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Strength of recommendation taxonomy (sort): a patient-centered approach to grading evidence in the medical literature - american family physician

Strength of Recommendation Taxonomy (SORT):
A Patient-Centered Approach to Grading Evidence
in the Medical Literature
MARK H. EBELL M.D., M.S., Michigan State University College of Human Medicine, East Lansing, Michigan
JAY SIWEK, M.D., Georgetown University Medical Center, Washington, D.C.
BARRY D. WEISS, M.D., University of Arizona College of Medicine, Tucson, Arizona
STEVEN H. WOOLF, M.D., M.P.H., Virginia Commonwealth University School of Medicine, Richmond, Virginia
JEFFREY SUSMAN, M.D., University of Cincinnati College of Medicine, Cincinnati, Ohio
BERNARD EWIGMAN, M.D., M.P.H., University of Chicago, Pritzker School of Medicine, Chicago, Illinois
MARJORIE BOWMAN, M.D., M.P.A., University of Pennsylvania Health System, Philadelphia, Pennsylvania
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 grad-
ing 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 stud-
ies 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. (Am Fam Physician 2004;69:548-56. Copyright 2004
American Academy of Family Physicians.)

used in some of the articles published in those journals. Other organizations and publica-tions also have developed evidence-grading Review articles (or overviews) are highly valued by physi-cians as a way to keep up-to-date with the medical lit- scales. The diversity of these scales can be erature. Sometimes, though, confusing for readers. More than 100 grading these articles are based more on the authors' scales are in use by various medical publica- personal experience, anecdotes, or incomplete tions.5 A level B recommendation in one jour- surveys of the literature than on a comprehen- nal may not mean the same thing as a level sive collection of the best available evidence. B recommendation in another. Even within As a result, there is an ongoing effort in the journals, different evidence-grading scales medical publishing field to improve the qual- sometimes are used in separate articles within ity of review articles through the use of more the same issue. Journal readers do not have the explicit grading of the strength of evidence on time, energy, or interest to interpret multiple which recommendations are based.1-4 grading scales, and more complex scales are Several journals, including American Family difficult to integrate into daily practice.
Physician and The Journal of Family Practice, Therefore, the editors of the U.S. family med- have adopted evidence-grading scales that are icine and primary care journals (i.e., American Family Physician, Family Medicine, The Journal of Family Practice, Journal of the American See editorial on page 483.
Board of Family Practice, and BMJ-USA) and Downloaded from the American Family Physician Web site at www.aafp.org/afp. Copyright 2004 American Academy of Family Physicians. For the private, noncommercial use of one individual user of the Web site. All other rights reserved.
the Family Practice Inquiries Network (FPIN) (or grade) of a recommendation for clinical came together to develop a unified taxonomy practice is based on a body of evidence (typi- for the strength of recommendations based cally more than one study). This approach on a body of evidence. The new taxonomy takes into account the level of evidence of indi- should: (1) be uniform in most family medi- vidual studies; the type of outcomes measured cine journals and electronic databases; (2) by these studies (patient-oriented or disease- allow authors to evaluate the strength of rec- oriented); the number, consistency, and coher- ommendation of a body of evidence; (3) allow ence of the evidence as a whole; and the rela- authors to rate the level of evidence for an tionship between benefits, harms, and costs.
individual study; (4) be comprehensive and Practice Guideline (Evidence-Based). These allow authors to evaluate studies of screening, guidelines are recommendations for practice diagnosis, therapy, prevention, and prognosis; that involve a comprehensive search of the liter- (5) be easy to use and not too time-consuming ature, an evaluation of the quality of individual for authors, reviewers, and editors who may studies, and recommendations that are graded be content experts but not experts in critical to reflect the quality of the supporting evi- appraisal or clinical epidemiology; and (6) dence. All search, critical appraisal, and grading be straightforward enough that primary care methods should be described explicitly and be physicians can readily integrate the recom- replicable by similarly skilled authors.
mendations into daily practice.
Practice Guideline (Consensus). Consensus guidelines are recommendations for practice based on expert opinions that typically do A number of relevant terms must be defined not include a systematic search, an assess- for clarification.
ment of the quality of individual studies, or a Disease-Oriented Outcomes. These out- system to label the strength of recommenda- comes include intermediate, histopathologic, tions explicitly.
physiologic, or surrogate results (e.g., blood Research Evidence. This evidence is pre- sugar, blood pressure, flow rate, coronary sented in publications of original research, plaque thickness) that may or may not reflect involving collection of original data or the improvement in patient outcomes.
systematic review of other original research Patient-Oriented Outcomes. These are out- publications. It does not include editorials, comes that matter to patients and help them opinion pieces, or review articles (other than live longer or better lives, including reduced systematic reviews or meta-analyses).
morbidity, reduced mortality, symptom Review Article. A nonsystematic overview of improvement, improved quality of life, or a topic is a review article. In most cases, it is not based on an exhaustive, structured review Level of Evidence. The validity of an indi- of the literature and does not evaluate the vidual study is based on an assessment of its quality of included studies systematically.
study design. According to some methodolo- Systematic Reviews and Meta-Analyses. A gies,6 levels of evidence can refer not only to systematic review is a critical assessment of individual studies but also to the quality of existing evidence that addresses a focused evidence from multiple studies about a spe- clinical question, includes a comprehensive cific question or the quality of evidence sup- literature search, appraises the quality of stud- porting a clinical intervention. For purposes ies, and reports results in a systematic manner. of maintaining simplicity and consistency in If the studies report comparable quantitative this proposal, we use the term "level of evi- data and have a low degree of variation in their dence" to refer to individual studies.
findings, a meta-analysis can be performed to Strength of Recommendation. The strength derive a summary estimate of effect.
FEBRUARY 1, 2004 / VOLUME 69, NUMBER 3 www.aafp.org/afp AMERICAN FAMILY PHYSICIAN-549 Existing Strength-of-Evidence Scales
studies on the same topic. Only seven of the 40 systems identified and addressed all three In March 2002, the Agency for Healthcare of these key elements.6-11 Research and Quality (AHRQ) published a report that summarized the state-of-the-art Strength of Recommendation
in methods of rating the strength of evi- dence.5 The report identified a large number The authors of this article represent the of systems for rating the quality of individual major family medicine journals in the United studies: 20 for systematic reviews, 49 for ran- States and a large family medicine academic domized controlled trials, 19 for observational consortium. Our process began with a series studies, and 18 for diagnostic test studies. of e-mail exchanges, was developed during a It also identified 40 scales that graded the meeting of the editors, and continued through strength of a body of evidence consisting of another series of e-mail exchanges.
one or more studies.
We decided that our taxonomy for rating The authors of the AHRQ report proposed the strength of a recommendation should that any system for grading the strength of address the three key elements identified in evidence should consider three key elements: the AHRQ report: quality, quantity, and con- quality, quantity, and consistency. Quality is sistency of evidence. We also were commit- the extent to which the identified studies min- ted to creating a grading scale that could imize the opportunity for bias and is synony- be applied by authors with varying degrees mous with the concept of validity. Quantity is of expertise in evidence-based medicine and the number of studies and subjects included clinical epidemiology, and interpreted by phy- in those studies. Consistency is the extent to sicians with little or no formal training in which findings are similar between different these areas. We believed that the taxonomy should address the issue of patient-oriented evidence versus disease-oriented evidence MARK H. EBELL, M.D., M.S., is associate professor at Michigan State University Col- explicitly and be consistent with the informa- lege of Human Medicine, East Lansing, Mich., and deputy editor of evidence-based tion mastery framework proposed by Slawson medicine for American Family Physician. and Shaughnessy.2 JAY SIWEK, M.D., is professor and chair of the Department of Family Medicine at After considering these criteria and review- Georgetown University Medical Center, Washington, D.C. He is also the editor of ing the existing taxonomies for grading the American Family Physician. strength of a recommendation, we decided BARRY D. WEISS, M.D., is professor at University of Arizona College of Medicine, that a new taxonomy was needed to reflect Tucson, and editor of Family Medicine. the needs of our specialty. Existing grading STEVEN H. WOOLF, M.D., M.P.H., is professor in the family practice, preventive medi- scales were focused on a particular kind of cine, and community health departments at Virginia Commonwealth University School of Medicine, Richmond, Va. He is past North American editor for BMJ. study (e.g., prevention or treatment), were too complex, or did not take into account the type JEFFREY SUSMAN, M.D., is professor at the University of Cincinnati College of Medicine, Cincinnati, Ohio, editor of The Journal of Family Practice, and editor for the American Academy of Family Physicians' Home Study Self-Assessment monographs.
Our proposed taxonomy is called the BERNARD EWIGMAN, M.D., M.P.H., is professor at the University of Chicago, Pritzker Strength of Recommendation Taxonomy School of Medicine, Chicago, and editor for the Family Practice Inquiries Network.
(SORT). It is shown in Figure 1. The tax- MARJORIE BOWMAN, M.D., M.P.A., is professor at the University of Pennsylvania onomy includes ratings of A, B, or C for the Health System, Philadelphia, Pa., and editor of the Journal of the American Board of strength of recommendation for a body of Family Practice. evidence. The table in the center of Figure 1 Address correspondence to Mark Ebell, M.D., M.S., 330 Snapfinger Dr., Athens, GA explains whether a body of evidence represents 30605 (e-mail: ebell@msu.edu). Reprints are not available from the authors. good-quality or limited-quality evidence, and whether evidence is consistent or inconsistent. 550-AMERICAN FAMILY PHYSICIAN www.aafp.org/afp VOLUME 69, NUMBER 3 / FEBRUARY 1, 2004 Strength of Recommendation Taxonomy (SORT)
In general, only key recommendations for readers require a grade of the "Strength of Recommendation." Recommendations should be based on the highest quality evidence available. For example, vitamin E was found in some cohort studies (level 2 study quality) to have a benefit for cardiovascular protection, but good-quality randomized trials (level 1) have not confirmed this effect. Therefore, it is preferable to base clinical recommendations in a manuscript on the level 1 studies.
Strength of recommendation Definition Recommendation based on consistent and good-quality patient-oriented evidence.* Recommendation based on inconsistent or limited-quality patient-oriented evidence.* Recommendation based on consensus, usual practice, opinion, disease-oriented evidence,* or case series for studies of diagnosis, treatment, prevention, or screening. Use the following table to determine whether a study measuring patient-oriented outcomes is of good or limited quality, and whether the results are consistent or inconsistent between studies.
Study quality Diagnosis Prognosis Level 1—good-quality Validated clinical decision rule SR/meta-analysis of RCTs with SR/meta-analysis of good-quality patient-oriented SR/meta-analysis of high-quality consistent findings High-quality individual RCT‡ Prospective cohort study with High-quality diagnostic cohort All-or-none study§ Level 2—limited-quality Unvalidated clinical decision rule SR/meta-analysis of lower-quality SR/meta-analysis of lower-quality patient-oriented SR/meta-analysis of lower-quality clinical trials or of studies with cohort studies or with studies or studies with inconsistent findings inconsistent results inconsistent findings Lower-quality clinical trial‡ Retrospective cohort study or Lower-quality diagnostic cohort prospective cohort study with study or diagnostic case-control Case-control study Case-control study Level 3—other Consensus guidelines, extrapolations from bench research, usual practice, opinion, disease-oriented evidence (intermediate or physiologic outcomes only), or case series for studies of diagnosis, treatment, prevention, or screening Consistency across studies Most studies found similar or at least coherent conclusions (coherence means that differences are explainable) If high-quality and up-to-date systematic reviews or meta-analyses exist, they support the recommendation Considerable variation among study findings and lack of coherence If high-quality and up-to-date systematic reviews or meta-analyses exist, they do not find consistent evidence in favor of the recommendation *—Patient-oriented evidence measures outcomes that matter to patients: morbidity, mortality, symptom improvement, cost reduction, and quality of life. Disease-oriented evidence measures intermediate, physiologic, or surrogate end points that may or may not reflect improvements in patient outcomes (e.g., blood pressure, blood chemistry, physiologic function, pathologic findings).
†—High-quality diagnostic cohort study: cohort design, adequate size, adequate spectrum of patients, blinding, and a consistent, well- defined reference standard.
‡—High-quality RCT: allocation concealed, blinding if possible, intention-to-treat analysis, adequate statistical power, adequate follow-up (greater than 80 percent).
§—In an all-or-none study, the treatment causes a dramatic change in outcomes, such as antibiotics for meningitis or surgery for appen-dicitis, which precludes study in a controlled trial. FIGURE 1. The Strength of Recommendation Taxonomy. (SR = systematic review; RCT = randomized controlled trial) FEBRUARY 1, 2004 / VOLUME 69, NUMBER 3 www.aafp.org/afp AMERICAN FAMILY PHYSICIAN-551 Strength of Recommendation Based on a Body of Evidence
Level of Evidence for an Individual Study
Is this a key recommendation for clinicians regarding diagnosis or Is the study a key citation for an important point of evidence Level of evidence not treatment that merits a label? under discussion? Is the recommendation based on patient-oriented evidence Is the key outcome of the study based on patient-oriented (i.e., an improvement in morbidity, mortality, symptoms, quality evidence (i.e., an improvement in morbidity, mortality, of life, or cost)? symptoms, quality of life, or cost)? Level of evidence = 3 Recommendation = C Is the recommendation based on opinion, bench research, a Is the study based on opinion, bench research, a consensus consensus guideline, usual practice, clinical experience, or a guideline, usual practice, clinical experience, or a case series? case series study? Is the study one of the following? Is the recommendation based on one of the following? 1. Systematic review/meta-analysis of high-quality studies with • Cochrane Review with a clear recommendation Strength of Recom- consistent findings • USPSTF Grade A recommendation 2. High-quality randomized controlled trial • Clinical Evidence rating of Beneficial • Allocation concealed Level of evidence = 1 • Consistent findings from at least two good-quality randomized • Blinding if possible controlled trials or a systematic review/meta-analysis of same • Intention-to-treat analysis • Validated clinical decision rule in a relevant population Strength of Recom- • Adequate size • Consistent findings from at least two good-quality diagnostic • Adequate follow-up (>80%) cohort studies or systematic review/meta-analysis of same 3. High-quality cohort study for prognosis (prospective, with >80% follow-up) FIGURE 2. Algorithm for determining the strength of a recommendation based on a body of 4. Validated clinical decision rule in a relevant population Level of evidence = 2 evidence (applies to clinical recommendations regarding diagnosis, treatment, prevention, or 5. High-quality diagnostic cohort study screening). While this algorithm provides a general guideline, authors and editors may adjust • Adequate size the strength of recommendation based on the benefits, harms, and costs of the intervention • Adequate spectrum of patients being recommended. (USPSTF = U.S. Preventive Services Task Force) • Consistent reference standard FIGURE 3. Algorithm for determining the level of evidence for an individual study.
The quality of individual studies is rated 1, 2, improvements in disease-oriented outcomes or 3; numbers are used to distinguish ratings of are not always associated with improvements individual studies from the letters A, B, and C in patient-oriented outcomes, as exemplified used to evaluate the strength of a recommen- by several well-known findings from the med- dation based on a body of evidence. Figure 2 ical literature. For example, doxazosin lowers provides information about how to determine blood pressure in black patients—a seemingly the strength of recommendation for manage- beneficial outcome—but it also increases ment recommendations, and Figure 3 explains mortality rates.12 Similarly, encainide and fle- how to determine the level of evidence for an cainide reduce the incidence of arrhythmias individual study. These two algorithms should after acute myocardial infarction, but they be helpful to authors preparing papers for also increase mortality rates.13 Finasteride submission to family medicine journals. The improves urinary flow rates, but it does not algorithms are to be considered general guide- significantly improve urinary tract symptoms lines, and special circumstances may dictate in patients with benign prostatic hypertro- assignment of a different strength of recom- phy,14 while arthroscopic surgery for osteoar- mendation (e.g., a single, large, well-designed thritis of the knee improves the appearance of study in a diverse population may warrant an cartilage but does not reduce pain or improve joint function.15 Additional examples of clini- Recommendations based only on improve- cal situations where disease-oriented evidence ments in surrogate or disease-oriented out- conflicts with patient-oriented evidence are comes are always categorized as level C, because shown in Table 1.12-24 Examples of how to 552-AMERICAN FAMILY PHYSICIAN www.aafp.org/afp VOLUME 69, NUMBER 3 / FEBRUARY 1, 2004 Level of Evidence for an Individual Study
Is the study a key citation for an important point of evidence Level of evidence not under discussion? Is the key outcome of the study based on patient-oriented evidence (i.e., an improvement in morbidity, mortality, symptoms, quality of life, or cost)? Level of evidence = 3 Is the study based on opinion, bench research, a consensus guideline, usual practice, clinical experience, or a case series? Is the study one of the following?1. Systematic review/meta-analysis of high-quality studies with consistent findings 2. High-quality randomized controlled trial • Allocation concealed Level of evidence = 1 • Blinding if possible • Intention-to-treat analysis • Adequate size • Adequate follow-up (>80%) 3. High-quality cohort study for prognosis (prospective, with >80% follow-up) 4. Validated clinical decision rule in a relevant population Level of evidence = 2 5. High-quality diagnostic cohort study • Adequate size • Adequate spectrum of patients • Consistent reference standard FIGURE 3. Algorithm for determining the level of evidence for an individual study.
apply the taxonomy are given in Table 2.
a clear recommendation that is strong (A), We believe there are several advantages to moderate (B), or weak (C) in its support of a our proposed taxonomy. It is straightforward particular intervention outweighs the theoretic and comprehensive, is easily applied by authors benefit of distinguishing between lower quality and physicians, and explicitly addresses the and higher quality observational studies, par- issue of patient-oriented versus disease-ori- ticularly because there is no objective evidence ented evidence. The latter attribute distin- that the latter distinction carries important dif- guishes SORT from most other evidence-grad- ferences in clinical recommendations.
ing scales. These strengths also create some Any publication applying SORT (or any limitations. Some clinicians may be concerned other evidence-based taxonomy) should that the taxonomy is not as detailed in its describe carefully the search process that assessment of study designs as others, such as preceded the assignment of a SORT rat- that of the Centre for Evidence-Based Medicine ing. For example, authors could perform a (CEBM).25 However, the primary difference comprehensive search of MEDLINE and the between the two taxonomies is that the CEBM gray literature, a comprehensive search of version distinguishes between good and poor MEDLINE alone, or a more focused search observational studies while the SORT version of MEDLINE plus secondary evidence-based does not. We concluded that the advantages sources of information.
of a system that provides the physician with FEBRUARY 1, 2004 / VOLUME 69, NUMBER 3 www.aafp.org/afp AMERICAN FAMILY PHYSICIAN-553 TABLE 1
Examples of Inconsistency Between Disease-Oriented and Patient-Oriented Outcomes
Disease or condition Disease-oriented outcome Doxazosin for blood pressure12 Reduces blood pressure in blacks Increases mortality Lidocaine for arrhythmia following Suppresses arrhythmias Increases mortality acute myocardial infarction13 Finasteride for benign prostatic Improves urinary flow rate No clinically important change in symptom scores Arthroscopic surgery for osteoarthritis Improves appearance of cartilage No change in function or symptoms at one year after débridement Sleeping infants on their stomach Knowledge of anatomy and physiology Increases risk of sudden infant death syndrome suggests that this will decrease the risk of aspiration Vitamin E for heart disease17 Reduces levels of free radicals No change in mortality Histamine antagonists and proton- Significantly reduce gastric pH levels Little or no improvement in symptoms in patients pump inhibitors for nonulcer with nongastroesophageal reflux disease, nonulcer dyspepsia Hormone therapy19 Reduces low-density lipoprotein No decrease in cardiovascular or all-cause mortality cholesterol levels, increases and an increase in cardiovascular events in high-density lipoprotein cholesterol women older than 60 years (Women's Health Initiative) with combined hormone ther- Insulin therapy in type 2 diabetes Keeps blood glucose levels below Does not reduce overall mortality 120 mg per dL (6.7 mmol per L) Sodium fluoride for fracture Increases bone density Does not reduce fracture rate Lidocaine prophylaxis following Suppresses arrhythmias Increases mortality acute myocardial infarction22 Clofibrate for hyperlipidemia23 Reduces lipid levels Does not reduce mortality Beta blockers for heart failure24 Reduce cardiac output Reduce mortality in moderate to severe disease Information from references 12 through 24. TABLE 2
Examples of How to Apply the Strength of Recommendation Taxonomy in Practice
Example 1: While 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. The strength of recommendation against routine, long-term use of vitamin E to prevent heart disease, based on the best available evidence, should be A.
Example 2: A Cochrane review finds seven clinical trials that are consistent in their support of a mechani- cal intervention for low back pain, but the trials were poorly designed (i.e., 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: A meta-analysis finds nine high-quality clinical trials of the use of a new drug in the treatment of pulmonary fibrosis. Two of the studies find harm, two find no benefit, and five show some benefit. The strength of recommendation in favor of this drug would be B (inconsistent results of good-quality, randomized controlled trials).
Example 4: A new drug increases the forced expiratory volume in one 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 is C (disease-oriented evidence only).
554-AMERICAN FAMILY PHYSICIAN www.aafp.org/afp VOLUME 69, NUMBER 3 / FEBRUARY 1, 2004 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 and
A. Consistent level 1 studies
good-quality patient-oriented evidence
B. Recommendation based on inconsistent or
B. Consistent level 2 or 3 studies
Likely to be beneficial limited-quality patient-oriented evidence or extrapolations from level 1 Likely to be ineffective or harmful (recommendation against) C. Level 4 studies or extrapolations
Unlikely to be beneficial from level 2 or 3 studies (recommendation against) C. Recommendation based on consensus, usual
D. Level 5 evidence or troublingly
Unknown effectiveness practice, disease-oriented evidence, case series for inconsistent or inconclusive studies of treatment or screening, and/or opinion studies of any level SORT = Strength of Recommendation Taxonomy; CEBM = Centre for Evidence-Based Medicine; BMJ = BMJ Publishing Group. tery approach and to incorporate evidence- Walkovers: Creating Linkages
based medicine into their patient care.
with SORT
Like any such grading scale, it is a work in Some organizations, such as the CEBM,25 progress. As we learn more about biases in the Cochrane Collaboration,7 and the U.S. study design, and as the authors and read- Preventive Services Task Force,6 have devel- ers who use the taxonomy become more oped their own grading scales for the strength sophisticated about principles of information of recommendation based on a body of evi- mastery, evidence-based medicine, and critical dence and are unlikely to abandon them. appraisal, it is likely to evolve. We remain open Other organizations, such as the FPIN,26 pub- to suggestions from the primary care commu- lish their work in a variety of settings and nity for refining and improving SORT.
must be able to move between taxonomies. We have developed a set of optional walkovers The authors thank Lee Green, M.D., M.P.H., John that suggest how authors, editors, and readers Epling, M.D., Kurt Stange, M.D., Ph.D., and Mar-garet Gourlay, M.D., for helpful comments on the might move from one taxonomy to another. Walkovers for the CEBM and BMJ Clinical Evidence taxonomies are shown in Table 3.
Many authors and experts in evidence- Suggested Walkover Between the SORT and the CEBM Tax-
based medicine use the "Level of Evidence" onomies for Assessing the Level of Evidence of an
taxonomy from the CEBM to rate the quality Individual Study
of individual studies.25 A walkover from the five-level CEBM scale to the simpler three- level SORT scale for individual studies is shown in Table 4.
SORT Level Other categories The SORT is a comprehensive taxonomy for Level 4 or 5 and any study Level 5 and any study that evaluating the strength of a recommendation that measures intermediate measures intermediate or based on a body of evidence and the quality or surrogate outcomes surrogate outcomes of an individual study. If applied consistently by authors and editors in the family medicine CEBM = Centre for Evidence-Based Medicine; SORT = Strength of Recommenda- literature, it has the potential to make it easier tion Taxonomy. for physicians to apply the results of research in their practice through the information mas- FEBRUARY 1, 2004 / VOLUME 69, NUMBER 3 www.aafp.org/afp AMERICAN FAMILY PHYSICIAN-555 The authors indicate that they do not have any randomized to doxazosin vs chlorthalidone: the conflicts of interest. Sources of funding: none antihypertensive and lipid-lowering treatment to prevent heart attack trial (ALLHAT) [published cor-rection in JAMA 2002;288:2976]. JAMA 2000; Simultaneously published in print and online by 13. Echt DS, Liebson PR, Mitchell LB, Peters RW, Obias- American Family Physician, Journal of Family Prac- Manno D, Barker AH, et al. Mortality and morbid- tice, Journal of the American Board of Family Prac- ity in patients receiving encainide, flecainide, or tice and online by Family Practice Inquiries Network. placebo. N Engl J Med 1991;324:781-8.
Copyright 2004 American Family Physician, a 14. Lepor H, Williford WO, Barry MJ, Brawer MK, publication of the American Academy of Family Dixon CM, Gormley G, et al. The efficacy of Physicians. All rights reserved. terazosin, finasteride, or both in benign prostatic hyperplasia. N Engl J Med 1996;335:533-9.
15. Moseley JB, O'Malley K, Petersen NJ, Menke TJ, Brody BA, Kuykendall DH, et al. A controlled trial of 1. Evidence-based medicine. A new approach to arthroscopic surgery for osteoarthritis of the knee. teaching the practice of medicine. JAMA 1992; N Engl J Med 2002;347:81-8.
16. Dwyer T, Ponsonby AL. Sudden infant death syn- 2. Slawson DC, Shaughnessy AF, Bennett JH. Becom- drome: after the "back to sleep" campaign. BMJ ing a medical information master: feeling good about not knowing everything. J Fam Pract 1994; 17. Yusuf S, Dagenais G, Pogue J, Bosch J, Sleight P. Vitamin E supplementation and cardiovascular 3. Shaughnessy AF, Slawson DC, Bennett JH. Becoming events in high-risk patients. N Engl J Med 2000; an information master: a guidebook to the medical information jungle. J Fam Pract 1994;39:489-99.
18. Moayyedi P, Soo S, Deeks J, Delaney B, Innes 4. Siwek J, Gourlay ML, Slawson DC, Shaughnessy M, Forman D. Pharmacological interventions for AF. How to write an evidence-based clinical review non-ulcer dyspepsia. Cochrane Database Syst Rev article. Am Fam Physician 2002;65:251-8.
5. Systems to rate the strength of scientific evidence. 19. Rossouw JE, Anderson GL, Prentice RL, LaCroix Summary, evidence report/technology assessment: AZ, Kooperberg C, Stefanick ML, et al. Risks and number 47. AHRQ publication no. 02-E015, March benefits of estrogen plus progestin in healthy 2002. Agency for Healthcare Research and Quality, postmenopausal women: principal results from the Rockville, Md. Accessed November 13, 2003, at: Women's Health Initiative randomized controlled trial. JAMA 2002;288:321-33.
20. Intensive blood-glucose control with sulphonyl- 6. Harris RP, Helfand M, Woolf SH, Lohr KN, Mulrow ureas or insulin compared with conventional CD, Teutsch SM, et al. Current methods of the treatment and risk of complications in patients U.S. Preventive Services Task Force: a review of the with type 2 diabetes (UKPDS 33). Lancet 1998; process. Am J Prev Med 2001;20(3 suppl):21-35.
7. Clarke M, Oxman AD. Cochrane reviewers' hand- 21. Meunier PJ, Sebert JL, Reginster JY, Briancon D, book 4.2.0. The Cochrane Collaboration, 2003. Appelboom T, Netter P, et al. Fluoride salts are no Accessed November 13, 2003, at: http://www. better at preventing new vertebral fractures than calcium-vitamin D in postmenopausal osteoporo- 8. Gyorkos TW, Tannenbaum TN, Abrahamowicz sis: the FAVOStudy. Osteoporos Int 1998;8:4-12.
M, Oxman AD, Scott EA, Millson ME, et al. An 22. MacMahon S, Collins R, Peto R, Koster RW, Yusuf approach to the development of practice guide- S. Effects of prophylactic lidocaine in suspected lines for community health interventions. Can J acute myocardial infarction. An overview of results Public Health 1994;85(suppl 1):S8-13.
from the randomized, control ed trials. JAMA 9. Briss PA, Zaza S, Pappaioanou M, Fielding J, Wright-De Aguero L, Truman BI, et al. Developing 23. Grumbach K. How effective is drug treatment of an evidence-based guide to community preventive hypercholesterolemia? A guided tour of the major services—methods. Am J Prev Med 2000;18(1 clinical trials for the primary care physician. J Am Board Fam Pract 1991;4:437-45.
10. Greer N, Mosser G, Logan G, Halaas GW. A practi- 24. Heidenreich PA, Lee TT, Massie BM. Effect of beta- cal approach to evidence grading. Jt Comm J Qual blockade on mortality in patients with heart failure: a meta-analysis of randomized clinical trials. J Am 11. Guyatt GH, Haynes RB, Jaeschke RZ, Cook DJ, Coll Cardiol 1997;30:27-34.
Green L, Naylor CD, et al. Users' guides to the 25. Centre for Evidence-Based Medicine. Levels of evi- medical literature: XXV. Evidence-based medicine: dence and grades of recommendation. Accessed principles for applying the users' guides to patient November 13, 2003, at: http://www.cebm.net/ care. JAMA 2000;284:1290-6.
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Genetics and Molecular Biology, 27, 4, 605-610 (2004) Copyright by the Brazilian Society of Genetics. Printed in Brazil A genetic algorithm for the ligand-protein docking problem Camila S. de Magalhães1, Hélio J.C. Barbosa1 and Laurent E. Dardenne21Laboratório Nacional de Computação Científica, Departamento de Matemática Aplicada e Computacional, Petrópolis, RJ, Brazil.

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European Heart Journal (2014) 35, 2797–2811 New strategies for heart failure with preservedejection fraction: the importance of targetedtherapies for heart failure phenotypes Michele Senni1, Walter J. Paulus2, Antonello Gavazzi1, Alan G. Fraser3, Javier Dı´ez4,Scott D. Solomon5, Otto A. Smiseth6, Marco Guazzi7, Carolyn S. P. Lam8,Aldo P. Maggioni9, Carsten Tscho¨pe10, Marco Metra11, Scott L. Hummel12,13,Frank Edelmann14, Giuseppe Ambrosio15, Andrew J. Stewart Coats16,17,Gerasimos S. Filippatos18, Mihai Gheorghiade19, Stefan D. Anker20,21,Daniel Levy22,23,24, Marc A. Pfeffer5, Wendy Gattis Stough25, and Burkert M. Pieske26*