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Strength of Recommendation Taxonomy (SORT):A Patient-Centered Approach to Grading Evidencein the Medical Literature
Mark H. Ebell, MD, MS, Jay Siwek, MD, Barry D. Weiss, MD,Steven H. Woolf, MD, MPH, Jeffrey Susman, MD, Bernard Ewigman, MD, MPH, andMarjorie Bowman, MD, MPA
A large number of taxonomies are used to rate the quality of an individual study and the strength of a
recommendation based on a body of evidence. We have developed a new grading scale that will be used
by several family medicine and primary care journals (required or optional), with the goal of allowing
readers to learn one taxonomy that will apply to many sources of evidence. Our scale is called the
Strength of Recommendation Taxonomy. It addresses the quality, quantity, and consistency of evidence
and allows authors to rate individual studies or bodies of evidence. The taxonomy is built around the
information mastery framework, which emphasizes the use of patient-oriented outcomes that measure
changes in morbidity or mortality. An A-level recommendation is based on consistent and good quality
patient-oriented evidence; a B-level recommendation is based on inconsistent or limited quality patient-
oriented evidence; and a C-level recommendation is based on consensus, usual practice, opinion,
disease-oriented evidence, or case series for studies of diagnosis, treatment, prevention, or screening.
Levels of evidence from 1 to 3 for individual studies also are defined. We hope that consistent use of
this taxonomy will improve the ability of authors and readers to communicate about the translation of
research into practice. (J Am Board Fam Pract 2004;17:59 – 67.)
Review articles (or overviews) are highly valued by
improve the quality of review articles through the
physicians as a way to keep up to date with the
use of more explicit grading of the strength of
medical literature. Sometimes, though, these arti-
evidence on which recommendations are based.1–4
cles are based more on the authors' personal expe-
Several journals, including
American Family Phy-
rience, or anecdotes, or incomplete surveys of the
sician and
Journal of Family Practice, have adopted
literature than on a comprehensive collection of the
evidence-grading scales that are used in some of the
best available evidence. As a result, there is an
articles published in those journals. Other organi-
ongoing effort in the medical publishing field to
zations and publications have also developed evi-dence-grading scales. The diversity of these scalescan be confusing for readers. More than 100 grad-
Submitted, revised 20 November 2003.
ing scales are in use by various medical publica-
From the Michigan State University College of Human
Medicine, East Lansing (MHE), Georgetown University
tions.5 Alevel B recommendation in one journal
Medical Center, Washington, DC (JS), University of Ari-
may not mean the same thing as a level B recom-
zona College of Medicine, Tucson (BDW), Virginia Com-monwealth University School of Medicine, Richmond
mendation in another. Even within journals, differ-
(SHW), University of Cincinnati College of Medicine, Cin-
ent evidence-grading scales sometimes are used in
cinnati, Ohio (JS), University of Chicago, Pritzker School ofMedicine, Chicago, Illinois (BE), and University of Penn-
different articles within the same issue of a journal.
sylvania Health System, Philadelphia (MAB). Address cor-
Journal readers do not have the time, energy, or
respondence to Mark Ebell, MD, MS, 300 Snapfinger Dr.,Athens, GA 30605 (e-mail:
[email protected]).
interest to interpret multiple grading scales, and
Simultaneously published in print and online by
American
more complex scales are difficult to integrate into
Family Physician,
Journal of Family Practice,
Journal of theAmerican Board of Family Practice, and online by
Family
daily practice.
Practice Inquiries Network. Copyright 2004 American Fam-
Therefore the editors of the US family medicine
ily Physician, a publication of the American Academy ofFamily Physicians. All rights reserved.
and primary care journals (ie,
American Family Phy-
Strength of Recommendation Taxonomy 59
sician, Family Medicine, Journal of Family Practice,
Strength of Recommendation
Journal of the American Board of Family Practice, and
The strength (or grade) of a recommendation for
BMJ-USA) and the Family Practice Inquiries Net-
clinical practice is based on a body of evidence
work (FPIN) came together to develop a unified
(typically more than one study). This approach
taxonomy for the strength of recommendations
takes into account the level of evidence of individ-
based on a body of evidence. The new taxonomy
ual studies, the type of outcomes measured by these
should include the following attributes: (1) be uni-
studies (patient-oriented or disease-oriented), the
form in most family medicine journals and elec-
number, consistency, and coherence of the evi-
tronic databases; (2) allow authors to evaluate the
dence as a whole, and the relationship between
strength of recommendation of a body of evidence;
benefits, harms, and costs.
(3) allow authors to rate the level of evidence for anindividual study; (4) be comprehensive and allow
Practice Guideline (Evidence-Based)
authors to evaluate studies of screening, diagnosis,
These guidelines are recommendations for practice
therapy, prevention, and prognosis; (5) be easy to
that involve a comprehensive search of the litera-
use and not too time-consuming for authors, re-
ture, an evaluation of the quality of individual stud-
viewers, and editors who may be content experts
ies, and recommendations that are graded to reflect
but not experts in critical appraisal or clinical epi-
the quality of the supporting evidence. All search,
demiology; and (6) be straightforward enough that
critical appraisal, and grading methods should be
primary care physicians can readily integrate the
described explicitly and be replicable by similarly
recommendations into daily practice.
skilled authors.
Practice Guideline (Consensus)
Anumber of relevant terms must be defined for
Consensus guidelines are recommendations for
practice based on expert opinions that typically donot include a systematic search, an assessment of
the quality of individual studies, or a system to label
These outcomes include intermediate, histopatho-
the strength of recommendations explicitly.
logic, physiologic, or surrogate results (ie, bloodsugar, blood pressure, flow rate, coronary plaque
Research Evidence
thickness) that may or may not reflect improve-
This evidence is presented in publications of orig-
ments in patient outcomes.
inal research, involving collection of original dataor the systematic review of other original research
publications. It does not include editorials, opinion
These are outcomes that matter to patients and
pieces, or review articles (other than systematic
help them live longer or better lives, including
reviews or meta-analyses).
reduced morbidity, reduced mortality, symptomimprovement, improved quality of life, or lower
Review Article
Anonsystematic overview of a topic is a reviewarticle. In most cases, it is not based on an exhaus-
Level of Evidence
tive, structured review of the literature and does
The validity of an individual study is based on an
not evaluate the quality of included studies system-
assessment of its study design. According to some
methodologies,6 levels of evidence can refer notonly to individual studies but also to the quality of
Systematic Reviews and Meta-Analyses
evidence from multiple studies about a specific
Asystematic review is a critical assessment of ex-
question or the quality of evidence supporting a
isting evidence that addresses a focused clinical
clinical intervention. For purposes of maintaining
question, includes a comprehensive literature
simplicity and consistency in this proposal, we use
search, appraises the quality of studies, and reports
the term level of evidence to refer to individual
results in a systematic manner. If the studies report
comparable quantitative data and have a low degree
60
JABFP January–February 2004 Vol. 17 No. 1
of variation in their findings, a meta-analysis can be
After considering these criteria and reviewing
performed to derive a summary estimate of effect.
the existing taxonomies for grading the strength ofa recommendation, we decided that a new taxon-omy was needed to reflect the needs of our spe-
Existing Strength-of-Evidence Scales
cialty. Existing grading scales were focused on a
In March 2002, the Agency for Healthcare Re-
particular kind of study (ie, prevention or treat-
search and Quality (AHRQ) published a report that
ment), were too complex, or did not take into
summarized the state of the art in methods of rating
account the type of outcome.
the strength of evidence.5 The report identified a
Our proposed taxonomy is called the Strength of
large number of systems for rating the quality of
Recommendations Taxonomy (SORT). It is shown
individual studies: 20 for systematic reviews, 49 for
in Figure 1
. The taxonomy includes ratings of A, B,
randomized controlled trials, 19 for observational
or C for the strength of recommendation for a body
studies, and 18 for diagnostic test studies. It also
of evidence. The table in the center of Figure 1
identified 40 scales that graded the strength of a
explains whether a body of evidence represents
body of evidence consisting of one or more studies.
good or limited-quality evidence and whether evi-
The authors of the AHRQ report proposed that
dence is consistent or inconsistent. The quality of
any system for grading the strength of evidence
individual studies is rated 1, 2, or 3; numbers are
should consider 3 key elements: quality, quantity,
used to distinguish ratings of individual studies
and consistency. Quality is the extent to which the
from the letters A, B, and C used to evaluate the
identified studies minimize the opportunity for bias
strength of a recommendation based on a body of
and is synonymous with the concept of validity.
evidence. Figure 2 provides information about how
Quantity is the number of studies and subjects
to determine the strength of recommendation for
included in those studies. Consistency is the extent
management recommendations, and Figure 3 ex-
to which findings are similar between different
plains how to determine the level of evidence for an
studies on the same topic. Only 7 of the 40 systems
individual study. These 2 algorithms should be
identified and addressed all 3 of these key ele-
helpful to authors preparing manuscripts for sub-
mission to family medicine journals. The algo-rithms are to be considered general guidelines, and
Strength of Recommendation Taxonomy
special circumstances may dictate assignment of a
different strength of recommendation (eg, a single,
The authors of this article represent the major
large, well-designed study in a diverse population
family medicine journals in the United States and a
may warrant an A-level recommendation).
large family practice academic consortium. Our
Recommendations based only on improvements
process began with a series of electronic mail ex-
in surrogate or disease-oriented outcomes are al-
changes, was developed during a meeting of the
ways categorized as level C, because improvements
editors, and continued through another series of
in disease-oriented outcomes are not always asso-
electronic mail exchanges.
ciated with improvements in patient-oriented out-
We decided that our taxonomy for rating the
comes, as exemplified by several well-known find-
strength of a recommendation should address the 3
ings from the medical literature. For example,
key elements identified in the AHRQ report: qual-
doxazosin lowers blood pressure in black pa-
ity, quantity, and consistency of evidence. We also
tients—a seemingly beneficial outcome— but it also
were committed to creating a grading scale that
increases mortality rates.12 Similarly, encainide and
could be applied by authors with varying degrees of
flecainide reduce the incidence of arrhythmias after
expertise in evidence-based medicine and clinical
acute myocardial infarction, but they also increase
epidemiology and interpreted by physicians with
mortality rates.13 Finasteride improves urinary flow
little or no formal training in these areas. We be-
rates, but it does not significantly improve urinary
lieved that the taxonomy should address the issue of
tract symptoms in patients with benign prostatic
patient-oriented evidence versus disease-oriented
hypertrophy,14 whereas arthroscopic surgery for
evidence explicitly and be consistent with the in-
osteoarthritis of the knee improves the appearance
formation mastery framework proposed by Slawson
of cartilage but does not reduce pain or improve
and Shaughnessy.2
joint function.15 Additional examples of clinical sit-
Strength of Recommendation Taxonomy 61
Figure 1. The Strength of Recommendation Taxonomy (SORT). SR, systematic review; RCT, randomized controlled
trial.
62
JABFP January–February 2004 Vol. 17 No. 1
Figure 2. Algorithm for determining the strength of a recommendation based on a body of evidence (applies to
clinical recommendations regarding diagnosis, treatment, prevention, or screening). Although this algorithm
provides a general guideline, authors and editors may adjust the strength of recommendation based on the
benefits, harms, and costs of the intervention being recommended. USPSTF, US Preventive Services Task Force.
uations where disease-oriented evidence disagrees
cians, and explicitly addresses the issue of patient-
with patient-oriented evidence are shown in Table
oriented versus disease-oriented evidence. The
1.12–24 Examples of how to apply the taxonomy are
latter attribute distinguishes SORT from most
given in Table 2.
other evidence grading scales. These strengths also
We believe there are several advantages to our
create some limitations. Some clinicians may be
proposed taxonomy. It is straightforward and com-
concerned that the taxonomy is not as detailed in its
prehensive, is easily applied by authors and physi-
assessment of study designs as others, such as that
Strength of Recommendation Taxonomy 63
Figure 3. Algorithm for determining the level of evidence for an individual study.
of the Centre for Evidence-Based Medicine
concluded that the advantages of a system that
(CEBM).25 However, the primary difference be-
provides the physician with a clear recommenda-
tween the 2 taxonomies is that the CEBM version
tion that is strong (A), moderate (B), or weak (C) in
distinguishes between good and poor observational
its support of a particular intervention outweighs
studies whereas the SORT version does not. We
the theoretic benefit of distinguishing between
64
JABFP January–February 2004 Vol. 17 No. 1
Table 1. Examples of Inconsistency between Disease-Oriented and Patient-Oriented Outcomes
Disease Or Condition
Disease-Oriented Outcome
Patient-Oriented Outcome
Doxazosin for blood pressure12
Reduces blood pressure
Increases mortality in blacks
Lidocaine for arrhythmia after acute
Suppresses arrhythmias
Increases mortality
myocardial infarction13
Finasteride for benign prostatic
Improved urinary flow rate
No clinically important change in
Sleeping infants on their stomach or
Knowledge of anatomy and physiology
Increased risk of sudden infant death
suggests that this will decrease the risk
Vitamin E for heart disease17
Reduces levels of free radicals
No change in mortality
Histamine antagonists and proton-pump
Significantly reduce gastric pH levels
Little or no improvement in symptoms
inhibitors for nonulcer dyspepsia18
in patients with nongastroesophagealreflux disease, nonulcer dyspepsia
Arthroscopic surgery for osteoarthritis of
Improved appearance of cartilage after
No change in function or symptoms at 1
Hormone therapy19
Reduced low-density lipoprotein
No decrease in cardiovascular or all-
cholesterol, increased high-density
cause mortality and an increase in
lipoprotein cholesterol
cardiovascular events in women olderthan 60 years (Women's HealthInitiative) with combined hormonetherapy
Insulin therapy in type 2 diabetes
Keeps blood sugar below 120 mg/dL (6.7
Does not reduce overall mortality
Sodium fluoride for fracture prevention21
Increases bone density
Does not reduce fracture rate
Lidocaine prophylaxis after acute
Suppresses arrhythmias
Increases mortality
myocardial infarction22
Clofibrate for hyperlipidemia23
Does not reduce mortality
-blockers for heart failure24
Reduce cardiac output
Reduce mortality in moderate to severe
lower quality and higher quality observational stud-
search of MEDLINE alone, or a more focused
ies, particularly because there is no objective evi-
search of MEDLINE plus secondary evidence-
dence that the latter distinction carries important
based sources of information.
differences in clinical recommendations.
Any publication applying SORT (or any other
evidence-based taxonomy) should describe care-
Walkovers: Creating Linkages with SORT
fully the search process that preceded the assign-
Some organizations, such as the CEBM,25 the
ment of a SORT rating. For example, authors
Cochrane Collaboration,7 and the US Preventive
could perform a comprehensive search of MED-
Services Task Force (USPSTF),6 have developed
LINE and the gray literature, a comprehensive
their own grading scales for the strength of recom-
Table 2. Examples of How to Apply the SORT in Practice
Example 1: Although a number of observational studies (level of evidence—2) suggested a cardiovascular benefit from vitamin E,
a large, well-designed, randomized trial with a diverse patient population (level of evidence—1) showed the opposite. Thestrength of recommendation against routine, long-term use of vitamin E to prevent heart disease, based on the best availableevidence, should be A.
Example 2: ACochrane review finds 7 clinical trials that are consistent in their support of a mechanical intervention for low back
pain, but the trials were poorly designed (ie, unblinded, nonrandomized, or with allocation to groups unconcealed). In this case,the strength of recommendation in favor of these mechanical interventions is B (consistent but lower quality clinical trials).
Example 3: Ameta-analysis finds 9 high-quality clinical trials of the use of a new drug in the treatment of pulmonary fibrosis.
Two of the studies find harm, 2 find no benefit, and 5 show some benefit. The strength of recommendation in favor of thisdrug would be B (inconsistent results of good-quality, randomized controlled trials).
Example 4: Anew drug increases the forced expiratory volume in 1 second (FEV1) and peak flow rate in patients with an acute
asthma exacerbation. Data on symptom improvement is lacking. The strength of recommendation in favor of using this drug isC (disease-oriented evidence only).
Strength of Recommendation Taxonomy 65
Table 3. Suggested Walkovers between Taxonomies for Assessing the Strength of a Recommendation Based on a
Body of Evidence
BMJ's Clinical Evidence
A. Recommendation based on consistent
A. Consistent level 1 studies
and good quality patient-orientedevidence
B. Recommendation based on
B. Consistent level 2 or 3 studies or
Likely to be beneficial
inconsistent or limited-quality patient-
extrapolations from level 1 studies
Likely to be ineffective or harmful
oriented evidence
(recommendation against)
C. Level 4 studies or extrapolations from
Unlikely to be beneficial
level 2 or 3 studies
(recommendation against)
C. Recommendation based on consensus,
D. Level 5 evidence or troublingly
Unknown effectiveness
usual practice, disease-oriented
inconsistent or inconclusive studies of
evidence, case series for studies of
treatment or screening, and/or opinion
SORT, Strength Of Evidence Taxonomy; CEBM, Centre for Evidence-Based Medicine; BMJ, BMJ Publishing Group.
Table 4. Suggested Walkover between the CEBM and the SORT Taxonomies for Assessing the Level of Evidence of
an Individual Study
Level 4 or 5 and any study that measures intermediate
Level 5 and any study that measures intermediate or
or surrogate outcomes
surrogate outcomes
CEBM, Centre for Evidence-Based Medicine; SORT, Strength of Recommendation Taxonomy.
mendations based on a body of evidence and are
the results of research in their practice through the
unlikely to abandon them. Other organizations,
information mastery approach and to incorporate
such as the FPIN,26 publish their work in a variety
evidence-based medicine into their patient care.
of settings and must be able to move between
Like any such grading scale, it is a work in
taxonomies. We have developed a set of optional
progress. As we learn more about biases in study
walkovers that suggest how authors, editors, and
design, and as the authors and readers who use the
readers might move from one taxonomy to an-
taxonomy become more sophisticated about prin-
other. Walkovers for the CEBM and USPSTF
ciples of information mastery, evidence-based med-
taxonomies are shown in Table 3
.
icine, and critical appraisal, it is likely to evolve. We
Many authors and experts in evidence-based
remain open to suggestions from the primary care
medicine use the "Level of Evidence" taxonomy
community for refining and improving SORT.
from the CEBM to rate the quality of individualstudies.25 Awalkover from the 5-level CEBM scaleto the simpler 3-level SORT scale for individual
We thank Lee Green, MD, MPH, John Epling, MD, Kurt
studies is shown in Table 4
.
Stange, MD, PhD, and Margaret Gourlay, MD, for helpfulcomments on the manuscript.
The SORT is a comprehensive taxonomy for
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Strength of Recommendation Taxonomy 67
Source: http://hematologienederland.nl/hematline/sites/default/files/SORT_Ebell-2004.pdf
Personalisierte Medizin Wie ist es möglich, dass zwei Menschen mit der gleichen Krankheit unterschiedlich auf die Behandlung mit demselben Medikament reagieren? Die Antwort liegt in den Genen. 1. Weniger Nebenwirkungen dank Pharmakogenomik Vergleicht man das Erbgut zweier Menschen, zum Beispiel das Erbgut einer Schülerin und ihres Banknachbarn, so wird man feststellen, dass sich die beiden Genome an etwa 30 bis 60 Millionen Basenpaaren, den «Buchstaben» des Erbguts, unterscheiden (einzige Ausnahme: der Banknachbar ist zugleich der eineiige Zwilling). Das entspricht etwa 1 bis 2 Prozent des gesamten Erbguts. Noch vor fünf Jahren meinten Wissenschafter, dass sich zwei Menschen nur etwa zu 0,1 Prozent genetisch voneinander unterscheiden.
PAINÒ 152 (2011) 2399–2404 Validity of four pain intensity rating scales Maria Alexandra Ferreira-Valente , José Luís Pais-Ribeiro , Mark P. Jensen a Faculdade de Psicologia e Ciências da Educação da Universidade do Porto, Porto, Portugalb Portuguese Foundation for Science and Technology, Lisbon, Portugalc Unidade de Investigação em Psicologia e Saúde (Psychology and Health Unit), Lisbon, Portugald Department of Rehabilitation Medicine, University of Washington School of Medicine, Seattle, WA, USA