Incidence, Survival Outcome, and Prognostic Nomogram of Patients with Angioimmunoblastic T-cell Lymphoma: a Population-based Analysis

Abstract

Objective

Due to the rarity of angioimmunoblastic T-cell lymphoma (AITL), very limited data concerning its incidence patterns and prognostic factors are available. This study aimed to explore the incidence, characteristics, survival outcomes, and prognostic factors of AITL.

Methods

Age-adjusted incidence and temporal trends were calculated based on 1247 AITL patients from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER)-13 database. A total of 1525 AITL patients from the SEER-18 database and 43 patients from our single center were included for survival analysis and nomogram construction.

Results

The age-adjusted incidence for overall cohort was 0.123 [95% confidence interval (CI), 0.117–0.131) per 100 000 during 1992–2017. The overall incidence increased steeply at the rate of 15.3% (95%CI 11.0%–19.8%, P<0.001) per year during 1992–2004, but remained stable during 2004–2017 (P=0.200). Similar incidence trends were observed in age, sex, and stage subgroups. The final nomograms consisted of four variables: age at diagnosis, sex, Ann Arbor stage, and primary site. The concordance index (C-index) of the nomogram for 5-year overall survival prediction was 0.717, 0.690 and 0.820 in the training cohort, validation cohort-1 and cohort-2, respectively. Regarding the disease-specific survival (DSS), the nomogram also demonstrated a good discrimination level, with the C-index for predicting the probability of DSS at 5 years of 0.716, 0.682 and 0.813 for the three cohorts, respectively. The calibration displayed good concordance between the nomogram-predicted and actual observed outcomes.

Conclusion

The age-adjusted incidence for AITL was low during 1992–2017. The incidence continuously increased during 1992–2004, but remained stable during 2004–2017. The nomograms as proposed may provide a favorable and accurate prognostic survival prediction in AITL.

Keywords

angioimmunoblastic T-cell lymphoma / incidence / prognosis / nomogram / SEER

References

[1] RudigerT, WeisenburgerDD, AndersonJR, et al.. Peripheral T-cell lymphoma (excluding anaplastic large-cell lymphoma): results from the Non-Hodgkin’s Lymphoma Classification Project. Ann Oncol, 2002, 13(1): 140-149

[2] VoseJ, ArmitageJ, WeisenburgerD, InternationalTCLP. International peripheral T-cell and natural killer/T-cell lymphoma study: pathology findings and clinical outcomes. J Clin Oncol, 2008, 26(25): 4124-4130

[3] MortonLM, WangSS, DevesaSS, et al.. Lymphoma incidence patterns by WHO subtype in the United States, 1992–2001. Blood, 2006, 107(1): 265-276

[4] TokunagaT, ShimadaK, YamamotoK, et al.. Retrospective analysis of prognostic factors for angioimmunoblastic T-cell lymphoma: a multicenter cooperative study in Japan. Blood, 2012, 119(12): 2837-2843

[5] FedericoM, RudigerT, BelleiM, et al.. Clinicopathologic characteristics of angioimmunoblastic T-cell lymphoma: analysis of the international peripheral T-cell lymphoma project. J Clin Oncol, 2013, 31(2): 240-246

[6] LunningMA, VoseJM. Angioimmunoblastic T-cell lymphoma: the many-faced lymphoma. Blood, 2017, 129(9): 1095-1102

[7] MouradN, MounierN, BriereJ, et al.. Clinical, biologic, and pathologic features in 157 patients with angioimmunoblastic T-cell lymphoma treated within the Groupe d’Etude des Lymphomes de l’Adulte (GELA) trials. Blood, 2008, 111(9): 4463-4470

[8] International Non-Hodgkin’s Lymphoma Prognostic Factors P. A predictive model for aggressive non-Hodgkin’s lymphoma. N Engl J Med, 1993, 329(14): 987-994

[9] GallaminiA, StelitanoC, CalviR, et al.. Peripheral T-cell lymphoma unspecified (PTCL-U): a new prognostic model from a retrospective multicentric clinical study. Blood, 2004, 103(7): 2474-2479

[10] Surveillance, Epidemiology, and End Results (SEER) Program SEER*Stat Databases. https://seer.cancer.gov/data-software/. Accessed 2021-12-01.

[11] HarrellFJr., LeeKL, MarkDB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med, 1996, 15(4): 361-387

[12] BorenE, GershwinME. Inflamm-aging: autoimmunity, and the immune-risk phenotype. Autoimmun Rev, 2004, 3(5): 401-406

[13] WeissLM, JaffeES, LiuXF, et al.. Detection and localization of Epstein-Barr viral genomes in angioimmunoblastic lymphadenopathy and angioimmunoblastic lymphadenopathy-like lymphoma. Blood, 1992, 79(7): 1789-1795

[14] de LevalL, ParrensM, Le BrasF, et al.. Angioimmunoblastic T-cell lymphoma is the most common T-cell lymphoma in two distinct French information data sets. Haematologica, 2015, 100(9): e361-364

[15] HongH, FangX, HuangH, et al.. The derived neutrophil-to-lymphocyte ratio is an independent prognostic factor in patients with angioimmunoblastic T-cell lymphoma. Br J Haematol, 2020, 189(5): 908-912

[16] BriskiR, FeldmanAL, BaileyNG, et al.. The role of front-line anthracycline-containing chemotherapy regimens in peripheral T-cell lymphomas. Blood Cancer J, 2014, 4: e214

[17] AbramsonJS, FeldmanT, Kroll-DesrosiersAR, et al.. Peripheral T-cell lymphomas in a large US multicenter cohort: prognostication in the modern era including impact of frontline therapy. Ann Oncol, 2014, 25(11): 2211-2217

[18] XuB, LiuP. No survival improvement for patients with angioimmunoblastic T-cell lymphoma over the past two decades: a population-based study of 1207 cases. PLoS One, 2014, 9(3): e92585

[19] d’AmoreF, RelanderT, LauritzsenGF, et al.. Up-front autologous stem-cell transplantation in peripheral T-cell lymphoma: NLG-T-01. J Clin Oncol, 2012, 30(25): 3093-3099

[20] FossardG, BroussaisF, CoelhoI, et al.. Role of up-front autologous stem-cell transplantation in peripheral T-cell lymphoma for patients in response after induction: an analysis of patients from LYSA centers. Ann Oncol, 2018, 29(3): 715-723

[21] HongH, FangX, WangZ, et al.. Angioimmunoblastic T-cell lymphoma: a prognostic model from a retrospective study. Leuk Lymphoma, 2018, 59(12): 2911-2916

[22] KameokaY, TakahashiN, ItouS, et al.. Analysis of clinical characteristics and prognostic factors for angioimmunoblastic T-cell lymphoma. Int J Hematol, 2015, 101(6): 536-542

[23] YooHY, SungMK, LeeSH, et al.. A recurrent inactivating mutation in RHOA GTPase in angioimmunoblastic T cell lymphoma. Nat Genet, 2014, 46(4): 371-375

[24] Sakata-YanagimotoM, EnamiT, YoshidaK, et al.. Somatic RHOA mutation in angioimmunoblastic T cell lymphoma. Nat Genet, 2014, 46(2): 171-175

[25] NguyenPN, TranNTB, NguyenTPX, et al.. Clinicopathological Implications of RHOA Mutations in Angioimmunoblastic T-Cell Lymphoma: A Meta-analysis: RHOA mutations in AITL. Clin Lymphoma Myeloma Leuk, 2021, 21(7): 431-438

[26] FukumotoK, NguyenTB, ChibaS, et al.. Review of the biologic and clinical significance of genetic mutations in angioimmunoblastic T-cell lymphoma. Cancer Sci, 2018, 109(3): 490-496

[27] ButzmannA, SridharK, JangamD, et al.. A comprehensive analysis of RHOA mutation positive and negative angioimmunoblastic T-cell lymphomas by targeted deep sequencing, expression profiling and single cell digital image analysis. Int J Mol Med, 2020, 46(4): 1466-1476

[28] YangY, ZhangYJ, ZhuY, et al.. Prognostic nomogram for overall survival in previously untreated patients with extranodal NK/T-cell lymphoma, nasal-type: a multicenter study. Leukemia, 2015, 29(7): 1571-1577

[29] HanY, YangJ, LiuP, et al.. Prognostic Nomogram for Overall Survival in Patients with Diffuse Large B-Cell Lymphoma. Oncologist, 2019, 24(11): e1251-e1261

[30] BalachandranVP, GonenM, SmithJJ, et al.. Nomograms in oncology: more than meets the eye. Lancet Oncol, 2015, 16(4): e173-180