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Clinically Meaningful Change and Clinical Relevance of the Functional Assessment of Cancer Therapy-Lung: Analysis of ECOG 5592 Data. David Cella & David T. Eton, Evanston Northwestern Healthcare & Northwestern University Diane L. Fairclough, AMC Cancer Research Center

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Clinically Meaningful Change and Clinical Relevance of the Functional Assessment of Cancer Therapy-Lung: Analysis of ECOG 5592 Data

David Cella & David T. Eton, Evanston Northwestern Healthcare & Northwestern University

Diane L. Fairclough, AMC Cancer Research Center

Philip Bonomi, Rush-Presbyterian St Luke’s Medical Center

David H. Johnson, Vanderbilt University

Anne Heyes, Cheryl Silberman, & Mike Wolf, AstraZeneca


Acknowledgements
Acknowledgements Functional Assessment of Cancer Therapy-Lung: Analysis of ECOG 5592 Data

  • National Cancer Institute (grants CA 23318, CA66636, CA21115, CA 17145, CA 49957)

  • AstraZeneca Pharmaceuticals


What is a clinically meaningful change
What is a (clinically) meaningful change? Functional Assessment of Cancer Therapy-Lung: Analysis of ECOG 5592 Data

  • Meaningful change: A difference or change in score on a health-related quality of life (HRQoL) questionnaire that is important to the involved person or people

  • “Clinically” meaningful corresponds to a clinically important difference or change in patient status.


How are cmcs determined
How are CMCs determined? Functional Assessment of Cancer Therapy-Lung: Analysis of ECOG 5592 Data

  • Anchor-based methods

- Anchoring score differences to

traditional clinical parameters

(e.g., tumor response, time to progression)

  • Distribution-based methods

- Standard deviation

- Standard error of measurement


The present study
The Present Study Functional Assessment of Cancer Therapy-Lung: Analysis of ECOG 5592 Data

  • Purpose: To determine CMCs in two score aggregates of the FACT-L (the Lung Cancer Subscale & the Trial Outcomes Index) in advanced non-small cell lung cancer patients.

  • Data source: Eastern Cooperative Oncology Group study 5592


Sample Characteristics E5592 (N = 573) Functional Assessment of Cancer Therapy-Lung: Analysis of ECOG 5592 Data

  • 63% Female; 37% Male

  • Mean age = 60 years; range = 32-81 years

  • 87% Caucasian; 10% Afric-Am; 3% Other

  • 81% Stage IV; 19% Stage IIIB

  • Baseline Performance Status:

- 68% ECOG 1

- 32% ECOG 0

  • Treatment Arm:

- 34% cisplatin + etoposide

- 33% cisplatin + paclitaxel (high dose) + g-csf

- 33% cisplatin + paclitaxel (std dose)


Hrqol assessment
HRQoL Assessment Functional Assessment of Cancer Therapy-Lung: Analysis of ECOG 5592 Data

  • The Functional Assessment of Cancer Therapy - Lung (FACT-L) Questionnaire

- Physical well-being (PWB) (7 items)

- Social/family well-being (SWB) (7 items)

- Emotional well-being (EWB) (5 items)

- Functional well-being (FWB) (7 items)

- Lung Cancer Subscale (LCS) (7 items)

- Trial Outcome Index (TOI) (21 items)


Hrqol assessment1
HRQoL Assessment Functional Assessment of Cancer Therapy-Lung: Analysis of ECOG 5592 Data

  • The Functional Assessment of Cancer Therapy - Lung Questionnaire (FACT-L)

- Lung Cancer Subscale (LCS): 7 items

- Trial Outcome Index (TOI): 21 items

  • Baseline & 12-week assessments used


- Independent samples t-tests (baseline)

- One-way ANCOVAs on changes in HRQoL

over time (controlling for baseline clinical

factors)

  • Distribution-based methods

- 1/3 and 1/2 standard deviation (SD)

- Standard error of measurement (SEM)

SEM = SD (1 - reliability)1/2

Data Analysis


Mean sd differences in baseline clinical indicators
Mean (SD) differences Functional Assessment of Cancer Therapy-Lung: Analysis of ECOG 5592 Datain baseline clinical indicators



Baseline to 12-week change in (best overall response)Lung Cancer Subscale score(time to progression: < 116 days vs. > 116 days)


Baseline to 12-week change in Trial (best overall response)Outcome Index score (best overall response)

CR/PR > PD


Baseline to 12-week change in (best overall response)Trial Outcome Index score(time to progression: < 116 days vs. > 116 days)


Distribution based criteria of clinical significance
Distribution-based criteria (best overall response)of clinical significance


Summary
Summary (best overall response)

Based on anchor &

distribution-based methods...

  • A 2 to 3 point score difference approximates a CMC on the LCS of the FACT-L

  • A 5 to 6 point score difference approximates a CMC on the TOI of the FACT-L


E5592 shortness of breath higher score corresponds to worse function
E5592 - Shortness of Breath (best overall response)(Higher score corresponds to worse function)

Very

much

Not

at all


E5592 weight loss higher score corresponds to worse function
E5592 - Weight loss (best overall response)(Higher score corresponds to worse function)

Very

much

Not

at all


E5592 good appetite higher score corresponds to better function
E5592 - Good appetite (best overall response)(Higher score corresponds to better function)

Very

much

Not

at all


Practical implications
Practical Implications (best overall response)

  • Determine sample size in clinical trials

  • Evaluate treatment efficacy


Summary1
Summary (best overall response)

  • Baseline HRQL predicts outcome in advanced NSCLC

  • Longitudinal HRQL adds to the prognostic ability of baseline HRQL

  • Physical well-being, functional well-being and pt. reported symptoms are reliable predictors of outcome in advanced NSCLC


Hrql as a predictor of outcome
HRQL as a Predictor of Outcome (best overall response)


The present study1
The Present Study (best overall response)

  • Data source: Eastern Cooperative Oncology Group study 5592

  • Objectives (3)

- Show that HRQL predicts outcome

- Show that changes in HRQL add to the

prediction of outcome

- Show that longitudinal HRQL data have clinical import


Hrqol assessment2
HRQoL Assessment (best overall response)

  • The Functional Assessment of Cancer Therapy - Lung Questionnaire (FACT-L)

- Physical well-being (PWB) (7 items)

- Social/family well-being (SWB) (7 items)

- Emotional well-being (EWB) (5 items)

- Functional well-being (FWB) (7 items)

- Lung Cancer Subscale (LCS) (7 items)

- Trial Outcome Index (TOI) (21 items)

  • Baseline & 6-week assessments used


Outcomes
Outcomes (best overall response)

  • Time to disease progression

  • Survival duration


Data Analysis (best overall response)

  • Spearman correlation ()

  • Cox proportional hazards regression

  • Survival curves


Correlations of baseline hrql outcome
Correlations ( (best overall response)) of Baseline HRQL & Outcome

*** p < .001



Stepwise Cox Regression for Survival (best overall response)


Does change in HRQL predict outcome? (best overall response)


1.0 (best overall response)

.8

.6

.4

.2

0.0

0

200

400

600

800

Time to progression based on Trial Outcome Index scores

-2 Log likelihood = 2940.24

Overall 2 (7) = 67.67, p<.001

Hi baseline - improve

Hi baseline - decline

Proportion not progressing

Lo baseline - improve

Lo baseline - decline

Time to progression in days


Survival duration based on Physical Well-Being scores (best overall response)

-2 Log likelihood = 3058.81

Overall 2 (8) = 67.21, p<.001

Hi baseline - improve

Hi baseline - decline

Proportion surviving

Lo baseline - improve

Lo baseline - decline

Survival post-randomization in days


Summary2
Summary (best overall response)

  • Baseline HRQL predicts outcome in advanced NSCLC

  • Longitudinal HRQL adds to the prognostic ability of baseline HRQL

  • Physical well-being, functional well-being and pt. reported symptoms are reliable predictors of outcome in advanced NSCLC


Practical implications1
Practical Implications (best overall response)

  • Patient stratification in clinical trials

  • Treatment planning & adjustment


Our next step: ALCaMP-2 (best overall response)Real-time (weekly) assessment of all lung cancer patients beginning chemotherapy


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