|
| |
 |
|
| ORIGINAL ARTICLE |
|
| Year : 2019 | Volume
: 2
| Issue : 1 | Page : 35-40 |
|
Comparison of flow cytometric and immunohistochemical immunophenotyping data for diagnosis of B-cell neoplasms and classic hodgkin's lymphoma
Fatma Saeed Alqahtani1, Karim Hamda Farhat2, Mashael Marzouq Alshebly3
1 Department of Pathology, College of Medicine, King Saud University and King Saud University Medical City, Riyadh, Saudi Arabia
2 Cancer Research Chair, College of Medicine, King Saud University, Riyadh, Saudi Arabia
3 Department of Obstetrics and Gynecology, College of Medicine, King Saud University and King Saud University Medical City, Riyadh, Saudi Arabia
| Date of Web Publication | 7-Jan-2019 |
Correspondence Address:
Karim Hamda Farhat
Cancer Research Chair, College of Medicine, King Saud University, P.O. Box 76047, Riyadh 11922
Saudi Arabia
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/JNSM.JNSM_22_18
Objective: This study was aimed to compare the results of immunophenotyping by flow cytometry (FC) and immunohistochemistry (IHC) in the diagnosis of B-cell lymphomas and classic Hodgkin's lymphoma (cHL). Methods: This was a retrospective cohort study of 280 patients with chronic B-cell neoplasms and cHL performed between 2008 and 2013. Percentages of B- and T-cell markers detected by FC and IHC were compared regardless of the final diagnosis. Results: FC and IHC results were obtained from 280 patient medical records. There were 155 (55.4%) patients with non-Hodgkin's lymphoma (NHL), 110 (39.3%) with cHL, and 15 (5.4%) with chronic lymphocytic leukemia (CLL). Disparity between FC and IHC was observed for CD19 expression in cHL group where 73.6% (n = 81) CD19 expression was detected by FC and 59.1% (n = 65) detected by IHC (P < 0.02). In NHL group, a higher percentage (81.3%; n = 126) of CD19 was detected by FC as opposed to 61.3% (n = 95) detected by IHC (P < 0.0001). CD19 expression was no different between the two groups. CD20 expression assessed by FC (61.3%; n = 95) was lower than 85.2% (n = 132) detected by IHC in NHL group (P < 0.0001). Whereas no differences were observed in cHL, IHC performed better (100%; n = 15) than FC (66.7%; n = 10) for CD20 detection in CLL group (P < 0.01). In cHL and NHL groups, flow cytometric detections of CD21 of 61.8% and 56.1% were higher than 46.4% (P < 0.02) and 41.9% (P < 0.01) detection rates by IHC. No disparities were observed between FC and IHC detection rates for CD5, CD10, CD23, and CD30 expressions. Conclusion: There was a considerable amount of disparity between FC and IHC results, warranting further evaluation.
Keywords: Flow cytometric, immunohistochemical immunophenotyping, lymphoproliferative disorder
How to cite this article:
Alqahtani FS, Farhat KH, Alshebly MM. Comparison of flow cytometric and immunohistochemical immunophenotyping data for diagnosis of B-cell neoplasms and classic hodgkin's lymphoma. J Nat Sci Med 2019;2:35-40 |
How to cite this URL:
Alqahtani FS, Farhat KH, Alshebly MM. Comparison of flow cytometric and immunohistochemical immunophenotyping data for diagnosis of B-cell neoplasms and classic hodgkin's lymphoma. J Nat Sci Med [serial online] 2019 [cited 2023 Feb 9];2:35-40. Available from: https://www.jnsmonline.org/text.asp?2019/2/1/35/242191 |
| Introduction | |  |
Relying only on morphological findings for diagnosing hematological malignancies is often challenging. Therefore, alternative diagnostic modalities such as immunophenotyping through flow cytometry (FC) and immunohistochemistry (IHC) are essential for arriving at a clear histological diagnosis. The clinical, immunophenotypic, cytogenetic, and morphological details are commonly evaluated in tandem by most pathologists and clinicians when diagnosing hematological malignancies and lymphoproliferative disorders.[1]
FC is an established adjunct to morphological evaluation and diagnosis of tissue samples of hematological neoplasms.[2] It can be used to distinguish between benign and malignant lymphoid infiltrates, which aids in the diagnosis of lymphomas[3] particularly for differentiating non-Hodgkin's lymphoma (NHL) and classic Hodgkin's lymphoma (cHL).[4] Moreover, FC can detect small populations of leukemia and lymphoma cells[5] and can therefore helpful in identification and classification of hematological malignancies.[6],[7] In addition, it also offers greater specificity in diagnosing lymphoid neoplasms than the analysis of bone marrow aspirates and biopsies.[8]
IHC has exhibited better performance than FC in detecting partial or focal tissue malignant cell involvement[9] and has detected some rare cases of diffuse large B-cell lymphomas, particularly when B- and T-cell mixtures infiltrate the bone marrow.[10] In contrast, FC can be more accurate than IHC for the diagnosis of follicular lymphoma, mantle cell lymphoma, and hairy cell leukemia;[11] the prognostic value of IHC was shown to be limited in these disease types, particularly with respect to B- and T-cell lymphomas.[12]
The cell surface antigens used for both FC- and IHC-based immunophenotypic profiling of B-cell neoplasms include CD22, CD20, surface IgM, and CD23.[13],[14] CD200 was recently shown to be useful in distinguishing chronic lymphocytic leukemia (CLL) from mantle cell lymphoma[15] and also between hairy cell leukemia, marginal zone lymphoma, and lymphoplasmacytic lymphoma.[16] Malignant B-cell neoplasms also show positivity for CD10, CD19, and CD79b, with or without CD45 expression.[17] Abdel-Ghafar et al. found IHC to be superior to FC in detecting bone marrow infiltration in NHL and hairy cell leukemia but found IHC and FC equally reliable in diagnosing CLL.[18] However, their analysis was based on a relatively small sample size, thus warranting a larger sample size study. The reported sensitivity of FC in diagnosing lymphoproliferative disorders ranges from 70% to 75%,[18],[19] while that of IHC varies substantially (20%–100%) according to the distinct subsets of lymphoproliferative diseases.[19]
Immunophenotyping results using FC versus IHC sometimes produce discordant results; in such cases, pathologists commonly base their diagnoses on FC findings. Consequently, the diagnostic and prognostic values of IHC-based immunophenotyping remain controversial and merit further investigation. We conducted this study in a larger population of Saudi patients with chronic B-cell neoplasms to assess the performance of FC and IHC immunophenotyping.
| Methods | | |
A retrospective cohort study was conducted at King Khalid University Hospital, King Saud University Medical City, Riyadh, Saudi Arabia, where medical records of all patients treated between 2008 and 2013 for chronic B-cell neoplasms and cHL were assessed. Ethics approval was obtained from our institute. Records of patients with the International Classification of Diseases codes 9590-9999 were retrieved;[20] they had been diagnosed based on standard clinical, laboratory, bone marrow aspirate, and trephine biopsy findings according to immunophenotypic criteria. Lymph node biopsy results for these patients were also used to confirm the presence of B-cell neoplasms and cHL. All FC and IHC results were retrieved, and a review of the marker used for immunophenotyping revealed B-cell-oriented markers such as CD19, CD20, CD21, and CD22 (for B-cells), CD10 (for immature B-cells), CD23 and CD5 (for CLL/small lymphocytic leukemia), CD30 and CD15 (for Reed–Sternberg cells of cHL), CD79b and CD25 (for activated B cells), the B-cell lymphoma proteins Bcl-2 and Bcl-6, and the immunoglobulin kappa and lambda light chains. We compared the immunophenotyping results obtained for samples analyzed both by FC and IHC. Percentages of relevant cell markers were compared regardless of the final diagnosis.
Flow cytometry analysis
Samples analyzed for FC comprised peripheral blood, bone marrow aspirates, and cells from lymph node biopsies. Samples were processed using the whole-blood lysis method and analyzed using a 4-color Coulter EPICS XL flow cytometer equipped with SYSTEM II software (Beckman Coulter, USA). Per the manufacturer's instructions, quality control testing of the flow cytometer was performed before sample acquisition to ensure that the instrument was set for proper alignment, calibration, and color compensation. Samples were diluted 1:1 with phosphate-buffered saline (PBS, pH 7.4; Sigma Chemicals, St. Louis, MO, USA). The final cell count of each suspension was adjusted to 5–10 × 109/L, and 50 μL of each sample was pipetted into separate experimental and control tubes. Fifteen microliters of fluorescein isothiocyanate-labeled monoclonal antibodies (Invitrogen, Life Technologies Limited, Scotland, UK) was added to the tubes containing test samples, whereas 5 μL of isotype-matched conjugated immunoglobulins was added to control tubes and incubated for 15 min at room temperature in the dark. Finally, 1 mL of PBS was added to the tubes. Initially, the lymphoid cell window was defined based on forward scatter/side scatter and CD45/side scatter patterns. The result for a particular marker was considered positive when at least 20% of the cells expressed the marker.
Immunohistochemistry analysis
Lymph node tissues were fixed in buffered formalin 4% and processed according to the standard protocols. Bone marrow trephines were fixed for 24 h and decalcified for 48 h using disodium ethylenediaminetetraacetic acid. Antigens were unmasked for 20 min in a microwave oven set at 800 W using the heat-induced, epitope retrieval method and an antigen retrieval solution (pH 6.0; Dako, Denmark).
Endogenous peroxidase activity was blocked by incubating the tissue sections with 3% hydrogen peroxide in water for 30 min, after which the sections were incubated with primary monoclonal antibodies (Dako); antibody staining was detected using streptavidin-conjugated primary antibodies and biotinylated, horseradish peroxidase-conjugated secondary antibodies (LSAB2, Dako). The sections were then counterstained with Mayer's hematoxylin, cover-slipped using DPX mounting media, and examined with bright-field microscopy. Positivity was defined as at least 10% staining of the tumor cells, as recommended by Fedchenko and Reifenrath.[21]
Predictive Analysis Software version 18.1 (IBM, SPSS Inc., Chicago, IL, USA) was used for statistical analysis. Descriptive statistics are reported as numbers and percentages for qualitative data; Chi-square test was used to determine the statistical significance between two groups. P < 0.05 was considered statistically significant.
| Results | | |
Of the 280 patients included in the study, 170 (60.7%) were males and 110 (39.3%) were females; the mean patient age ± standard deviation was 41.9 ± 10.9 years (median age: 40.5 years). This group of patients included 155 patients with NHL (55.4%), 110 patients with cHL (39.3%), and 15 patients with CLL (5.4%). Diagnosis for all patients was confirmed by histopathology.
[Table 1] summarizes the positivity rates for each of the marker antibodies tested using FC and IHC. Detection rates were higher using FC compared to IHC among samples from patients with CLL and cHL. Disparity between FC and IHC was observed for CD19 expression in cHL group where 73.6% (n = 81) CD19 expression was detected by FC compared to 59.1% (n = 65) detected by IHC (P < 0.02). In NHL group, a higher percentage (81.3%; n = 126) of CD19 was detected by FC as opposed to 61.3% (n = 95) detected by IHC (P < 0.0001). CD19 expression was no different between the two groups. CD20 expression assessed by FC (61.3%; n = 95) was lower than 85.2% (n = 132) detected by IHC in NHL group (P < 0.0001). Whereas no differences were observed in cHL, IHC performed better (100%; n = 15) than FC (66.7%; n = 10) for CD20 detection in CLL group (P < 0.01). In cHL and NHL groups, flow cytometric detections of CD21 of 61.8% and 56.1% were higher than 46.4% (P < 0.02) and 41.9% (P < 0.01) detection rates by IHC. No disparities were observed between FC and IHC detection rates for CD5, CD10, CD23, and CD30 expressions. [Table 2] shows data for percentages of positive markers among patients with CLL, cHL, and NHL. The overall detection rate among patients with CLL was 76.7%, among cHL group, it was 78.9%, and among patients with NHL, it was 86.6%. | Table 1: Comparison of the percentage positivity of markers obtained through flow cytometry and through immunophenotyping
Click here to view |
 | Table 2: Percentages of markers detected among patients with chronic lymphocytic leukemia, classic Hodgkin's lymphoma, and non-Hodgkin's lymphoma
Click here to view |
[Figure 1] and [Figure 2] show representative findings from patients with and without similarity in the positivity of the markers between FC and IHC, respectively. | Figure 1: Concordance between flow cytometry and immunohistochemistry findings. Bone morrow trephine biopsy section from a patient with chronic lymphocytic leukemia showing interstitial infiltration of small lymphocytes; CD5 is positive (paraffin-embedded, ×20 magnification). Flow cytometric quadrant analysis of the bone marrow sample from the same patient with chronic lymphocytic leukemia, with a majority of the cells positive for CD5
Click here to view |
 | Figure 2: Nonconcordance between flow cytometry and immunohistochemistry findings. Bone morrow trephine biopsy section from a patient with chronic lymphocytic leukemia showing interstitial infiltration small lymphocytes; CD5 is positive (paraffin-embedded, ×20 magnification). Flow cytometric quadrant analysis of a bone morrow sample from the same patient with chronic lymphocytic leukemia showing positivity for CD5
Click here to view |
| Discussion | | |
Based on a comprehensive search of the published literature, our study appears to be thefirst study to report concordance/discordance rates between FC and IHC immunophenotyping results. Our purpose was not to compare the diagnostic capabilities of FC and IHC per se but to examine the degree of concordance of the results by the positivity of the cells for each cellular marker used for both FC and IHC. To that end, we found varying percentages of positivity when using distinct antibody markers. There was a significant difference in the positivity rates of markers obtained between FC and IHC, particularly in cHL cases using CD19 and CD21 where these markers exhibited higher positivity rates with FC than with IHC. For NHL cases, significant differences in the positivity rates in CD19, CD20, and CD21 findings were revealed; CD19 and CD21 positivity was higher in FC compared to IHC, while the opposite was true for CD20. For the remaining markers, no significant differences in the positivity rates were observed between FC and IHC.
Our results may be attributable in part to heterogeneous antigen expression in distinct chronic B-cell neoplasm subsets. Furthermore, results obtained using antibody panels were better attained with FC than with IHC because some antigenic epitopes are normally lost during the processing and preparation of IHC specimens, particularly because of formalin treatment.[22] Conversely, the positivity rate was notably high when samples were analyzed by IHC for CD20 expression in the NHL group. One likely reason is that surface CD20 expression could be blocked when preparing cell for FC, particularly if the expression level is already low because the patient received chemotherapy beforehand (especially rituximab). However, in the CLL group, we observed comparatively lower positivity rates with IHC.
The positivity rates we observed were lower than those obtained in a previous study,[23] wherein a positivity rate of 96.1% for CD23 in patients with CLL was observed. We observed positivity rates of 86.7% and 80% using FC and IHC, respectively, in the subset of patients with CLL. However, firm conclusions are difficult to draw given our sample size of 15 patients with CLL. A high CD10 positivity rate in CLL samples was not expected since CD10 is normally not expressed on the surface of B-CLL cells; however, B-CLL cells can convert to CD10-positive status following apoptosis.[24] On the other hand, the low percentage of CD5-positive cells in CLL samples can be explained by the fact that <5% of mononuclear cells remain after T-cell subtraction. Furthermore, some studies have shown that 7%–20% of B-CLL cells do not express CD5.[25] The values of CD20 and CD5 positivity in cHL also appear to be uncertain.[26],[27]
The FC positivity rates for CD19, CD20, CD21, CD10, CD23, and CD5 were higher than those for IHC by >10% in most instances. These relatively minor differences in positivity between FC and IHC, particularly when using antibodies against CD10, CD23, and CD5, might be explained by differences in antibody detection between the two methods. However, both FC and IHC yielded a positivity rate of >75%, with the concordance in positivity rates between FC and IHC higher for NHL than for cHL and CLL. Large differences in positivity rates for any particular marker might be related to the relative sensitivity and specificity of either detection method with a particular antibody. Furthermore, other factors to be considered include the method used to prepare specimens, the availability of positive and negative controls for IHC, and importantly, the pathologists' interpretations of test results.
Although the positivity rates observed in some instances were lower than those obtained in the study conducted by Ma et al.,[26] we found no significant differences in the rates (whether positive or negative) of at least 60% with most of the antibody markers that we used for CLL, cHL, and NHL. A 60% similarity in the positivity rate is far from optimal, leaving pathologists to deliberate which findings to depend on; in most cases, FC findings are relied on when test results are in conflict especially between FC and IHC because surface antigens are detected without formalin fixing/paraffin embedding, which can mask the target antigens. No tumor marker has been identified that is sufficiently sensitive to be the sole screening method for a particular cancer.[28]
The overall similarity in the positivity rate was 76.7% for CLL, 78.9% for cHL, and 86.6% for NHL, indicating that a difference in the test results between FC and IHC will be obtained in 1 out of every 4 samples analyzed using either FC or IHC. When differences in the results are observed, measures may be adopted by the institution regarding the appropriate next steps such as the centralization of pathology testing to reduce differences in the interpretation and test results.[29] Kukreti also noted that differences in histopathological diagnoses are potentially harmful because they result in markedly different treatment or management strategies. Furthermore, treatment strategies vary from one disease type to the other, particularly for malignant and nonmalignant tumors.[29] Another probable cause for the difference in the test results for pathological diagnosis is the variations in the morphological interpretation and immunohistochemical results between different pathologists.[30] In 2004, the National Comprehensive Cancer Network listed discordance in the diagnosis with of NHL cases using FC and IHC at 6%, which was substantially lower than detection rates our after rate.[31] The World Health Organization criteria for the diagnosis of lymphoma also reported a 6% discordance rate between FC and IHC results.[30] Because of the low rate in the similarity of results obtained between FC and IHC results, the final diagnosis may now rely much on the pathologist who is doing the interpretation of the results.
| Conclusion | | |
Our results suggest that concerted efforts should be made to address existing disparities in test results between FC and IHC. Attempts to increase the reliability of diagnoses of hematologic malignancies by pathologists should be encouraged. Frequent consultations among experts involved in patient care should be encouraged for accurate interpretation of the results particularly in the event of disparity between FC and IHC results.
Acknowledgment
The authors are grateful to the Deanship of Scientific Research, King Saud University, for funding though Vice Deanship of Scientific Research Chairs.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | Agarwal R, Juneja S. Pitfalls in the diagnosis of haematological malignancies. NZ J Med Lab Sci 2013;67:39-44.  |
| 2. | Demurtas A, Stacchini A, Aliberti S, Chiusa L, Chiarle R, Novero D, et al. Tissue flow cytometry immunophenotyping in the diagnosis and classification of non-Hodgkin's lymphomas: A retrospective evaluation of 1,792 cases. Cytometry B Clin Cytom 2013;84:82-95. |
| 3. | Bangerter M, Brudler O, Heinrich B, Griesshamnuer M. Fine needle aspiration cytology and flow cytometry in the diagnosis and subclassification of non-Hodgkin's lymphoma based on the World Health Organization classification. Acta Cytol 2007;51:390-8. |
| 4. | Dunphy CH. Applications of flow cytometry and immunohistochemistry to diagnostic hematopathology. Arch Pathol Lab Med 2004;128:1004-22. |
| 5. | Szczepański T, van der Velden VH, van Dongen JJ. Flow-cytometric immunophenotyping of normal and malignant lymphocytes. Clin Chem Lab Med 2006;44:775-96. |
| 6. | van Wering ER, van Lochem EG, Leenders M, van der Sluijs-Gelling AJ, Wind H, Gratama JW, et al. Three-color flowcytometric analysis of mature and immature hematological malignancies. A guideline of the Dutch Foundation for Immunophenotyping of Hematological Malignancies (SIHON). J Biol Regul Homeost Agents 2004;18:313-26. |
| 7. | Martínez A, Aymerich M, Castillo M, Colomer D, Bellosillo B, Campo E, et al. Routine use of immunophenotype by flow cytometry in tissues with suspected hematological malignancies. Cytometry B Clin Cytom 2003;56:8-15. |
| 8. | Promsuwicha O, Songmuang W, Auewarakul CU. Detection of lymphoid neoplasms in bone marrow by flow cytometric analysis and comparison to bone marrow aspiration and biopsy. J Med Assoc Thai 2013;96 Suppl 2:S210-5. |
| 9. | Li S, Eshleman JR, Borowitz MJ. Lack of surface immunoglobulin light chain expression by flow cytometric immunophenotyping can help diagnose peripheral B-cell lymphoma. Am J Clin Pathol 2002;118:229-34. |
| 10. | Sandeep, Sharma P, Ahluwalia J, Sachdeva MU, Varma N, Malhotra P, et al. Primary bone marrow T-cell/histiocyte-rich large B-cell lymphoma: A diagnostic challenge. Hematology 2013;18:85-8. |
| 11. | Johansson U, Bloxham D, Couzens S, Jesson J, Morilla R, Erber W, et al. Guidelines on the use of multicolour flow cytometry in the diagnosis of haematological neoplasms. British Committee for Standards in Haematology. Br J Haematol 2014;165:455-88. |
| 12. | Krause DS, Delelys ME, Preffer FI. Flow cytometry for hematopoietic cells. Methods Mol Biol 2014;1109:23-46. |
| 13. | Perković S, Bašić-Kinda S, Aurer I, Ugrina I, Duletić-Načinović A, Lozić D, et al. Multiparameter flow cytometry is necessary for detection, characterization and diagnostics of composite mature B-cell lymphoproliferative neoplasms. Int J Hematol 2013;98:589-96. |
| 14. | Solano-Genesta M, Tarín-Arzaga L, Velasco-Ruiz I, Lutz-Presno JA, González-Llano O, Mancías-Guerra C, et al. CD20 expression in B-cell precursor acute lymphoblastic leukemia is common in Mexican patients and lacks a prognostic value. Hematology 2012;17:66-70. |
| 15. | Sandes AF, de Lourdes Chauffaille M, Oliveira CR, Maekawa Y, Tamashiro N, Takao TT et al. CD200 has an important role in the differential diagnosis of mature B-cell neoplasms by multiparameter flow cytometry. Cytometry B Clin Cytom 2014;86:98-105. |
| 16. | Pillai V, Pozdnyakova O, Charest K, Li B, Shahsafaei A, Dorfman DM, et al. CD200 flow cytometric assessment and semiquantitative immunohistochemical staining distinguishes hairy cell leukemia from hairy cell leukemia-variant and other B-cell lymphoproliferative disorders. Am J Clin Pathol 2013;140:536-43. |
| 17. | Palmeira C, Sousa ME, Godinho I, Pires AM, Mendes C, Martins G, et al. Flow cytometry CD45-negative B-NHL: A case report of a diffuse large B-cell lymphoma without extranodal involvement. Cytometry B Clin Cytom 2012;82:369-71. |
| 18. | Abdel-Ghafar AA, El Din El Telbany MA, Mahmoud HM, El-Sakhawy YN. Immunophenotyping of chronic B-cell neoplasms: Flow cytometry versus immunohistochemistry. Hematol Rep 2012;4:e3. |
| 19. | Ensani F, Mehravaran S, Irvanlou G, Aghaipoor M, Vaeli S, Hajati E, et al. Fine-needle aspiration cytology and flow cytometric immunophenotyping in diagnosis and classification of non-Hodgkin lymphoma in comparison to histopathology. Diagn Cytopathol 2012;40:305-10. |
| 20. | Fritz AG, Percy C, Jack A, Shanmugaratnam K, Sobin L, Max Parkin D, et al., editors. International Classification of Diseases for Oncology, ICD-0. 3 rd ed. Geneva: World Health Organization; 2000. p. 1-252. |
| 21. | Fedchenko N, Reifenrath J. Different approaches for interpretation and reporting of immunohistochemistry analysis results in the bone tissue - A review. Diagn Pathol 2014;9:221. |
| 22. | Werner M, Chott A, Fabiano A, Battifora H. Effect of formalin tissue fixation and processing on immunohistochemistry. Am J Surg Pathol 2000;24:1016-9. |
| 23. | Zucchetto A, Cattarossi I, Nanni P, Zaina E, Prato G, Gilestro M, et al. Cluster analysis of immunophenotypic data: The example of chronic lymphocytic leukemia. Immunol Lett 2011;134:137-44. |
| 24. | Morabito F, Mangiola M, Rapezzi D, Zupo S, Oliva BM, Ferraris AM, et al. Expression of CD10 by B-chronic lymphocytic leukemia cells undergoing apoptosis in vivo and in vitro. Haematologica 2003;88:864-73. |
| 25. | Cartron G, Linassier C, Bremond JL, Desablens B, Georget MT, Fimbel B, et al. CD5 negative B-cell chronic lymphocytic leukemia: Clinical and biological features of 42 cases. Leuk Lymphoma 1998;31:209-16. |
| 26. | Barakzai MA, Pervez S. CD20 positivity in classical Hodgkin's lymphoma: Diagnostic challenge or targeting opportunity. Indian J Pathol Microbiol 2009;52:6-9. [ PUBMED] [Full text] |
| 27. | Tzankov A, Bourgau C, Kaiser A, Zimpfer A, Maurer R, Pileri SA, et al. Rare expression of T-cell markers in classical Hodgkin's lymphoma. Mod Pathol 2005;18:1542-9. |
| 28. | |
| 29. | |
| 30. | Turner JJ, Hughes AM, Kricker A, Milliken S, Grulich A, Kaldor J, et al. Use of the WHO lymphoma classification in a population-based epidemiological study. Ann Oncol 2004;15:631-7. |
| 31. | LaCasce AS, Kho ME, Friedberg JW, Niland JC, Abel GA, Rodriguez MA, et al. Comparison of referring and final pathology for patients with non-Hodgkin's lymphoma in the National Comprehensive Cancer Network. J Clin Oncol 2008;26:5107-12. |
[Figure 1], [Figure 2]
[Table 1], [Table 2]
|
Search Pubmed for