Strength of Recommendations Taxonomy(SORT)

The Strength of Recommendations Taxonomy (SORT) grades clinical evidence with a patient-centered focus, considering both the overall evidence and the quality of individual studies. It addresses the following three key elements of rating the strength of evidence:

• Quality: Assesses the validity of studies by minimizing bias.

• Quantity: Considers the number of studies and subjects involved.

• Consistency of Evidence: Evaluates the similarity of findings across studies on the same topic.

Multiple U.S. family medicine and primary care journals, including American Family Physician and The Journal of Family Practice, historically used diverse evidence-grading scales, creating confusion for readers. Over 100 different scales exist, and even the same letter grade (e.g., level B) may have different meanings across journals or articles. To address this, editors from key journals and the Family Practice Inquiries Network (FPIN) developed a unified taxonomy for the strength of recommendations.^[1] This system was designed to:

• Be consistent across publications.

• Allow evaluation of both a body of evidence and individual studies.

• Cover screening, diagnosis, therapy, prevention, and prognosis.

• Remain simple and practical for authors, reviewers, editors, and clinicians.

*-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)^[1]

The table below demonstrates how to evaluate whether a study measuring patient-oriented outcomes is of good or limited quality.

*-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 all-or-none study, the treatment causes a dramatic change in outcomes, such as antibiotics for meningitis or surgery for appendicitis, which precludes study in a controlled trial.^[1]

^[1]

Following two algorithms can be used to determine the strength of recommendations and level of evidence for an individual study respectively.

*Algorithm for determining the strength of a recommendation based on a body of evidence (applies to clinical recommendations regarding diagnosis, treatment, prevention, or screening). While 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 = U.S. Preventive Services Task Force).

The above two algorithms have been adopted from AAFP SORT Recommendation Scheme^[1]

• SORT takes into account the outcomes of a study, unlike other grading systems that focus only on a specific type of study (e.g., prevention or treatment) or are too complex.
• SORT clearly distinguishes between patient-oriented and disease-oriented evidence, which sets it apart from most other grading systems.
• SORT does not distinguish high- and low-quality observational studies like CEBM. Instead, it gives clear recommendations—strong (A), moderate (B), or weak (C)—for specific interventions. This approach is more practical, as there is no evidence that distinguishing observational study quality significantly alters clinical guidance.

Following tables provide information for authors, editors, and readers to transition between different taxonomies, with examples for Centre for Evidence-Based Medicine and British Medical Journal Clinical Evidence. shown below.^[1]

AAFP SORT Scheme.