Disclaimer
This information collection is a core HTA, i.e. an extensive analysis of one or more health technologies using all nine domains of the HTA Core Model. The core HTA is intended to be used as an information base for local (e.g. national or regional) HTAs.

Prognostic tests for breast cancer recurrence (uPA/PAI-1 [FEMTELLE], MammaPrint, Oncotype DX )

UPA/PAI-1 (FEMTELLE), MammaPrint, Oncotype DX compared to Standard of care in selecting treatment for Breast cancer recurrence in females

(See detailed scope below)

HTA Core Model Application for Diagnostic Technologies (1.1)
Core HTA
Published
Tom Jefferson (age.na.s, Italy), Nicola Vicari (age.na.s, Italy), Heike Raatz (SNHTA, Switzerland)
Sarah Baggaley, NICE (Health problem and current use); Antonio Migliore, Agenas (Description and technical characteristics); Iris Pasternack, THL-FINOHTA (Safety); Mirjana Huic, AAZ (Clinical effectiveness), Isaura Vieira, INFARMED (Costs and economic evaluation); Dario Sacchini, A.Gemelli (Ethical analysis); Jennifer Butt, NICE (Organisational aspects); Marco Marchetti, A.Gemelli (Social and Legal aspects)
Agenzia nationale per i servizi sanitari regionali (age.na.s), Italy
A. Gemelli (Italy), AAZ (Croatia), Agenas (Italy), AHTAPol (Poland), AVALIA-t (Spain), INFARMED (Portugal), IPH-RS (Slovenia), NICE (United Kingdom), Regione Veneto (Italy), SNHTA (Switzerland), THL (Finland), UMIT (Austria)
13.6.2011 14.00.00
31.1.2013 18.05.00
Jefferson T, Vicari N, Raatz H [eds.]. Prognostic tests for breast cancer recurrence (uPA/PAI-1 [FEMTELLE], MammaPrint, Oncotype DX ) [Core HTA], Agenzia nationale per i servizi sanitari regionali (age.na.s), Italy ; 2013. [cited 24 October 2021]. Available from: http://corehta.info/ViewCover.aspx?id=113

Prognostic tests for breast cancer recurrence (uPA/PAI-1 [FEMTELLE], MammaPrint, Oncotype DX )

<< SafetyCosts and economic evaluation >>

Clinical Effectiveness

Authors: Authors: Mirjana Huic, Narine Sahakyan, Gurleen Jhuti, Anna Panasiuk, Heike Raatz, Petra Schnell-Inderst, Katarzyna Sejbuk, Eva Turk, Marjetka Jelenc

Summary

Aim: The primary aim of this assessment was to determine whether, compared with current practice, using the three prognostic tests (uPA/PAI-1, MammaPrint® and Oncotype DX®) to guide the use of adjuvant chemotherapy effectively improves long-term clinical outcomes, safety (adverse events due to adjuvant chemotherapy) and quality of life in women with early-stage breast cancer. The secondary aims were to assess changes both in clinical decisions about the choice of treatment with adjuvant chemotherapy and in patient satisfaction.

Methods: As currently only three applications of the HTA (health technology assessment) Core Model exist (medical and surgical interventions, diagnostic technologies, and screening technologies), the Core Model for Diagnostic technologies was used. A number of HTA Core assessment elements questions for diagnostic technologies are not suited for prognostic technologies and prognostic or predictive accuracy was not assessed. A systematic review was done according to Cochrane methodology. Only a qualitative synthesis was planned.

Results: Overall, 4539 references were available for screening, with 15 observational studies included in the qualitative synthesis. There are no randomised controlled trials (RCTs) or prospective cohort studies that determined whether using these three prognostic tests to help guide the use of adjuvant chemotherapy effectively improves long-term clinical outcomes compared with current practice. A number of ongoing RCTs will not give direct evidence on these important clinical outcomes. Oncotype DX influenced the physicians’ adjuvant treatment recommendation in 19–51% of patients. Using MammaPrint would have resulted in altered treatment advice in up to 40% of patients.

Quality of life remained stable according to the Functional Assessment of Cancer Therapy 12 months after the Oncotype DX test recurrence score (RS). So-called state or situational anxiety (STAI) mean scores decreased significantly over time. More than 90% of patients continued to feel satisfied that they had used the RS assay and were satisfied with their treatment decision 12 months after the RS assay. Only five patients, who were not satisfied, noted a negative impact on quality of life, treatment side-effects including aches, hot flashes, pain, mood alteration, and a negative impact on self image. Most women (95%) reported that they would have the Oncotype DX test again if they had to decide today, and would recommend the test to other women.

Further high quality evidence on uPA/PAI-1, Oncotype DX and MammaPrint tests from RCTs is needed to guide the use of adjuvant chemotherapy in women with early invasive breast cancer. There is a clear need for communication, at an early stage, between the manufacturers and the European Medicines Agency (EMA), the US Food and Drug Administration (FDA) and the HTA bodies on so-called “early scientific advice” for designing RCTs.

Introduction

The Clinical Effectiveness Domain describes the spectrum and extent of beneficial effects on health and quality of life expected through the use of the technology {1}.

There are still no gold standard tools or guidelines to assist decision-making relating to adjuvant chemotherapy in women with early-stage breast cancer. This may result either in unnecessary use of chemotherapy with short- or long-term serious adverse drug reactions or in avoidable death if chemotherapy was withheld.

The primary aim of our assessment was to determine whether use of the three prognostic tests (uPA/PAI-1, MammaPrint® and  Oncotype DX®) to guide the use of adjuvant chemotherapy improves long-term clinical outcomes, safety (adverse events due to adjuvant chemotherapy) and quality of life in women with early-stage breast cancer compared with current practice. The secondary aims were to evaluate the impact of prognostic tests on clinical decision making and patients’ satisfaction.

Currently there are only three applications of the HTA Core Model: medical and surgical interventions, diagnostic technologies, and screening technologies. The Core Model for diagnostic technologies was selected as the most appropriate for assessing the clinical effectiveness of the three prognostic tests. However, there are fundamental differences in the assessment of diagnostic and prognostic tests. Some HTA Core assessment element questions for diagnostic technologies are thus not suited for prognostic technologies {2}. The methodology for designing and assessing genetic risk prediction models is still developing, and methods specific to conducting a systematic review of a prognostic test are not well established {3}.

A prognostic factor or prognostic marker is any patient or tumour characteristic that is predictive of the patient’s outcome. Outcomes are usually measured in terms of overall survival and/or disease-free survival. A prognostic index is a quantitative set of values based on the results of a prognostic model. A prognostic model is a statistical combination of at least two separate prognostic variables used to predict a patient outcome.

A predictive factor or predictive marker is defined as any patient or tumour characteristic that is predictive of the patient’s response to a specified treatment. Response is usually measured in terms of overall survival and/or disease-free survival. A predictive model is a statistical combination of at least two predictive factors used to predict the response to a specified treatment {4}.

A prognostic test is used to estimate a patient’s likelihood of developing a disease or experiencing a medical event over time. The “reference test” is the observed probability of developing the event being predicted within prognostic groups, and is defined by the predicted probabilities that are estimated using the prognostic test. The predictive accuracy of a prognostic test is evaluated as the difference between the observed and predicted outcome probabilities within prognostic groups {2}.

A separate category of prognostic test is a test that predicts responsiveness to treatment (success or adverse effects). Predictive genetic tests are characterised by a delayed time between testing and observing clinically important outcomes. Many prognostic tests, unlike diagnostic tests, are based on multivariable regression models {2}.

The only reliable evidence on whether a prognostic test does more good than harm are well conducted RCTs (randomised controlled trials; gold standard methodology for research into the effectiveness of an intervention, so-called “direct evidence”) with a study population representative of those eligible for the prognostic test. The control group should receive usual care. A problem in evaluating predictive genetic tests is that direct evidence for the impact of the test results on health outcomes is often lacking.

As stated for diagnostic technologies, inferences regarding the effectiveness of prognostic technologies are often based on so-called “linked evidence” from studies on accuracy, change in management and treatment effectiveness, because test treatment RCTs are rare. If the clinical endpoints (patient-relevant endpoints) are not available then surrogate endpoints may be used to indicate or predict clinically important outcomes {1}. To be valid, it must have been shown that the effect on the surrogate correlates sufficiently with the effect on the outcome of interest {5}.

The authors of a recent systematic review of RCTs on positron emission tomography (PET) stated that, in addition to diagnostic and prognostic accuracy studies, RCTs on PET should be conducted to prove its benefit in terms of patient-relevant outcomes. Despite the fact that 12 RCTs have already been published on PET, and 5 will be published per year in the future, the authors stressed that more high quality RCTs on PET are needed to prove its benefit for patients. They also pointed out that funding is usually difficult because RCTs are not yet mandatory for the approval of non-drug interventions {6}.

The majority of previous HTAs and systematic reviews of clinical effectiveness of prognostic genetic tests have used frameworks for the evaluation of genetic tests developed by the United States Preventive Services Task Force, the CDC (US Centers for Disease Control and Prevention), and EGAPP (Evaluation of Genomic Applications in Practice and Prevention). These examine: (1) analytical validity (technical accuracy and reliability), (2) clinical validity (ability to detect or predict an outcome, disorder, or phenotype), and (3) clinical utility (whether use of the test to direct clinical management improves patient outcomes) (Box 1). A fourth criterion has also been added: (4) ethical, legal, and social implications {2, 7}.

Box 1. Definitions of analytic validity, clinical validity and clinical utility {2, 7}

Analytic validity

the ability of the test to accurately and reliably measure the expression of mRNA or proteins by breast cancer tumour cells

Clinical validity

the degree to which the test could accurately predict the risk of an outcome and discriminate patients with different outcomes

Clinical utility

the utility of the test in relation to harm, evidence of improvement in clinical outcomes and healthcare costs, impact on clinical decision making

There is no consensus on the meaning/definition of clinical utility and multiple perspectives have been adopted. Direct evidence of clinical utility of a gene expression profile can only be provided in the context of a randomised clinical trial where benefit can be measured in terms of an improvement of clinical outcomes such as overall survival, disease-free survival, chemotherapy toxicity or quality of life {8-11}. Well-designed clinical trials should be used to assess the clinical utility of markers, multiple markers or a comprehensive set of markers, a unit or classifier. Four clinical trial designs for assessing the clinical utility of a predictive marker have been described: (1) Marker by treatment interaction design, separate tests; (2) Marker by treatment interaction design, test of interaction; (3) Marker-based strategy design and (4) Modified marker-based strategy design {12}.

Methodology

Frame

A modified collection scope is used in this domain.

TechnologyuPA/PAI-1 (FEMTELLE), MammaPrint, Oncotype DX
Description

Urokinase plasminogen activator /plasminogen activator inhibitor 1 ELISA (uPA/PAI-1) is a registered enzyme-linked immunoassay (ELISA) kit (FEMTELLE) for the analysis of uPA/PAI-1 in fresh frozen tissue and is being provided by American Diagnostica Inc. It is CE marked in Europe but for research use only in the USA. Other commercial ELISA kits for separate in-house analysis of uPA and/or PAI-1 are available from different suppliers. These also use samples other than tissue and are also used for indications other than cancer {1}.

Technical details:

- Inspection of unfixed tissue

- Removal of a representative piece of tumour tissue (>50 mg)

- Freezing of the unfixed tissue (-20°C or colder)

- Storage of the frozen tissue (-20°C or colder) possible up to 3 weeks

Clinical Laboratory (Pathology, Hospital)

- Transport of frozen tumour tissue on dry ice

- Extraction of uPA and PAI-1

- Perform FEMTELLE uPA/PAI-1 ELISA

- Transfer of test results to physician

Costs for FEMTELLE including preparation, shipping and analysis of samples in a qualified laboratory amount to €400 (http://www.hkk.de/info/aktuelles/brustkrebs_tumorprognosetest). In house analysis with separate ELISA kits costs about €200.

Possible logistic issues to consider are {2}:

- Relatively large samples are needed. Given that the mean tumour size is <2 cm in many centres, this means that a substantial part of the tissue may be lacking for light microscopic investigation.

- Many centres no longer routinely freeze breast tissue and therefore lack the expensive equipment for this process.

Oncotype DX (Genomic Health) quantifies gene expression for 21 genes in breast cancer tissue by real-time reverse transcriptase-polymerase chain reaction (RT-PCR).

MammaPrint (Agendia) is a gene expression profiling platform based on microarray technology which uses a 70-gene expression profile {3}. The sample studied is fresh or frozen tissue. It has received 510(k) clearance from the FDA (premarket notification for medical devices), which also covers the use of Asuragen's RNARetain®, a room temperature, molecular fixative that supersedes freezing the tissue before shipment to the central US laboratory (www.agendia.com).

The test requires a fresh sample of tissue  composed of a minimum of 30% malignant cells and must be received by the company in their kit within 5 days of obtaining the material. The MammaPrint assay was developed on the basis of research initially conducted at the Netherlands Cancer Institute (Amsterdam) and collaborating institutions. Primary tumours from 117 patients with axillary lymph node-negative primary breast cancer were analysed on oligonucleotide microarrays. The data were subjected to supervised classification to establish a 70-gene RNA expression profile that correlated with a relatively short interval to distant metastases. [from NICE protocol and ASCO guideline]

Oncotype DX and MammaPrint have been evaluated and large-scale studies (TAILORx and MINDACT) are underway. The German Working Group for Gynecological Oncology1 (AGO) and the American Society of Clinical Oncology (ASCO) have recommended uPA/PAI-1 as risk-group-classification markers for routine clinical decision making in node-negative breast cancer, alongside established clinical and histomorphological factors.

Oncotype DX is recommended for node negative, oestrogen receptor-positive women and MammaPrint is applied in all early breast cancers. The tests are expensive: MammaPrint costs €2675 and Oncotype DX, US $3400.

RT-PCR and microarray analysis usually cost US $3500 or more. Oncotype and MammaPrint are not routinely covered by German statutory health insurance. MammaPrint is covered by Medicare and Medicaid in the USA (Pharmacogenomics Reporter: 23 December 2009; www.genomeweb.com.)

MeSH Terms:

There are no MeSH-Terms for Oncotype DX and MammaPrint.

Intended use of the technologyDefining an existing health condition in further detail to assist selection of appropriate or optimal treatment

Assessment of risk of breast cancer recurrence

Target condition
Breast cancer recurrence
Target condition description

Assessment of risk of breast cancer recurrence and likelihood of benefit from adjuvant treatment (particularly chemotherapy).

As testing for oestrogen receptor positivity is already considered to be part of the standard of care using these tests to decide on adjunctive treatment with Tamoxifen will not be considered part of the study question.

Target population

Target population sex: Female. Target population age: Any age except fetuses. Target population group: Patients who have the target condition.

Target population description

Women with invasive breast cancer in whom adjunctive treatment might be indicated

ComparisonStandard of care
Description

Standard care without any of the three index tests (uPA/PAI-1, MammaPrint, Oncotype DX).

Depending on manpower and time resources the three index tests may also be compared with each other.

More information

Our tests are prognostic tests, not diagnostic tests. Prognostic/predictive accuracy will not be assessed in this HTA Core Model for diagnostic technologies.

Assessment elements

TopicIssue RelevantResearch questions or rationale for irrelevance
D0010Change-in managementHow does the technology modify the need for hospitalization?yesDoes the test-treatment chain of uPA/PAI, Mammaprint, or Oncotype for adjuvant therapy reduce or increase the number of women (diagnosed with early stage, invasive breast cancer) requiring hospitalization or hospitalization due side-effects compared to treatment on the basis of the standard practice?
D0023Change-in managementHow does the technology modify the need for other technologies and use of resources?yesDo uPA/PAI, Mammaprint, or Oncotype compared to the standard practice in women diagnosed with early stage invasive breast cancer increase or decrease the probability of adjuvant therapy performed?
D0021Change-in managementDoes the use of the technology lead to a change in the physicians' management decisions?yesDid the results in uPA/PAI, Mammaprint, or Oncotype tests in women diagnosed with early stage invasive breast cancer lead to changes in the treatment choice with adjuvant therapy and/or further imaging compared to the standard practice?
D0020Change-in managementDoes the use of the technology lead to improved detection of the disease?noOur tests are prognostic tests, not diagnostic tests. Prognostic/predictive accuracy will not be assessed in this HTA Core Model for diagnostic technologies.
D0022Change-in managementDoes the use of technology detect other health conditions which have impact on the treatment decisions concerning the target condition?noOur tests are prognostic tests, not diagnostic tests.
D0012Function / HRQL (Health-related quality of life)What is the effect of the technology on health-related quality of life?yesWhat is the effect of adjuvant therapy on the basis of uPA/PAI, Mammaprint, or Oncotype test results on health related quality of life compared to treatment on the basis of the standard practice?
D0016Function / HRQL (Health-related quality of life)How does the use of technology affect activities of daily living?yesDoes adjuvant therapy on the basis of uPA/PAI, Mammaprint, or Oncotype test results compared to treatment on the basis of the standard practice affect their activities of daily living?
D0017Patient satisfactionWas the use of technology worth it?yesDo women diagnosed with early stage, invasive breast cancer feel that the guidance of their adjuvant therapy on the basis of uPA/PAI, Mammaprint, or Oncotype test results was worth it?
D0018Patient satisfactionWould the patient be willing to use the technology again?yesWould the patient be willing to use the technology (uPA/PAI or Mammaprint or Oncotype test) again?
D0030Patient satisfactionDoes the knowledge of the test result improve the patient's quality of life?yesDoes the knowledge of the tests results (uPA/PAI, Mammaprint, or Oncotype) improve the patient quality of life in women diagnosed with early stage invasive breast cancer compared to standard practice?
D0025Test-treatment chainWhat is the effect of the test-treatment intervention on mortality?yesWhat is the effect of adjuvant therapy on the basis of uPA/PAI, Mammaprint, or Oncotype test compared to treatment on the basis of the standard practice in women diagnosed with early stage invasive breast cancer on overall survival and disease specific survival (for example: disease-free-, progression free-, recurrence-free-survival)?
D0032Test-treatment chainHow does the test-treatment intervention modify the magnitude and frequency of morbidity?yesHow does the treatment with adjuvant therapy on the basis of the test results of uPA/PAI, Mammaprint, or Oncotype compared to treatment on the basis of the standard practice in women diagnosed with early stage invasive breast cancer modify the magnitude and frequency of morbidity?
D0024Test-treatment chainIs there an effective treatment for the condition the technology is detecting?noOur tests are prognostic tests, not diagnostic tests. Prognostic/predictive accuracy will not be assessed in this HTA Core Model for diagnostic technologies.
D0026MorbidityHow does the technology modify the effectiveness of subsequent interventions?yesDoes adjuvant therapy on the basis of genetic testing results (uPA/PAI, Mammaprint or Oncotype) compared to treatment on the basis of the standard practice in women diagnosed with early stage invasive breast cancer improve patient morbidity?
D0004MortalityWhat is the mortality related to the technology studied?noAs the tissue is usually being taken in a routine surgical procedure we could assume that it doesn’t add to the mortality of the surgery.
D0027Test accuracyWhat are the negative consequences of further testing and delayed treatment in patients with false negative test result?noOur tests are prognostic tests, not diagnostic tests. Prognostic/predictive accuracy will not be assessed in this HTA Core Model for diagnostic technologies.
D0028Test accuracyWhat are the negative consequences of further testing and treatments in patients with false positive test result?noOur tests are prognostic tests, not diagnostic tests. Prognostic/predictive accuracy will not be assessed in this HTA Core Model for diagnostic technologies.
D0029Test accuracyWhat are the overall benefits and harms in health outcomes considering the amount of false positive and false negative test results.noOur tests are prognostic tests, not diagnostic tests. Prognostic/predictive accuracy will not be assessed in this HTA Core Model for diagnostic technologies.
D1001Test accuracyWhat is the accuracy of the test against reference standard?noOur tests are prognostic tests, not diagnostic tests. Prognostic/predictive accuracy will not be assessed in this HTA Core Model for diagnostic technologies.
D1002Test accuracyHow does the technology compare to other optional diagnostic technologies in terms of accuracy measures?noOur tests are prognostic tests, not diagnostic tests. Prognostic/predictive accuracy will not be assessed in this HTA Core Model for diagnostic technologies.
D1003Test accuracyWhat is the reference standard and how likely does it classify the target condition correctly?noOur tests are prognostic tests, not diagnostic tests. Prognostic/predictive accuracy will not be assessed in this HTA Core Model for diagnostic technologies.
D1004Test accuracyWhat are the requirements for accuracy in the context the technology will be used?noOur tests are prognostic tests, not diagnostic tests. Prognostic/predictive accuracy will not be assessed in this HTA Core Model for diagnostic technologies.
D1005Test accuracyWhat is the optimal threshold value in this context?noOur tests are prognostic tests, not diagnostic tests. Prognostic/predictive accuracy will not be assessed in this HTA Core Model for diagnostic technologies.
D1006Test accuracyDoes the technology have the potential to reliably rule in or rule out the target condition?noOur tests are prognostic tests, not diagnostic tests. Prognostic/predictive accuracy will not be assessed in this HTA Core Model for diagnostic technologies.
D1007Test accuracyHow does test accuracy vary in different settings?noOur tests are prognostic tests, not diagnostic tests. Prognostic/predictive accuracy will not be assessed in this HTA Core Model for diagnostic technologies.
D1008Test accuracyWhat is known about the intra- and inter-observer variation in test interpretation?noOur tests are prognostic tests, not diagnostic tests. Prognostic/predictive accuracy will not be assessed in this HTA Core Model for diagnostic technologies.
D1019Test accuracyIs there evidence that the replacing technology is more specific or safer than the old one?noOur tests are prognostic tests, not diagnostic tests. Prognostic/predictive accuracy will not be assessed in this HTA Core Model for diagnostic technologies.
D0031SafetyWhat is the mortality and morbidity related to the diagnostic technology?noOur tests are prognostic tests, not diagnostic tests. This question belongs to safety domain and seems not to be relevant to genetic test.

Methodology description

Domain frame

Deviations from the project scope: More information:

The tests being investigated are prognostic tests, not diagnostic tests.

Because currently only three applications of the HTA Core Model exist (medical and surgical interventions, diagnostic technologies, and screening technologies), the Core Model for Diagnostic technologies was used to assess the clinical effectiveness of the three prognostic tests.

There are fundamental differences between diagnostic and prognostic tests. A number of the HTA Core assessment element questions for diagnostic technologies are not suited to prognostic technologies. Prognostic/predictive accuracy was not assessed in this HTA Core Model.

Information sources

A systematic literature review was performed according to the Cochrane methodology {13}. This was carried out on standard medical and HTA databases.

Literature search and selection of literature

Using PICO (D), the overall research question for this domain is as follows.

Population: Women with early invasive breast cancer.

Intervention: Use of at least one of the following prognostic tests: uPA/PAI-1, MammaPrint or  Oncotype DX.

Comparison: standard/or current practice. As currently there is no standard universally accepted practice, different practices may be involved, such as testing with St Gallen consensus recommendations, National Comprehensive Cancer Network guidelines (NCCN), Adjuvant! Online, or Nottingham Prognostic Index (NPI).

Outcomes: morbidity and survival, safety (adverse events due to adjuvant chemotherapy), quality of life, the impact of prognostic tests on clinical decision making and patients’ satisfaction.

Design: studies comparing the effects of treatment with and without the use of the index test, but excluding studies limited to the prognostic/predictive accuracy of the test. An ideal testing plan for tests to direct treatment would be assessment in randomised conditions as the first level of evidence (followed by prospective cohort studies if RCTs are not available) of each test compared with standard first and then, if found dominant, compared with treatment, direct (head to head) comparison of the effects of each of the dominant tests compared with the others.

Due to the nature of the disease stage, tests and treatment (which is envisaged to be chemotherapy), prospective study designs are preferred to retrospective designs.

As a consequence the inclusion criteria were studies that:

  1. included women who had been diagnosed with early invasive breast cancer;
  2. compared at least one of the following prognostic tests: uPA/PAI-1, MammaPrint or  Oncotype DX with standard/current practice;
  3. addressed questions on clinical (health) outcomes like morbidity and survival, safety (adverse events due to adjuvant chemotherapy), quality of life, the impact of prognostic tests on clinical decision making and patients’ satisfaction;
  4. reported sufficient methodological details to allow critical appraisal of study quality;
  5. were in English;
  6. reported on humans only.

Exclusion criteria were studies that:

  1. did not involve women with early stage invasive breast cancer;
  2. did not compare use of at least one of the following tests: uPA/PAI-1, MammaPrint, and Oncotype DX to standard/current practice;
  3. did not provide data on at least one of the domain questions on clinical (health) outcomes like morbidity and survival; safety (adverse events due to adjuvant chemotherapy); quality of life, the impact of prognostic tests on clinical decision making and patients’ satisfaction;
  4. assessed only the prognostic/predictive accuracy of the test;
  5. papers with RCTs and observational studies without sufficient methodological details to allow critical appraisal of study quality;
  6. papers (publications) published in a language other than English;
  7. duplicated the original publication;
  8. reported studies relating to these tests in the neo-adjuvant setting only.

Literature search

The systematic literature search was performed according to the search strategy described in Appendix COL-1, in October 2011, in the following databases: Ovid MEDLINE(R) <1948 to September Week 4 2011>; Ovid MEDLINE(R) In-Process & Other Non-Indexed Citations <October 07, 2011>; Embase <1980 to 2011 Week 40>; Cochrane Issue 4 of 4, October 2011; Cinahl (Accessed 12 October 2011); CRD databases: DARE, NHS EED, HTA (Accessed 13 October 2011).

In addition, the following clinical trials registries were assessed (13 October 2011), for registered ongoing clinical trials or observational studies: ClincalTrials.gov, ISRCTN, metaRegister of Controlled Trials (mRCT) and International Clinical Trials Registry Platform (ICTRP). The last database update was on 19 December 2011.

Selection of literature

Relevant references, after duplicates were removed, were screened and assessed for eligibility independently by two reviewers. The reference lists of relevant systematic review and health technology assessment reports were also checked for other relevant studies.

Differences in selection results were discussed in order to achieve consensus; a third reviewer was involved where there was uncertainty.

Following removal of duplicates, 4539 references were available for screening. Finally, only 15 studies were included to answer domain assessment element questions (Appendix 1). The PRISMA flowchart outlining the study selection process is presented in Figure 1.

Figure 1. Selection process according to the PRISMA flowchart {14}

113.EFF Figure 1
Quality assessment tools or criteria

Quality of evidence

 There were no RCTs or prospective cohort studies that assessed whether use of the prognostic tests (uPA/PAI-1, MammaPrint or Oncotype DX) to guide the use of adjuvant chemotherapy improves long-term clinical outcomes. For this reason, neither the internal validity (risk of bias) of the studies nor quality of the body of evidence (assessed by two researchers independently) could be assessed. This assessment was performed using a few studies, although they did not satisfy the inclusion criteria, to raise important ethical and legal questions on the current use of these three prognostic tests, which are part of the medical devices technology group.

Differences in reviewer findings were discussed in order to achieve consensus. A third reviewer was involved in cases of uncertainty.

The Cochrane Collaborations tools were used to assess risk of bias {15, 16}.

The GRADE working group approach was used to assess the quality of the evidence {17}. This approach specifies four levels of quality:

  • high: further research is very unlikely to change our confidence in the estimate of effect
  • moderate: further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimates
  • low: further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate
  • very low: we are very uncertain about the estimate
Analysis and synthesis

Data extraction was done independently by two researchers. Data on study characteristics (study design, registration number, country and centre, study period, ethics committee approval, sponsor, study methodology); patient characteristics (age, gender, tumour size, histological grade, lymph node status, oestrogen and progesterone receptor status, human epidermal growth factor receptor (HER2), menopausal status); outcomes; intervention (test characteristics—threshold values for categorisation of risk recurrence); comparator; flow of patients; results on primary and secondary outcomes; and conflict of interest data were all extracted. Any differences in extraction results were discussed to achieve consensus; a third reviewer was involved where there was uncertainty. Synthesis was limited to a qualitative synthesis of the data.

Result cards

Change-in management

Result card for EFF15: "Does the test-treatment chain of uPA/PAI, Mammaprint, or Oncotype for adjuvant therapy reduce or increase the number of women (diagnosed with early stage, invasive breast cancer) requiring hospitalization or hospitalization due side-effects compared to treatment on the basis of the standard practice?"

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EFF15: Does the test-treatment chain of uPA/PAI, Mammaprint, or Oncotype for adjuvant therapy reduce or increase the number of women (diagnosed with early stage, invasive breast cancer) requiring hospitalization or hospitalization due side-effects compared to treatment on the basis of the standard practice?
Result

Importance: Critical

Transferability: Completely

Result card for EFF7: "Do uPA/PAI, Mammaprint, or Oncotype compared to the standard practice in women diagnosed with early stage invasive breast cancer increase or decrease the probability of adjuvant therapy performed?"

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EFF7: Do uPA/PAI, Mammaprint, or Oncotype compared to the standard practice in women diagnosed with early stage invasive breast cancer increase or decrease the probability of adjuvant therapy performed?
Result

Importance: Important

Transferability: Completely

Result card for EFF6: "Did the results in uPA/PAI, Mammaprint, or Oncotype tests in women diagnosed with early stage invasive breast cancer lead to changes in the treatment choice with adjuvant therapy and/or further imaging compared to the standard practice?"

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EFF6: Did the results in uPA/PAI, Mammaprint, or Oncotype tests in women diagnosed with early stage invasive breast cancer lead to changes in the treatment choice with adjuvant therapy and/or further imaging compared to the standard practice?
Result

Importance: Important

Transferability: Completely

Function / HRQL (Health-related quality of life)

Result card for EFF3: "What is the effect of adjuvant therapy on the basis of uPA/PAI, Mammaprint, or Oncotype test results on health related quality of life compared to treatment on the basis of the standard practice?"

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EFF3: What is the effect of adjuvant therapy on the basis of uPA/PAI, Mammaprint, or Oncotype test results on health related quality of life compared to treatment on the basis of the standard practice?
Result

Importance: Critical

Transferability: Completely

Result card for EFF4: "Does adjuvant therapy on the basis of uPA/PAI, Mammaprint, or Oncotype test results compared to treatment on the basis of the standard practice affect their activities of daily living?"

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EFF4: Does adjuvant therapy on the basis of uPA/PAI, Mammaprint, or Oncotype test results compared to treatment on the basis of the standard practice affect their activities of daily living?
Result

Importance: Optional

Transferability: Partially

Patient satisfaction

Result card for EFF5: "Do women diagnosed with early stage, invasive breast cancer feel that the guidance of their adjuvant therapy on the basis of uPA/PAI, Mammaprint, or Oncotype test results was worth it?"

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EFF5: Do women diagnosed with early stage, invasive breast cancer feel that the guidance of their adjuvant therapy on the basis of uPA/PAI, Mammaprint, or Oncotype test results was worth it?
Result

Importance: Important

Transferability: Partially

Result card for EFF14: "Would the patient be willing to use the technology (uPA/PAI or Mammaprint or Oncotype test) again?"

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EFF14: Would the patient be willing to use the technology (uPA/PAI or Mammaprint or Oncotype test) again?
Result

Importance: Critical

Transferability: Partially

Result card for EFF12: "Does the knowledge of the tests results (uPA/PAI, Mammaprint, or Oncotype) improve the patient quality of life in women diagnosed with early stage invasive breast cancer compared to standard practice?"

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EFF12: Does the knowledge of the tests results (uPA/PAI, Mammaprint, or Oncotype) improve the patient quality of life in women diagnosed with early stage invasive breast cancer compared to standard practice?
Result

Importance: Important

Transferability: Partially

Test-treatment chain

Result card for EFF9: "What is the effect of adjuvant therapy on the basis of uPA/PAI, Mammaprint, or Oncotype test compared to treatment on the basis of the standard practice in women diagnosed with early stage invasive breast cancer on overall survival and disease specific survival (for example: disease-free-, progression free-, recurrence-free-survival)?"

View full card
EFF9: What is the effect of adjuvant therapy on the basis of uPA/PAI, Mammaprint, or Oncotype test compared to treatment on the basis of the standard practice in women diagnosed with early stage invasive breast cancer on overall survival and disease specific survival (for example: disease-free-, progression free-, recurrence-free-survival)?
Result

Importance: Critical

Transferability: Completely

Result card for EFF13: "How does the treatment with adjuvant therapy on the basis of the test results of uPA/PAI, Mammaprint, or Oncotype compared to treatment on the basis of the standard practice in women diagnosed with early stage invasive breast cancer modify the magnitude and frequency of morbidity?"

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EFF13: How does the treatment with adjuvant therapy on the basis of the test results of uPA/PAI, Mammaprint, or Oncotype compared to treatment on the basis of the standard practice in women diagnosed with early stage invasive breast cancer modify the magnitude and frequency of morbidity?
Result

Importance: Critical

Transferability: Completely

Morbidity

Result card for EFF11: "Does adjuvant therapy on the basis of genetic testing results (uPA/PAI, Mammaprint or Oncotype) compared to treatment on the basis of the standard practice in women diagnosed with early stage invasive breast cancer improve patient morbidity?"

View full card
EFF11: Does adjuvant therapy on the basis of genetic testing results (uPA/PAI, Mammaprint or Oncotype) compared to treatment on the basis of the standard practice in women diagnosed with early stage invasive breast cancer improve patient morbidity?
Result

Importance: Critical

Transferability: Completely

Discussion

The primary aim of our assessment was to determine whether, compared with current practice, using these three prognostic tests (uPA/PAI-1, MammaPrint and Oncotype DX) to help guide the use of adjuvant chemotherapy effectively improves long-term clinical outcomes, safety (adverse events due to adjuvant chemotherapy) and quality of life in women with early-stage breast cancer.

The secondary aims were to assess changes both in clinical decisions made about choice of treatment with adjuvant chemotherapy and in patient satisfaction.

There are no RCTs or prospective cohort studies that determined whether using these three prognostic tests to help guide the use of adjuvant chemotherapy effectively improves long-term clinical outcomes compared with current practice. A few studies were found that did not satisfy the inclusion criteria (Appendix 6). All but one {39} of these studies had a retrospective design {40–46}; they assessed the predictive accuracy of the test (“does the test accurately predict patients who will benefit most from chemotherapy?”), or the studies did not have a standard/current care comparator. These studies were assessed internally, and it was concluded that all were of very low level of quality according to the GRADE working group approach {17}. The very low quality of the studies raises important ethical and legal questions on the current use of these three tests, which are part of the medical devices technology group. We also found evidence of duplicate publications, author non-cooperation with our requests for more data, and inadequate trial registration in public, non-profit clinical trials registries.

A number of ongoing RCTs will also not produce direct evidence on these important clinical outcomes.  Clearly, the manufacturers should communicate at an early stage with the EMA, FDA and HTA bodies to obtain so-called “early scientific advice” for designing RCTs {47}.

The majority of previous HTAs and Systematic Reviews of clinical effectiveness on the two prognostic genetic tests (Oncotype DX and MammaPrint) came to the same conclusion on these important clinical questions {8–11}.

Smart et al. 2010 {9} updated the Marchionni et al. 2008 {8} systematic review and concluded, similarly to the original review, that there were no studies that provided direct high quality evidence that Oncotype DX and MammaPrint lead to any improvement in outcome or that they are able to predict the response to chemotherapy. The most likely source of evidence on clinical utility will be the two ongoing RCTs: MINDACT and the TAILOR X trial.

The Ontario 2010 report {48} on Oncotype DX concluded that low quality evidence exists on its prognostic value in women who are being treated with adjuvant tamoxifen or anastrazole, and have newly diagnosed early breast cancer (stage I–II) that is oestrogen receptor-positive and/or progesterone receptor-positive and lymph node-negative. The same is true for lymph node-positive patients.

Very low quality evidence showed that Oncotype DX could predict which women will benefit from adjuvant CMF/MF chemotherapy in those being treated with adjuvant tamoxifen, in lymph node- negative as well as lymph node-positive early breast cancer patients.

The Blue Cross 2010 report {49} concluded that the use of the Oncotype DX test for selecting adjuvant chemotherapy in patients with lymph node-positive breast cancer is not recommended.

The systematic review by Ward et al. 2011 {10} reported that very limited evidence exists on the clinical utility of Oncotype DX and MammaPrint, so additional robust evidence is needed.

Very recently a NICE report {11} concluded that MammaPrint and Oncotype DX are not recommended in guiding the use of adjuvant chemotherapy in women aged 75 years or under with oestrogen receptor -positive, lymph node-negative and human epidermal growth factor receptor 2 (HER2) negative early breast cancer. The committee could not recommend these tests because of uncertainty in the evidence on clinical effectiveness leading to uncertainty about cost effectiveness.

According to the St. Gallen Consensus Document 2011 {50}, only the multiparameter gene assay Oncotype DX (Genomic Health Inc., Redwood City, CA, USA) was considered by a majority (84%) as potentially useful for decision making on adjuvant chemotherapy in cases where other factors (grade, HER2 etc.) do not help. On the other hand, the alternative test, the multigene array MammaPrint (Agendia, Amsterdam, The Netherlands), was not accepted (69% against). The option of using uPA/PAI-1 as a potential help in decision making was also not accepted (23% in favour, 50% against) {50}.

According to the assessment and report of the Dutch Health Insurance Board College voor zorgverzekeringen’ (CVZ) regarding the gene expression test, MammaPrint {51} the clinical utility of using MammaPrint has not yet been demonstrated. The current MINDACT trial, a prospective, randomised, multicentre study that compares use of MammaPrint with standard clinical risk estimates will have to demonstrate whether its use really does lead to health benefits. CVZ concluded that using the medical test MammaPrint, based on the results of the literature search relating to its clinical utility, does not comply with the criterion “established medical science and medical practice”.

All included studies in this domain that address the other assessment element questions were observational studies. Oncotype DX influenced a change in the physician’s adjuvant treatment recommendation in 19%–51% of patients. Using MammaPrint would have resulted in altered treatment advice in up to 40% of patients.

It should be noted that if a study finds that such changes in management are frequent, this does not imply that these changes in therapy are beneficial for the patients.

Only limited evidence was found on Quality of life, which remained stable according to Functional Assessment of Cancer Therapy 12 months after the Oncotype DX RS test. So-called State or situational anxiety (STAI) mean scores significantly decreased over time. More than 90% of patients continued to feel satisfied that they had used the RS assay and were satisfied with their treatment decision at 12 months after the RS assay. Five patients who were not satisfied noted a negative impact on quality of life, treatment side-effects including aches, hot flashes, pain, mood alteration, and negative impact on self image.

Most women (95%) reported that they would have the Oncotype DX test again if they had to decide today, and would recommend the test to other women {22}.

Unsuitable evidence was found on the question of whether knowledge of the test results (uPA/PAI-1, MammaPrint, or Oncotype DX) improves the patient’s quality of life compared with standard practice (once again only on the Oncotype DX test). The majority of women agreed that the Oncotype DX test gave them a better understanding of the chances of success of their treatment options; only a few women had concerns about the test or agreed that this information about one’s cancer is better left unknown {23,24}. Approximately one quarter of women agreed or strongly agreed that receiving the Oncotype DX test result made them worried and anxious {24}.

In the Constructive Technology Assessment {52}, as part of the clinical RASTER study on the MammaPrint test, a questionnaire was sent to part of the patient population (only 77 were analysed, out of 427 patients in the RASTER study in which prognostic signatures were assessed, out of 812 accrued patients), and showed that the satisfaction about receiving the 70-gene signature per risk group was 76%. It should be noted that the distribution of the risk groups was different from that of the total RASTER population (more concordant low-risk patients) {52}.

The assessment has several limitations. The major limitation was that we assessed prognostic tests within  the framework of a Core HTA Model for diagnostic technologies. Due to the different assessment element questions we were not able to assess analytical and clinical validity, only clinical utility. Prognostic/predictive accuracy was not assessed in this HTA Core Model. Despite these limitations our conclusion on uncertainty in the evidence of clinical effectiveness was the same as in other systematic reviews and HTA reports {8–11, 48, 49, 51}.

Clinical utility is based on a study defined as providing direct evidence of improvement in clinical outcomes. The use of the prognostic test in decision making is compared with not using the test, with health outcomes as an endpoint, generally in an RCT; so the primary intervention is the use of the prognostic test (with additional therapeutic decision making directed by the results) and the clinical outcomes are, for example, patient morbidity, mortality and/or quality of life. The analytical and clinical validity are of course of utmost importance for the assessment of clinical utility (or effectiveness).

There is a clear need to develop a new Core HTA Model for prognostic technologies, and probably for genetic tests separately. As pointed out in the published literature, in order to assess their reliability and generalisability for use, prognostic models need to have been validated and measures of model performance reported. Previously published studies and reviews of prognostic factors results highlight serious concerns about the quality of prognostic studies. Many published prognostic models have been developed using poor methods and many are poorly reported, both of which compromise the reliability and clinical relevance of the models, and of prognostic indices and risk groups derived from them. It is of concern that health professionals may direct patient treatment on the basis of poorly developed and reported prognostic studies. Good reporting is also critical for the interpretability and clinical applicability of prognostic studies. Reporting of key information is currently poor, resulting in reporting bias, which has a negative influence on the further development of systematic reviews and evidence-based medicine. Study publication and outcome reporting biases are two major obstacles to evidence-based practice because they overestimate the effect of experimental treatments, can cause harm, and are unethical {53–56}.

Genetic tests are considered to be part of the group of medical devices technologies. Different regulations, according to marketing authorisation, even on innovative high-risk medical devices (class III) are recognised in the USA and the EU, putting the EU patients at higher risk of developing serious adverse events as a result of decision making based on these results {57}. As remarked in the report, HTA agencies are repeatedly confronted with a relative lack of clinical data when assessing the value of innovative high-risk devices when they enter the market in Europe (innovative high-risk devices in Europe include innovative class III devices and innovative implantable devices). In the USA innovative high-risk devices (class III) typically undergo a pre-market approval (PMA) process. In Europe, the pre-market clinical evaluation is defined as the assessment and analysis of clinical data pertaining to a medical device to verify the clinical safety and performance of the device when used as intended by the manufacturer. Clinical safety is the absence of unacceptable clinical risks, when using the device according to the manufacturer’s instructions for use. Clinical performance is the ability of a medical device to achieve its intended purpose as claimed by the manufacturer. In the USA, under the PMA process, each manufacturer must independently demonstrate “reasonable assurance of the safety and effectiveness” of the device for its intended use.

High quality evidence on the clinical effectiveness (clinical utility) of uPA/PAI-1, MammaPrint and Oncotype DX tests is lacking. The majority of included observational studies have retrospective or cross-sectional study designs, and small sample sizes with heterogeneity of patient cohorts. Although current ongoing RCTs were found some of these will not give direct evidence on important clinical outcomes. There is a clear need for early manufacturers’ communication with EMA, FDA and HTA bodies on so-called “early scientific advice” for designing RCTs. Further high quality evidence on uPA/PAI-1, MammaPrint and Oncotype DX tests from RCTs is needed to guide the use of adjuvant chemotherapy in women with early invasive breast cancer.

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Appendices

Appendix EFF-1 List of included studies in the systematic review of Clinical Effectiveness domain

Oncotype DX test

Ademuyiwa FO et al. The effects of oncotype DX recurrence scores on chemotherapy utilization in a multi-institutional breast cancer cohort. Breast Cancer Res Treat. 2011;126:797-802.

Asad J et al. Does oncotype DX recurrence score affect the management of patients with early-stage breast cancer? The American Journal of Surgery.2008; 196:527–9.

Geffen et. al. The impact of the 21-gene recurrence score assay on decision making about adjuvant chemotherapy in early-stage estrogen-receptor-positive breast cancer in an oncology practice with a unified treatment policy. Annals of Oncology. 2011;22: 2381–6.

Henry LR et al. The influence of a gene expression profile on breast cancer decision. Journal of Surgical Oncology. 2009;99:319-23.

Joh JE et al. The Effect of Oncotype DX Recurrence Score on Treatment Recommendations for Patients with Estrogen Receptor–Positive Early Stage Breast Cancer and Correlation with Estimation of Recurrence Risk by Breast Cancer Specialists. The Oncologist. 2011;16:1520-26.

Kamal AH et al. Breast Medical Oncologists’ Use of Standard Prognostic Factors to Predict a 21-Gene Recurrence Score. The Oncologist. 2011;16:1359-66.

Lo SS et al. Prospective multicenter study of the impact of the 21-gene recurrence score assay on medical oncologist and patient adjuvant breast cancer treatment selection. J Clin Oncol. 2010;28:1671-6. Epub 2010 Jan 11.

Oratz et.al. Physician Survey of the Effect of the 21-Gene Recurrence Score Assay Results on Treatment Recommendations for Patients With Lymph Node–Positive, Estrogen Receptor–Positive Breast Cancer. Journal Of Oncology Practice. 2011;7:94-9.

Oratz R et al. Impact of a Commercial Reference Laboratory Test Recurrence Score on Decision Making in Early-Stage Breast Cancer. JOP. 2007;3:182-6.

Partin JF et al. Impact of the 21-gene recurrence score assay compared with standard clinicopathologic guidelines in adjuvant therapy selection for node-negative, estrogen receptor-positive breast cancer.

Annals of Surgical Oncology. 2011;18: 3399-3406.

Rayhanabad JA et al. Changing paradigms in breast cancer management: introducing molecular genetics into the treatment algorithm. The American Surgeon. 2009;74:887-90.

Richman AR et al. Knowledge of genomic testing among early-stage breast cancer patients. Psycho-Oncology. 2011;20:28-35.

Tzeng JP et al. Women’s Experiences With Genomic Testing for Breast Cancer Recurrence Risk Cancer. 2010;116:1992-2000.

MammaPrint test

Bueno-de-Mesquita JM et al. Use of 70-gene signature to predict prognosis of patients with

node-negative breast cancer: a prospective community-based feasibility study (RASTER).

Lancet Oncol. 2007;8:1079–87.

Gevensleben et al. Comparison of MammaPrint and TargetPrint results with clinical parameters in German patients with early stage breast cancer; International Journal of Molecular Medicine. 2010; 26:837-43.

Appendix EFF-2 Ongoing RCTs in clinical trials registries on the uPA/PAI-1, Oncotype DX and MammaPrint tests

Table 1. Clinical trials registries—ongoing RCTs on the uPA/PAI-1 test (FEMTELLE, ELISA tests, American Diagnostica Inc.)

Official Study title

 
 

Randomized Multicenter Study Comparing 6xFEC With 3xFEC-3xDoc in High-risk Node-negative Patients With Operable Breast Cancer: Comparison of Efficacy and Evaluation of Clinico-pathological and Biochemical Markers as Risk Selection Criteria

NNBC3-Europe trial

Study characteristics

 

Study design

Partially RCT

Study Registration number

NCT01222052

Country of recruitment

Germany and France

Sponsor

Martin-Luther-Universität Halle-Wittenberg

Collaborators

Not reported

Study methodology

Risk assessment tool; classification of patients by uPA /PAI-1 results or clinicopathological results (each centre was allowed to select the method of risk assessment for all of their patients, according to the results they selected in one of two groups)

Low vs High (by either clinicopathological results or uPA /PAI-1 test results)

Low risk (by prognostic test: uPA ≤3 ng/mg and PAI-1 ≤14 ng/mg or clinicopathological results )

- observation only

High risk (by prognostic test, uPA /PAI-1 or clinicopathological results; patients will be stratified by HER2 receptor and then randomly assigned)

RANDOMISATION (patients will be randomly assigned to one of two chemotherapy arms

- chemo th FEC (anthracycline-containing chemotherapy; 5-fluorouracil/epirubicin/cyclophosphamide)

vs.

- chemo th FEC-docetaxel (anthracycline and taxane-containing chemotherapy; 5-fluorouracil/epirubicin/cyclophosphamide followed by docetaxel)

Study start

January 2001

Estimated completion date

February 2019

Patient characteristics

 

Age of patients

18–65

Gender

 

Tumour size

0.5–5.0 cm

Histological grade

T1–T2

Lymph-node status

Negative

Oestrogen receptor status

 

HER 2

Positive and negative

Progesterone receptor status

 

Menopausal status

Pre- and postmenopausal

Estimated Enrolment

4149 (from literature)

Intervention

 

Test

uPA/PAI-1 (FEMTELLE, ELISA tests - American Diagnostica Inc.): Low and High risk

Comparator

 
 

Clinicopathological algorithm

Outcomes

 

Primary

Disease-free survival (DFS)

Secondary

Overall survival (OS); compliance; toxicity of chemotherapy in each patient group; The proportion of low risk versus high risk patients; DFS; OS

Table 2. Clinical trials registries—ongoing RCTs on the Oncotype DX test

Official Study title

  
 

Program for the Assessment of Clinical Cancer Tests (PACCT-1): Trial Assigning Individualized Options for Treatment: The TAILORx Trial

Randomised Comparison of Adjuvant Docetaxel/Cyclophosphamide With Sequential Adjuvant EC/Docetaxel Chemotherapy in Patients With HER2/Neu Negative Early Breast Cancer, WSG Plan B trial

Study characteristics

  

Study design

Partially RCT

Partially RCT

Registration number

NCT00310180

NCT01049425

Country of recruitment

United States, Australia, Canada, Peru

Germany

Sponsor

Eastern Cooperative Oncology Group

West German Study Group

Collaborators

National Cancer Institute (NCI); Southwest Oncology Group; Cancer and Leukemia Group B; American College of Surgeons; North Central Cancer Treatment Group; NCIC Clinical Trials Group; National Surgical Adjuvant Breast and Bowel Project (NSABP)

Sanofi-Aventis, Amgen

Study methodology

Risk assessment tool; classification of patient by genetic test results Oncotype DX alone

Low vs. intermediate vs. high ) (by Oncotype DX test results)

Low risk, RS<11

- hormone th alone

Intermediate risk, RS 11-25 RANDOMISATION (the patient will be randomly assigned to two arms)

-hormone therapy alone

-hormone therapy + chemotherapy

High risk RS >25

- hormone therapy + chemotherapy

Risk assessment tool; classification of patient by genetic test results Oncotype DX (in addition optional uPA/PAI-1 may be done)

Low vs. High (including Intermediate) (by Oncotype DX test results)

Low risk RS≤11

- hormone therapy alone

High risk (including intermediate) RS>11 RANDOMISATION (the patient will be randomly assigned to two chemotherapy arms)

- chemotherapy; epirubicin/cyclophosphamide followed by docetaxel

vs.

- chemotherapy: docetaxel/ cyclophosphamide

Study start

Not reported

January 2009

Estimated Primary outcome completion date

April 2014

October 2016

Estimated completion date

Not reported

Not reported

Patient characteristics

  

Age of patients

17–75

18–75

Gender

Female

Female

Tumour size

1.1–5.0 cm

 

Histological grade

Not reported

T1–T4

Lymph-node status

Negative

Positive and negative

Oestrogen receptor status

Positive

Positive

HER 2

Negative

Negative

Progesterone receptor status

Positive

Positive

Menopausal status

Pre- and postmenopausal

Pre- and postmenopausal

Estimated Enrolment

11248

2448

Intervention

  

Test

The Oncotype DX 21-gene Recurrence Score (RS)

(Oncotype DX, Genomic Health, Redwood City, CA):

Low, Intermediate, High

The Oncotype DX 21-gene Recurrence Score (RS)

(Oncotype DX, Genomic Health, Redwood City, CA):

Low, Intermediate, High

Comparator

  
 

None. Risk assessment according Oncotype DX

None. Risk assessment according Oncotype DX (in addition optional uPA/PAI-1 may be done)

Outcomes

  

Primary

Disease-free survival; distant recurrence-free interval; recurrence-free interval ; overall survival; comparison of FACT-Cog perceived cognitive impairment scores between participants at 3 months

Disease-free survival in two chemotherapy arms (patients treated with either 6 cycles of docetaxel / cyclophosphamide chemotherapy vs 4 cycles of EC followed by 4 cycles of docetaxel as adjuvant treatment (time frame: 5 years)

Secondary

Comparison of FACT-Cog scores between arms B and C at 3, 12, 18, 24, and 36 months; Differences in FACT-Cog change scores from randomisation to 3, 6, 12, 18, 24, and 36 months;

Differences between arms B and C on other patient-reported outcomes measures; Differences between participants receiving hormonal treatment alone (arm B vs arm A) on patient-reported outcomes measures; Differences between participants receiving chemotherapy followed by hormonal treatment (arm C vs arm D) on patient-reported outcomes measures

Not reported

Table 3. Clinical trials registries-ongoing RCTs on the MammaPrint test

Official Study title

 
 

MINDACT (Microarray In Node-Negative and 1 to 3 Positive Lymph Node Disease May Avoid Chemotherapy): A Prospective, Randomized Study Comparing the 70-gene Signature With the Common Clinical-Pathological Criteria in Selecting Patients for Adjuvant Chemotherapy in Breast Cancer With 0 to 3 Positive Nodes

Study characteristics

 

Study design

Partially RCT

Study Registration number

NCT00433589

Country of recruitment

Netherlands

Sponsor

European Organization for Research and Treatment of Cancer - EORTC

Collaborators

Not reported

  

Study methodology

Risk assessment tool; classification of patient by both genetic test (MammaPrint) results and clinicopathological results

Low vs. High risk (with both clinicopathological and genetic test [MammaPrint] results)

Clinicopathological and MammaPrint Low risk

- hormone therapy alone: tamoxifen vs letrozole

Clinicopathological and MammaPrint  High risk

- chemotherapy: antracycline based vs docetaxel + capecitabine

Discordant risk between genetic test risk assessment and clinicopathological risk assessment (Clinicopathological High and MammaPrint Low or Clinicopathological Low and MammaPrint High)

RANDOMISATION (the patient will be randomly assigned for assessment either by clinicopathological risk results or by MammaPrint risk results to decide on the use of chemotherapy or not)

- Low risk

hormone therapy: sequential tamoxifen-letrozole vs letrozole

- High risk

chemotherapy: antracycline based vs docetaxel + capecitabine

Study start

December 2006

Estimated primary outcome completion date

March 2019

Estimated completion date

 

Patient characteristics

 

Age of patients

18 years and older

Gender

Female

Tumour size

 

Histological grade

T1-T3

Lymph-node status

Positive and negative

Oestrogen receptor status

Positive

HER 2

 

Progesterone receptor status

Positive

Menopausal status

Pre- and postmenopausal

Estimated Enrolment

6600

Intervention

 

Test

MammaPrint (the 70-gene prognosis signature, Amsterdam, Netherlands): low and high risk

Comparator

 
 

Clinicopathological algorithm using Adjuvant! Online

Outcomes

 

Primary

Distant metastasis-free survival at 5 years; disease-free survival (DFS)

Secondary

Proportion of patients treated with chemotherapy based on clinical prognosis compared with 70-gene signature prognosis; overall survival at 5 years; DFS at 5 years; safety (early and late)

Appendix EFF-3 Evidence table on Oncotype DX test on the research question: changes in health related quality of life

Table 1. Oncotype DX (21-gene recurrence score (RS) assay, Genomic Health, Redwood City, CA) on research question: changes in health related quality of life (22)

Author, year, reference number:

 
 

Lo SS et al. J Clin Oncol. Apr 1;28(10):1671-6. Epub 2010 Jan 11.

Study title

 
 

Prospective multicentre study of the impact of the 21-gene recurrence score assay on medical oncologist and patient adjuvant breast cancer treatment selection

Study characteristics

 

Study design

Observational study— prospective, pre-post design (patients and physicians served as their own controls at two time-points, pre- and post-RS assay)

Study Registration number

Not reported

Country

USA

Centre

Multicentre (one community and three academic practices)

Ethics Committee Approval

Yes

Sponsor

Unrestricted clinical trials grant from Genomic Health Inc.

Study period (study start, study end)

December 2005–August 2006

(pre-, and immediately post RS assay, and follow up at 12 months)

Patient characteristics

 

Age of patients mean with SD (range)

55 (35–77)

Tumour size (diameter)

1.7 cm (0.6–3.5)

Histological grade (1-good, 2-intermediate, 3-poor)

1–2

Lymph-node status (negative, positive)

Negative

Oestrogen receptor status (negative, positive)

Positive

HER 2 (positive, negative)

Both

Progesterone receptor status (negative, positive)

Not reported

Menopausal status

Both

Intervention

 

Test

Oncotype DX (21-gene recurrence score (RS) assay, Genomic Health, Redwood City, CA); High-Intermediate-Low

Threshold values for categorisation of high/intermediate/low risk and number of patients

Low <18 n = 38 (42.7%)

Intermediate 18–30 n = 42 (47.2%)

High >31 n = 9 (10.1%)

Central analysis/centre specific of test

Not reported

Comparator

 
 

Standard clinicopathological prognostic factors (41 physicians (46%) also use Adjuvant!Online)

Outcomes

 
 

Change in patient satisfaction with choice of treatment; Change in patient anxiety; Change in patient decisional conflict; Change in patient quality of life

Flow of patients

 

No of patients enrolled

N = 93

Number of analysed patients

N = 89 (96%)

N = 67 (75%) after 12 months

Results

 

Change in patient quality of life

FACT-B: pre-RS mean 112.2 (SD = 17.4): 12 months post-RS 114.3 (SD = 18.6); P = 0.55

FACT-G: pre-RS mean 88.7 (SD = 12.3): 12 months post-RS 87.6 (SD = 14.9); P = 0.49

Change in patient satisfaction

Immediately post-RS assay:

78 (95%) were glad they took the RS assay test.

77 (87%) understand how the assay work.

79 (89%) felt that the results were easy to understand.

74 (83%) indicated that the results of the RS assay influenced their decision making.

12-month post-RS assay:

67 (75%) completed the 12-month questionnaire.

62 (92.5%) continued to feel satisfied that they had used the RS assay.

64 (95.5%) were satisfied with their treatment decision.

54 (80.6%) continued to believe that the results influenced their treatment decision.

Those patients (n = 5) not satisfied noted a negative impact on quality of life, treatment side-effects including aches, hot flashes, pain, mood alteration, and negative impact on self image.

Change in patient anxiety

State or situational anxiety (STAI) mean scores significantly decreased over time; 39.6 (SD = 14.5): 36 (SD = 12.6): 34 (SD  = 11.5); P = 0.007

Trait anxiety or the dispositional tendency to be anxious mean did not significantly decreased over time; 32.2 (SD = 14.5): 31.7 (SD = 13.3): 33.2 (SD = 11.0), P = 0.27

Change in patient decisional conflict

Statistically significant decreased immediately post-RS; mean DSC 1.99 (SD = 0.62): 1.69 (SD = 0.50); P<0.001

Author disclosure (Conflict of interest)

 
 

Genomic Health (Research funding: Consultant or Advisory Role: Honoraria )

Appendix EFF-4 Evidence table on Oncotype DX test on patient satisfaction questions

Table 1. Oncotype DX (21-gene recurrence score (RS) assay, Genomic Health, Redwood City, CA) (23,24)

Author, year, reference number:

  
 

Richman AR et al. Psycho-Oncology. 2011;20:28-35.

Tzeng JP et al. Cancer. 2010;116:1992-2000.

Study title

  
 

Knowledge of genomic testing among early-stage breast cancer patients

Women’s experiences with genomic testing for breast cancer recurrence risk

Study characteristics

  

Study design

Observational study: cross-sectional study (questionnaire), supplemented by medical chart review

Observational study: cross-sectional study (questionnaire), supplemented by medical chart review

Study registration number

Not reported

Not reported

Country

USA and Netherlands

USA

Centre

Multicentre

Multicentre

Ethics committee approval

Yes

Yes

Sponsor

Grant MSRG-06-259-01-CPPB from the American Cancer Society

Grant MSRG-06-259-01-CPPB from the American Cancer Society

Study period (study start, study end)

December 2008 and June 2009

December 2008 and May 2009

   

Study period (study start, study end)

December 2008 and June 2009

December 2008 and May 2009

Patient characteristics

  

Age of patients

58 (38-83)

58 (38-83)

Tumour size (diameter)

Not reported

Not reported

Histological grade (1-good, 2-intermediate, 3-poor)

1-2

1-2

Lymph-node status

Majority node negative (66/68, 97%)

Majority node negative (66/68, 97%)

Oestrogen receptor status

Positive

Positive

HER 2

Not reported

Not reported

Progesterone receptor status

Positive

Positive

Menopausal status

Both

Both

Intervention

  

Test

Oncotype DX (21-gene recurrence score (RS) assay, Genomic Health, Redwood City, CA); High-Intermediate-Low

Oncotype DX (21-gene recurrence score (RS) assay, Genomic Health, Redwood City, CA); High-Intermediate-Low

Threshold values for categorisation of high/intermediate/low risk and number of patients

Low (≤11%) n = 34/68 (50%)

Intermediate (12–21%) n = 25/68 (37%)

High (>21%) n = 9/68 (13%)

Low (≤11%) n = 34/68 (50%)

Intermediate (12–21%) n = 25/68 (37%)

High (>21%) n = 9/68 (13%)

Central analysis/centre specific of test

Not reported

Not reported

Comparator

  
 

None

None

Outcomes

  

Primary and

Secondary

Knowledge of genomic testing (identify correlates of knowledge, including patient characteristics, experiences with breast cancer treatment, and experiences with genomic testing, whether different ways of presenting test results was associated with higher knowledge);

Role in treatment decision; how patients received test results; patients perceived consequences of genomic recurrence risk testing

Patient numeracy and literacy; breast cancer worres; how patients learnt about the test; how patients received the test results; patients attitudes towards Oncotype DX testing; participants recalled recurrence risk; perceived recurrence risk; patient treatment decision.

Flow of patients

  

No of patients enrolled

N = 104 invited women

N = 104 invited women

N = 78 completed the survey

Number of analysed patients

N = 78 completed the survey

N = 68 (87%) gave authorisation to review medical charts

N = 77 analysed

Results

  

Change in patient satisfaction

Most women (96%, 74/77) reported that they would have the test again if they had to decide today.

95%, 73/77 would recommend the test to other women.

95%, 73/77 agreed that having the test gave them a better understanding of their treatment option’s chances of success.

Few women had concerns about the test:

8% (6/77) of women reported that they had the test only because other family members wanted them to; 5% (4/77) reported that having the test had a negative effect on their family; only 3% (2/76) agreed that this information about one’s cancer is better left unknown.

Most women reported that they would have the test again if they had to decide today (96%).

95% would recommend the test to other women in the same situation.

Almost all women (95%) agreed that having the test gave them a better understanding of their treatment option’s chances of success.

Few women agreed that they had the test only because other family members wanted them to (8%); the test had a negative effect on their family (5%); that information about one’s cancer is better left unknown (3%, 2 of 76).

About 25% of women recalled experiencing test-related distress.

Approximately 26% (17 of 65) of women agreed or strongly agreed that receiving the test result made them worried and anxious.

Greater endorsement of test-related distress was associated with higher actual recurrence risk based on the test, as the majority of women who experienced test-related distress had intermediate or high recurrence risks based on their test results (low=18%, 6 of 33; intermediate =30%, 7 of 23; high=44%, 4 of 9). Stronger feelings of distress were also related to receiving chemotherapy, not receiving radiation, and having more frequent worries about breast cancer recurrence.

Approximately 3/4 said they trusted the test results (77%, 57 of 74); believed they were accurate (71%, 53 of 75); found the test useful because it could determine with certainty whether their cancer had a high chance of coming back (76%, 57 of 75).

Author disclosure (Conflict of interest)

  
 

No conflict of interest

Not reported

       

Appendix 5 Evidence table on uPA/PAI-1, Oncotype DX, MammaPrint test on research question: Changes in the treatment choice with adjuvant therapy

pdf113.EFF Appendix 5

Appendix 6 Excluded studies from the Systematic review of Clinical Effectiveness Domain (assessed only predictive accuracy or studies without standard/current care comparator) on assessment element question: ”Whether use of the three prognostic tests (uPA/PAI-1, OncotypeDX and MammaPrint to guide adjuvant chemotherapy effectively improves long term clinical outcomes, like overall survival and disease free survival”, with quality assessment according the GRADE

pdf113.EFF Appendix 6

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