Abstract
To find the independent factors affecting the prognosis of AITL patients, establish a novel predictive model, and stratify the prognosis of AITL patients. We retrospectively analyzed the clinical data of 86 patients diagnosed with AITL in the First Affiliated Hospital of Wenzhou Medical University from December 2010 to March 2022. The clinical features, recurrence time, and death time of patients were collected and analyzed statistically. The median age of our patients was 68 years old, and the male-to-female ratio was 2.2: 1. There are differences between males and females in ECOG PS score (p = 0.037), β2 microglobulin levels (p = 0.018) and IgM (p = 0.021). Multivariate COX regression analysis showed that C-reactive protein > 39.3 mg/L (hazard ratio (HR), 5.41; p = 0.0001), Age > 66 years (hazard ratio (HR), 3.06; p = 0.0160), Ki67 positive (hazard ratio (HR), 4.86; p = 0.0010) and early progression of disease within 24 months (POD24) after diagnosis (hazard ratio (HR), 12.47; p = 0.0001) were independent factors affecting the prognosis of OS. KM analysis showed that the predictive model established by these four factors could effectively predict the prognosis of patients with AITL (p < 0.0001), and the ROC curve showed that the predictive ability of the new predictive model (AUC = 0.909) was significantly better than that of the traditional predictive models, such as IPI (AUC = 0.730), PIT (AUC = 0.720), PIAI (AUC = 0.715) and AITL score (AUC = 0.724). Age, C-reactive protein, Ki67, and POD24 were independent factors affecting the prognosis of OS. The prognostic model established by them combined clinical features, and serological and pathological indicators and could effectively predict the prognosis of AITL patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12288-024-01767-1.