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Writing and Reviewing Abstracts

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Writing and Reviewing Abstracts Society for Epidemiologic Research Student Caucus Why is sample B a good abstract? Authors Used active voice and defined acronyms ... – PowerPoint PPT presentation

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Title: Writing and Reviewing Abstracts


1
Writing and Reviewing Abstracts
  • Society for Epidemiologic Research Student
    Caucus

2
What is an abstract?
  • Concise summary of a full scientific research
    project describing the study and its results
  • Abstracts generally include the most important
    aspects of the studys purpose, design, findings,
    and implications

3
What do I include in an abstract?
  • Background and significance
  • Why do we care about the problem and results?
  • Include the importance of your work, challenges
    in this research area, and the potential impact
    of your work
  • Hypothesis
  • What question are you trying to answer?
  • What is the scope of your work?

4
What do I include in an abstract?
  • Methods
  • How did you address your hypothesis?
  • How did you collect your data?
  • What analytic methods did you use?
  • Results
  • What are some characteristics of your data?
  • Sample size
  • Age range
  • Racial breakdown
  • What did you find?
  • Report noteworthy results and findings

5
What do I include in an abstract?
  • Conclusions
  • What are the implications of your study?
  • Are the results generalizable?
  • What is the take home message for the audience?

6
Abstract considerations
  • Stay within the word limit
  • Most journals and conference submissions will not
    accept abstracts that are over the word limit
  • Use active voice and simple sentences
  • Spell out any abbreviations
  • Think of key words for searches and be sure to
    use them in your abstract
  • Have someone else review your abstract before
    submission

7
Example Abstracts
  • Disclaimer Abstract reviews are the opinions of
    the SER-SC Executive Board

8
Sample 1 Home Use of Paints and Petroleum
Products and Risk of Childhood Leukemia
  • Associations between childhood leukemia and
    parental occupational exposures to paints,
    solvents, and other petroleum products have been
    reported, however, little is known about the
    effect of these products when used at home. The
    role of home exposures to paints and petroleum
    products on the risk of childhood leukemia was
    evaluated in the Northern California Childhood
    Leukemia Study (NCCLS), an ongoing
    population-based case-control study. The current
    analyses include 382 incident leukemia cases
    (aged 0-14) enrolled from 1995-2002, and matched
    to 482 controls on age, sex, Hispanic status, and
    maternal race. A detailed history on home use of
    paints and petroleum products, time of exposure,
    and user was collected during an in home
    interview. Exposures were censored one year
    before diagnosis. Conditional logistic regression
    was performed adjusting for annual household
    income. An increased risk of childhood leukemia
    was observed with parental use of paints anytime
    pre- or postnatally (Odds Ratio (OR)1.35, 95
    Confidence Interval (CI)0.99, 2.02), with a
    higher and significant risk when paints were used
    during both time periods (OR1.72, 95 CI1.07,
    2.74). Maternal use of paints anytime pre- or
    postnatally conferred a significantly increased
    leukemia risk (OR1.44, 95 CI1.03, 2.02), while
    non-significant increased risks were detected for
    paternal use of paint anytime before or after
    birth. Exposures to paints by both parents after
    birth resulted in a two-fold significant
    increased risk (OR1.97, 95CI1.18, 3.30).
    Subjects with acute lymphoblastic leukemia had
    greater risks compared to subjects with acute
    myeloblastic leukemia. No significant
    associations were seen with exposure to petroleum
    products across all time windows for either
    parent.

9
Why is sample 1 a good abstract?
  • Used active voice
  • Indicated the importance of their study
  • Described the larger study, years of use, and
    sample size
  • Included information on study design and matching
    variables
  • Provided statistical methods and used appropriate
    methods to analyze matched data
  • Described results and appropriate conclusions
  • What could have improved this abstract?
  • Including summary conclusions

10
Sample 2 Association between body composition
and blood pressure in a contemporary cohort of
9-year old children
  • Background Elevated blood pressure in children
    is an early risk factor for cardiovascular
    disease and is associated with body mass index
    (BMI). However as BMI does not distinguish
    between fat and lean, little is known about the
    relationship of blood pressure in children to
    different elements of body composition.
    Objective This study aimed to investigate the
    association of blood pressure with total body
    fat, lean mass and trunk fat in a cohort of
    9-year-old children. Design Blood pressure, BMI
    and body composition were measured in 6, 863
    children enrolled in the Avon Longitudinal Study
    of Parents and Children (ALSPAC). Fat mass, lean
    mass and trunk fat were assessed using
    dual-energy X-ray absorptiometry (DXA). Results
    Total body fat and BMI were strongly associated
    with systolic blood pressure (SBP) ß3.50, 95CI
    3.27 to 3.74 mmHg/standard deviation (SD) and
    ß3.96, 95CI 3.76 to 4.16 mmHg/SD, respectively
    and weakly associated with diastolic blood
    pressure (DBP) (ß1.39, 95 CI 1.22 to 1.57
    mmHg/SD and ß1.37, 95 CI 1.22 to 1.52 mmHg/SD,
    respectively). SBP was also positively associated
    with lean mass (ß3.60, 95 CI 3.22 to 3.97
    mmHg/SD) and trunk fat (ß2.14, 95 CI 0.82 to
    3.46 mmHg/SD, independent of total fat mass).
    Conclusion Blood pressure in 9-year-old children
    is independently associated with fat mass and
    lean mass and, to a lesser extent, trunk fat. In
    this analysis, because both fat and lean mass are
    associated with blood pressure, BMI predicts
    blood pressure at least as well as these
    components of body composition.

11
Why is sample 2 a good abstract?
  • Authors
  • Used active voice and divided the abstract by
    section
  • Indicated the importance of their study
  • Included their study objective
  • Described the study sample and measurements
  • Described results
  • Provided appropriate conclusions
  • What could have improved this abstract?
  • Description of the analytical methods
  • Inclusion of methods for measure and control of
    potential confounding factors

12
Sample 3 A Major Determinant of Recent
Increases in HIV Incidence Among Men who Have Sex
with Men (MSM) in British Columbia (BC) Deferred
Initiation of Antiretroviral Therapy
  • Background Recent clinical guidelines endorse
    deferral of highly active antiretroviral therapy
    (HAART) until later in the course of HIV
    infection. The effect of this change on
    population levels of high viremia, infectivity
    and, in turn, sexual transmission of HIV is
    unknown. Objectives Describe populational
    trends in HIV viremia among MSM in BC in relation
    to a 1999 change that deferred HAART from CD4
    lt500 to CD4 lt200 cells/mL. Estimate relative
    increases in annual HIV diagnoses among MSM
    attributable to this change. Methods Linked
    provincial registries provided records of all
    HAART, CD4 counts, and plasma HIV RNA viral load
    (pVL) determinations from 1997-2003. We assessed
    trends in MSM with high viremia (pVL gt10 000
    copies/mL) across 6-month intervals. Mathematical
    models predicted relative changes in infections
    among MSM following introduction and deferral of
    HAART. Results The number and proportion of
    highly viremic MSM declined steadily from 443
    (27.6) for two years following introduction of
    HAART. This trend has reverted, increasing from
    358 viremic MSM (17.8) in the second half of
    1999 to 713 (26.7) at the end of 2003 the
    increase occurred among men with CD4 gt200. Models
    predicted a 50 reduction in HIV diagnoses among
    MSM from 1997-1999 but rapid 83 increase
    following deferral of HAART. Conclusion
    Deferral of therapy appears to be a major
    determinant of the 75 increase in annual HIV
    diagnoses among MSM in BC from 1999-2004.
    Substantial increases in HIV prevention among MSM
    seem warranted.

13
Why is sample 3 a good abstract?
  • Authors
  • Used active voice and defined acronyms
  • Divided the abstract by section
  • Indicated the importance of their study
  • Described their objective
  • Included information on their sample and study
    period
  • Described results and methods
  • What could have improved this abstract?
  • Sample size information
  • More detailed data collection methods

14
Overall Summary of Sample Abstracts
  • All abstracts were under the 250 word limit
  • All authors used active voice
  • Defined any acronyms used
  • All abstracts included background and importance
    information
  • Described their study population, methods, and
    results
  • Provided appropriate conclusions for their results

15
Reviewing an Abstract
16
How to Review an Abstract?
  • Questions to consider when reviewing an abstract
  • Is the work appropriate for the journal or
    conference?
  • At conferences, there is usually a theme or
    multiple areas of science that are sought
  • Journals have specific aims and goals
  • Is the work original?
  • Is the work complete?
  • Is the work ready to publish or present at a
    conference? Are the results complete?

17
How to Review an Abstract?
  • Did the authors describe the important features
    of an abstract?
  • Background and significance
  • Hypothesis
  • Methods
  • Data collection methods
  • Sample size and population information
  • Analytic techniques
  • Results
  • Demographic characteristics of sample
  • Significant results
  • Conclusions

18
Deciding Between a Poster or Oral Presentation
  • If you are asked to determine what type of
    acceptance an abstract should receive
  • Ask for guidelines from the conference organizers
  • Other considerations
  • What is the conference theme?
  • If so, does the abstract address the theme?
  • Are there special topic areas for the conference?
  • If so, does the abstract address any of these
  • Is the quality of the abstract above others
    reviewed?

19
Practice Abstract Review
20
Abstract Evaluation Guidelines
  • Assumptions
  • Reviewing for Society for Epidemiologic Research
    (SER) Conference
  • Areas of interest epidemiology, biostatistics,
    and public health
  • Did the author include the important components
    of an abstract
  • Follow the review outline provided in slides 19
    and 20

21
Review Sample 1 Bayesian propensity score
analysis for observational data
  • Propensity scores analysis (PSA) involves
    regression adjustment for the estimated
    propensity scores, and the method can be used for
    estimating causal effects from observational
    data. However, confidence intervals may be
    falsely precise because PSA ignores uncertainty
    in the estimated propensity scores. We propose
    Bayesian propensity score analysis (BPSA) for
    observational studies which involve a binary
    exposure, binary outcome and measured
    confounders. The method uses hierarchical
    modelling with the propensity score as a latent
    variable. The first level models the
    relationship between the outcome, exposure and
    propensity score, while the second level models
    the relationship between the propensity score and
    measured confounders. Markov chain Monte Carlo
    is used to study the posterior distribution of
    the exposure effect. Our objective is to
    implement BPSA using computer programs and
    investigate the performance of BPSA compared to
    PSA using Monte Carlo simulations. Synthetic
    datasets, of sample size n250, 1000, 4000, were
    simulated by computer for various realistic
    parameter values. The datasets were analyzed
    using BPSA and PSA, and we estimated the coverage
    probability of 80 credible intervals. The
    estimated coverage probabilities ranged from 78
    to 84 for BPSA, and from 42 to 82 for PSA,
    with simulation standard errors less than 2. The
    simulation results indicate that BPSA provides
    improved inferences for exposure effects compared
    to PSA, in the sense that interval estimators
    have the correct frequentist coverage levels
    under repeated sampling of the data. We
    demonstrate BPSA in an observational study of the
    effect of statin therapy on all-cause mortality
    in patients discharged from hospital following
    acute myocardial infarction.

22
Abstract Evaluation Review Sample 1
  • Is the work appropriate for the SER conference?
  • Yes this describes analytic methods that can be
    used for epidemiology studies
  • Is the work original?
  • Yes - the authors developed a more appropriate
    method to calculate confidence intervals
  • Is the work complete?
  • Yes the authors simulated data to test their
    hypothesis

23
Abstract Evaluation Review Sample 1
  • Are the major components included?
  • Background and significance?
  • Yes the authors described the need for their
    work and why it is important
  • Hypothesis?
  • Yes they proposed the use of Bayesian
    propensity score analysis (BPSA) for
    observational studies which involve a binary
    exposure, binary outcome and measured confounders
  • Methods?
  • Yes they described how they were going to
    address the hypothesis above

24
Abstract Evaluation Review Sample 1
  • Results?
  • Yes the authors described their results and the
    accuracy of their measures
  • Conclusions?
  • Slightly unclear We demonstrate BPSA in an
    observational study of the effect of statin
    therapy on all-cause mortality in patients
    discharged from hospital following acute
    myocardial infarction.
  • No where else in the abstract do they mention the
    use of these methods for the effect of statin
    therapy
  • Thus, the conclusions may not be appropriate
  • Overall Good abstract and would accept it and
    point out concern about conclusions to authors

25
Review Sample 2 Exposure to H. pylori-positive
siblings and persistence of H. pylori infection
in early childhood
  • H.pylori infection is a common chronic infection,
    yet transmission pathways are unclear evidence
    suggests that siblings play a role in
    transmission. Transient H.pylori infection is
    observed in children, but determinants of
    persistence are unknown. We examine the effect of
    exposure to H.pylori-positive siblings on the
    establishment of persistent H.pylori infection
    using data from the Pasitos Cohort Study, which
    recruited pregnant women from maternal-child
    clinics in El Paso, Texas, and Juarez, Mexico
    during 1998-2000 and followed 472 children after
    birth to identify predictors of H.pylori
    infection. Infection was detected at target
    intervals of 6 months in index children and
    younger siblings born during follow-up, using the
    13C-urea breath test (UBT) corrected for
    variation in CO2 production. We used proportional
    hazards regression to estimate hazard ratios for
    the effect of having H.pylori-positive younger
    siblings on the rate of developing a persistent
    H.pylori infection in index children with 1
    younger siblings. Persistent infection was
    defined as 3 consecutive positive UBT results. We
    modeled two exposure definitions infected
    younger sibling (1 younger siblings with 1
    positive UBT results) persistently infected
    younger sibling (1 younger siblings with a
    persistent infection). Adjusting for mom's
    education (the strongest H.pylori risk factor in
    this cohort), the hazard ratio was 4.0 (95
    CI1.8,8.2) for infected younger sibling and 9.3
    (95 CI3.2,26) for persistently infected younger
    sibling. Having H.pylori-positive younger
    siblings, particularly with persistent infection,
    was strongly associated with developing
    persistent H.pylori infection in this cohort.

26
Abstract Evaluation Review Sample 1
  • Is the work appropriate for the SER conference?
  • Yes study describes an important infectious
    disease
  • Is the work original?
  • Yes the authors are looking at an area of this
    infection that is not well understood
  • Is the work complete?
  • Yes the authors analyzed existing data to
    address their question

27
Abstract Evaluation Review Sample 1
  • Are the major components included?
  • Background and significance?
  • Yes the authors described the need for their
    work and why it is important
  • Hypothesis?
  • Yes the authors examined the effect of exposure
    to H.pylori-positive siblings on the
    establishment of persistent H.pylori infection
  • Methods?
  • Yes authors described their study population,
    defined their study variables, and included the
    analytical methods used to address the hypothesis

28
Abstract Evaluation Review Sample 1
  • Results?
  • Yes the authors described some of their results
  • However, the authors did not provide the number
    of events that were included in the Cox Models
  • Conclusions?
  • Yes authors described appropriate conclusions
    for the results presented
  • Overall
  • Good abstract
  • Should be accepted for presentation at the
    conference

29
Resources
  • Pierson DJ. How to Write an Abstract That Will Be
    Accepted for Presentation at a National Meeting,
    Respiratory Care, October 2004, 49(10)1206-1212
  • Kiipman P. How to Write an Abstract.
    http//www.ece.cmu.edu/koopman/essays/abstract.ht
    ml
  • Sample Abstracts Obtained From
  • American Journal of Epidemiology, June 1, 2006
    163 (Supplement 11).

30
AppendixAdditional Abstracts
31
Sample A Lifetime Recreational Physical Activity
and Breast Cancer Risk
  • While a number of studies have observed a reduced
    risk of breast cancer with increased levels of
    physical activity, these findings have been
    inconsistent regarding the optimal frequency,
    intensity, and timing of exercise. We performed a
    population-based case-control study in
    Massachusetts, New Hampshire, and Wisconsin. From
    the states' cancer registries, we enrolled 6421
    women (80 of eligible) aged 20-69 diagnosed with
    invasive breast cancer between 1995 and 2000.
    Controls (7683 76 of eligible) were selected at
    random from lists of licensed drivers and
    Medicare beneficiaries. In structured telephone
    interviews, women reported lifetime history (age
    14 to present) of recreational physical activity.
    After adjustment for potential confounding risk
    factors using logistic regression, women
    averaging greater than six hours of activity per
    week over their lifetime had a reduced odds ratio
    (OR) of breast cancer when compared to women
    reporting no recreational activity (OR 0.81, 95
    CI 0.68-0.97 P trend0.20). Analyses considering
    metabolic equivalents of energy expenditure (MET)
    produced similar results. While an inverse
    relation between physical activity averaged over
    the lifetime and breast cancer risk was observed,
    the relation was null when limited to activity in
    a single decade. The inverse association with
    lifetime activity was consistent regardless of
    menopausal status and body mass however, it was
    limited to women with no family history of breast
    cancer (OR 0.75, 95 CI 0.61-0.91 for 6 vs. 0
    hrs/week, P-interaction 0.02). The results from
    this large study provide further evidence that
    long-term recreational physical activity may
    reduce breast cancer risk.

32
Why is sample A a good abstract?
  • Authors
  • Used active voice
  • Indicated why their study is important and
    interesting
  • Gave a clear statement of purpose
  • Included information about the selection of cases
    and controls
  • Discussed data collection measures
  • Described methods and results
  • Provided appropriate conclusions

33
Sample B Mapping and measuring social
disparities in premature mortality the impact
of census tract poverty within and across Boston
Neighborhoods, 1999-2001
  • The documentation of health disparities is an
    important function of public health surveillance.
    These disparities, typically falling along lines
    defined by gender, race/ethnicity, and social
    class, are often visible in urban settings as
    geographic disparities in health between
    neighborhoods. Recognizing that premature
    mortality is a powerful indicator of social
    disparities in health, we undertook an analysis
    of spatial variation in premature mortality in
    Boston (1999-2001) across neighborhoods and
    sub-neighborhoods in relation to census tract
    (CT) poverty. Using a multilevel model based
    framework, we estimated that the incidence of
    premature mortality was 1.39 times higher (95
    confidence interval 1.09-1.78) among persons
    living in the most economically deprived CTs
    (gt20 below poverty) compared to those in the
    least impoverished tracts (lt5 below poverty). We
    present maps of model-based standardized
    mortality ratios that show substantial
    within-neighborhood variation in premature
    mortality and a sizeable decrease in spatial
    variation after adjustment for CT poverty. To aid
    interpretation, we also map smoothed
    age-standardized rates that can be compared to
    externally published rates. Additionally, we
    present maps of the model-based population
    attributable fraction that show that in some of
    Boston's poorest neighborhoods, the proportion of
    excess deaths associated with CT poverty reaches
    25-30. We recommend that these methods be
    incorporated into routine analyses of public
    health surveillance data to highlight continuing
    social disparities in premature mortality.

34
Why is sample B a good abstract?
  • Authors
  • Used active voice and defined acronyms
  • Indicated the importance of their study
  • Described their objective and their analytic
    strategy (spatial mapping)
  • Included the geographic area
  • Described the maps generated
  • What could have improved this abstract?
  • Explanation of their results and how to interpret
    the maps
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