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4480 A Prognostic Nomogram Survival Model for Newly Diagnosed Patients with AIDS-Related Diffuse Large B-Cell Lymphoma: A Multicenter Cohort Study in China

Program: Oral and Poster Abstracts
Session: 627. Aggressive Lymphomas: Clinical and Epidemiological: Poster III
Hematology Disease Topics & Pathways:
Lymphomas, Diseases, aggressive lymphoma, Lymphoid Malignancies
Monday, December 11, 2023, 6:00 PM-8:00 PM

Tao Yang1*, Yang Liang, MD, PhD2, Chaoyu Wang1*, Jun Liu1*, Yan Wu3*, Haiyan Min4*, Yunhong Huang5*, Guo Wei6*, Wei Zhang7*, Min Wang8*, Xiaoqiong Tang9*, Zailin Yang1*, Li Jun, MD1*, Hui Zhou10* and Yao Liu, PhD, MD1

1Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
2Department of Hematologic Oncology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
3Henan Infectious Disease Hospital, The Sixth People’s Hospital of Zhengzhou, Zhengzhou, China
4The Second Affiliated Hospital of Kunming Medical University, Kunming, China
5The Affiliated Cancer Hospital of Guizhou Medical University, Guiyang, China
6public health clinical center of Chengdu, Chengdu, China
7Department of Hematology, Peking Union Medical College Hospital, Beijing, China, Beijing, China
8The First Hospital of Changsha, Changsha, China
9Department of Hematology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
10Hunan Cancer Hospital, Changsha, China

BACKGROUND

The prognosis of patients with AIDS-related diffuse large B-cell lymphoma(AR-DLBCL) becomes very poor when the lymphoma relapses or is refractory to first line immunochemotherapy. We aimed to develop a novel ARDPI nomogram prognostic model for risk stratification so as to guide individualized treatment to achieve sustained remission and improve the overall prognosis for newly-diagnosed AR-DLBCL patients.

METHODS

We interrogated data from 306 patients with newly-diagnosed AR-DLBCL. We filtered variables using LASSO regression and Cox regression to identify prognostic co-variates and develop a survival model, we termed AR-DLBCL Prognostic Index (ARDPI). We evaluated model discrimination, calibration and clinical benefit by Area Under the Receiver-Operator Characteristic (AUROC), calibration plots and decision curve analysis (DCA). Next, we compared the ARDPI model discrimination, calibration and clinical benefit with the IPI and NCCN-IPI models using the same methods. Lastly, we stratified patients into three survival risk cohorts based on ARDPI model by X-tile selecting cutoff point.

RESULTS

7 co-variates were independently correlated with survival and were used to develop the ARDPI model including age, lymphocyte monocyte ratio (LMR), CD5 expression on lymphoma cells, blood EBV-DNA copy number, CD4/CD8 ratio, central nervous system (CNS) involvement and anti-HIV therapy (ART). AUROCs of ARDPI model for 1-, 3-, and 5-year were 0.80 (95% Confidence Interval [CI], 0.72, 0.88), 0.78 (0.69, 0.87) and 0.77 (0.63, 0.91). Predicted and calibrated values were concordant. The DCA curve had higher net benefit using the ARDPI model. Prediction accuracy of the ARDPI model was better compared with the IPI and NCCN-IPI models. For example, 3-year survival AUROC in the ARDPI model was 0.78 (0.69, 0.87) compared with the IPI (0.53 [0.43, 0.63] P < 0.001) and the NCCN-IPI (0.52 [0.42, 0.62] P < 0.001). Using the ARDPI model, we identified 3 survival risk cohorts with 3-year survivals of 0.80 , 0.38 and 0.09 (P<0.001).

CONCLUSION

The ARDPI has good survival prediction accuracy in newly-diagnosed persons with AIDS-related DLBCL and using it has clinical benefit. Accuracy is better than the IPI and NCCN-IPI models. Validation of our conclusions is needed.

Disclosures: No relevant conflicts of interest to declare.

*signifies non-member of ASH