Herceptin® (trastuzumab) in HER2-positive early breast cancer: protocol for a systematic review and cumulative network meta-analysis
Wilson et al. Systematic Reviews
Herceptin® (trastuzumab) in HER2-positive early breast cancer: protocol for a systematic review and cumulative network meta-analysis
Florence R. Wilson 2
Megan E. Coombes 1
Quinlan Wylie 2
Mariya Yurchenko 1
Christine Brezden-Masley 0
Brian Hutton 4 5
Becky Skidmore 3
Chris Cameron 2
0 St. Michael's Hospital , Toronto, Ontario , Canada
1 F. Hoffmann-La Roche Ltd , Mississauga, Ontario , Canada
2 Cornerstone Research Group, Inc. , Suite 204, 3228 South Service Road, Burlington, Ontario L7N 3H8 , Canada
3 Independent information specialist , Ottawa, Ontario , Canada
4 Public Health and Preventative Medicine, University of Ottawa School of Epidemiology , Ottawa, Ontario , Canada
5 Ottawa Hospital Research Institute , Ottawa, Ontario , Canada
Background: Human epidermal growth factor receptor 2-positive (HER2+) breast cancer is an aggressive disease that makes up about 20% of all invasive breast cancers. HER2+ breast cancer is associated with poor prognosis and high mortality rates, but the development of HER2-targeted therapies, such as originator trastuzumab (Herceptin®), has substantially improved patient survival. Numerous clinical trials and reviews have investigated the efficacy of HER2-targeted therapies over the past few decades; however, no study has specifically investigated the vast body of evidence on trastuzumab in comparison to chemotherapy regimens, endocrine therapies, and other targeted therapies. This systematic review and cumulative network meta-analysis (NMA) will synthesize available evidence to evaluate the survival benefit conferred by the addition of originator trastuzumab to standard chemotherapy and to compare the most widely used trastuzumab regimens in patients with HER2+ early breast cancer, based on results from randomized controlled trials (RCTs) and comparative observational studies. Methods/design: A systematic search of Embase, MEDLINE®, and the Cochrane Library has been designed by an experienced medical information specialist and peer reviewed by another senior information specialist. RCTs and comparative observational studies of patients with HER2+ early breast cancer indexed from 1990 onwards will be eligible for inclusion. Two investigators will independently assess studies for inclusion and use standardized data extraction templates to collect data on study and patient characteristics. The primary outcome of interest is overall survival. Bayesian cumulative NMA methods will be used to quantify the evolution of publicly available evidence using both fixed and random effects models. Discussion: This study will evaluate survival trends associated with originator trastuzumab in patients with HER2+ early breast cancer. As originator trastuzumab has been researched in both clinical and real-world settings for close to 20 years, a cumulative NMA is likely to show improved precision around the parameter estimates for trastuzumab now compared with when the drug was initially launched in the USA in 1998. A better understanding of the evolution of publicly available comparative evidence for originator trastuzumab will further inform treatment for patients with HER2+ early breast cancer, providing benefit to patients, health professionals, and researchers. Systematic review registration: PROSPERO CRD42017055763 https://www.crd.york.ac.uk/PROSPERO
Early breast cancer; HER2-positive breast cancer; Herceptin®; Targeted therapy; Trastuzumab; Survival; Systematic review; Network meta-analysis
Breast cancer is one of the most common types of
cancer, making up about 25% of all cancer diagnoses in
]. Advances in treatment and diagnostic
techniques have drastically lowered mortality rates; however,
breast cancer remains the second leading cause of death
for women [
]. Human epidermal growth factor receptor
2 (HER2) is a transmembrane tyrosine kinase that
controls cellular division and repair in breast cells. The
overexpression of HER2, termed HER2-positive (HER2+),
can result in uncontrolled growth and division of breast
]. Approximately 20% of all invasive breast
cancers are HER2+, which is a particularly aggressive form
of the disease [
]. Before current treatment options
became available, only 2–5% of HER2+ breast cancer
patients were classified as “long-term survivors” .
Fortunately, HER2-targeted therapies have been developed
beginning with originator trastuzumab (Herceptin®; F.
Hoffmann-La Roche Ltd.) in the 1990s to help combat
this aggressive cancer.
In 1998, the US Food and Drug Administration (FDA)
approved originator trastuzumab (Herceptin®) as the first
antibody-targeted therapy for breast cancer [
Canada followed suit in 1999 and approved originator
trastuzumab (Herceptin®) for the treatment of metastatic
breast cancer [
]. Soon after, the FDA and Health
Canada expanded the approved use of originator
trastuzumab for the treatment of early stage HER2+ breast
cancer following the promising results of adjuvant breast
cancer clinical trials [
]. Trastuzumab binds to the
extracellular domain IV of HER2, thereby inhibiting
downstream cell signaling that is implicated in cell
proliferation, survival, motility, and adhesion .
Clinical trials in HER2+ breast cancer have established that
treatment with originator trastuzumab in combination
with chemotherapy, compared with chemotherapy alone,
increases the time to disease progression and overall
survival (OS) in both the metastatic and adjuvant
Many clinical trials have investigated the efficacy and
safety of originator trastuzumab over the past few
decades, including NSABP B-31, NCCTG N9831,
BCIRG-006, and the Herceptin® Adjuvant (HERA) trials.
The NSABP B-31/NCCTG N9831 joint analysis and the
BCIRG-006 clinical trial investigated the use of
originator trastuzumab in combination with standard adjuvant
chemotherapies, such as doxorubicin, cyclophosphamide,
and paclitaxel, compared with standard chemotherapy
]. In both cases, treatment with
originator trastuzumab significantly improved disease-free
survival (DFS) and OS in HER2+ early breast cancer
]. The HERA trial was a phase III
randomized controlled trial (RCT) that investigated the
efficacy of originator trastuzumab administered for 1
or 2 years in combination with standard
chemotherapy, compared with standard chemotherapy alone
]. The initial trial results were overwhelmingly
positive, and patients assigned to chemotherapy alone
were allowed to receive originator trastuzumab [
At a median follow-up of 8 years, DFS and OS were
significantly improved for patients who received 1 year
of trastuzumab compared with chemotherapy alone,
although neither DFS nor OS differed between the
trastuzumab groups [
]. These key trials suggest that
originator trastuzumab is a highly efficacious treatment
for patients with HER2+ early breast cancer.
While originator trastuzumab is used worldwide, there
are a number of other HER2-targeted therapies that have
since been developed and used successfully, including
lapatinib, pertuzumab, and trastuzumab emtansine.
Several systematic literature reviews (SLRs) and
metaanalyses (MAs) have been conducted to evaluate the
safety and efficacy of HER2-targeted therapies. A recent
systematic review by Nagayama et al. [
MEDLINE® and the Cochrane Central Register of
Controlled Trials for RCTs published up to August
2012. Eligible studies contained at least two treatment
arms, including chemotherapy and/or an anti-HER2
agent in patients with pre-operative HER2+ breast
cancer. Outcomes were analyzed from 10 RCTs, and a
Bayesian network meta-analysis (NMA) was conducted
to investigate the effect of different neoadjuvant
therapies on pathologic complete response (pCR). Findings
from this NMA suggest that the combination of
originator trastuzumab and pertuzumab with neoadjuvant
chemotherapy is more effective than chemotherapy and
originator trastuzumab alone [
]. Outcomes were
significantly worse for chemotherapy and lapatinib
than for chemotherapy and originator trastuzumab
]. An NMA consists of a network of multiple
comparators (i.e., interventions to treat the same disease)
to assess how they compare in achieving a certain
outcome (e.g., patient survival). The advantage of
using an NMA instead of a more conventional MA is
that the network allows indirect comparisons to be
made between interventions which did not exist in
the primary research.
While studies such as that by Nagayama et al. [
invaluable to our understanding of anti-HER2 therapies
in treating breast cancer, no study has yet been carried
out to specifically investigate the vast body of publicy
available evidence on originator trastuzumab and how
this evidence has changed over time. We will perform
an SLR and cumulative NMA to investigate the survival
advantage conferred by the addition of originator
trastuzumab to standard chemotherapy and also to compare
the most widely used trastuzumab regimens in HER2+
early breast cancer. This will serve to quantify the value
of decades of research on originator trastuzumab and to
further define its benefit to patient survival.
This protocol is registered on PROSPERO (CRD42017
055763), https://www.crd.york.ac.uk/PROSPERO, and is
designed to identify and summarize the published
comparative data on originator trastuzumab relative to
existing treatments on survival outcomes in HER2+ early
breast cancer. This protocol has been designed and
reported according to the Preferred Reporting Items for
Systematic Review and Meta-Analysis Protocols (PRISMA-P)
] (Additional file 1).
An experienced medical information specialist
developed and tested the search strategy using an iterative
process in consultation with the review team. Another
senior information specialist peer-reviewed the strategy
prior to its execution using the PRESS checklist [
(Additional file 2). Using the OVID platform, we will
search Embase and Ovid MEDLINE®, including Epub
Ahead of Print and In-Process & Other Non-Indexed
Citations. We will also search the Cochrane Library
on Wiley. Monthly alerts will be established.
Strategies will use a combination of controlled vocabulary
(e.g., “Breast Neoplasms,” “Chemotherapy, Adjuvant,”
“Trastuzumab”) and keywords (e.g., “HER 2,”
“adjuvant chemotherapy,” “Herceptin”). Vocabulary and
syntax will be adjusted across databases. Standardized
filters will be applied for study designs, including the
Cochrane highly sensitive search strategy for RCTs.
Results will be limited to the English language and
publication dates January 1, 1990, to present. Although
the first originator trastuzumab trial was initiated in 1992
in metastatic breast cancer, the first adjuvant originator
trastuzumab trial was not published until 2005 [
Therefore, we chose 1990 as our starting period to ensure
the capture of all relevant studies.
In addition, we will perform a targeted gray
literature search of trial registries using ClinicalTrials.gov,
and we will review bibliographies of relevant SLRs
and MAs identified via the database searches. These
targeted searches will allow us to cross-reference our
study list with registered clinical trials, and existing
reviews to ensure that no studies are missed. Specific
details regarding the proposed search strategies
appear in Additional file 3.
Studies that meet the following PICOS
criteria will be included in this review:
Studies involving adult patients (≥ 18 years) with HER2+
early breast cancer (stages 0 to IIIC) will be included.
Patients with locally advanced or inflammatory breast
cancer and patients receiving neoadjuvant and adjuvant
therapies will be included.
The intervention of interest in the NMA will be
originator trastuzumab administered intravenously (IV) in the
early breast cancer setting. All trastuzumab doses,
treatment schedules, and durations will be eligible.
Trastuzumab may be combined with any other drug regimen.
Various drug regimens for HER2+ early breast cancer
that do not include trastuzumab IV will be included as
comparators, including chemotherapy agents (e.g.,
carboplatin, docetaxel, epirubicin), hormonal therapies (e.g.,
anastrozole, fulvestrant, tamoxifen), and targeted
therapies (e.g., bevacizumab, lapatinib, trastuzumab
emtansine). All doses, formulations, and treatment durations
will be eligible. All included comparators are provided in
Additional file 3.
Overall survival is the primary outcome of interest. If
possible, we may also evaluate at least one measure of
xfree survival (xFS), where x stands for measures such as
disease (DFS), invasive disease (iDFS), event (EFS), and
recurrence (RFS). The choice of xFS outcome will be
based on data availability and homogeneity of outcome
definitions across studies. If possible, pCR will also be
evaluated. Median endpoints and hazard ratios (HR) will
be extracted for each outcome, when available.
Randomized controlled trials and comparative
observational studies (e.g., case-control, cross-sectional,
longitudinal, and cohort studies) will be included.
Any comparative observational studies that meet our
inclusion criteria will be potentially eligible for
inclusion, including but not limited to studies using
propensity score methods or multivariable regression,
provided that hazard ratios that appropriately adjust
for covariates are available.
Study screening will be conducted by two reviewers who
will independently review the study records, citation
titles, and abstracts identified in the literature search to
assess study eligibility based on the PICOS criteria.
Reviewers will document reasons for exclusion and present
the results in the form of a PRISMA flow diagram [
Citations considered to describe potentially eligible
articles will be independently reviewed in full-text form for
formal inclusion in the final review. Disagreements will
be resolved by discussion or by an independent third
reviewer not involved in the data collection process.
Details for selected articles will be collected using
standardized data extraction templates, including general
study information (trial name, author, publication date,
NCT number), study characteristics (study design,
blinding, setting, interventions, dosing regimens, treatment
duration, length of follow-up), baseline population
characteristics (sample size, age, gender, Eastern Cooperative
Oncology Group (ECOG) performance status, disease
status [stage, hormone receptor status, HER2 status],
previous treatments/surgeries, presence of risk factors),
definition of survival measures, results, assessment of
risk of bias by outcome, and study limitations
(compliance, cross-over). For non-randomized studies,
additional details outlined in STROBE Guidelines will be
]. For example, we will capture information
related to study design, statistical methods and analysis
(including those used to control for confounding),
covariates considered, data sources, methods used to examine
subgroups and interactions, how missing data was
addressed, confounder-adjusted estimates, unadjusted
estimates and their precision, and numbers of individuals at
each stage of the study (numbers potentially eligible,
examined for eligibility, confirmed eligible, included in the
study, completing follow-up, and analyzed). An
independent reviewer will review the data extraction
document to check data accuracy and will document quality
review throughout. No adverse events/safety information
will be extracted as per protocol; therefore, the study
report and final publication will not include a summary of
Risk of bias assessment
The risk of bias assessment of eligible studies will be
performed in duplicate using the Cochrane Risk of Bias
Assessment Tool for Randomized Controlled Trials [
and the Cochrane Risk Of Bias in Non-randomized
Studies - of Interventions tool (ROBINS-I) [
results will be reported as summary tables in the final
analysis to highlight any weaknesses in the studies and to
help us address any discrepancies in results.
Approach to evidence synthesis
Based on the findings of the SLR, Bayesian NMAs will
be conducted to calculate the effect of Herceptin® on the
survival outcomes of interest, based on well-established
methods by the National Institute for Health and Care
Excellence (NICE) [
]. We will perform a cumulative
NMA to illustrate the survival advantage conferred by the
addition of originator trastuzumab to standard
chemotherapy and also to compare the most widely used
trastuzumab regimens. Studies selected for inclusion will
be reviewed to assess the distribution of treatment
effect modifiers across studies and to assess the validity
of the assumptions of homogeneity, similarity, and
Cumulative network meta-analysis methods
A cumulative meta-analysis is a series of meta-analyses
sequenced according to the chronology of the
publication date of included trials, wherein each meta-analysis
in the series incorporates additional studies over time;
however, most cumulative meta-analyses to date have
focused on only comparing two treatments (i.e.,
traditional meta-analysis). A cumulative NMA will be used
to evaluate networks of originator trastuzumab over
time. This method will be particularly beneficial to
quantify the value associated with the years of clinical
experience and publicly available information about the
survival benefit conferred by originator trastuzumab in
patients with HER2+ early breast cancer. As originator
trastuzumab has been researched in both clinical and
real-world settings for close to 20 years, it is likely to have
greater precision around its parameter estimates now
compared with when the drug was initially launched in
the USA in 1998, and this can be clearly reflected using a
cumulative NMA rather than a standard NMA.
Evidence network geometry
Evidence networks will be constructed to best reflect the
interventions of interest, based on advice from clinical
experts. To maximize clinical relevance, therapy doses
that are importantly different will be separated into
distinct nodes, while other similar treatments will be
pooled together. Separate evidence networks will be
generated over time and separate NMAs will be conducted
based on survival outcomes of interest, publication date,
and study design.
Planned methods of analysis and summary measures of treatment effect
Both fixed effects and random effects NMA models will
be conducted. A cumulative NMA using the random
effects model will be used as the reference case. Vague
or flat priors, such as N(0, 1002), will be assigned for
basic parameters throughout, although informative
priors will also be considered. A normal likelihood
model which accounts for use of multi-arm trials will be
used for analyses. In accordance with NICE Technical
Support Document (TSD) methods [
], the log HR
will be treated as a continuous outcome and the final
results will be subsequently exponentiated. As a measure
of the association between each treatment and its
efficacy, Markov Chain Monte Carlo methods will be used
to model HR point estimates and 95% credible intervals
(CrIs) for each pairwise comparison for survival
outcomes of interest. Time permitting, we will also run
NMAs analyzing whole survival curves as a sensitivity
analysis, whereby a multi-dimensional treatment effect
approach will be used to model the hazard over time
with fractional polynomials [
]. The cumulative
NMA will focus on pairwise comparisons between the
two most widely used trastuzumab regimens and a
reference treatment. We will generate “probability better”
values as a measure of effect to show the probability of
one treatment regimen being better than another within
each pairwise comparison of interest.
All analyses will be conducted using R (R Core Team,
Vienna, Austria) and WinBUGS software (MRC
Biostatistics Unit, Cambridge, UK) based on the WinBUGS
code outlined in the NICE Evidence Synthesis TSD
]. Model convergence will be assessed
using trace plots, the Brooks-Gelman-Rubin statistic,
and inspection of Monte Carlo errors . Three
chains will be fitted in WinBUGS for each analysis,
with at least 40,000 iterations, and a burn-in of at least
Assessment of heterogeneity and inconsistency
A key assumption behind NMA is that the analyzed
network is consistent; that is, there is no conflict
between direct and indirect evidence. We will assess
inconsistency using methods outlined in NICE Evidence
Synthesis Technical Support Series [
assessment of consistency will be based on assessing
model fit using the deviance information criterion (DIC)
and comparison of the posterior residual deviance from
each NMA to the corresponding number of
unconstrained data points (approximately equal if fit is
]. Scatterplots of deviance residuals and
consistency versus inconsistency estimates for each
outcome will be inspected to identify potential studies
contributing to inconsistency. Additionally, NMA results
will be qualitatively compared with direct frequentist
Network meta-analysis requires that studies are
sufficiently similar in order to pool the results.
Exchangeability is a key assumption underlying NMA, and additional
concerns arise when RCTs and non-randomized studies
are both included [
]. Including high-quality
nonrandomized studies can allow larger, diverse populations,
and additional treatments to be included; however,
including low-quality non-randomized studies can
introduce confounding bias if the baseline characteristics and
risk factors are substantially different between treatment
]. Based on these factors, available study
and patient characteristics will be thoroughly assessed to
ensure similarity and to investigate the potential impact
of heterogeneity on effect estimates. Depending on data
availability, clinical and methodological heterogeneity
will be assessed, and sensitivity, subgroup, and
metaregression analyses will be conducted where possible.
Group-level factors will also be considered, such as
neoadjuvant investigational therapy, adjuvant investigational
therapy, treatment with anthracycline-based
chemotherapy, treatment with non-anthracycline-based
chemotherapy, node positive breast cancer, node negative breast
cancer, hormone receptor-positive (HR+) breast cancer,
hormone receptor-negative (HR-) breast cancer, small
(< 2 cm) tumor size, and large (≥ 2 cm) tumor size.
Network meta-analysis methods for incorporating non-randomized studies
There are various approaches for combining RCTs and
non-randomized studies in NMAs, and the validity of
the studies must be carefully evaluated [
analyses or sensitivity analyses incorporating
nonrandomized studies, we will use a Bayesian hierarchical
model, which is generally considered the most flexible
]. A Bayesian hierarchical model is a statistical
model that estimates the parameters of the posterior
distribution using the Bayesian method [
]. In the
model, a study design level (e.g., RCT, non-randomized
study) is introduced [
]. This approach allows for
bias adjustments, as well as a direct comparison of
study design-specific estimates to overall estimates. For
example, evidence from individual studies of the same
design can first be combined to produce study design
level estimates; the study design level estimates can
then be combined to obtain overall estimates [
It also gives an estimate of consistency between study
designs. NMA results from the Bayesian hierarchical
model will be stratified by RCTs alone, by
nonrandomized studies alone (if possible), and by
combining RCTs and non-randomized studies. Stratification on
various non-randomized study designs (e.g.,
casecontrol, cross-sectional, longitudinal, cohort studies)
and statistical analyses for certain study designs (e.g.,
propensity score matching, disease risk scores,
multivariable regression) will also be considered.
The development of HER2-targeted therapies, such as
trastuzumab, has been the key for treating HER2
overexpressing cancers which were previously associated with
high relapse and mortality rates. Since the FDA approval
of originator trastuzumab (Herceptin®) in 1998, other
drugs have been approved which similarly act on the
HER2 tyrosine kinase. After decades of research on
originator trastuzumab and now that there are various
therapy options available for HER2+ breast cancer, the
oncology field would benefit from a large-scale appraisal
of the body of evidence. To our knowledge, we are the
first to carry out such a large-scale evaluation of the
survival advantage of originator trastuzumab in
comparison to chemotherapeutic regimens, endocrine therapies,
and other HER2-targeted therapies in the curative
setting. Our decision to include both RCTs and
nonrandomized studies makes this NMA unique as most
NMAs do not include comparative observational studies.
While this complicates the Bayesian analysis, including
non-randomized studies will provide more data on
competing therapies and will expand the evidence network
to provide more evidence to strengthen the
comparisons. Additionally, observational studies may more
accurately reflect the realities of the patient experience
as they navigate the medical field.
The primary outcome of interest will be overall
survival, typically measured as the percentage of patients
in a given treatment group who survive to the end of
the study or measured from the time of
randomization to the time of death from any cause
]. The selection of OS as the primary endpoint
was a strategic choice based on several factors.
Importantly, OS is a universal measurement that directly
evaluates the benefit of a given treatment and thus is
traditionally considered to be the most clinically
relevant endpoint. It is an objective endpoint that is
easily measured and consistently defined across
studies, and therefore rarely subject to error [
If possible, we may also evaluate at least one measure
of pCR or xFS, including DFS/iDFS, EFS, or RFS. These
endpoints provide important measurements for clinical
outcome in patients. The use of xFS in analyses relies
on data availability and homogeneity of outcome
definitions across studies; however, there is variability in the
definitions of each of these outcomes. For example,
DFS can be reported as time passed until symptoms of
cancer arise, as the FDA and National Cancer Institute
both define it [
], whereas other institutions such as
Cancer Research UK report DFS as the proportion of
patients who are alive and cancer-free after a specified
amount of time, usually a year [
]. Additionally, there
are inconsistencies in what defines a breast cancer
event, such as instances where in situ carcinomas could
include both lobular and ductal cases or ductal cases
]. There are also inconsistencies in what
defines a secondary cancer (i.e., if it includes
contralateral breast cancer, excludes non-breast cancers or
unknown cancer at non-breast sites) [
]. There is also
a greater chance of missing or incomplete data for xFS
endpoints, which may lead to biased results due to
]. Based on these reasons, our analyses
will focus primarily on OS.
The current study will be the first systematic review
and cumulative NMA that specifically evaluates the
totality of the publicly available evidence on originator
trastuzumab as a treatment for HER2+ early breast
cancer, and the first NMA that combines RCTs and
nonrandomized studies of originator trastuzumab compared
with alternative treatments. These analyses will be an
important contribution to the field, which needs a
comprehensive summary of the evolution of publicly
available comparative evidence for the survival benefit
conferred by originator trastuzumab. By investigating
the survival advantage conferred by the addition of
originator trastuzumab to standard chemotherapy regimens
and by comparing the most widely used trastuzumab
regimens, we will further inform the treatment of
patients with HER2+ early breast cancer.
Additional file 1: PRISMA-P Checklist. Contains the completed PRISMA-P
checklist. (DOCX 31 kb)
Additional file 2: PRESS Checklist. Contains the completed PRESS
checklist. (DOCX 80 kb)
Additional file 3: Search Strategy. Contains the search strategy to be
used for the planned systematic literature review. (DOCX 37 kb)
CrI: Credible interval; DFS: Disease-free survival; ECOG: Eastern Cooperative
Oncology Group; EFS: Event-free survival; HER2: Human epidermal growth
factor receptor 2; HR: Hazard ratio; HR−: Hormone receptor-negative; HR
+: Hormone receptor-positive; IDFS: Invasive disease-free survival;
IV: Intravenous; MA: Meta-analysis; NMA: Network meta-analysis; OS: Overall
survival; pCR: Pathologic complete response; PRISMA: Preferred Reporting
Items for Systematic Reviews and Meta-Analysis; RCT: Randomized controlled
trial; RFS: Recurrence-free survival; ROBINS-I: Risk Of Bias in Non-randomized
Studies - of Interventions; SLR: Systematic literature review; xFS: x-free
Financial support for this study was provided by Roche Canada.
Availability of data and materials
All authors contributed significantly to the conception, design, and writing
of the manuscript. FW contributed to the conception of the study question
and design, and drafted the initial version of the manuscript. MC contributed
to the conception of the clinical question to be addressed by the review,
and provided clinical expertise in designing the project and developing the
manuscript. QW contributed to the conception of the study question, and
drafted the initial version of the manuscript. MY contributed to the
conception of the clinical question to be addressed by the review, and
provided clinical expertise in designing the project and developing the
manuscript. CB provided clinical expertise in designing the project and
developing the manuscript. BH provided methodological advice for data
analysis and interpretation. BS derived the literature search strategy for the
review. CC contributed to the design and refinement of methodologies for
the review. All authors read and approved the final manuscript.
Ethics approval and consent to participate
Not applicable; this analysis is based on published aggregate data and does
not require ethical approval or informed consent.
Consent for publication
MC and MY are employees of F. Hoffmann-La Roche Ltd. CC is a partner at
Cornerstone Research Group Inc., while FW and QW are employees of
Cornerstone Research Group Inc. BH provides methodological advice for
Cornerstone Research Group Inc. Cornerstone Research Group Inc. received
financial support from F. Hoffmann-La Roche Ltd. Cornerstone Research
Group Inc. consults for various pharmaceutical, medical device, and biotech
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
1. GLOBOCAN 2012: Estimated cancer incidence, mortality and prevalence worldwide in 2012 . http://globocan.iarc.fr/Pages/fact_sheets_cancer. aspx. Accessed 23 Aug 2016 .
2. Yeo B , Turner N , Jones A . An update on the medical management of breast cancer . BMJ . 2014 ; 348 : g3608 .
3. HER2 status. http://www.breastcancer.org/symptoms/diagnosis/her2. Accessed 22 Aug 2016 .
4. Fabi A , Malaguti P , Vari S , Cognetti F. First-line therapy in HER2 positive metastatic breast cancer: is the mosaic fully completed or are we missing additional pieces ? J Exp Clin Cancer Res . 2016 ; 35 : 104 .
5. HER2 Testing for Breast Cancer . http://www.cancer.net/research-andadvocacy/ asco-care-and-treatment-recommendations-patients/her2-testingbreast-cancer . Accessed 17 July 2017 .
6. Siegel J . Herceptin FDA approval letter . 1998 . https://www.accessdata.fda. gov/drugsatfda_docs/appletter/1998/trasgen092598L.pdf. Accessed 22 Aug 2016 .
7. Health Canada . Product Information: Herceptin . 2017 . https://healthproducts.canada.ca/dpd-bdpp/info.do? lang=en&code=64277. Accessed 4 Oct 2017 .
8. Genentech Inc . Herceptin USPI . 2016 . https://www.gene.com/download/ pdf/herceptin_prescribing. pdf. Accessed 23 Aug 2016 .
9. Hoffmann-La Roche . Product Monograph: Herceptin . 2015 . http://www. rochecanada.com/content/dam/roche_canada/en_CA/documents/Research/ ClinicalTrialsForms/Products/ConsumerInformation/MonographsandPublic Advisories/Herceptin/Herceptin_PM_E.pdf. Accessed 23 Aug 2016 .
10. Ross JS , Slodkowska EA , Symmans WF , Pusztai L , Ravdin PM , Hortobagyi GN . The HER-2 receptor and breast cancer: ten years of targeted anti-HER-2 therapy and personalized medicine . Oncologist . 2009 ; 14 : 320 - 68 .
11. Slamon DJ , Leyland-Jones B , Shak S , Fuchs H , Paton V , Bajamonde A , et al. Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2 . N Engl J Med . 2001 ; 344 : 783 - 92 .
12. Piccart-Gebhart MJ , Procter M , Leyland-Jones B , Goldhirsch A , Untch M , Smith I , et al. Trastuzumab after adjuvant chemotherapy in HER2-positive breast cancer . N Engl J Med . 2005 ; 353 : 1659 - 72 .
13. Romond EH , Perez EA , Bryant J , Suman VJ , Geyer CE Jr, Davidson NE , et al. Trastuzumab plus adjuvant chemotherapy for operable HER2-positive breast cancer . N Engl J Med . 2005 ; 353 : 1673 - 84 .
14. Gianni L , Dafni U , Gelber RD , Azambuja E , Muehlbauer S , Goldhirsch A , et al. Treatment with trastuzumab for 1 year after adjuvant chemotherapy in patients with HER2-positive early breast cancer: a 4-year follow-up of a randomised controlled trial . Lancet Oncol . 2011 ; 12 : 236 - 44 .
15. Gianni L , Eiermann W , Semiglazov V , Lluch A , Tjulandin S , Zambetti M , et al. Neoadjuvant and adjuvant trastuzumab in patients with HER2-positive locally advanced breast cancer (NOAH): follow-up of a randomised controlled superiority trial with a parallel HER2-negative cohort . Lancet Oncol . 2014 ; 15 : 640 - 7 .
16. Perez EA , Romond EH , Suman VJ , Jeong JH , Sledge G , Geyer CE Jr, et al. Trastuzumab plus adjuvant chemotherapy for human epidermal growth factor receptor 2-positive breast cancer: planned joint analysis of overall survival from NSABP B-31 and NCCTG N9831. J Clin Oncol . 2014 ; 32 : 3744 - 52 .
17. Slamon DJ , Eiermann W , Robert NJ , Giermek J , Martin M , Jasiowka M , et al. Ten year follow-up of BCIRG-006 comparing doxorubicin plus cyclophosphamide followed by docetaxel (AC→T) with doxorubicin plus cyclophosphamide followed by docetaxel and trastuzumab (AC→TH) with docetaxel, carboplatin and trastuzumab (TCH) in HER2+ early breast cancer [abstract] . In: Proceedings of the 38th Annual CTRC-AACRSan Antonio Breast Cancer Symposium: 2015 Dec 8 -12; San Antonio, TX, United States . Cancer Research . 2016 ; 76 ( 4 Suppl) : S5 - 04 .
18. Goldhirsch A , Gelber RD , Piccart-Gebhart MJ , de Azambuja E , Procter M , Suter TM , et al. 2 years versus 1 year of adjuvant trastuzumab for HER2- positive breast cancer (HERA): an open-label, randomised controlled trial . Lancet . 2013 ; 382 : 1021 - 8 .
19. Nagayama A , Hayashida T , Jinno H , Takahashi M , Seki T , Matsumoto A , et al. Comparative effectiveness of neoadjuvant therapy for HER2-positive breast cancer: a network meta-analysis . J Natl Cancer Inst . 2014 ; 106 : 1 - 9 .
20. Moher D , Shamseer L , Clarke M , Ghersi D , Liberati A , Petticrew M , et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement . Syst Rev . 2015 ; 4 : 1 .
21. McGowan J , Sampson M , Salzwedel DM , Cogo E , Foerster V , Lefebvre C . PRESS peer review of electronic search strategies: 2015 guideline statement . J Clin Epidemiol . 2016 ; 75 : 40 - 6 .
22. Harries M , Smith I. The development and clinical use of trastuzumab (Herceptin) . Endocr Relat Cancer . 2002 ; 9 : 75 - 85 .
23. Moher D , Liberati A , Tetzlaff J , Altman DG , Group P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement . Ann Intern Med . 2009 ; 151 : 264 - 9 . W64
24. von Elm E , Altman DG , Egger M , Pocock SJ , Gotzsche PC , Vandenbroucke JP , et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies . Prev Med . 2007 ; 45 : 247 - 51 .
25. Higgins JP , Altman DG , Gotzsche PC , Juni P , Moher D , Oxman AD , et al. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials . BMJ . 2011 ; 343 : d5928 .
26. Sterne JAC , Higgins JPT , and Reeves BC . On behalf of the development group for ROBINS-I. ROBINS-I: a tool for assessing Risk Of Bias In Nonrandomized Studies of Interventions, Version 5 July 2016 . http://www. riskofbias. info. Accessed 9 Sep 2016 .
27. Dias S , Sutton AJ , Ades AE , Welton NJ . Evidence synthesis for decision making 2: a generalized linear modeling framework for pairwise and network meta-analysis of randomized controlled trials . Med Decis Mak . 2013 ; 33 : 607 - 17 .
28. Dias S , Welton NJ , Sutton AJ , Ades AE . Evidence synthesis for decision making 1: introduction . Med Decis Mak . 2013 ; 33 : 597 - 606 .
29. Donegan S , Williamson P , D'Alessandro U , Tudur SC . Assessing key assumptions of network meta-analysis: a review of methods . Res Synth Methods . 2013 ; 4 : 291 - 323 .
30. Jansen JP . Network meta-analysis of survival data with fractional polynomials . BMC Med Res Methodol . 2011 ; 11 : 61 .
31. Cope S , Zhang J , Saletan S , Smiechowski B , Jansen JP , Schmid P. A process for assessing the feasibility of a network meta-analysis: a case study of everolimus in combination with hormonal therapy versus chemotherapy for advanced breast cancer . BMC Med . 2014 ; 12 : 93 .
32. Ouwens MJ , Philips Z , Jansen JP . Network meta-analysis of parametric survival curves . Res Synth Methods . 2010 ; 1 : 258 - 71 .
33. Guyot P , Ades AE , Ouwens MJ , Welton NJ . Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves . BMC Med Res Methodol . 2012 ; 12 : 9 .
34. Dias S , Welton NJ , Sutton AJ , Caldwell DM , Lu G , Ades AE . Evidence synthesis for decision making 4: inconsistency in networks of evidence based on randomized controlled trials . Med Decis Mak . 2013 ; 33 : 641 - 56 .
35. Cameron C , Fireman B , Hutton B , Clifford T , Coyle D , Wells G , et al. Network meta-analysis incorporating randomized controlled trials and nonrandomized comparative cohort studies for assessing the safety and effectiveness of medical treatments: challenges and opportunities . Syst Rev . 2015 ; 4 : 147 .
36. Walker AM . Confounding by indication . Epidemiology . 1996 ; 7 : 335 - 6 .
37. Grimes DA , Schulz KF . Bias and causal associations in observational research . Lancet. 2002 ; 359 : 248 - 52 .
38. Verde PE , Ohmann C. Combining randomized and non-randomized evidence in clinical research: a review of methods and applications . Res Synth Methods . 2015 ; 6 : 45 - 62 .
39. Schmitz S , Adamsb R , Walsha C . Incorporating data from various trial designs into a mixed treatment comparison model . Stat Med . 2013 ; 32 : 2935 - 49 .
40. McCarron CE , Pullenayegum EM , Thabane L , Goeree R , Tarride JE . Bayesian hierarchical models combining different study types and adjusting for covariate imbalances: a simulation study to assess model performance . PLoS One . 2011 ; 6 : e25635 .
41. McCarron CE , Pullenayegum EM , Thabane L , Goeree R , Tarride JE . The importance of adjusting for potential confounders in Bayesian hierarchical models synthesising evidence from randomised and non-randomised studies: an application comparing treatments for abdominal aortic aneurysms . BMC Med Res Methodol . 2010 ; 10 : 64 .
42. U.S. Department of Health and Human Services Food and Drug Administration. Guidance for Industry Clinical Trial Endpoints for the Approval of Cancer Drugs and Biologics . 2007 .https://www.fda.gov/ downloads/Drugs/.../Guidances/ucm071590.pdf. Accessed 23 Aug 2016 .
43. National Cancer Institute-Dictionary of terms. https://www.cancer.gov/ publications/dictionaries/cancer-terms ?cdrid=44023. Accessed 19 Oct 2016 .
44. Cancer Research UK. What do clinical trial results mean? 2015 . http://www. cancerresearchuk.org/aboutcancer/find -a-clinical-trial/clinical-trial-results/ what-do-clinical-trial-results-mean . Accessed 19 Oct 2016 .
45. Hudis CA , Barlow WE , Costantino JP , Gray RJ , Pritchard KI , Chapman JA , et al. Proposal for standardized definitions for efficacy end points in adjuvant breast cancer trials: the STEEP system . J Clin Oncol . 2007 ; 25 : 2127 - 32 .
46. Villaruz LC , Socinski MA . The clinical viewpoint: definitions, limitations of RECIST, practical considerations of measurement . Clin Cancer Res . 2013 ; 19 : 2629 - 36 .
47. Sridhara R , Mandrekar SJ , Dodd LE . Missing data and measurement variability in assessing progression-free survival endpoint in randomized clinical trials . Clin Cancer Res . 2013 ; 19 : 2613 - 20 .