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Quality of Life in Breast Cancer Survivors: A Latent Growth Analysis

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Title: Quality of Life in Breast Cancer Survivors: A Latent Growth Analysis


1
Quality of Life in Breast Cancer Survivors A
Latent Growth Analysis
  • Lu Jing
  • MS, HPA
  • Joe Vasey, PhD
  • Research Associate, Center for
  • Health Care and Policy Research

2
Breast Cancer in the US
  • Breast cancer is the most common type of cancer
    among women
  • Breast cancer accounts for 31 of new cancer
    cases among women nearly 204,000 cases in 2002
    (ACS, 2002)
  • Other common cancers among women include
  • Lung cancer (12)
  • Colo-rectal cancer (12)
  • Uterine cancer (6)
  • Ovarian cancer (4)
  • 13 of all US women will eventually develop
    breast cancer
  • Breast cancer is survivable, and the probability
    of surviving is improving (ACS, 2002)
  • 1974 5-year survival rate was 75
  • 1992 5-year survival rate was 86
  • 5-year survival is strongly related to stage at
    diagnosis
  • Local (Stage I) 96
  • Regional (Stage II) 78
  • Distant (Stage III) 21

3
Quality of Life
  • The increased probability of surviving cancer has
    led to greater interest in survivors lives after
    diagnosis and treatment.
  • After treatment survivors may experience a
    variety of physical and psychological problems
  • Quality of Life (QoL) is concerned with The
    complete social and psychological being the
    individuals performance of social roles, her
    mental acuity, her emotional state, her sense of
    well being, and her relationship with others.
    (Levine, 1987)
  • Multidimensional .
  • Physical well-being the control, coping, or
    relief of physical symptoms and the maintenance
    of function and independence
  • Psycho-social - Maintenance of a sense of
    control, cognitive and emotional functioning,
    roles, and relationships with others in a variety
    of settings
  • Spiritual the maintenance of a sense of hope,
    meaningfulness, and purpose to life

4
Quality of Life Research
  • Cross-sectional studies at a single point in
    time, what associations exist between QoL
    measures and various surivivor characteristics
    (demographic, medical, etc)?
  • Longitudinal studies over a period of time,
    what changes occur in QoL measures, and what
    accounts for these changes?

5
Summary of FindingsQoL Level
6
Summary of FindingsChange in QoL
  • Poorly studied 5 studies
  • All rely on mean QoL levels across time
  • Conflicting findings
  • Maximum physical and psychological QoL achieved
    1-2 years after treatment. QoL measures declined
    in 2nd and 3rd years
  • Highest physical and psychological QoL occurred
    in 2nd through 5th year after treatment. Lower
    levels were observed immediately after treatment
    and long term (5 years)

7
Purpose
  • Address shortfalls in existing research
  • Describe and model individual trajectories in
    QoL, rather than mean differences across time
  • Identify predictors of change in QoL
  • Address limitations of traditional analytic
    methods
  • Recognize that observed scores are not true
    scores (measurement error)
  • Account for varying temporal points of
    observation across participants
  • Account for time-varying covariates
  • Maximize the use of available data

8
Method
  • Sample
  • Part of a larger observational study of 1763
    cancer survivors
  • 25-62 years of age at time of diagnosis
  • Stage I, II, or III
  • 1st diagnosis between January 1997 and December
    1999.
  • Data collection began in the fall of 2000, so at
    the time of their first interview survivors were
    between 1 to nearly 5 years post-diagnosis.

9
Timing of Data Collection
Time frame covered by four annual interviews was
determined by time since diagnosis at the time of
the first interview
W1 W2 W3 W4
W1 W2 W3 W4
W1 W2 W3 W4
W1 W2 W3 W4
1 2 3 4
5 6 7 8
Years since diagnosis
10
Sample Characteristics
  • 405 out of 550 breast cancer survivors completed
    all four interviews
  • Average age at diagnosis 52.4
  • 15 under 45, 50 45-55, 35 over 55
  • Average time between diagnosis and 1st interview
    2.7 years
  • Race Predominantly white (94)
  • Education
  • 2 less than HS, 31 HS, 25 some college, 20
    college, 22 post college
  • Cancer stage at diagnosis
  • 50 Stage I, 44 Stage II, 6 Stage III
  • Recurrance of cancer 20
  • Treatment Status at 1st interview
  • 77 not in treatment, 7 in treatment for active
    cancer, 16 in treatment but no active cancer
  • Other conditions
  • 61 reported 1 or more chronic conditions
  • Marital Status
  • 84 married or living with a partner
  • Employment
  • 59 were working at all four interviews
  • 25 were working intermittently

11
Measures
  • Quality of Life
  • SF-12 Physical and Mental Scores
  • Demographic
  • Age, race, education, marital status, employment
    status, home ownership
  • Medical
  • Stage at diagnosis, recurrance, treatment status,
    presence of chronic health conditions
  • Time
  • Time since diagnosis

12
Analysis Plan
  • Latent growth modeling
  • Unconditional means model does variation in QoL
    measures exist, and is it sufficient to warrant
    further analysis?
  • Unconditional latent growth model to what extent
    does time account for significant variability in
    QoL among participants?
  • Conditional latent growth model to what extent
    do demographic and medical/health covariates
    account for significant variability?

13
Unconditional Means Model
  • Significant within-person variance and
    between-person variance for both physical and
    mental QoL measures
  • Within Individuals QoL changed over time
  • Between Individuals differed from one another
  • Significant variability exists, some of which may
    be may be explainable by time from diagnosis.

14
Individual SF-12 Trajectories
15
Change in Mean SF-12 Scores
16
Unconditional Latent Growth Model
plt.1, plt.05, plt.001
  • Significant within person variance in both
    physical and mental QoL suggest that
  • survivors deviate significantly from their
    predicted trajectories
  • Significant variability exists for both initial
    status and rate of change for both
  • measures
  • substantive covariates are needed to explain
    further individual differences.

17
?0 initial status (intercept) D1 variance in
initial status ?1 rate of change (slope) D2
variance in rate of change Yi QoL at time I Ti
individually varying point in time
Covariates
18
Latent Growth Model with Covariates
plt.1, plt.05, plt.001
  • Physical QoL negative but non-significant rate
    of change
  • Mental QoL positive but non-significant rate of
    change
  • both measures Variance in initial status and
    rate of change declined compared to
  • the unconditional model, indicating covariates
    have some explanatory power
  • negative covariance survivors with higher
    levels of QoL 1 year after diagnosis
  • experienced lower rate of change in QoL over
    time

19
ML Estimates For Effects of Covariates Physical
QoL
plt.1, plt.05, plt.001
20
Summary Physical QoL
Negative significant covariance suggests that
survivors with better initial QoL Experienced
smaller rates of change over time.
21
ML Estimates For Effects of Covariates Mental
QoL
plt.1, plt.05, plt.001
22
Summary Mental QoL
Negative significant covariance suggests that
survivors with better initial QoL experienced
smaller rates of change over time.
23
Summary
  • Mean (group) physical and mental QoL measures are
    stable over time
  • Significant individual differences exist in
    change trajectories over time
  • Diverse trajectory patterns point to the need to
    better understand the process of QoL development
    and change over time
  • Investigation of additional covariates is needed
    to explain the heterogeneity in individuals
    initial status and rates of change

24
Limitations
  • Sample homogeneity
  • Race (largely white)
  • Geographic location (largely rural)
  • Alternative QoL measures
  • Is the SF-12 too general a measure for the issues
    confronting this sample?
  • Breast cancer specific instruments?
  • Additional (currently unidentified) covariates
  • Longer term changes (8 years)
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