Improving the ICAHT grading criteria using time-series clustering.
Authors: Emily C. Liang, Aya Albittar, Andrew Jay Portuguese, Jennifer Jing Huang, Aiko Torkelson, Delaney Kirchmeier, Abigail Chutnik, Barbara Pender, Joshua A. Hill, Noam Edward Kopmar, Rahul Banerjee, Andrew Cowan, Christina Poh, Mazyar Shadman, Alexandre V. Hirayama, Brian G. Till, Erik Lesley Kimble, Lorenzo Iovino, Ryan Daniel Cassaday, Jordan Gauthier
Journal: Journal of Clinical Oncology (2024)

7018 Background: Hematotoxicity is a major cause of morbidity after CAR T-cell therapy. We compared the performance of unsupervised time-series clustering versus the EHA/EBMT immune effector cell-associated hematotoxicity (ICAHT) grading system in describing ANC recovery after CAR T-cell therapy. Methods: Adults who underwent CAR T-cell therapy for hematologic malignancies with commercial or investigational products at our center between 2013 and 2023 were included (n = 602). Log10-transformed ANC trajectories were clustered using non-supervised longitudinal k-means based on Euclidean distances (latrend and kml packages in R). Overall survival (OS) was modeled using Cox regression. Results: The most common disease types were aggressive NHL (n = 293; 49%), indolent NHL (n = 150; 25%), and ALL (n = 94; 16%). The most common CAR T-cell products were the investigational CD19 CAR T-cell product JCAR014 (n = 197; 33%), axi-cel (n = 129; 21%), and liso-cel (n = 73; 12%). Median follow-up was 31 months (IQR, 11-60). The longitudinal ANC data clustered into 4 distinct trajectories (“clusters”): 1) very good (high nadir followed by rapid recovery), n = 460 (76%); 2) good (low nadir followed by rapid recovery), n = 109 (18%); 3) poor (low nadir followed by intermittent recovery), n = 20 (3%); 4) very poor (aplastic phenotype), n = 13 (2%). Grade 1, 2, 3, and 4 ICAHT occurred in 319 (53%), 96 (16%), 60 (10%), and 35 (6%) patients, respectively. Clusters were more strongly associated with OS (poor vs. very good, HR = 3.30, 95% CI, 1.88-5.80, p &lt; 0.0001; very poor vs. very good, HR = 11.5, 95% CI, 6.45-20.4, p &lt;0.001), compared to ICAHT categories (grade 3 vs. 0-1, HR = 2.00, 95% CI, 1.43-2.81, p &lt; 0.0001; grade 4 vs. 0-1, HR = 4.64, 95% CI, 3.10-6.96, p &lt; 0.0001). When evaluating concordance of clusters versus ICAHT grades, we found that 65% of grade 3-4 ICAHT patients were in the very good (17%) or good (48%) clusters; they exhibited distinct and more favorable patterns of ANC recovery (e.g., stable ANC recovery by day +15) compared to poor/very poor clusters. Among grade 3-4 ICAHT patients, those in the good/very good clusters had longer median OS than those in the poor/very poor clusters (9 vs. 3 months, p &lt; 0.001). This led us to modify the ICAHT criteria (mICAHT). When patients with grade 3-4 ICAHT and good/very good recovery were re-classified as grade 2 mICAHT, we observed greater distinction and improved model fit in median OS between mICAHT grades compared to original ICAHT grades. The median OS of grade 3-4, 2, and 1 mICAHT patients was 3, 19, and 35 months, respectively, compared to 7, 35, and 35 months using the original ICAHT criteria. Conclusions: Unsupervised time-series clustering identified patterns of ANC recovery not captured by the ICAHT grading system and more strongly associated with OS than ICAHT grades. Incorporating these distinct patterns of recovery into a modified ICAHT grading system improved predictions of OS compared to the original ICAHT grades.