Consensus Statement on next-generation-sequencing-based diagnostic testing of hereditary phaeochromocytomas and paragangliomas

TL;DR: The study group recommends target gene panels for screening of germ line DNA, technical adaptations to address different modes of disease transmission, orthogonal validation of NGS findings, standardized classification of variant pathogenicity and uniform reporting of the findings.

Abstract: As a large number of genes have been implicated in the development of hereditary phaeochromocytomas and paragangliomas (PPGLs), next-generation sequencing (NGS) technology is ideally suited for carrying out genetic screening. This Consensus Statement proposes specific recommendations for the use of diagnostic NGS in hereditary PPGLs.

Full text

Phaeochromocytomas and paragangliomas (PPGLs) are
catecholamine-secreting, neural-crest-derived tumours
of the adrenal medulla and extra-adrenal sympathetic
nervous system, respectively
1,2
. Paragangliomas can also
arise from the parasympathetic nervous system; these
tumours are usually located in the head and neck and
typically do not secrete catecholamines
3
. Approximately
50% of PPGLs are caused by a single driver germ line
mutation, which means that these tumours are the most
highly heritable tumours in humans
1
. Due to this high
heritability, genetic testing has been recommended in
all patients with PPGLs independent of a clear family
history
4
. Another striking characteristic of PPGLs is their
genetic heterogeneity. Over 15 different susceptibility
genes have been implicated in familial cases; however,
the susceptibility gene has not been identified in all cases,
which indicates that this number will continue to grow in
the near future
1,2
(TABLE1). As a result of this large number
of driver genes, genetic diagnosis of PPGLs by traditional
technologies, including PCR-based amplification followed
by Sanger sequencing and multiplex ligation-dependent
probe amplification (MLPA) for larger gene disruptions,
is becoming impractical as they are laborious, costly and
time consuming.
Correspondence to P.L.M.D.
and A.-P.G.-R.
dahia@uthscsa.edu;
anne-paule.gimenez-
roqueplo@aphp.fr
doi:10.1038/nrendo.2016.185
Published online 18 Nov 2016
EXPERT CONSENSUS DOCUMENT
Consensus Statement on next-
generation-sequencing-based
diagnostic testing of hereditary
phaeochromocytomas and
paragangliomas
The NGS in PPGL (NGSnPPGL) Study Group, Rodrigo A.Toledo
1,2
, Nelly Burnichon
3,4
,
Alberto Cascon
5
, Diana E.Benn
6
, Jean-Pierre Bayley
7
, Jenny Welander
8
, Carli M.Tops
9
,
Helen Firth
10
, Trish Dwight
6
, Tonino Ercolino
11
, Massimo Mannelli
11
, Giuseppe Opocher
12
,
Roderick Clifton-Bligh
6
, Oliver Gimm
13
, Eamonn R.Maher
10
, Mercedes Robledo
5
,
Anne-Paule Gimenez-Roqueplo
3,4
and Patricia L.M.Dahia
1
Abstract
|
Phaeochromocytomas and paragangliomas (PPGLs) are neural-crest-derived tumours
of the sympathetic or parasympathetic nervous system that are often inherited and are
genetically heterogeneous. Genetic testing is recommended for patients with these tumours and
for family members of patients with hereditary forms of PPGLs. Due to the large number of
susceptibility genes implicated in the diagnosis of inherited PPGLs, next-generation sequencing
(NGS) technology is ideally suited for carrying out genetic screening of these individuals. This
Consensus Statement, formulated by a study group comprised of experts in the field, proposes
specific recommendations for the use of diagnostic NGS in hereditary PPGLs. In brief, the study
group recommends target gene panels for screening of germ line DNA, technical adaptations to
address different modes of disease transmission, orthogonal validation of NGS findings,
standardized classification of variant pathogenicity and uniform reporting of the findings. The
use of supplementary assays, to aid in the interpretation of the results, and sequencing of tumour
DNA, for identification of somatic mutations, is encouraged. In addition, the study group
launches an initiative to develop a gene-centric curated database of PPGL variants, with annual
re-evaluation of variants of unknown significance by an expert group for purposes of
reclassification and clinical guidance.
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CONSENSUS
STATEMENT
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Genetic testing algorithms based on clinical features
(that is, tumour localization, malignancy and syndromic
characteristics), biochemical profile (that is, types of cat-
echolamines secreted by the tumour) or immunohisto-
chemistry pattern have been developed to aid prioritizing
genetic testing of a single or a few PPGLs susceptibility
genes
5–9
. Although this approach is helpful for patients
in whom a pathogenic driver mutation is identified
promptly, it can be cumbersome when this quick identifi-
cation does not happen, as the analysis must be extended
to the remaining susceptibility genes. Notably, when var-
iants of unknown significance (VUS; variants for which
the pathogenicity is not clear) are found in the initial test,
expanded screening is required in an effort to identify a
more plausible causative mutation
10
.
The technology that has become widely known as
next-generation sequencing (NGS) was first introduced
in 2005 (REF.11 ). Using novel methods of sequencing by
ligation or synthesis, NGS platforms enhanced the capa-
bility of genetic testing by many orders of magnitude.
In the first decade of its use, NGS methodology was
improved to increase throughput, accuracy and speed,
while simultaneously reducing costs and experimen-
tal complexity. Currently available NGS platforms are
powerful and flexible, and can be adapted easily to the
analysis of a single gene region in thousands of samples,
or for sequencing the entire genome of a single patient.
The implementation of NGS has been a paradigm shift in
genetics research and is now considered the gold stand-
ard for genetic diagnosis
12,13
. NGS has also been widely
embraced by the fields of cancer and hereditary diseases.
Therefore, inherited neoplasia, a group to which PPGLs
belong, represent a particularly relevant class of disorders
where the use of NGS for diagnostic purposes deserves
specialfocus.
Recognizing the need to develop standards for broad
implementation of NGS as a methodology for clinical
diagnosis of hereditary PPGL, a Study Group compris-
ing international experts from the Pheochromocytoma
and paraganglioma RESearch Support Organization
(PRESSOR, R.A.T., P.L.M.D., A.-P.G.-R., N.B., M.R.,
A.C., D.E.B., T.D., R. C.-B., J.P.B., C.M.T., J.W., O.G., H.F.,
E.M., M.M., T.E., G.O.) and the PPGL working group of
the European Network for the Study of Adrenal Tumors
(ENS@T, A.-P.G.-R., N.B., M.R., A.C., J.P.B., C.M.T., J.W.,
O.G., H.F., E.M., M.M., T.E., G.O.) was formed to spear-
head discussions on the application of NGS for diagnostic
genetic testing in PPGLs (NGSnPPGL).
Methods
The NGSnPPGL Study Group was comprised of 18
experts in PPGLs from ten separate institutions rep-
resenting eight countries and included both clinicians
who provide genetic counselling for their patients and
basic researchers who design and perform the diagnos-
tic tests. All participants have adopted, and reported
on, NGS-based technologies in their research and/or
clinical practice
14–26
. Discussions took place via confer-
ence calls, e-mail communications and file exchanges
and one plenary session (at the 14th ENS@T Scientific
Meeting on November 20th, 2015, Munich, Germany).
In these multiple exchanges, current practices and lit-
erature evidence were critically reviewed and a set of
recommendations was developed to guide broad imple-
mentation of this methodology for the diagnosis of
hereditary PPGLs. During these encounters, pertinent
technical, ethical and reporting issues were addressed.
This Consensus Statement summarizes the outcome of
these discussions.
While many of the topics included in this Consensus
Statement are common to other hereditary conditions
and/or cancers, aspects unique to PPGLs were con-
sidered when making recommendations (BOX1). As in
many other fields, guidelines for NGS-based testing
are continually evolving and the recommendations set
out here will be subject to change as our knowledge
advances. Therefore, the current guidelines are based
on the evidence available in2016.
Author addresses
1
Division of Hematology and Medical Oncology,
Department of Medicine, Cancer Therapy and Research
Center, University of Texas Health Science Center at San
Antonio (UTHSCSA), 7703 Floyd Curl Drive, MC7880, San
Antonio, Texas 78229, USA.
2
Spanish National Cancer Research Centre, CNIO, Calle de
Melchor Fernández Almagro, 3, 28029, Madrid, Spain.
3
Assistance Publique Hôpitaux de Paris, Hôpital Européen
Georges Pompidou, Service de Génétique; Université Paris
Descartes, Sorbonne Paris Cité, Faculté de Médecine, 20
Rue Leblanc, 75015 Paris, France.
4
INSERM, UMR970, Paris Cardiovascular Research Center
(PARCC), 56 Rue Leblanc, 75015, Paris, France.
5
Hereditary Endocrine Cancer Group, Spanish National
Cancer Research Centre (CNIO) and ISCIII Center for
Biomedical Research on Rare Diseases (CIBERER), Calle de
Melchor Fernández Almagro, 3, 28029, Madrid, Spain.
6
Cancer Genetics Unit, Kolling Institute, Royal North Shore
Hospital, St Leonards, University of Sydney, Reserve Road,
St Leonards, Sydney, New South Wales 2065, Australia.
7
Department of Human Genetics, Leiden University
Medical Center, P.O. Box 9600, 2300 RC Leiden,
Netherlands.
8
Department of Clinical and Experimental Medicine,
Linköping University, 58183 Linköping, Sweden.
9
Department of Clinical Genetics, Leiden University
Medical Center, P.O. Box 9600, 2300 RC Leiden,
Netherlands.
10
Department of Medical Genetics, University of
Cambridge, Cambridge and NIHR Cambridge
Biomedical Research Centre, Hills Road, Cambridge,
CB2 0QQ, UK.
11
Department of Experimental and Clinical Biomedical
Sciences “Mario Serio”, University of Florence,
Viale GB Morgagni 50, 50134, Florence, Italy.
12
Familial Cancer Clinic, Veneto Institute of Oncology,
IRCCS, Via Gattamelata, 64 Padova, Veneto 35128,
Padova, Italy.
13
Department of Surgery, Region Östergötland,
Linköping University, 581 83 Linköping, Sweden.
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General ethical considerations
Specific written informed consent must be obtained from
all patients following standards for diagnostic genetic
testing established by certified and accredited diagnostic
laboratories of individual countries
27,28
. Special consider-
ation is required when whole-exome sequencing (WES),
whole-genome sequencing (WGS) or extended gene pan-
els (that is, not limited to PPGL susceptibility genes) are
used. In these circumstances, patients should indicate if
they wish to be informed of incidental findings. These
findings represent significant genetic variants in a specific
group of genes (unrelated to PPGLs) that are implicated
in disorders that require medical action, such as those
specified in recommendations by the American College
of Medical Genetics and Genomics (ACMG)
29
.
Samples
The sample requirements for NGS are similar to those
currently adopted for clinical diagnosis of PPGLs using
Sanger sequencing. For the analysis of germ line variants
in PPGLs susceptibility genes, laboratories should
request blood (fresh (collected <7days ago) or frozen)
or a frozen leukocyte pellet. When a blood sample is not
available, laboratories can accept buccal cells either as
a cheek swab or in saliva obtained with specific collec-
tion kits containing preservatives
30
. DNA extraction and
quality assessment should follow standard procedures
established for conventional genetic testing
29,31,32
.
For the analysis of somatic variants in PPGLs sus-
ceptibility genes, laboratories should require fresh fro-
zen tumour fragments (50 mg of frozen tissue provides
a sufficient amount of high-molecular weight DNA
for sequencing). Alternatively, formalin-fixed paraffin
embedded (FFPE) sections or other fixed tumour material
(for example, maintained in alcohol) might also be accept-
able; however, the quality of DNA from these materials is
variable and can be suboptimal
33,34
. DNA from the tumour
should be processed and assessed for quality according to
standard protocols
29,31,32
. Over the past few years, protocols
for DNA, and even RNA, isolation from FFPE samples
have considerably improved, and technical adaptations
for handling potential artefacts generated from these
materials have yielded increasingly reliable sequencing
data, which has expanded the use of FFPE in clinical set-
tings
35
. Tumour tissue, when available, can provide val-
uable information that will aid interpretation of results
from germ line samples. For example, identification of
loss of heterozygosity (LOH) in a region where a potential
pathogenic germ line mutation of a tumour suppressor
gene is detected supports and reinforces the likelihood
of pathogenicity. In patients with hereditary PPGLs, the
tumour DNA is used exclusively for the purposes of sup-
plementing the diagnostic value of germ line variants of
unclear pathogenic status (see additional details in a sub-
sequent section). To this end, the tumour sample could be
analysed by either Sanger sequencing or specific targeted
sequencing (single gene or exon); therefore, the tumour
sample (frozen or FFPE) should be of sufficient amount
and quality to provide reliable genotype results.
NGS-based platform and processing
After considering costs, turnaround time, autonomy
of individual laboratories, assay flexibility, scalability,
bioinformatics needs, data storage and data interpre-
tation, a consensus was achieved by the Study Group
that targeted NGS is currently the favoured method for
genetic diagnosis of PPGLs. Specific recommendations
for implementing this method are as follows.
Approach. Amplicon-based targeted sequencing was the
approach preferred by the Study Group, as this approach
has been adopted and successfully optimized by the
majority of the group members in their own laborato-
ries. However, no objections were raised regarding the
use of the hybridization-captured NGS method.
Depth coverage. The minimum recommended sequence
depth coverage was 100x for each sample from blood
or saliva. Higher coverages (200x or higher) might
be required for detection of mosaic variants in blood
orsaliva.
Table 1
|
Genes involved in PPGL pathogenesis
Gene Frequency of mutations detected
in PPGLs (mutation type)
Refs
ATRX <5% (S) 96,98
BRAF <2% (S) 15,45
CDKN2A <2% (S) 96
EGLN1/PHD2 <1% (G or S)* 99,100
EPAS1 6–12% (M or S) 19,43,52,77
FGFR1 ~1% (S) 14
FH 1–2% (G) 24,43,101
H3F3A <2% (M)* 14
HRAS 7–8% (S) 43,102
IDH2 <0.5% (S) 103
KIF1B <5% (G or S) 18,104,105
KMT2D <2% (G or S)* 106
MAX 1–2% (G or S) 107
MDH2 <2% (G)* 108
MERTK <2% (G)* 14
MET <2% (G) or <2–10% (S)* 14,96
NF1 3% (G) or 20–25% (S) 109,110
RET 5–6% (G or S) 44,111
SDHA <1% (G or S) 112
SDHAF2 <1% 113
SDHB 8–10% (G) 43,111
SDHC 1–2% (G) 43,47,111
SDHD 5–7% (G) 43,111
TMEM127 1–2% (G) 43,114
TP53 <5% (S) 96
VHL 7–10% (G or S) 43,111
The numbers shown here are in part based on data generated by the TCGA (The Cancer Genome
Atlas) Research Network for Pheochromocytoma and Paraganglioma (unpublished data, publicly
available through cBioPortal). G, germ line; S, somatic; M, mosaic; PPGLs, phaeochromocytomas
and/or paragangliomas. *Frequency based on one or two clinical cases.
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In‑laboratory validation. Sensitivity and specificity
of the developed NGS assay should be established by
individual groups based on data obtained from a set of
samples carrying known mutations (identified by Sanger
sequencing). This positive control group should include
samples spanning a comprehensive set of mutations
(point mutations and indels) and origins (germ line,
mosaic and somatic). The Study Group also suggested
that samples positive for rare mutations, which might
not be available to every laboratory in their positive
control set, could be shared among multiple laboratories
to enable the development of more uniform and com-
prehensive ‘calibration sets’. Distribution of such DNA
materials in an anonymized manner would be subject
to sample availability, approval of the institutions’ ethics
committees and material transfer agreement arrange-
ments. Importantly, it is recommended that a set of nor-
mal reference samples of matching ethnic background is
also sequenced using the same NGS platform to deter-
mine false positive rates of the assay and to establish the
frequency of common and private or population-specific
polymorphisms.
Limitations. Special attention should be given to lim-
itations of NGS methods for sequencing and detection
of variants in specific regions of the genome, includ-
ing homopolymer repeats, indels, AT-rich regions and
GC-rich regions
36
. Some NGS techniques, such as Ion
Torrent (Life Technologies/ThermoFisher, Waltham,
Massachusetts, USA), rely on single-nucleotide additions
and can have a high error rate for indel detection (1%)
37
.
Illumina platforms have high sensitivity (0.1%); however,
false-positive errors have also been reported
37,38
. AT-rich
regions and GC-rich regions are well known to be prob-
lematic in conventional PCR and Sanger sequencing
38
.
These areas can also be challenging for capture by target
and WES probes and, therefore, tend to be underrepre-
sented by NGS. If regions of low coverage are noticed,
complementary assays should be designed using a differ-
ent method (for example, Sanger sequencing) to achieve
the desired minimal coverage of the target region. Off-
target sequencing (unwanted regions) might occur in
genomic regions with low sequence complexity, which
can be removed by filtering during sequencing analysis.
Confirmation. Given the reasons outlined in the previous
section, the detection of a variation or mutation in a new
sample should be confirmed using an orthogonal method,
such as Sanger sequencing, real-time PCR geno typing or
a distinct NGS-based assay. As in conventional genetic
testing, whenever possible, confirmation of the NGS-
identified variant in a separate aliquot of the patient’s
DNA (ideally obtained from an independent blood or
saliva sample) is highly recommended. However, the
Study Group recognizes that this practice is not universally
adopted by diagnostic laboratories.
Whole‑exome sequencing. The Study Group chose
WES as the preferred method for investigational genetic
analysis for PPGLs, with the research purpose of dis-
covering the primary mutation when none is found
among the PPGLs susceptibility genes. WES coverage
can vary greatly but a mean coverage of 50x or higher
was recommended for identification of germ line var-
iants. With decreasing costs of NGS methodology, the
ability to sequence at progressively higher depth with-
out added budgetary burden makes this coverage goal
easily attainable.
Quality control. Efficient capture of exons and adjacent
regions, quality of sequencing and error rates are influ-
enced by the reagents and kits used in library prepa-
ration and exome capture, as well as by the chemicals
and equipment used for sequencing
38
. For laboratories
that adopt commercial NGS services or institutional
core facilities for processing their samples, it is critical
to ensure that every step of the protocol is performed
following strict quality control standards, using relia-
ble reagents and sequencers with low error rates. The
Study Group recommends establishing a bioinformatics
pipeline in which at least two algorithms are used for
sequence alignment with the goal of enhancing both the
sensitivity and specificity of sequence calls
12
.
Other considerations. Low-coverage WES is not suitable
for clinical sequencing. WES should be considered for
patients with PPGLs who have no germ line mutations in
the genes analysed by targeted NGS, also referred to as a
‘negative PPGL’. However, before labelling a sample ‘neg-
ative’ it is imperative to establish a comprehensive analy-
sis of all known PPGLs susceptibility genes. This analysis
should not only include sequence evaluation of coding
regions and exon–intron boundaries of target genes, but
also large indels or gene rearrangements. These grosser
defects, which have been reported in the VHL, SDH
and MAX genes
39–42
, might not be identifiable by WES
performed at average depth of coverage. Instead, other
Box 1
|
Features unique to PPGLs
Hereditary Mendelian diseases are caused by one driver mutation inherited in an
autosomal dominant or recessive manner. This feature is relevant because the finding of
a single unquestionably pathogenic mutation will define the proband’s diagnosis and
should trigger testing of the specific mutation in at‑risk family members. Approximately
50% of phaeochromocytomas and paragangliomas (PPGLs), a rate higher than any
other human neoplasia, are caused by an autosomal dominantly inherited mutation
detectable in the germ line
1,2
.
Mosaic transmission, in addition to classic germ line transmission, of PPGLs can also
occur. The EPAS1 gene was found to be somatically mutated in PPGLs and in patients
who had an association between these tumours and polycythaemia and/or, rarely,
duodenal somatostatinomas
19,75–77
. Further studies have demonstrated that these
mutations can be mosaic, and are occasionally detected in non‑tumorous tissue at a low
frequency
78
. Detection of these low‑representation alleles requires the use of highly
sensitive techniques such as NGS. Therefore, the Study Group suggests inclusion of
EPAS1 in the group of genes mutated at the germ line level.
The extent to which mosaicism occurs in PPGLs has not been systematically examined
across all known susceptibility genes. Both NF1 and VHL, which are established PPGL
susceptibility genes, have been detected as mosaic, post‑zygotic mutations in
neurofibromatosis type1 or von Hippel–Lindau syndrome; however, this finding has not
been described in the specific setting of PPGLs
79,80
. In 2015, mosaic mutations leading to
a syndrome involving PPGL and giant cell tumours of bone were reported in association
with the H3F3A gene
14
. Therefore, mosaic transmission might occur more frequently in
PPGLs than hitherto appreciated.
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methods that are well-established for detection of these
genetic lesions, such as MLPA, quantitative multiplex
PCR or other genome-wide copy number analysis assays,
can be performed
43,44
. Alternatively, targeted NGS panels
can be designed to optimize detection of larger deletions,
insertions or rearrangements, as reported in hereditary
breast cancer diagnostic panels
45
. Finally, the existence of
epimutations, such as those detected in the promoter of
the SDHC gene should also be considered in cases where
no mutations are detected
46,47
. Specific attention to the
mode of inheritance and the existence of mosaicism are
briefly discussed in BOX1.
Targeted NGS PPGLs gene panels
With the important advances in our understanding of the
genetics of PPGLs that have occurred in the past decade,
a large number of genes have been implicated in suscep-
tibility to PPGLs, which are also known as ‘driver’ genes
(TABLE1). Some of these driver genes are only mutated at
the germ line level, while others can be mutated either
at the germ line or somatic level. A third group of driver
genes are only mutated somatically
1,2,48
. The relative
frequency of overall mutations and specific germ line
and/ or somatic events for each of these genes varies
(TABLE1). Although accumulated evidence regarding the
role of some of these susceptibility genes is fairly exten-
sive, as expected, the discoveries from the past few years
have not yet been fully validated clinically, genetically
or functionally.
An extensive discussion on the requirements for
determining a bonafide ‘driver status’ of the PPGLs sus-
ceptibility genes is beyond the scope of this Consensus
Statement. Therefore, to harmonize the current evidence
available for each gene we have applied general concepts
of tumour predisposition genes
49
and the ‘review status’
established by ClinVar, the public archive of reports of
the relationships among human variations and pheno-
types curated by the National Center for Biotechnology
Information (NCBI). ClinVar uses a five-level rank of
evidence to establish variant pathogenicity that was sug-
gested by the American College of Medical Genetics and
Genomics
50,51
(TABLE2). In this Consensus Statement, we
adopted a modified version of ClinVar’s ‘gold star’ scale
to create three PPGLs panel types based on the current
evidence of involvement of these genes in PPGLs suscep-
tibility at the germ line (the basic premise for hereditary
PPGLs screening) and somatic level. On the basis of the
current literature, we propose the development of three
sets of gene panels for the diagnosis of PPGLs (TABLE3).
TABLE4 lists the genes that belong to each panel type, and
summarizes the current level of evidence of their patho-
genic driver status. Importantly, as our knowledge of the
genetics of PPGLs evolves, re-evaluation of this list and
reclassification of susceptibility genes will be warranted.
Basic panel. The basic panel includes genes with the
highest level of evidence for their involvement in the
pathogenesis of PPGLs and that are mutated at the germ
line level. These genes have been extensively validated
in the literature and are predominantly associated with
familial disease or syndromic features.
Extended panel. The extended panel includes all ‘basic
panel’ genes, along with other candidate susceptibility
genes that are mutated at the germ line level and are
found at a low frequency (<1% of hereditary PPGLs)
but that have been proven to be functionally rele-
vant. This panel also includes genes that can contain
mutations with mosaic transmission and that might
occasionally also be detected in non-tumour tissue,
including blood or saliva (for example, EPAS1, also
known as HIF2A).
Table 2
|
Modified ClinVar review status adapted for this Consensus Statement on PPGLs driver genes
Original ClinVar classification Modified classification
Number of
gold stars
Description and review status Evidence
level
Specific applicability to PPGLs
None No submitter provided an interpretation with
assertion criteria (no assertion criteria provided), or no
interpretation was provided (no assertion provided)
0 N/A
One One submitter provided an interpretation with
assertion criteria (criteria provided, single submitter)
or multiple submitters provided assertion criteria
but there are conflicting interpretations, in which
case the independent values are enumerated for
clinical significance (criteria provided, conflicting
interpretations)
1 Single source (one published
report)
Two Two or more submitters providing assertion criteria
provided the same interpretation (criteria provided,
multiple submitters, no conflicts)
2 Two or more sources without
functional validation
Three Reviewed by expert panel 3 Two or more sources with some
functional validation
Four Practice guideline 4 Established evidence from: clinical,
genetic, computational prediction,
functional evidence and/or
analysis of population frequency
N/A, not applicable; PPGLs, phaeochromocytomas and/or paragangliomas.
CONSENSUS STATEMENT
NATURE REVIEWS
|
ENDOCRINOLOGY VOLUME 13
|
APRIL 2017
|
237
©
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