074

Funded by: FundRef http://dx.doi.org/10.13039/501100001102, Cancer Council NSW;

Funded by: Friends of the Mater

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Keywords: oncology,cancer,chemotherapy,cognitive impairment,quality of life,minimal clinically important difference,fact-cog,responder,clinically important difference,cumulative distribution function

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Keywords: oncology, cancer, chemotherapy, cognitive impairment, quality of life, minimal clinically important difference, fact-cog, responder, clinically important difference, cumulative distribution function

Important differences and meaningful changes for the Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog)

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Karger: Oncology

Most cited references 22

Further evidence supporting an SEM-based criterion for identifying meaningful intra-individual changes in health-related quality of life.

Handling missing data in RCTs; a review of the top medical journals

Combining distribution- and anchor-based approaches to determine minimally important differences: the FACIT experience.

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