Diagnosis of Blood and Bone Marrow Disorders

413 Pages·2018·50.61 MB·English

by  Sa A. Wang

Sa A. Wang
Robert P. Hasserjian
Editors
Diagnosis of Blood and
Bone Marrow Disorders
123
Diagnosis of Blood and Bone
Marrow Disorders
Sa A. Wang • Robert P. Hasserjian
Editors
Diagnosis of Blood and
Bone Marrow Disorders
Editors
Sa A. Wang, M.D. Robert P. Hasserjian, M.D.
Department of Hematopathology Department of Pathology
The University of Texas MD Anderson Massachusetts General Hospital
Cancer Center Boston, MA
Houston, TX USA
USA
ISBN 978-3-319-20278-5 ISBN 978-3-319-20279-2 (eBook)
https://doi.org/10.1007/978-3-319-20279-2
Library of Congress Control Number: 2017962627
© Springer International Publishing AG, part of Springer Nature 2018
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Preface
This book presents a comprehensive and practical approach to the diagnosis
of diseases that primarily affect the blood and bone marrow. These diseases
encompass both benign and neoplastic disorders that affect cells of hemato-
poietic lineages (leukocytes, red cells and their precursors, platelets, and
megakaryocytes) and present with abnormalities primarily manifesting in the
blood. The diagnostic approach to malignant hematologic diseases has
recently been updated in the revised World Health Organization Classification
of Tumours of Haematopoietic and Lymphoid Tissues published in 2017 and
this book uses the current classification and nomenclature.
The diagnosis and classification of abnormalities of hematopoiesis are
increasingly complex and constantly changing, in part due to the rapid
advance in molecular genetic testing and accelerating development of new
therapies that requires us to constantly refine our ability to effectively diag-
nose and classify these diseases. Next-generation sequencing represents a
powerful tool that is rapidly entering routine clinical practice. While sequenc-
ing results help us understand disease biologies and are critical in diagnosing
certain neoplasms, they add to the large amounts of information that must be
digested and incorporated for individual cases. This data includes clinical
features, bone marrow and blood morphology, flow cytometry immunophe-
notyping, and cytogenetics, as well as molecular genetic information. This
comprehensive information set must be integrated by the diagnostician for
each case in arriving at a specific and correct diagnosis and classification,
which should ideally inform clinical management. Moreover, the diagnosti-
cian must weigh each piece of data to resolve contradictory information that
often emerges. The purpose of this book is to guide the diagnostician as he/
she navigates this process, providing detailed approaches to hematologic
abnormalities and their differential diagnosis.
The book is uniquely organized by the specific clinical scenarios in which
blood and bone marrow diseases present, rather than by each individual dis-
ease subtype. This allows the book to be used in real life situations, in which
the diagnostician is confronted by abnormal blood and/or bone marrow test-
ing (e.g. thrombocytosis or pancytopenia) that has a broad differential diag-
nosis. Each chapter has been organized to maximize its practical utility,
including introductory information about hematopoietic cell types in normal
and abnormal states, as well as clinical features, morphology, immunopheno-
type, genetics, and differential diagnosis of each specific disease. All chapters
are extensively illustrated with images that underscore the salient features of
v
vi Preface
the diseases discussed in the text and with tables that present diagnostic cri-
teria for neoplasms and differential diagnoses. Most chapters additionally
contain algorithms that present a framework for the diagnostic approach to
the specific clinical scenarios.
We are deeply indebted to all the authors who have contributed to this
book and who have shared their collective wealth of experience in these chal-
lenging topics. We learned a great deal from our author colleagues in prepar-
ing this book; we hope that our readers will likewise benefit from the expertise
put forth by this outstanding group of hematopathologists.
Houston, TX, USA Sa A. Wang
Boston, MA, USA Robert P. Hasserjian
Contents
1 Identifying Blood and Bone Marrow Abnormalities
in the Laboratory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Aliyah R. Sohani
2 Cytopenias: Reactive and Neoplastic . . . . . . . . . . . . . . . . . . . . . 17
Sanam Loghavi and Robert P. Hasserjian
3 Inherited Bone Marrow Failure Syndromes, Myeloid
Neoplasms with Germline Predisposition and Myeloid
Proliferations Associated with Down Syndrome . . . . . . . . . . . . 81
Jyotinder Nain Punia, Sa A. Wang, and M. Tarek Elghetany
4 Cytopenias: Acquired Bone Marrow Failure . . . . . . . . . . . . . . . 119
Sa A. Wang
5 Leukocytosis: Neutrophilia, Basophilia, and Blasts . . . . . . . . . . 135
Chi Young Ok and Robert P. Hasserjian
6 Leukocytosis: Eosinophilia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
Roberto N. Miranda and Sa A. Wang
7 Monocytosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
Julia Turbiner Geyer
8 Thrombocytosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225
Beenu Thakral and Sa A. Wang
9 Erythrocytosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243
Olga Pozdnyakova
10 Mixed Cytoses and Cytopenias . . . . . . . . . . . . . . . . . . . . . . . . . . 257
Sanam Loghavi and Sa A. Wang
11 T- and NK-Cell Lymphocytosis . . . . . . . . . . . . . . . . . . . . . . . . . . 281
Sa A. Wang
12 B-Cell Lymphocytosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329
Robert P. Hasserjian
13 Multiple Myeloma and Other Plasma Cell Neoplasms . . . . . . . 383
Pei Lin
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 405
vii
Contributors
Julia Turbiner Geyer, M.D. Department of Pathology and Laboratory
Medicine, Weill Cornell Medical College, New York, NY, USA
Robert P. Hasserjian, M.D. Department of Pathology, Massachusetts
General Hospital, Boston, MA, USA
Pei Lin, M.D. Department of Hematopathology, The University of Texas
MD Anderson Cancer Center, Houston, TX, USA
Sanam Loghavi, M.D. Department of Hematopathology, The University of
Texas MD Anderson Cancer Center, Houston, TX, USA
Roberto N. Miranda, M.D. Department of Hematopathology, The
University of Texas MD Anderson Cancer Center, Houston, TX, USA
Chi Young Ok, M.D. Department of Hematopathology, The University of
Texas MD Anderson Cancer Center, Houston, TX, USA
Olga Pozdnyakova, M.D., Ph.D. Department of Pathology, Brigham and
Women’s Hospital, Harvard Medical School, Boston, MA, USA
Jyotinder Nain Punia, M.D. Department of Pathology and Immunology,
Baylor College of Medicine/Texas Children’s Hospital, Houston, TX, USA
Aliyah R. Sohani, M.D. Department of Pathology, Massachusetts General
Hospital, Boston, MA, USA
M. Tarek Elghetany, M.D. Department of Pathology and Immunology,
Baylor College of Medicine/Texas Children’s Hospital, Houston, TX, USA
Beenu Thakral, M.D. Department of Hematopathology, The University of
Texas MD Anderson Cancer Center, Houston, TX, USA
Sa A. Wang, M.D. Department of Hematopathology, The University of
Texas MD Anderson Cancer Center, Houston, TX, USA
ix
1
Identifying Blood and Bone
Marrow Abnormalities
in the Laboratory
Aliyah R. Sohani
Overview cell classification between different observers,
cell distribution artifact that results in larger cell
Automated analysis of peripheral blood samples types (e.g., neutrophils, monocytes, and eosino-
for complete blood count (CBC) and white phils) being spread along the edges of a blood
blood cell (WBC) differential evaluation was smear, and the inherent statistical limitation that
introduced in the early 1950s and since that time stems from enumerating a relatively small num-
has developed into the primary approach by ber of cells, typically in the range of 100–200
which blood samples are analyzed for cellular per sample.
constituents and the main avenue through which Modern-day hematology instrumentation
hematologic abnormalities first come to clinical comprises multichannel analyzers that employ a
attention. Prior to that time, the CBC, one of the combination of methods, including electrical
most commonly ordered laboratory tests, was impedance, light scatter, radiofrequency con-
performed using entirely manual methods. For ductivity, and/or cytochemistry, to perform cell
example, WBC, red blood cell (RBC), and counts [1]. The technology has evolved to the
platelet counts were performed using dilution of point that automated approaches to CBC and
whole blood samples followed by manual count- WBC differential analysis have proven to be
ing under the microscope using a hemocytome- efficient and cost-effective, as well as accurate
ter counting chamber; hematocrit was and reliable in detecting clinically significant
determined by high- speed column centrifuga- abnormalities. However, automated cell coun-
tion; and WBC differential analysis always ters come with their own sources of error, con-
required examination, classification, and enu- founding variables, and artifacts that may
meration of cells under the microscope. impede in the timely detection of peripheral
Inarguably, these methods proved very time- blood abnormalities or result in falsely abnor-
consuming in a high-volume laboratory. mal test results. In addition, it is generally
Furthermore, manual WBC differential analysis accepted that these instruments serve a dual pur-
is susceptible to errors related to consistency of pose as both diagnostic tools and screening
devices, the latter implying that certain numeri-
cal abnormalities or analyzer- specific operator
alerts (also known as “instrument flags”) should
A.R. Sohani, M.D. trigger microscopic blood smear review by a
Department of Pathology, Massachusetts General
skilled laboratory technologist or pathologist,
Hospital, Boston, MA, USA
e-mail: [email protected] particularly at the time of their initial occur-
© Springer International Publishing AG, part of Springer Nature 2018 1
S.A. Wang, R.P. Hasserjian (eds.), Diagnosis of Blood and Bone Marrow Disorders,
https://doi.org/10.1007/978-3-319-20279-2_1
2 A.R. Sohani
rence. For these reasons, a general understand- hematocrit (HCT), mean corpuscular volume
ing of the methods underlying automated CBC (MCV) measured in femtoliters (fL), mean cor-
and WBC differential analysis is critical to a puscular hemoglobin (MCH) measured in pico-
sound diagnostic approach to disorders involv- grams/cell, mean corpuscular hemoglobin
ing the blood and, by extension, originating concentration (MCHC) measured in g/dL, and
from the bone marrow. red cell distribution width (RDW). Reference
This chapter provides an overview of auto- ranges vary by age and gender and are readily
mated analysis of whole blood constituents, obtained by consulting reference hematology or
including RBCs, platelets, and WBCs, with a laboratory medicine texts [1]. Typical reference
focus on interferences, sources of error, and find- ranges for adults are listed in Table 1.1. However,
ings for which microscopic review or confirma- it is recommended that individual laboratories
tion should be considered. In addition, situations confirm standard reference ranges for the specific
in which peripheral blood flow cytometric analy- patient population(s) they serve, as reference
sis may be warranted will be addressed. Finally, ranges for certain parameters may be affected by
appropriate preparation and microscopic evalua- ethnic and geographic variations.
tion of peripheral blood and bone marrow aspirate Most automated cell counters measure HGB
smears and trephine biopsies will be discussed. using a spectrophotometric method, following
RBC lysis and conversion of the HGB molecule
to a derivative that can be measured using light
Analysis of Red Blood Cells absorbance at a specific wavelength. Historically,
and Associated Parameters this process has required the use of potassium
cyanide to convert HGB to hemiglobincyanide;
The standard CBC includes the following RBC however, cyanide-free measurement methods
parameters: RBC count, hemoglobin concentra- now exist [1]. RBC count is determined in many
tion (HGB) measured in grams/deciliter (g/dL), instances via electrical impedance, whereby cells
Table 1.1 Red blood cell indices: calculation, normal ranges, and interpretation in patients with
anemia
Red blood cell (RBC) Definition/calculation Normal rangea Abnormal values and some common
parameter associations
Mean corpuscular Average size of RBCs 80–100 Decreased MCV and decreased MCH:
volume (MCV) (fL) =HCT/RBC × 10 iron deficiency, lead poisoning, thalassemia
Mean corpuscular Amount of HGB per RBC 26–33 Normal MCV and normal MCH: sudden
HGB (MCH) (pg) =HGB/RBC × 10 blood loss, chronic inflammation, kidney
failure, pregnancy
High MCV: vitamin B12 or folate
deficiency, certain drugs, MDS, hemolysis
Mean corpuscular Amount of HGB per cell 31–36 Decreased: lead poisoning, vitamin B6
HGB concentration relative to RBC size deficiency, copper deficiency
(MCHC) (g/dL) =HGB/HCT × 100 Normal: iron deficiency
Increased: hereditary spherocytosis, sickle
cell disease, and homozygous hemoglobin
C disease
Red cell Variability in RBC size 12–15 Increased: recent transfusion, iron
distribution width = coefficient of variation deficiency, vitamin B12 or folate deficiency,
(RDW) (%) or standard deviation of RBC fragmentation or agglutination,
MCV × 100% sideroblastic anemia, MDS
Decreased: Not clinically relevant
HCT hematocrit, MDS myelodysplastic syndrome, HGB hemoglobin
aMay vary by patient population and between laboratories