Reporting Results

	P9419
	Class #6
	November 17, 2003

Why discuss Results in the Proposal course?

	Components of proposal abstract
	Research question
	Background
	Hypotheses
	Methods
	Results?
	Discussion?

Epidemiologic detective story

	Results=who done it
	May also exonerate the innocent
	Results answer research question.
	Support/falsify hypotheses.
	Background/literature review will help readers appreciate your results

Dataset issues

	Population
	Variables
	Can the data help to answer your research question?
	Sample size constraints
	Exploratory/hypothesis-generating vs. hypothesis-testing

Go back to your literature review

	How do other investigators present their results?
	Weaknesses and strengths

Statistical methods

	What methods can be applied to your dataset to get those answers?
	Credibility of your answers depends on appropriateness of your methods.

Results I.

	How did your methods work out?
	Not the same as in Methods
	Methods describes:
		Study design, population, time period
		recruitment methods
		eligibility criteria
		informed consent
		follow-up, etc.
	Results I describes:
		how many study participants you contacted
		how many refused, were ineligible, could not be reached, etc.
		Usually text, but if important, table

Table 1

	Demographic characteristics
		Age
		Sex
		Race/ethnicity
		Income . . .
	Clinical characteristics
		Stage of disease
		Presence/absence/level of biomarkers
		Comorbid conditions . . .
	Confounders/effect modifiers

The most important question in epidemiology

	Compared to what?
	Participants to refusers
	Cases to controls
	Exposed to unexposed
	Subjects recruited/interviewed by one method to subjects recruited/interviewed by another method

Table 1.  Demographic characteristics of cases
        and controls

Results II:  Main finding(s)

	Measure(s) of effect of the hypothesized exposure on the hypothesized outcome
	Risk/rate ratio, odds ratio, prevalence ratio
	Correlation
	Risk/rate difference
	Mean difference
	Assessment of statistical significance
	Statistical tests used
	Confidence intervals
	P values and P for trend
	Identification of confounders/effect modifiers

Reporting on covariates

	Adjusting
	Stratifying
	Separate analysis of interaction
	Interaction term in multivariable model

Other important findings

	Secondary endpoints/exposures
	Subgroup analyses
	Analyses done in response to questions raised by the main findings

Reporting on adjusted analyses

	OR=3.2 (95% CI 1.5-6.8)*
	*Adjusted for age, sex, tobacco use . . .
	Variable OR 95% CI
	Main exposure 3.2 1.5-6.8
	Age >50          0.9             0.8-1.0
	Sex, female              1.1             1.0-1.2
	Tobacco use             1.5             1.2-1.8

Reporting on stratified analyses

	OR=3.0 (95% CI 1.5-8.9) among males*
	OR=3.5 (95% CI 1.8-9.5) among females*
	*Adjusted for age, birthplace, alcohol intake . . .
	Table 3.  Odds ratios for main exposure and other factors among males.
	Variable OR 95% CI
	Main exposure 3.0 1.5-8.9
	Age >50          0.9             0.8-1.0
	Birthplace
	NYC 1.0 (Referent)
	USA, not NYC 1.2 0.7-1.8
	Not USA 1.6 1.0-2.5

Slide 16

Slide 17

Your results may. . .

	Confirm your hypotheses – gratifying but doesn’t mean you are a better epidemiologist than if they
	Refute your hypotheses – annoying, but not a cause for shame or mourning
	Be inconclusive – may be embarrassing unless you knew in front that your dataset had limitations (e.g., small sample size, narrow range of exposures, etc.)
	Surprise you – report surprises as hypothesis generating . . .

Discussion

	Interpret results
	Limit to results presented
	Identify unresolved questions
	Recommend ways to address them