Elsevier Editorial Policy for Off-Label Data within Drug Information Products and Databases
Date last reviewed: March 5, 2015
I. Background and Summary
The United States Food and Drug Administration (FDA) focuses on regulating the approval of prescription drugs rather than regulating the prescribing practices of physicians. Therefore, the use of medications for indications beyond those formally evaluated is allowable in medical clinical practice.
The full and ultimate use of a drug is rarely evident at the time of initial FDA-approval or marketing. The discovery and clinical adoption of new uses for marketed drugs or for investigational drugs often precedes FDA approval of such uses. In some cases, as in treatments for rare diseases or for underserved populations, there may be substantial literature evidence and/or clinical experience, yet little financial incentive, for a manufacturer to pursue FDA approval. A 1996 GAO report (Prescription Drugs, Implications of Drug Labeling and Off-Label Use) has shown that “off-label” drug use (e.g., the use of a drug for an indication not approved by the FDA) is substantial in situations where satisfactory treatment is not available and that there are lower rates of off-label use when there is an effective therapy.
An expected role of any drug compendia in regards to off-label drug use listings is to consolidate published scientific literature and to provide the user quick access to appropriate information that may assist in making a decision regarding the appropriate use of the drug for a specific patient. Our team of medical professionals recognizes the importance of emerging therapies that promote medical advancements in the treatment of human disease and health conditions. The exclusive inclusion of only “labeled” information (e.g., uses for or information about a drug approved by the FDA and included within the FDA-approved product labeling) within our database would limit the utility and scope of our information to clinicians. Elsevier drug information includes off-label indications and other clinical data for drug therapy that may be outside the scope of the FDA-approved drug product labeling. Off-label data may be included in the monographs of FDA-approved drugs, investigational drugs, or dietary supplements.
The Elsevier drug information editorial team is committed to providing unbiased, comprehensive drug information that is accurate, clinically relevant, and current. In order to represent such best practices in drug therapy, the Elsevier drug information editorial team follows a policy for content style and production, which includes a specific policy regarding off-label drug indication data.
II. Identifying Off-Label Drug Indication Data
Off-label drug indication data are included in our drug information database when identified as a clinically relevant or emerging treatment by the drug information editorial team. Off-label data are primarily identified by the drug information editorial team for inclusion in the database through regular and comprehensive review of:
Primary published literature
New or updated national practice guidelines
Surveillance of other accepted sources of medical information (e.g., FDA, CDC, NIH communications)
Dialogue with customers or other external reviewers of our content
The Elsevier drug information editorial team will review external requests to add off-label indication information. External requests are handled in the same manner as those indications identified through the internal review processes.
III. Review and Evaluation of Off-Label (e.g; non-FDA approved) Drug Indications
Elsevier conducts a thorough search of primary literature and other accepted sources of information to identify relevant, published information, including negative or equivocal findings. Searches ensure that relevant and timely publications are considered. After the research is completed, the evidence is reviewed and independently evaluated by the Elsevier drug information editorial team. Elsevier will rate all off-label indications using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system.1-6 Each off-label use will be assigned a quality of evidence rating and a strength of recommendation by the Elsevier drug information editorial team. Because many studies may be used to evaluate a single off-label use, each individual study will be graded for quality of evidence; the results of the individual ranking will be combined to provide an overall quality of evidence and strength of recommendation for each off-label use.
The GRADE system provides guidelines for evaluating and rating the quality of evidence and utilizes four (4) quality of evidence levels:
High
Moderate
Low
Very Low
Initially, a well-designed randomized phase III trial receives a “High” quality of evidence level. Factors that may cause the quality of evidence to be downgraded to a lower quality level include study design flaws, inconsistent results from other studies, imprecise results (e.g., small patient numbers, wide confidence intervals), use of study endpoints that are disease focused vs. patient focused (e.g., overall response rate vs. overall survival, LDL cholesterol concentration vs. myocardial infarction or stroke), and other biases, including publication bias. When multiple studies are used to evaluate an off-label use, the Elsevier Drug Information Editorial Team will use a modified approach to GRADE to assign the overall quality of evidence; the studies with the lowest quality of evidence for the most critically important outcome will be used to assign the overall quality of evidence for the off-label use.
GRADE utilizes two grades or strengths of recommendation: Strong and Weak. The strength of recommendation is primarily derived by evaluating the risks vs. benefits of the recommendation to the alternatives, the quality of the evidence, the variability in the importance of the risks and benefits to the patients and clinicians (i.e., an outcome that is important to most patients such as preventing a stroke vs. the inconvenience of warfarin in atrial fibrillation is more likely to receive a strong recommendation), and resources or costs of the intervention.
Strong Recommendation:
An off-label use that carries a Strong Recommendation “For” or “Against” use, with any level of evidence, should be considered binding and reflect that Elsevier recommends or does not recommend, respectively, the use of the drug for that indication in the situation described. All off-label uses with a strong level of recommendation will appear in the referential database and be clearly identified as recommended or not recommended; however, a strong recommendation “Against use” will not be found within the clinical decision support data.
Equivocal/Weak Recommendation:
Off-label uses that have inconclusive data “For” or “Against” use carry a Weak Recommendation. A Weak recommendation, with any level of evidence, reflects a neutral or equivocal position (i.e., neither for or against use) by Elsevier. All off-label uses with a weak level of recommendation will appear in the referential database and be clearly identified as equivocal; however, a weak recommendation “Against use” will not be found within the clinical decision support data.
The documentation of off-label data includes all evidentiary references and will include a summary of the evidence in descriptive fashion. All off-label indications, dosage, and related data are clearly designated within the content of our products.
IV. Internal Peer-Review
The Elsevier Drug Information Editorial Policy governs all clinical drug data production. A peer-review process is ensured via the editorial policy and our electronic drug data production systems.
V. External Peer-Review
Content may be sent for external review and validation to a member of the external Elsevier Editorial Board, or to a Board member within other Elsevier publishing efforts who exhibits expertise in the area of question.
VI. Conflict of Interest
All editorial staff members must comply with Elsevier Drug Information Conflict of Interest Policy. In addition, all external reviewers must comply with the Elsevier Conflict of Interest policy for external reviewers.
VII. Citations for Grading of Recommendations Assessment, Development and Evaluation (GRADE)
Guyatt GH, Oxman AD, Vist G, Kunz R, Falck-Ytter Y, Alonso-Coello P, Schünemann HJ, for the GRADE Working Group. Rating quality of evidence and strength of recommendations GRADE: an emerging consensus on rating quality of evidence and strength of recommendations.
Guyatt GH, Oxman AD, Kunz R, Vist GE, Falck-Ytter Y, Schünemann HJ; GRADE Working Group. Rating quality of evidence and strength of recommendations: What is “quality of evidence” and why is it important to clinicians?
BMJ. 2008 May 3;336(7651):995-8 abre em uma nova guia/janela
Schünemann HJ, Oxman AD, Brozek J, Glasziou P, Jaeschke R, Vist GE, Williams JW Jr, Kunz R, Craig J, Montori VM, Bossuyt P, Guyatt GH; GRADE Working Group. Grading quality of evidence and strength of recommendations for diagnostic tests and strategies.
BMJ. 2008 May 17;336(7653):1106-10 abre em uma nova guia/janela
Guyatt GH, Oxman AD, Kunz R, Jaeschke R, Helfand M, Liberati A, Vist GE, Schünemann HJ; GRADE working group. Rating quality of evidence and strength of recommendations: Incorporating considerations of resources use into grading recommendations.
BMJ. 2008 May 24;336(7654):1170-3 abre em uma nova guia/janela
Guyatt GH, Oxman AD, Kunz R, Falck-Ytter Y, Vist GE, Liberati A, Schünemann HJ; GRADE Working Group. Rating quality of evidence and strength of recommendations: Going from evidence to recommendations.
BMJ. 2008 May 10;336(7652):1049-51 abre em uma nova guia/janela
Jaeschke R, Guyatt GH, Dellinger P, Schünemann H, Levy MM, Kunz R, Norris S, Bion J; GRADE working group. Use of GRADE grid to reach decisions on clinical practice guidelines when consensus is elusive.