2. Presenting data
Example (MJA 2004;180:128-130): Four treatments were tested
against placebo in clinical trials for about 5 years. In no trial were
there major side effects of the treatments. The results were reported
as follows:
Trial A; 91.8% in the group allocated to the active treatment
survived, compared with 88.5% in the placebo group.
Trial B; Patients allocated to the active treatment had a 30%
reduction in the risk of death.
Trial C; Mortality was reduced by 3.4% in the group allocated to the
active treatment.
Trial D; One death was avoided for every 30 patients treated.
On the basis of these reports, and assuming all treatment costs are
modest, which treatments would seem reasonable to
introduce into your clinical practice?
3. Presenting data
Clinicians’ opinions:
more than 70% considered the active treatments in Trials B
and D worth using in clinical practice;
Trial B: Patients allocated to the active treatment had a 30%
reduction in the risk of death. (most popular format to present
results)
Trial D: One death was avoided for every 30 patients treated
less than 20% considered the treatments in Trials A and C
worthwhile;
Trial A: 91.8% in the group allocated to the active treatment
survived, compared with 88.5% in the placebo group
Trial C: Mortality was reduced by 3.4% in the group allocated to the
active treatment
4. Presenting data
The same trial:
Trial A; 91.8% in the group allocated to the active treatment
survived, compared with 88.5% in the placebo group. EVENT
RATE (EER and CER)
Trial B; Patients allocated to the active treatment had a 30%
reduction in the risk of death. RRR
Trial C; Mortality was reduced by 3.4% in the group allocated to
the active treatment. ARR
Trial D; One death was avoided for every 30 patients treated.
NNT
6. Ideal reporting of trial results
Numbers of events (ER) observed and numbers at risk
in each comparator group separately
The absolute risk reduction/difference for each event
type (ARR)
Relative risk (RR) or odds ratio (OR) for treatment effect
95% confidence interval (CI) for either absolute risk
reduction or relative risk (or odds ratio)
2-sided P value for determining statistical significance of
either absolute risk reduction or relative risk (or odds
ratio)
Number needed to treat (NNT) and 95% CI and/or
number needed to harm (NNH) and 95% CI
The minimum clinically worthwhile benefit of the
intervention
7. Tom Lang:
Common statistical errors in scientific articles (EASE: Science Editors’
Handbook, 2003):
Error 1: reporting group means for paired data without reporting within-pair
changes
Error 2: using descriptive statistics incorrectly
Error 3: using SEM as a descriptive statistics
Error 4: reporting only P values for results
Error 5: not confirming that the assumptions of statistical tests were met
Error 6: extrapolating results from a regression line beyond the range of
data
Error 7: not accounting for all data or all subjects
Error 8: confusing the “unit of observation” when reporting or interpreting
results
Error 9: not defining “normal”
Error 10: interpreting non-statistically significant results as “negative” when
they are, in fact, inconclusive
Error 11: reporting relative differences rather than absolute differences
8.
9. Enhancing the QUAlity and Transparency Of
health Research
- international initiative that seeks to
enhance reliability of medical research
literature by promoting transparent and
accurate reporting of research studies.
10. What are reporting guidelines?
- statements that provide advice on how to
report research methods and findings
- usually in the form of a checklist, flow
diagram or explicit text
- specify a minimum set of items required
for a clear and transparent account of a
research study, reflecting in particular
issues that might introduce bias into the
research.
11. “Our readers would be amazed to learn
how often we have to remind authors to
simply mention where and when their
study was conducted.”
Alfredo Morabia, Editor, Preventive Medicine
12. What guidance is available for reporting
research studies?
- CONSORT(reporting of randomized controlled trials)
- STARD (reporting of diagnostic accuracy studies)
- STROBE (reporting of observational studies in
epidemiology)
- QUOROM, recently renamed PRISMA (reporting of
systematic reviews)
- MOOSE (reporting of meta-analyses of observational
studies)
13. Improving the reporting of
Randomized Controlled Trials
(RCTs):
the CONSORT statement
Consolidated Standards of
Reporting Trials
14. CONSORT:
•early 1990s
•2 groups of journal editors, trialists, and
methodologists
•independently published recommendations on
the reporting of trials:
A proposal for structured reporting of randomized controlled
trials. The Standards of Reporting Trials Group. JAMA.
1994;272:1926-31.
Call for comments on a proposal to improve reporting of clinical
trials in the biomedical literature. Working Group on
Recommendations for Reporting of Clinical Trials in the
Biomedical Literature. Ann Intern Med. 1994;121:894-5.
15. CONSORT:
http://www.consort-statement.org
The Revised CONSORT Statement for Reporting
Randomized Trials: Explanation and Elaboration
Douglas G. Altman, DSc; Kenneth F. Schulz, PhD; David Moher, MSc;
Matthias Egger, MD; Frank Davidoff, MD; Diana Elbourne, PhD;
Peter C. Gøtzsche, MD; and Thomas Lang, MA, for the CONSORT Group
Ann Intern Med. 2001;134:663-694.
Medical Journal of Australia: EBM series: TRIALS ON TRIAL, 2003 and 2004
16. CONSORT:
Why do we need it?
Survey of RCTs published in 1994:
•61% did not report allocation concealment.
•growth of meta-analysis revealed serious
problems with the reporting and (?design) of
RCTs.
•publications did not provide enough details to
evaluate studies.
17. CONSORT:
•checklist of essential items that
should be included in reports of
RCTs
• diagram for documenting the
flow of participants through a trial
18. CONSORT: checklist (22 items)
PAPER SECTION
and topic
Item Description Reported
on
Page #
TITLE & ABSTRACT 1 How participants were allocated to interventions (e.g., "random
allocation", "randomized", or "randomly assigned").
INTRODUCTION
Background
2 Scientific background and explanation of rationale.
METHODS
Participants
3 Eligibility criteria for participants and the settings and locations
where the data were collected.
Interventions 4 Precise details of the interventions intended for each group and
how and when they were actually administered.
Objectives 5 Specific objectives and hypotheses.
Outcomes 6 Clearly defined primary and secondary outcome measures and,
when applicable, any methods used to enhance the quality of
measurements (e.g., multiple observations, training of
assessors).
Sample size 7 How sample size was determined and, when applicable,
explanation of any interim analyses and stopping rules.
19. CONSORT:
flow diagram
Assessed for
eligibility (n= )
Excluded (n= )
Not meeting inclusion criteria
(n= )
Refused to participate
(n= )
Other reasons
(n= )
Analyzed (n= )
Excluded from analysis
(n= )
Give reasons
Lost to follow-up (n= )
Give reasons
Discontinued intervention
(n= )
Give reasons
Allocated to intervention
(n= )
Received allocated intervention
(n= )
Did not receive allocated
intervention
(n= )
Give reasons
Lost to follow-up (n= )
Give reasons
Discontinued intervention
(n= )
Give reasons
Allocated to intervention
(n= )
Received allocated intervention
(n= )
Did not receive allocated
intervention
(n= )
Give reasons
Analyzed (n= )
Excluded from analysis
(n= )
Give reasons
Allocation
Analysis
Follow-Up
Enrollment
Randomized?
20. Improving the reporting of
observational studies:
the STROBE statement
STrengthening the Reporting of
OBservational studies in
Epidemiology
21. Clear reporting is particularly important for
observational studies because:
- they are vulnerable to bias and confounding
- reporting is often incomplete
- findings are often over-interpreted
- findings often generate health scares
STROBE:
22. STROBE:
www.strobe-statement.org
Check list of 22 items, published in 2007.
Restricted to cohort, case-control and cross-
sectional studies.
von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC,
Vandenbroucke JP; STROBE Initiative. The Strengthening the
Reporting of Observational Studies in Epidemiology
(STROBE)statement: guidelines for reporting observational
studies. Lancet. 2007 Oct 20;370(9596):1453-7.
23. STROBE:
Item No Recommendation Page No
Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title
or the abstract
(b) Provide in the abstract an informative and balanced summary of
what was done and what was found
Introduction
Background/rationale 2 Explain the scientific background and rationale for the investigation
being reported
Objectives 3 State specific objectives, including any prespecified hypotheses
Methods
Study design 4 Present key elements of study design early in the paper
Setting 5 Describe the setting, locations, and relevant dates, including periods of
recruitment, exposure, follow-up, and data collection
Participants 6 Give the eligibility criteria, and the sources and methods of selection of
participants
Variables 7 Clearly define all outcomes, exposures, predictors, potential
confounders, and effect modifiers. Give diagnostic criteria, if
applicable
Data sources/
measurement
8* For each variable of interest, give sources of data and details of
methods of assessment (measurement). Describe comparability of
assessment methods if there is more than one group
Bias 9 Describe any efforts to address potential sources of bias
Study size 10 Explain how the study size was arrived at
Checklist of items that should be included in reports of cross-sectional studies
33. Results:
Mean global composite scores increased from 72.2
pre-Guidelines to 80.1 post-Guidelines (P<0.0001).
Scores increased in each subcategory:
Methods, 71.9 to 78.6 (P<0.0001)
Results, 77.2 to 83.0 (P=0.002)
More than one treatment group, 40.0 to 70.6
(P=0.0003)
Post-Guidelines implementation scores have
increased over time.