The addition of EBV and C3 complement risk factors formed a better angioimmunoblastic T-cell lymphoma prognostic scoring system

Abstract

Abstract Background: Angioimmunoblastic T-cell lymphoma (AITL), a distinct subtype of peripheral T-cell lymphoma (PTCL), exhibits unique clinical and pathological characteristics with poor prognosis. Primarily affecting elderly patients, AITL is characterized by aggressive disease progression. While the overall prognosis remains poor, significant heterogeneity exists. Developing a more accurate prognostic scoring system for AITL holds crucial importance for both clinical evaluation and therapeutic guidance. Purpose ： This study aims to better characterize the clinical features, outcomes and prognostic factors of AITL in China. To identify prognostic markers, compare the predictive value of various international prognostic scores, and explore a better prognostic evaluation system. Method ： We conducted a retrospective multicenter analysis of 350 patients with Angioimmunoblastic T-cell lymphoma (AITL), from 4 medical centers, from August 2015 to November 2023. LASSO regression was employed to identify risk factors for progression-free survival (PFS) and overall survival (OS). ROC analysis was used to develop predictive models and compare prognostic value of various international scoring systems in our cohort. All probabilities were double-tailed, and p <0.05 was considered statistically significant. Empower Stats(www.empowerstats.com; X & Y Solution, Inc. (Boston, MA, USA) and R software (http://www.R-project) were used. Results： In multicenter study involving 350 AITL patients with an average age of 65.36 years (59.14% male), the median progression-free survival (PFS) was 14.5 months and median overall survival (OS) 24.8 months during follow-up. Multivariate analysis identified multiple baseline clinical indicators associated with PFS and OS. We incorporated both PFS-and OS-associated factors into LASSO regression analysis. Based on overlapping factors identified through LASSO regression, we established prognostic correlates: age ≥65 years, ECOG score ≥2, platelet count ≤150×10^9/L, LDH> upper limit of normal (ULN), β2-MG> ULN, log(EBV copy number) ≥3.0, C3 ≥40 mg/dl, and extranodal involvement ≥2. ROC analysis validated the predictive model using 75% of samples for prediction and 25% for verification. Results showed Internal validation C indices (95% CI) for PFS and OS at 0.7018 (0.6638,0.7398) and 0.7588 (0.7243,0.7934), respectively. Building upon previous research, we developed a new AITL score system named AITL-HZ (Low Risk: 0 or 1 risk factors; Low-Mid Risk: 2 or 3 risk factors; Mid-High Risk: 4 or 5 risk factors; High Risk: ≥6 risk factors). The study introduced EBV copy number and C3 complement as novel risk factors compared to existing prognostic scoring systems. The K-M curve analysis further demonstrated that patients with different AITL-HZ scores exhibited distinct PFS and OS outcomes (p values were <0.001). Furthermore, we compared AITL-HZ scores with existing prognostic scoring systems (including IPI, PIT, ATPI, AITL score (2021 Blood), and AITL score (2022 Chinese)). ROC analysis of multivariate predictors demonstrated that the AITL-HZ score showed AUC values of 0.6783 for PFS and 0.7420 for OS, both significantly outperforming previous prognostic evaluation systems. Conclusion ： The retrospective analysis of medical records from 350 Chinese AITL patients established a novel prognostic scoring system, the AITL-HZ score. The K-M curve demonstrated distinct PFS and OS outcomes among patients with different AITL-HZ scores. ROC analysis comparing multiple predictors revealed that the AITL-HZ score effectively predicted PFS and OS, building upon existing prognostic systems including IPI, PIT, ATPI, PIAI_RISK, AITL score (2021 Blood), and AITL score (2022 Chinese). Keyword ： Angioimmunoblastic T-cell lymphoma (AITL), prognosis score, PFS, OS, EB virus, C3 complement