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Guideline Summary
Guideline Title
Recommendations from the EGAPP Working Group: can tumor gene expression profiling improve outcomes in patients with breast cancer?
Bibliographic Source(s)
Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. Recommendations from the EGAPP Working Group: can tumor gene expression profiling improve outcomes in patients with breast cancer. Genet Med. 2009 Jan;11(1):66-73. PubMed External Web Site Policy
Guideline Status

This is the current release of the guideline.

Scope

Disease/Condition(s)

Stage I or stage II node-negative female breast cancer

Guideline Category
Evaluation
Management
Risk Assessment
Technology Assessment
Clinical Specialty
Medical Genetics
Oncology
Pathology
Radiation Oncology
Surgery
Intended Users
Advanced Practice Nurses
Health Care Providers
Health Plans
Managed Care Organizations
Physician Assistants
Physicians
Utilization Management
Guideline Objective(s)

To provide recommendations regarding tumor gene expression profiling in women with newly diagnosed, stage I or II, node-negative breast cancer

Target Population

Women with newly diagnosed, stage I or II, node-negative breast cancer

Interventions and Practices Considered
  1. Tumor gene expression testing:
    • MammaPrint® test in women with newly diagnosed, stage I or II, node negative, estrogen receptor (ER) positive or negative breast cancer
    • Oncotype DX® test in women with newly diagnosed, stage I or II, node negative, ER-positive breast cancer
    • Quest H:I test® in women with newly diagnosed, stage I or II, node negative, ER-positive breast cancer
  2. Counseling and patient education
Major Outcomes Considered

Analytic Validity

  • Analytic sensitivity and specificity of tumor gene expression profiling tests in breast cancer
  • Technical performance of assays (e.g., reproducibility, assay failure rates, robustness, quality control)

Clinical Validity

  • Clinical sensitivity and specificity
  • Tests ability to accurately and reliably identify or predict the disorder or phenotype of interest, in this case prediction of overall survival or recurrence-free survival 5-10 years after surgery versus avoidance of chemotherapy toxicity and quality of life.

Clinical Utility

  • Influence of tumor gene expression profiling (testing) on clinical management
  • Influence of tumor gene expression profiling (testing) on health-related outcomes (reduced adverse events, prevention of cancer recurrence)
  • Clinical utility is assessed by investigating the balance of benefits (reduced adverse events due to low risk women avoiding chemotherapy) and harms (cancer recurrence that might have been prevented) associated with the use of the test, and how that compares to the use of alternative management strategies.

Methodology

Methods Used to Collect/Select the Evidence
Hand-searches of Published Literature (Primary Sources)
Hand-searches of Published Literature (Secondary Sources)
Searches of Electronic Databases
Searches of Unpublished Data
Description of Methods Used to Collect/Select the Evidence

Note from the National Guideline Clearinghouse (NGC): An evidence review commissioned by the Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group (EWG) and funded by the Office of Public Health Genomics (OPHG) at the Centers for Disease Control and Prevention (CDC) was prepared by the Johns Hopkins University Evidence-Based Practice Center (EPC) under contract to the Agency for Healthcare Research and Quality (AHRQ). (See the "Availability of Companion Documents" field).

Key Questions

The core EPC team worked with the technical experts and representatives of the EGAPP and AHRQ to develop the Key Questions:

Key Question 1. What is the direct evidence that gene expression profiling tests in women diagnosed with breast cancer (or any specific subset of this population) lead to improvement in outcomes?

Key Question 2. What are the sources of and contributions to analytic validity in these gene expression-based prognostic estimators for women diagnosed with breast cancer?

Key Question 3. What is the clinical validity of these tests in women diagnosed with breast cancer?

  1. How well does this testing predict recurrence rates for breast cancer when compared to standard prognostic approaches? Specifically, how much do these tests add to currently known factors or combination indices that predict the probability of breast cancer recurrence (e.g., tumor type or stage, estrogen receptor [ER] and human epidermal growth factor receptor 2 [HER-2] status)?
  2. Are there any other factors, which may not be components of standard predictors of recurrence (e.g., race/ethnicity or adjuvant therapy), that affect the clinical validity of these tests and thereby the generalizability of the results to different populations?

Key Question 4. What is the clinical utility of these tests?

  1. To what degree do the results of these tests predict the response to chemotherapy, and what factors affect the generalizability of that prediction?
  2. What are the effects of using these two tests and the subsequent management options on the following outcomes: testing- or treatment-related psychological harms, testing or treatment-related physical harms, disease recurrence, mortality, utilization of adjuvant therapy, and medical costs?
  3. What is known about the utilization of gene expression profiling in women diagnosed with breast cancer in the United States?
  4. What projections have been made in published analyses about the cost-effectiveness of using gene expression profiling in women diagnosed with breast cancer?

Literature Search Methods

Searching the literature involved identifying reference sources, formulating a search strategy for each source, and executing and documenting each search. For the searching of electronic databases medical subject heading (MeSH) terms were used that were relevant to breast cancer and gene expression profiling. A systematic approach for searching the literature to minimize the risk of bias in selecting articles for inclusion in the review was used. In this systematic approach, the team was very specific about defining the eligibility criteria for inclusion in the review. The systematic approach was intended to help identify gaps in the published literature.

This strategy was used to identify all the relevant literature that applied to our Key Questions. The EPC team specifically looked for articles that would provide information about the gene expression profiling tests identified in the Key Questions. The team also looked for eligible studies by reviewing the references in eligible studies and pertinent reviews, by querying experts, by contacting the manufacturers of the two tests, and by reviewing abstracts from relevant professional conferences.

Sources

The comprehensive search plan included electronic and hand searching. On January 9, 2007, the team ran searches of the MEDLINE® and EMBASE® databases, and on February 7, 2007, the team searched the Cochrane database, including Cochrane Reviews and The Cochrane Central Register of Controlled Trials (CENTRAL), and CINAHL®. All searches were limited to articles published in 1990 or later. This cut-off year was established based on the introduction date of the MeSH heading "gene expression profiling," 2000, and the introduction date of the MeSH heading "gene expression," 1990. Also, test searches of earlier dates returned limited and irrelevant results.

"Gray" literature was searched following a protocol that was reviewed and approved by EGAPP and the technical expert panel:

  1. Conference abstracts were reviewed using the same criteria as for journal articles but were only included if the EPC team felt they had a sufficient understanding of the underlying study and the data reported were critical enough to merit inclusion.
  2. Web sites for the gene profiling tests included in this review, Agendia (MammaPrint®) and Genomic Health (Oncotype DX™), were searched for additional information not available in the peer-reviewed literature.
  3. Agendia and Genomic Health, Inc. were contacted directly with requests for the following information:
    1. A listing of articles that applied to the analytic validity or clinical utility of the gene profiling test
    2. Marketing materials on the gene profiling test
    3. Any pertinent unpublished data
  4. The Web site of the Food and Drug Administration (FDA) Center for Devices and Radiological Health was searched for additional publicly available, unpublished information.
  5. A request was sent to the Center for Medical Technology Policy (CMTP) Gene Expression Profiling for Early Stage Breast Cancer Work Group to provide all background materials available on the study topic.

Search Terms and Strategies

Search strategies specific to each database were designed to enable the team to focus available resources on articles most likely to be relevant to the Key Questions. The EPC team developed a core strategy for MEDLINE, accessed via PubMed, based on an analysis of the MeSH terms and text words of key articles identified a priori. The PubMed strategy formed the basis for the strategies developed for the other electronic databases.

Abstract Review

Inclusion and Exclusion Criteria

The abstract review phase was designed to identify articles that reported on the analytic validity, clinical validity, and/or clinical utility of the gene expression profile tests of interest. Abstracts were reviewed independently by two investigators and were excluded only if both investigators agreed that the article met one of the following exclusion criteria:

  1. The study applied only to breast cancer biology
  2. The study did not involve Oncotype DX or MammaPrint
  3. The study did not involve original data or original data analysis
  4. The study did not involve women
  5. The study did not involve breast cancer patients
  6. The study was not in the English language
  7. The study did not apply to the key questions

Letters to the editor and editorials were excluded when they did not present original data (usually in the form of electronic supplements in the case of letters). If a letter or editorial cited some original data, it generally was not sufficiently original for consideration in this report.

Abstracts were promoted to the article review level if both reviewers agreed that the abstract could apply to one or more of the key questions. Differences of opinion regarding abstract eligibility were resolved through consensus adjudication.

Article Inclusion/Exclusion

Full articles selected for review during the abstract review phase underwent another independent review by paired investigators to determine whether they should be included in the full data abstraction. At this phase of review, investigators determined which of the Key Questions each article addressed. If articles were deemed to have applicable information, they were included in the final data abstraction.

Differences of opinion regarding article eligibility were resolved through consensus adjudication.

See Appendices F, G, and H of the companion document "Impact of Gene Expression Profiling Tests on Breast Cancer Outcomes." (See the "Availability of Companion Documents" field for more details.)

Number of Source Documents

21 studies were included

Methods Used to Assess the Quality and Strength of the Evidence
Weighting According to a Rating Scheme (Scheme Given)
Rating Scheme for the Strength of the Evidence

The EGAPP Working Group (EWG) ranks individual studies as Good, Fair, or Marginal based on critical appraisal using the criteria in Tables 3 and 4 (of Teutsch et al., 2009; see "Availability of Companion Documents" field). The designation Marginal (rather than Poor) acknowledges that some studies may not have been "poor" in overall design or conduct, but may not have been designed to address the specific key question in the evidence review.

Methods Used to Analyze the Evidence
Review of Published Meta-Analyses
Systematic Review with Evidence Tables
Description of the Methods Used to Analyze the Evidence

Note from the National Guideline Clearinghouse (NGC): An evidence review commissioned by the Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group (EWG) and funded by the Office of Public Health Genomics (OPHG) at the Centers for Disease Control and Prevention (CDC) was prepared by the Johns Hopkins University Evidence-based Practice Center (EPC) under contract to the Agency for Healthcare Research and Quality (AHRQ). (See the "Availability of Companion Documents" field).

Quality Assessment

The EPC team used a synthesis of the general principles of the REporting recommendations for tumour MARKer prognostic studies (REMARK) and Standards for Reporting of Diagnostic Accuracy (STARD) guidelines.

Because of the extreme variability of the articles included in this report, the team did not systematically apply the general principles to them. The strengths and weaknesses of each study were also dependent on the question(s) to which it applied (see the companion document "Impact of Gene Expression Profiling Tests on Breast Cancer Outcome [see the "Availability of Companion Documents" field]). The EPC team appraised economic analyses using published guidelines for good practice in decision-analytic modeling in health technology assessment. The appraisal took into consideration the domains of structure, data, and consistency.

Data Synthesis

The team created a set of detailed evidence tables containing all the information extracted from eligible studies and stratified the tables according to the gene expression profile test. The investigators reviewed the tables and eliminated items that were rarely reported. They then used the resulting versions of the evidence tables to prepare the text of the report and selected summary tables.

Data Entry and Quality Control

Initial data were abstracted by the investigators and entered directly into the data abstraction tables. Second reviewers were generally more experienced members of the research team, and one of their main priorities was to check the quality and consistency of the first reviewers' answers. In addition to the second reviewers checking the consistency and accuracy of the first reviewers, a senior investigator examined all reviews to identify problems with the data abstraction. If problems were recognized in a reviewer's data abstraction, the problems were discussed at a meeting with the reviewers. In addition, research assistants used a system of random data checks to assure data abstraction accuracy.

Grading of the Evidence

After reviewing the available evidence on the Key Questions, the core team concluded that it would be inappropriate to grade the overall body of evidence using any of the published schemes for grading evidence. None of the grading schemes fit the nature of the data in these studies about gene expression profiling tests. The team therefore decided that it was more appropriate to focus on the specific strengths and weaknesses of the studies on each Key Question.

Methods Used to Formulate the Recommendations
Expert Consensus
Description of Methods Used to Formulate the Recommendations

Note from the National Guideline Clearinghouse (NGC): An evidence review commissioned by the Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group (EWG) and funded by the Office of Public Health Genomics (OPHG) at the Centers for Disease Control and Prevention (CDC) was prepared by the Johns Hopkins University Evidence-Based Practice Center (EPC) under contract to the Agency for Healthcare Research and Quality (AHRQ). (See the "Availability of Companion Documents" field).

EGAPP Working Group (EWG) members reviewed the evidence report, key primary publications, other sources of information, and comments on the evidence report from the test developers and a group of eight peer reviewers. The process also included assessment of key gaps in knowledge and relevant contextual factors (e.g., availability of diagnostic or therapeutic alternatives, feasibility and practicality of implementation, cost-effectiveness). The final EWG recommendation statement was formulated based on magnitude of effect, certainty of evidence, and consideration of contextual factors.

Key factors considered in the development of a recommendation are: the relative importance of the outcomes selected for review; the benefits (e.g., improved clinical outcome, reduction of risk) that result from the use of the test and subsequent actions or interventions (or if not available, maximum potential benefits); the harms (e.g., adverse clinical outcome, increase in risk or burden) that result from the use of the test and subsequent actions/interventions (or if not available, largest potential harms); and the efficacy and effectiveness of the test and follow-up compared with currently used interventions (or doing nothing). Simple decision models or outcomes tables may be used to assess the magnitudes of benefits and harms, and estimate the net effect. Consistent with the terminology used by the USPSTF, the magnitude of net benefit (benefit minus harm) may be classified as Substantial, Moderate, Small, or Zero.*

Standard EGAPP language for recommendation statements uses the terms: Recommend For, Recommend Against, or Insufficient Evidence (Table 6 in Teutsch et al., 2009). Because the types of emerging genomic tests addressed by EGAPP are more likely to have findings of Insufficient Evidence, three additional qualifiers may be added. Based on the existing evidence and consideration of contextual issues and modeling, Insufficient Evidence could be considered "Neutral" (not possible to predict with current evidence), "Discouraging" (discouraged until specific gaps in knowledge are filled or not likely to meet evidentiary standards even with further study), and "Encouraging" (likely to meet evidentiary standards with further studies or reasonable to use in limited situations based on existing evidence while additional evidence is gathered).

Teutsch SM, Bradley LA, Palomaki GE, Haddow JE, Piper M, Calonge N, Dotson WD, Douglas MP, Berg AO; EGAPP Working Group. The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) initiative: methods of the EGAPP Working Group. Genet Med. 2009 Jan;11(1):3-14.

*Sawaya GF, Guirguis-Blake J, LeFevre M, et al. Update on methods of the U.S. Preventive Services Task Force: estimating certainty and magnitude of net benefit. Ann Intern Med 2007;147:871-5.

Rating Scheme for the Strength of the Recommendations

Recommendations Based on Certainty of Evidence, Magnitude of Net Benefit, and Contextual Issues

High or Moderate Recommend for:
  • If the magnitude of net benefit is Substantial, Moderate, or Small, unless additional considerations warrant caution.
  • Consider the importance of each relevant contextual factor and its magnitude or finding.
Recommend against:
  • If the magnitude of net benefit is Zero or there are net harms.
  • Consider the importance of each relevant contextual factor and its magnitude or finding.
Low Insufficient evidence:
  • If the evidence for clinical utility or clinical validity is insufficient in quantity or quality to support conclusions or make a recommendation.
  • Consider the importance of each contextual factor and its magnitude or finding.
  • Determine whether the recommendation should be Insufficient (neutral), Insufficient (encouraging), or Insufficient (discouraging).
  • Provide information on key information gaps to drive a research agenda.

Teutsch SM, Bradley LA, Palomaki GE, Haddow JE, Piper M, Calonge N, Dotson WD, Douglas MP, Berg AO; EGAPP Working Group. The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) initiative: methods of the EGAPP Working Group. Genet Med. 2009 Jan;11(1):3-14.

Cost Analysis

Two of three studies addressing the potential cost-effectiveness of gene expression profile tests concluded that use of one gene expression profile test (Oncotype DX) would be "relatively cost-effective" for those defined as low risk, and cost saving for those at high risk. However, concerns about the parameter estimates, lack of sensitivity analyses to assess sources of bias, and changes in the National Comprehensive Cancer Network (NCCN) guidelines reduce the confidence and relevance of one of these studies. The second study had substantial limitations in the descriptions of the model structure, assumptions and comparators, as well as deficiencies in data specification, utilities, and sensitivity analyses. Both studies were sponsored by the manufacturer. The EWG judged this body of evidence to be inconclusive.

An earlier study, meeting most standards for appraising the quality of an economic analysis, projected that MammaPrint would result in an absolute 5% decrease in the proportion of distant recurrence cases prevented and would yield slightly fewer quality-adjusted life years, but would marginally lower total costs ($2882 in United States dollars). The authors suggested the need for further validation before use in clinical practice.

Method of Guideline Validation
Comparison with Guidelines from Other Groups
External Peer Review
Internal Peer Review
Description of Method of Guideline Validation

The guideline developers reviewed recommendations from the National Comprehensive Cancer Network (NCCN) and the American Society of Clinical Oncologists (ASCO), and a policy statement from ECRI Institute.

Recommendations

Major Recommendations

Summary of Recommendation

The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group (EWG) found insufficient evidence to make a recommendation for or against the use of tumor gene expression profiles to improve outcomes in defined populations of women with breast cancer. For one test, the EWG found preliminary evidence of potential benefit of testing results to some women who face decisions about treatment options (reduced adverse events due to low risk women avoiding chemotherapy), but could not rule out the potential for harm for others (breast cancer recurrence that might have been prevented). The evidence is insufficient to assess the balance of benefits and harms of the proposed uses of the tests. The EWG encourages further development and evaluation of these technologies.

Rationale

The measurement of gene expression in breast tumor tissue is proposed as a way to estimate the risk of distant disease recurrence in order to provide additional information beyond current clinicopathological risk stratification and to influence decisions about treatment in order to improve health outcomes. Based on their review of the EGAPP-commissioned evidence report, Impact of Gene Expression Profiling Tests on Breast Cancer Outcomes and other data summaries, the EWG found no direct evidence linking tumor gene expression profiling of women with breast cancer to improved outcomes, and inadequate evidence to construct an evidence chain. However, further evaluation on the clinical utility of some tests and management algorithms, including well-designed randomized controlled trials, is warranted.

Analytic Validity: Some data on technical performance of assays were identified for MammaPrint and Oncotype DX, though estimates of analytic sensitivity and specificity could not be made. Published performance data on the laboratory developed Quest H:I Test were limited. Overall, the EWG found the evidence to be inadequate.

Clinical Validity: The EWG found adequate evidence regarding the association of the Oncotype DX Recurrence Score with disease recurrence and adequate evidence for response to chemotherapy. The EWG found adequate evidence to characterize the association of MammaPrint with future metastases, but inadequate evidence to assess the added value to standard risk stratification, and could not determine the population to which the test would best apply. The evidence was inadequate to characterize the clinical validity of the Quest H:I Test.

Clinical Utility: The EWG found no evidence regarding the clinical utility of the MammaPrint and Quest H:I Ratio tests, and inadequate evidence regarding Oncotype DX. These technologies have potential for both benefit and harm.

Contextual Issues: The EWG reviewed economic studies that used modeling to predict potential effects of using gene profiling, and judged the evidence inadequate.

Clinical Considerations

Definitions Used by EGAPP

  • Analytic validity refers to a test's ability to accurately and reliably measure the genotype or analyte of interest, in this case the expression of mRNA by breast cancer tumor cells.
  • Clinical validity defines the ability of the test to accurately and reliably identify or predict the intermediate or final outcomes of interest. This is usually reported as clinical sensitivity and specificity.
  • Clinical utility defines the balance of benefits and harms associated with the use of the test in practice, including improvement in measureable clinical outcomes and usefulness/added value in clinical management and decision-making compared with not using the test.

Patient Population under Consideration

These recommendations apply to individuals diagnosed with Stage I or Stage II, node-negative breast cancer. Tumors may be estrogen receptor (ER) positive or negative for MammaPrint testing, but must be estrogen receptor positive to be eligible for Oncotype DX or Quest H:I testing.

Considerations for Practice

  • Until more data are available, clinicians must decide on a case by case basis if the use of a gene expression profile test adds value beyond the use of the current prognostic markers (and how to weigh and combine these risks), and if each test's validation population is relevant to their patients' age, disease status, and race/ethnicity.
  • If a clinician considers use of gene expression profiling in an individual with newly diagnosed breast cancer, provision of counseling and educational materials is suggested to inform the patient about both the potential benefits and harms associated with testing and discuss whether the test results are likely to change the patient's decision about therapy.

Contextual Issues Important to the Recommendation

  • The use of gene expression profiling tests in this clinical scenario provides the potential for significant benefit but also potential for harm. More work is needed to better understand the balance of benefits and harms.
  • No firm guidance can be given to clinicians on how MammaPrint and Oncotype DX results can be acted upon until data are available from the TAILORx and MINDACT trials.
  • Studies of changes to clinical management using the Oncotype DX test are minimally informative because they have not specified the information actually given to the patient or how clinicians combine test results with other risk factors to limit or expand therapeutic choices. Consequently, it cannot be determined whether documented changes in management are due to compliance with physician recommendations, with weighing of risks and benefits, or reflect the effects of test marketing.
  • Better understanding of risk tolerance in women will be needed to identify patients who might benefit most from testing and to help direct discussion with women about the potential risks and benefits of the tests. What is the recurrence risk below which women are comfortable with a decision to decline chemotherapy? How does the presentation of risk affect choices?
  • A future scenario with a proliferation of competing licensed products without comparative effectiveness data has potential to confuse patients and clinicians, and not deliver on the potential improvement in clinical outcomes that the current evidence individually suggests.

Definitions:

Recommendations Based on Certainty of Evidence, Magnitude of Net Benefit, and Contextual Issues

High or Moderate Recommend for:
  • If the magnitude of net benefit is Substantial, Moderate, or Small, unless additional considerations warrant caution.
  • Consider the importance of each relevant contextual factor and its magnitude or finding.
Recommend against:
  • If the magnitude of net benefit is Zero or there are net harms.
  • Consider the importance of each relevant contextual factor and its magnitude or finding.
Low Insufficient evidence:
  • If the evidence for clinical utility or clinical validity is insufficient in quantity or quality to support conclusions or make a recommendation.
  • Consider the importance of each contextual factor and its magnitude or finding.
  • Determine whether the recommendation should be Insufficient (neutral), Insufficient (encouraging), or Insufficient (discouraging).
  • Provide information on key information gaps to drive a research agenda.

Teutsch SM, Bradley LA, Palomaki GE, Haddow JE, Piper M, Calonge N, Dotson WD, Douglas MP, Berg AO; EGAPP Working Group. The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) initiative: methods of the EGAPP Working Group. Genet Med. 2009 Jan;11(1):3-14.

Clinical Algorithm(s)

None provided

Evidence Supporting the Recommendations

Type of Evidence Supporting the Recommendations

The type of supporting evidence is not specifically stated for each recommendation.

Benefits/Harms of Implementing the Guideline Recommendations

Potential Benefits
  • Improved professional and consumer understanding of the use of tumor gene profiling in patients with newly diagnosed, stage I and II, node-negative breast cancer
  • Inform a translational research agenda by identifying gaps in knowledge that might be addressed in future research.
Potential Harms

Not stated

Qualifying Statements

Qualifying Statements
  • This recommendation statement is a product of the independent Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. Although the Centers for Disease Control and Prevention (CDC) provides support to the EGAPP Working Group, including staff support in the preparation of this document, recommendations made by the EGAPP Working Group should not be construed as official positions of the CDC or the U.S. Department of Health and Human Services.
  • The EGAPP Working Group found the research literature insufficient, but encouraging in many respects, and recommends further studies that could address important gaps in knowledge. See the original guideline document for a detailed lists of gaps in the research.

Implementation of the Guideline

Description of Implementation Strategy

An implementation strategy was not provided.

Institute of Medicine (IOM) National Healthcare Quality Report Categories

IOM Care Need
Living with Illness
IOM Domain
Effectiveness
Patient-centeredness

Identifying Information and Availability

Bibliographic Source(s)
Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. Recommendations from the EGAPP Working Group: can tumor gene expression profiling improve outcomes in patients with breast cancer. Genet Med. 2009 Jan;11(1):66-73. PubMed External Web Site Policy
Adaptation

Not applicable: The guideline was not adapted from another source.

Date Released
2009 Jan
Guideline Developer(s)
Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group - Independent Expert Panel
Guideline Developer Comment

This recommendation statement is a product of the independent EGAPP Working Group. Although the Centers for Disease Control and Prevention (CDC) provides support to the EGAPP Working Group, including staff support in the preparation of this document, recommendations made by the EGAPP Working Group should not be construed as official positions of the CDC or the U.S. Department of Health and Human Services.

Source(s) of Funding

United States Government

Guideline Committee

The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group

Composition of Group That Authored the Guideline

Group Members: Alfred O. Berg, MD, MPH (University of Washington) (Chair); Katrina Armstrong, MD, MSCE (University of Pennsylvania School of Medicine); Jeffrey Botkin, MD, MPH (University of Utah); Ned Calonge, MD, MPH (Colorado Department of Public Health and Environment); James Haddow, MD (The Warren Alpert Medical School of Brown University); Maxine Hayes, MD, MPH (Washington State Department of Health); Celia Kaye, MD, PhD (University of Colorado School of Medicine); Kathryn A. Phillips, PhD (University of California, San Francisco); Margaret Piper, PhD, MPH (Blue Cross/Blue Shield Association Technology Evaluation Center); Carolyn Sue Richards, PhD, FACMG (Oregon Health & Science University); Joan A. Scott, MS, CGC (Johns Hopkins University); Ora L. Strickland, PhD, DSc (Hon.), RN, FAAN (Emory University); Steven Teutsch, MD, MPH (Merck & Co.)

Financial Disclosures/Conflicts of Interest

Steven Teutsch is an employee, option and stock holder in Merck & Co., Inc.

Margaret Piper is employed by the Blue Cross Blue Shield Association Technology Evaluation Center and has previously authored a technology assessment on breast cancer gene expression profiling. TEC Assessment Program 2008;22(13):1-51. Available at: http://www.bcbs.com/blueresources/tec/vols/22/22_13.pdf External Web Site Policy.

Guideline Status

This is the current release of the guideline.

Guideline Availability
Availability of Companion Documents

The following are available:

  • Systematic review: gene expression profiling assays in early-stage breast cancer. Ann Intern Med. 2008;148:358-369. Electronic copies: Available from the Annals of Internal Medicine External Web Site Policy.
  • Impact of gene expression profiling tests on breast cancer outcomes. Evidence Report/Technology Assessment No. 160. (Prepared by the Johns Hopkins University Evidence-based Practice Center, Baltimore, MD under Contract No. 290-02-0018.) AHRQ Publication No. 08-E002. Rockville (MD): Agency for Healthcare Research and Quality. 2008 Jan. 230 p. Electronic copies: Available from the AHRQ Web site External Web Site Policy.
  • The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) initiative: methods of the EGAPP Working Group. 2009 Jan. 12 p. Available from the Genetics in Medicine Journal External Web Site Policy and the Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Web site External Web Site Policy.
Patient Resources

None available

NGC Status

This NGC summary was completed by ECRI Institute on February 20, 2009. The information was verified by the guideline developer on July 23, 2009.

Copyright Statement

This NGC summary is based on the original guideline: Recommendations from the EGAPP Working Group: can tumor gene expression profiling improve outcomes in patients with breast cancer. Genet Med 2009 Jan;11(1):66-73. ©American College of Medical Genetics. Reprinted with permission of Lippincott Williams & Wilkins.

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