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Journal Club for Analysis of Complex Datasets

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Objective: evaluate effects of ginseng use on breast cancer survival & survivors' ... All ginseng users received mainstream tx: ... – PowerPoint PPT presentation

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Title: Journal Club for Analysis of Complex Datasets


1
Journal Club for Analysis of Complex Datasets
  • Cui Y, Shu X-O, Gao Y-T, Cai H, Tao M-H, Zheng W.
    Assocation of ginseng use with survival and
    quality of life among breast cancer patients.
  • Am J Epidemiol 2006 163 645-653.

2
Summary
  • Objective evaluate effects of ginseng use on
    breast cancer survival survivors QOL.
  • Design cohort study.
  • Setting Shanghai Breast Cancer Study.
  • Population-based case-control study.
  • Subjects women aged 25-64 years w/ newly
    diagnoses breast cancer Aug1996 Mar1998
    (N1455).
  • Cases from Shanghai Study.
  • Followed through Dec2002.

3
Summary (2)
  • In-person interviews conducted 66 days post-dx.
  • Exposure ginseng use.
  • Type, duration, frequency of use.
  • Outcome
  • Overall survival.
  • Disease-free survival.
  • QOL.
  • Assessed during in-person follow-up interviews
    for 1065 of 1248 surviving patients.
  • Sociodemographic, medical, other CAM info
    collected as well.

4
Analysis
  • Overall survival disease-free survival
  • Kaplan-Meier plots log-rank tests.
  • Proportional hazards regression.
  • Adjusted for age, education, income, stage of
    disease, estrogen progesterone receptor status,
    std cancer txs.
  • QOL
  • Linear regression.
  • Adjusted for age, marital status, education,
    income, menopausal status, recurrence of disase,
    time since cancer dx, use of other CAM.

5
Results Survival
  • Ginseng use
  • 398 (27.4) regular use.
  • 1057 (72.6) nonusers (never used before cancer
    dx).
  • All ginseng users received 1 mainstream tx.

6
Overall Survival
7
Disease-Free Survival
8
Results Survival
9
Results QOL
  • Ginseng use
  • Before/after dx
  • Never use before or after.
  • Use before but not after.
  • Use after but not before.
  • Use both before after.
  • Ever/current use after dx.
  • Cumulative use by current users.

10
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11
Strengths
  • Large population-based sample.
  • Excellent participation rate.
  • All ginseng users received mainstream tx
  • provides well-defined sample to evaluate ginseng
    as complementary rather than alternative therapy.
  • Differentiate between types of ginseng use
  • Red (hot) used for short periods.
  • White Asian American (cold) used for longer
    periods.

12
Strengths (2)
  • QOL
  • Assessed timing of ginseng use (before/after dx).
  • Assessed ever/current use
  • Ever users quit using ginseng?
  • Placebo/healthy user effect for current users?
  • Assessed dose-response.
  • caution is required in interpreting the
    resultsfindings need to be confirmed in more
    rigorous and randomized clinical trials.

13
Limitations
  • Lack of info on ginseng use after dx for patients
    who died before follow-up interview.
  • Unable to exclude confounding by other CAM.
  • Self-reported data potential recall
    self-report bias.
  • Could not evalute methods of ginseng use.

14
Suggestions Survival
  • Time-dependent ginseng use (eg, QOL analysis).
  • Account for timing of cancer tx.
  • Adjustment for other healthy patient factors
    possibly associated with ginseng?
  • Trend analyses of categorized continuous measures
    (eg, cumulative ginseng use)?

15
Suggestions QOL
  • lack of ginsengs effect on physical well-being
    obsrved in this study may be due to the fact that
    patients had already fully recovered physically
    by the time the survey was conducted.
  • Time-dependent analysis of ginseng use physical
    state.
  • Authors state need to further study effect of
    ginseng on physical well-being at earlier time
    points.

16
Sensitivity analysis
  • Lin DY, Psaty BM, Kronmal RA. Assessing the
    sensitivity of regression results to unmeasured
    confounders in observational studies. Biometrics
    1998 54 948-963.
  • Assess effect of unmeasured binary or normal
    confounder.
  • For binary confounder, effect is function of
    prevalence effect among E/E- groups.

17
Survival Binary Unmeasured Confounder (U)
  • where
  • ? log(HR(E)) when U unobserved
  • ? log(HR(E)) when U observed
  • ?0 logHR(UE-)
  • ?1 logHR(UE)
  • P0 Pr(UE-)
  • P1 Pr(UE)

18
Sensitivity AnalysisOverall Survival, Any
Ginseng, HR(U) 2.0
19
Sensitivity AnalysisDisease-Free Survival, Any
Ginseng, HR(U)2.0
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