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Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

Postal Subscription Code 80-967

2018 Impact Factor: 1.847

Front. Med.    2019, Vol. 13 Issue (1) : 94-103    https://doi.org/10.1007/s11684-019-0680-1
RESEARCH ARTICLE
Presence of multiple abnormal immunologic markers is an independent prognostic factor of diffuse large B-cell lymphoma
Yiwen Cao1, Zhenhua Liu2, Wen Wu1, Ying Qian1, Qin Shi1, Rong Shen1, Binshen Ouyang3, Pengpeng Xu1, Shu Cheng1, Jin Ye4, Yiming Lu4, Chaofu Wang3, Chengde Yang5, Li Wang1,4(), Weili Zhao1,4()
1. State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
2. Department of Ultrasonography, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
3. Department of Pathology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
4. Pôle de Recherches Sino-Français en Science du Vivant et Génomique, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
5. Department of Rheumatology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
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Abstract

Autoimmune diseases (ADs) increase the risk of non-Hodgkin’s lymphoma and contribute to poor prognosis of patients. However, the association between immunologic markers and clinical outcome has rarely been investigated. This study aims to analyze the prognostic value of pretreatment immunologic markers in newly diagnosed patients with diffuse large B-cell lymphoma (DLBCL). We retrospectively reviewed the data on 502 patients with DLBCL treated in our institution from January 2013 to March 2018. Survival functions were estimated using Kaplan–Meier method and Cox regression model. The 3-year progression free survival (PFS) and overall survival (OS) rates were 70.2% and 80.9%, respectively, and the complete remission (CR) rate was 78.1%. Among the patients, those with multiple (≥3) abnormal immunologic markers had significantly shorter 3-year PFS (52.7% vs. 77.3%, P<0.001) and OS (68.5% vs. 85.8%, P=0.001) than those without multiple abnormal immunologic markers. Multivariate analysis revealed that the presence of multiple abnormal immunologic markers and the elevated serum levels of lactate dehydrogenase were the independent adverse prognostic factors for PFS (P=0.008, P<0.001) and OS (P=0.003, P<0.001). Meanwhile, advanced Ann Arbor stage was an independent adverse prognostic factor for PFS (P=0.001) and age>60 years for OS (P=0.014). In conclusion, the immunologic status was closely related to lymphoma progression, and this study provides new insights into the risk stratification of patients with DLBCL.

Keywords immunologic marker      diffuse large B-cell lymphoma      prognosis     
Corresponding Authors: Li Wang,Weili Zhao   
Just Accepted Date: 10 January 2019   Online First Date: 31 January 2019    Issue Date: 12 March 2019
 Cite this article:   
Yiwen Cao,Zhenhua Liu,Wen Wu, et al. Presence of multiple abnormal immunologic markers is an independent prognostic factor of diffuse large B-cell lymphoma[J]. Front. Med., 2019, 13(1): 94-103.
 URL:  
http://academic.hep.com.cn/fmd/EN/10.1007/s11684-019-0680-1
http://academic.hep.com.cn/fmd/EN/Y2019/V13/I1/94
Characteristic Number (%)
All patients 502 (100.0%)
Gender
Male 273 (54.4%)
female 229 (45.6%)
Age (year)
>60 232 (46.2%)
≤60 270 (53.8%)
IPI score
0–2 342 (68.1%)
3–5 160 (31.9%)
LDH
Abnormal 201 (38.8%)
Normal 301 (61.2%)
Performance status (ECOG)
0–1 443 (88.2%)
≥2 59 (11.8%)
No. of extranodal involvement
0–1 347 (69.1%)
≥2 155 (30.9%)
Ann Arbor stage
I–II 283 (56.4%)
III–IV 219 (43.6%)
Tab.1  Clinical features of patients with DLBCL
Characteristic All patients IPI P value LDH P value Ann Arbor P value ECOG P value Extranodal involvement P value Age (year) P value
3–5 0–2 Elevated Normal III–IV I–II ≥2 0–1 ≥2 0–1 >60 ≤60
n n n n n n n n n n n n n
(%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%)
160 342 201 301 219 283 59 443 155 347 232 270
(31.9) (68.1) (40) (60) (43.6) (56.4) (11.8) (88.2) (30.9) (69.1) (46.2) (53.8)
CIC n.s. n.s. n.s. n.s. n.s. n.s.
Elevated 147 51 96 57 90 72 75 22 125 52 95 66 81
(29.3) (34.7) (65.3) (38.8) (61.2) (49.0) (51.0) (15.0) (85.0) (35.4) (64.6) (44.9) (55.1)
Normal 355 109 246 144 211 147 208 37 318 103 252 166 189
(70.7) (30.7) (69.3) (40.6) (59.4) (41.4) (58.6) (10.4) (89.6) (29.0) (71.0) (46.8) (53.2)
IgG n.s. n.s. n.s. n.s. n.s. n.s.
Elevated 76 23 53 30 46 34 42 8 68 27 49 37 39
(15.1) (30.3) (69.7) (39.5) (60.5) (44.7) (55.3) (10.5) (89.5) (35.5) (64.5) (48.7) (51.3)
Normal 426 137 289 171 255 185 241 51 375 128 298 195 231
(84.9) (32.2) (67.8) (40.1) (59.9) (43.4) (56.6) (12.0) (88.0) (30.0) (70.0) (45.8) (54.2)
IgM n.s. n.s. n.s. n.s. 0.008 n.s.
Elevated 21 9 12 7 14 12 9 3 18 12 9 11 10
(4.2) (42.9) (57.1) (33.3) (66.7) (57.1) (42.9) (14.3) (85.7) (57.1) (42.9) (52.4) (47.6)
Normal 481 151 330 194 287 207 274 56 425 143 338 221 260
(95.8) (31.4) (68.6) (40.3) (59.7) (43.0) (57.0) (11.6) (88.4) (29.7) (70.3) (45.9) (54.1)
IgA n.s. n.s. n.s. n.s. n.s. n.s.
Elevated 20 8 12 11 9 7 13 4 16 9 11 11 9
(4) (40.0) (60.0) (55.0) (45.0) (35.0) (65.0) (20.0) (80.0) (45.0) (55.0) (55.0) (45.0)
Normal 482 152 330 190 292 212 270 55 427 146 336 221 261
(96) (31.5) (68.5) (39.4) (60.6) (44.0) (56.0) (11.4) (88.6) (30.3) (69.7) (45.9) (54.1)
IgE 0.034 n.s. n.s. n.s. n.s. n.s.
Elevated 98 40 58 40 58 47 51 16 82 38 60 51 47
(19.5) (40.8) (59.2) (40.8) (59.2) (48.0) (52.0) (16.3) (83.7) (38.8) (61.2) (52.0) (48.0)
Normal 404 120 284 161 243 172 232 43 361 117 287 181 223
(80.5) (29.7) (70.3) (39.9) (60.1) (42.6) (57.4) (10.6) (89.4) (29.0) (71.0) (44.8) (55.2)
C3 n.s. n.s. n.s. 0.018 n.s. n.s.
Abnormal 110 41 69 51 59 57 53 20 90 36 74 53 57
(21.9) (37.3) (62.7) (46.4) (53.6) (51.8) (48.2) (18.2) (81.8) (32.7) (67.3) (48.2) (51.8)
Normal 392 119 273 150 242 162 230 39 353 119 273 179 213
78.1 (30.4) (69.6) (38.3) (61.7) (41.3) (58.7) (9.9) (90.1) (30.4) (69.6) (45.7) (54.3)
C4 n.s. n.s. n.s. n.s. n.s. n.s.
Abnormal 95 36 59 44 51 49 46 16 79 33 62 41 54
18.9 (37.9) (62.1) (46.3) (53.7) (51.6) (48.4) (16.8) (83.2) (34.7) (65.3) (43.2) (56.8)
Normal 407 124 283 157 250 170 237 43 364 122 285 191 216
81.1 (30.5) (69.5) (38.6) (61.4) (41.8) (58.2) (10.6) (89.4) (30.0) (70.0) (46.9) (53.1)
RF 0.012 0.029 n.s. n.s. n.s. n.s.
Elevated 41 20 21 23 18 21 20 9 32 15 26 23 18
10.9 (48.8) (51.2) (56.1) (43.9) (51.2) (48.8) (22.0) (78.0) (36.6) (63.4) (56.1) (43.9)
Normal 336 99 237 129 207 140 196 38 298 102 234 155 181
89.1 (29.5) (70.5) (38.4) (61.6) (41.7) (58.3) (11.3) (88.7) (30.4) (69.6) (46.1) (53.9)
Anti-dsDNA IgG n.s. n.s. n.s. n.s. n.s. n.s.
Elevated 3 1 2 1 2 1 2 0 3 1 2 2 1
0.8 (33.3) (66.7) (33.3) (66.7) (33.3) (66.7) (0.0) (100.0) (33.3) (66.7) (66.7) (33.3)
Normal 374 118 256 151 223 160 214 47 327 116 258 176 198
99.2 (31.6) (68.4) (40.4) (59.6) (42.8) (57.2) (12.6) (87.4) (31.0) (69.0) (47.1) (52.9)
Anti-SSA n.s. n.s. n.s. 0.029 n.s. n.s.
Positive 6 2 4 4 2 3 3 3 3 1 5 1 5
1.6 (33.3) (66.7) (66.7) (33.3) (50.0) (50.0) (50.0) (50.0) (16.7) (83.3) (16.7) (83.3)
Negative 371 117 254 148 223 158 213 44 327 116 255 177 194
98.4 (31.5) (68.5) (39.9) (60.1) (42.6) (57.4) (11.9) (88.1) (31.3) (68.7) (47.7) (52.3)
ANA n.s. n.s.. n.s. 0.044 n.s. n.s.
Elevated 73 24 49 36 37 32 41 4 69 22 51 38 35
19.4 (32.9) (67.1) (49.3) (50.7) (43.8) (56.2) (5.5) (94.5) (30.1) (69.9) (52.1) (47.9)
Normal 304 95 209 116 188 129 175 43 261 95 209 140 164
80.6 (31.3) (68.8) (38.2) (61.8) (42.4) (57.6) (14.1) (85.9) (31.2) (68.8) (46.1) (53.9)
ASO n.s. n.s. n.s. n.s. n.s. n.s.
Elevated 18 4 14 8 10 11 7 2 16 6 12 5 13
4.8 (22.2) (77.8) (44.4) (55.6) (61.1) (38.9) (11.1) (88.9) (33.3) (66.7) (27.8) (72.2)
Normal 359 115 244 144 215 150 209 45 314 111 248 173 186
95.2 (32.0) (68.0) (40.1) (59.9) (41.8) (58.2) (12.5) (87.5) (30.9) (69.1) (48.2) (51.8)
Tab.2  Correlation between clinical features and immunologic markers in DLBCL
Variates Total CR non-CR P value
Gender 0.708
Female 229/502 (45.6%) 183/229 (79.9%) 46/229 (20.1%)
Male 273/502 (54.4%) 209/273 (76.6%) 64/273 (23.4%)
Age (year) 0.768
>60 232/502 (46.2%) 177/232 (76.3%) 55/232 (23.7%)
≤60 270/502 (53.8%) 215/270 (79.6%) 55/270 (20.4%)
IPI scores <0.001
3–5 160/502 (31.9%) 102/160 (63.8%) 58/160 (36.3%)
0–2 342/502 (68.1%) 290/342 (84.8%) 52/342 (15.2%)
LDH <0.001
Elevated 201/502 (40.0%) 131/201 (65.2%) 70/201 (34.8%)
Normal 301/502 (60.0%) 261/301 (86.7%) 40/301 (13.3%)
ECOG 0.172
≥2 59/502 (11.8%) 32/59 (54.2%) 27/59 (45.8%)
0–1 443/502 (88.2%) 360/443 (81.3%) 83/443 (18.7%)
Extranodal 0.182
0–1 347/502 (69.1%) 281/347 (81.0%) 66/347 (19.0%)
≥2 155/502 (30.9%) 111/155 (71.6%) 44/155 (28.4%)
Ann Arbor stage 0.032
III–IV 219/502 (43.6%) 147/219 (67.1%) 72/219 (32.9%)
III 283/502 (56.4%) 245/283 (86.6%) 38/283 (13.4%)
CIC 0.575
Elevated 147/502 (29.3%) 109/147 (74.1%) 38/147 (25.9%)
Normal 355/502 (70.7%) 283/355 (79.7%) 72/355 (20.3%)
IgG 0.411
Elevated 76/502 (15.1%) 59/76 (77.6%) 17/76 (22.4%)
Normal 426/502 (84.9%) 333/426 (78.2%) 93/426 (21.8%)
IgM 0.089
Elevated 21/502 (4.2%) 19/21 (90.5%) 2/21 (9.5%)
Normal 481/502 (95.8%) 373/481 (77.5%) 108/481 (22.5%)
IgA 0.118
Elevated 20/502 (4.0%) 13/20 (65.0%) 7/20 (35.0%)
Normal 482/502 (96.0%) 379/482 (78.6%) 103/482 (21.4%)
IgE 0.093
Elevated 98/502 (19.5%) 71/98 (72.4%) 27/98 (27.6%)
Normal 404/502 (80.5%) 321/404 (79.5%) 83/404 (20.5%)
C3 0.986
Abnormal 110/502 (21.9%) 85/110 (77.3%) 25/110 (22.7%)
Normal 392/502 (78.1%) 307/392 (78.3%) 85/392 (21.7%)
C4 0.718
Abnormal 95/502 (18.9%) 72/95 (75.8%) 23/95 (24.2%)
Normal 407/502 (81.1%) 320/407 (78.6%) 87/407 (21.4%)
RF 0.221
Elevated 41/377 (10.9%) 28/41 (68.3%) 13/41 (31.7%)
Normal 336/377 (89.1%) 271/336 (80.7%) 65/336 (19.3%)
Anti-dsDNA IgG 0.374
Elevated 3/377 (0.8%) 3/3 (100.0%) 0/3 (0.0%)
Normal 374/377 (99.2%) 296/374 (79.1%) 78/374 (20.9%)
Anti-SSA 0.074
Positive 6/377 (1.6%) 3/6 (50.0%) 3/6 (50.0%)
Negative 371/377 (98.4%) 296/371 (79.8%) 75/371 (20.2%)
ANA 0.351
Elevated 73/377 (19.4%) 55/73 (75.3%) 18/73 (24.7%)
Normal 304/377 (80.6%) 244/304 (80.3%) 60/304 (19.7%)
ASO 0.28
Elevated 18/377 (4.8%) 12/18 (66.7%) 6/18 (33.3%)
Normal 359/377 (95.2%) 287/359 (79.9%) 72/359 (20.1%)
Abnormal immunologic markers 0.117
≥3 76/377 (20.2%) 54/76 (71.1%) 22/76 (28.9%)
0–2 301/377 (79.8%) 245/301 (81.4%) 56/301 (18.6%)
Tab.3  Effects of clinical factors on treatment response
Fig.1  Progression-free survival (A) and overall survival (B) curves of 502 patients with DLBCL.
Fig.2  Progression-free survival (A) and overall survival (B) curves of 377 patients with and without multiple abnormal immunologic markers.
   PFS      OS  
Variates HR 95% CI P value   HR 95% CI P value
Age>60 / / 0.064   2.311 1.475–3.621 <0.001
Elevated LDH 3.404 2.394–4.838 <0.001   3.756 2.361–5.976 <0.001
ECOG≥2 3.116 2.096–4.633 <0.001   3.213 1.957–5.275 <0.001
Extranodal involvement≥2 1.775 1.263–2.494 0.001   1.720 1.109–2.667 0.015
Advanced stage 3.551 2.468–5.109 <0.001   3.571 2.221–5.740 <0.001
Multiple abnormal Immunologic markers 2.141 1.389–3.299 0.001 2.511 1.441–4.377 0.001
Tab.4  Univariate analysis on PFS and OS in patients with DLBCL
PFS OS
Variable RR 95% CI P value RR HR (95% CI) P value
Age>60 / / 0.864 2.025 1.152–3.557 0.014
Elevated LDH 2.372 1.489–3.777 <0.001 3.649 2.025–6.574 <0.001
ECOG≥2 / / 0.165 / / 0.135
Extranodal involvement≥2 / / 0.132 / / 0.319
Advanced stage 2.285 1.413–3.696 0.001 / / 0.078
Multiple abnormal immunologic markers 1.799 1.163–2.784 0.008 2.326 1.333–4.059 0.003
Tab.5  Multivariate analysis on PFS and OS in patients with DLBCL
1 K Ekström Smedby, CM Vajdic, M Falster, EA Engels, O Martínez-Maza, J Turner, H Hjalgrim, P Vineis, A Seniori Costantini, PM Bracci, EA Holly, E Willett, JJ Spinelli, C La Vecchia, T Zheng, N Becker, S De Sanjosé, BC Chiu, L Dal Maso, P Cocco, M Maynadié, L Foretova, A Staines, P Brennan, S Davis, R Severson, JR Cerhan, EC Breen, B Birmann, AE Grulich, W Cozen. Autoimmune disorders and risk of non-Hodgkin lymphoma subtypes: a pooled analysis within the InterLymph Consortium. Blood 2008; 111(8): 4029–4038
https://doi.org/10.1182/blood-2007-10-119974 pmid: 18263783
2 E Baecklund, A Iliadou, J Askling, A Ekbom, C Backlin, F Granath, AI Catrina, R Rosenquist, N Feltelius, C Sundström, L Klareskog. Association of chronic inflammation, not its treatment, with increased lymphoma risk in rheumatoid arthritis. Arthritis Rheum 2006; 54(3): 692–701
https://doi.org/10.1002/art.21675 pmid: 16508929
3 A Bilici, HS Yapici, S Ercan, M Seker, BB Ustaalioglu, T Salman, A Orcun, M Gumus. The prevalence and significance of autoantibodies in patients with non-Hodgkin’s lymphoma: are they correlated with clinicopathological features? Journal of B.U.ON. 17: 502-507, 2012
pmid: 23033289
4 R Solans-Laqué A López-Hernandez, JA Bosch-Gil, A Palacios, M Campillo, M Vilardell-Tarres. Risk, predictors, and clinical characteristics of lymphoma development in primary Sjögren’s syndrome. Semin Arthritis Rheum 2011; 41(3): 415–423
https://doi.org/10.1016/j.semarthrit.2011.04.006 pmid: 21665245
5 E Sabattini, F Bacci, C Sagramoso, SA Pileri. WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues. Pathologica 2010;102(3):83–87.
https://doi.org/10.1590/S0080-623420140000400008 pmid: 21171509
6 S Ramiro, C Gaujoux-Viala, JL Nam, JS Smolen, M Buch, L Gossec, D van der Heijde, K Winthrop, R Landewé. Safety of synthetic and biological DMARDs: a systematic literature review informing the 2013 update of the EULAR recommendations for management of rheumatoid arthritis. Ann Rheum Dis 2014; 73(3): 529–535
https://doi.org/10.1136/annrheumdis-2013-204575 pmid: 24401994
7 M Petri, AM Orbai, GS Alarcón, C Gordon, JT Merrill, PR Fortin, IN Bruce, D Isenberg, DJ Wallace, O Nived, G Sturfelt, R Ramsey-Goldman, SC Bae, JG Hanly, J Sánchez-Guerrero, A Clarke, C Aranow, S Manzi, M Urowitz, D Gladman, K, Kalunian M Costner, VP Werth, A Zoma, S Bernatsky, G Ruiz-Irastorza, MA Khamashta, S Jacobsen, JP Buyon, P Maddison, MA Dooley, RF van Vollenhoven, E Ginzler, T Stoll, C Peschken, JL Jorizzo, JP Callen, SS Lim, BJ Fessler, M Inanc, DL Kamen, A Rahman, K Steinsson, AG Jr Franks, L Sigler, S Hameed, H Fang, N Pham, R Brey, MH Weisman, G Jr McGwin, LS Magder. Derivation and validation of the Systemic Lupus International Collaborating Clinics classification criteria for systemic lupus erythematosus. Arthritis Rheum 2012; 64(8): 2677–2686
https://doi.org/10.1002/art.34473 pmid: 22553077
8 CH Shiboski, SC Shiboski, R Seror, LA Criswell, M Labetoulle, TM Lietman, A Rasmussen, H Scofield, C Vitali, SJ Bowman, X Mariette; International Sjögren’s Syndrome Criteria Working Group. 2016 American College of Rheumatology/European League Against Rheumatism Classification Criteria for Primary Sjögren’s Syndrome: A Consensus and Data-Driven Methodology Involving Three International Patient Cohorts. Arthritis Rheumatol 2017; 69(1):35–45
https://doi.org/10.1002/art.39859 pmid: 27785888
9 IF Horvath, P Szodoray, M Zeher. Primary Sjögren’s syndrome in men: clinical and immunological characteristic based on a large cohort of Hungarian patients. Clin Rheumatol 2008; 27(12): 1479–1483
https://doi.org/10.1007/s10067-008-0944-7 pmid: 18553114
10 N Watanabe, A Arimura, M Kobayashi, M Oshima. ASO, ASK and ADNase-B values rheumatic fever, rheumatic heart disease and other infections by hemolytic streptococcus: Proceedings of the IV Conference on Prevention for Rheumatic Fever and Rheumatic Heart Disease, January 1979, Kyoto. Jpn Circ J 1980; 44(10): 808–809
https://doi.org/10.1253/jcj.44.808 pmid: 7431636
11 K Ohyama, M Baba, M Tamai, N Aibara, K Ichinose, N Kishikawa, A Kawakami, N Kuroda. Proteomic profiling of antigens in circulating immune complexes associated with each of seven autoimmune diseases. Clin Biochem 2015; 48(3): 181–185
https://doi.org/10.1016/j.clinbiochem.2014.11.008 pmid: 25438073
12 H Tsukamoto, A Ueda, K Nagasawa, Y Tada, Y Niho. Increased production of the third component of complement (C3) by monocytes from patients with systemic lupus erythematosus. Clin Exp Immunol 1990; 82(2): 257–261
https://doi.org/10.1111/j.1365-2249.1990.tb05436.x pmid: 2242606
13 BD Cheson, B Pfistner, ME Juweid, RD Gascoyne, L Specht, SJ Horning, B Coiffier, RI Fisher, A Hagenbeek, E Zucca, ST Rosen, S Stroobants, TA Lister, RT Hoppe, M Dreyling, K Tobinai, JM Vose, JM Connors, M Federico, V; International Harmonization Project on Lymphoma. DiehlRevised response criteria for malignant lymphoma. J Clin Oncol 2007; 25(5): 579–586
https://doi.org/10.1200/JCO.2006.09.2403 pmid: 17242396
14 J Candido, T Hagemann. Cancer-related inflammation. J Clin Immunol 2013; 33( Suppl 1): S79–S84
https://doi.org/10.1007/s10875-012-9847-0 pmid: 23225204
15 U Vitolo, A Chiappella, E Angelucci, G Rossi, AM Liberati, MG Cabras, B Botto, G Ciccone, G Gaidano, L Falchi, R Freilone, D Novero, L Orsucci, V Pavone, E Pogliani, D Rota-Scalabrini, F Salvi, A Tonso, A Tucci, A; Gruppo Italiano Multiregionale Linfomi e Leucemie (GIMURELL). LevisDose-dense and high-dose chemotherapy plus rituximab with autologous stem cell transplantation for primary treatment of diffuse large B-cell lymphoma with a poor prognosis: a phase II multicenter study. Haematologica 2009; 94(9): 1250–1258
https://doi.org/10.3324/haematol.2009.007005 pmid: 19586937
16 ET Sayegh, O Bloch, AT Parsa. Complement anaphylatoxins as immune regulators in cancer. Cancer Med 2014; 3(4): 747–758
https://doi.org/10.1002/cam4.241 pmid: 24711204
17 M Fallah, X Liu, J Ji, A Försti, K Sundquist, K Hemminki. Autoimmune diseases associated with non-Hodgkin lymphoma: a nationwide cohort study. Ann Oncol 2014; 25(10): 2025–2030
https://doi.org/10.1093/annonc/mdu365 pmid: 25081899
18 O Ngalamika, Y Zhang, H Yin, M Zhao, ME Gershwin, Q Lu. Epigenetics, autoimmunity and hematologic malignancies: a comprehensive review. J Autoimmun 2012; 39(4): 451–465
https://doi.org/10.1016/j.jaut.2012.09.002 pmid: 23084980
19 SM Hayter, MC Cook. Updated assessment of the prevalence, spectrum and case definition of autoimmune disease. Autoimmun Rev 2012; 11(10): 754–765
https://doi.org/10.1016/j.autrev.2012.02.001 pmid: 22387972
20 GS Firestein. Evolving concepts of rheumatoid arthritis. Nature 2003; 423(6937): 356–361
https://doi.org/10.1038/nature01661 pmid: 12748655
21 S Bernatsky, A Clarke, R Ramsey-Goldman. Malignancy and systemic lupus erythematosus. Curr Rheumatol Rep 2002; 4(4): 351–358
https://doi.org/10.1007/s11926-002-0045-6 pmid: 12126588
22 RI Fox, HI Kang. Pathogenesis of Sjogren’s syndrome. Rheum Dis Clin North Am 1992; 18(3):517–538 PMID: 1323135
https://doi.org/10.1097/BOR.0b013e32832eba21
23 H Nogai, B Dörken, G Lenz. Pathogenesis of non-Hodgkin’s lymphoma. J Clin Oncol 2011; 29(14): 1803–1811
https://doi.org/10.1200/JCO.2010.33.3252 pmid: 21483013
24 SA Riemersma, ES Jordanova, RF Schop, K Philippo, LH Looijenga, E Schuuring, PM Kluin. Extensive genetic alterations of the HLA region, including homozygous deletions of HLA class II genes in B-cell lymphomas arising in immune-privileged sites. Blood 2000; 96(10): 3569–3577
https://doi.org/10.2307/3343410 pmid: 11071656
25 E Lech-Maranda, J Bienvenu, AS Michallet, R Houot, T Robak, B Coiffier, G Salles. Elevated IL-10 plasma levels correlate with poor prognosis in diffuse large B-cell lymphoma. Eur Cytokine Netw 2006; 17(1): 60–66
https://doi.org/10.1097/01.COH.0000209585.67081.22 pmid: 16613764
26 LM Rimsza, RA Roberts, TP Miller, JM Unger, M LeBlanc, RM Braziel, DD Weisenberger, WC Chan, HK Muller-Hermelink, ES Jaffe, RD Gascoyne, E Campo, DA Fuchs, CM Spier, RI Fisher, J Delabie, A Rosenwald, LM Staudt, TM Grogan. Loss of MHC class II gene and protein expression in diffuse large B-cell lymphoma is related to decreased tumor immunosurveillance and poor patient survival regardless of other prognostic factors: a follow-up study from the Leukemia and Lymphoma Molecular Profiling Project. Blood 2004; 103(11): 4251–4258
https://doi.org/10.1182/blood-2003-07-2365 pmid: 14976040
27 KY Urayama, RF Jarrett, H Hjalgrim, A Diepstra, Y Kamatani, A Chabrier, V Gaborieau, A Boland, A Nieters, N Becker, L Foretova, Y Benavente, M Maynadié, A Staines, L Shield, A Lake, D Montgomery, M Taylor, KE Smedby, RM Amini, HO Adami, B Glimelius, B Feenstra, IM Nolte, L Visser, GW van Imhoff, T Lightfoot, P Cocco, L Kiemeney, SH Vermeulen, I Holcatova, L Vatten, GJ Macfarlane, P Thomson, DI Conway, S Benhamou, A Agudo, CM Healy, K Overvad, A Tjønneland, B Melin, F Canzian, KT Khaw, RC Travis, PH Peeters, CA González, JR Quirós, MJ Sánchez, JM Huerta, E Ardanaz, M Dorronsoro, F Clavel-Chapelon, HB Bueno-de-Mesquita, E Riboli, E Roman, P Boffetta, S de Sanjosé, D Zelenika, M Melbye, A van den Berg, M Lathrop, P Brennan, JD McKay. Genome-wide association study of classical Hodgkin lymphoma and Epstein-Barr virus status-defined subgroups. J Natl Cancer Inst 2012; 104(3): 240–253
https://doi.org/10.1093/jnci/djr516 pmid: 22286212
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