Cancer Medicine (Aug 2023)

A nomogram for predicting the rapid progression of diffuse large B‐cell lymphoma established by combining baseline PET/CT total metabolic tumor volume, lesion diffusion, and TP53 mutations

  • Cong Liu,
  • Pengyue Shi,
  • Zhenjiang Li,
  • Baosheng Li,
  • Zengjun Li

DOI
https://doi.org/10.1002/cam4.6295
Journal volume & issue
Vol. 12, no. 16
pp. 16734 – 16743

Abstract

Read online

Abstract Objectives This study aimed to integrate positron emission tomography/computed tomography (PET/CT) metrics and genetic mutations to optimize the risk stratification for diffuse large B‐cell lymphoma (DLBCL) patients. Methods The data of 94 primary DLBCL patients with baseline PET/CT examination completed in the Shandong Cancer Hospital and Institute (Jinan, China) were analyzed to establish a training cohort. An independent cohort of 45 DLBCL patients with baseline PET/CT examination from other hospitals was established for external validation. The baseline total metabolic tumor volume (TMTV) and the largest distance between two lesions (Dmax) standardized by patient body surface area (SDmax) were calculated. The pretreatment pathological tissues of all patients were sequenced by a lymphopanel including 43 genes. Results The optimal TMTV cutoff was 285.3 cm3 and the optimal SDmax cutoff was 0.135 m−1. TP53 status was found as an independent predictive factor significantly affecting complete remission (p = 0.001). TMTV, SDmax, and TP53 status were the main factors of the nomogram and could stratify the patients into four distinct subgroups based on their predicted progression‐free survival (PFS). The calibration curve demonstrated satisfactory agreement between the predicted and actual 1‐year PFS of the patients. The receiver operating characteristic curves showed this nomogram based on PET/CT metrics and TP53 mutations had a better predictive ability than the clinic risk scores. Similar results were identified upon external validation. Conclusions The nomogram based on imaging factors and TP53 mutations could lead to a more accurate selection of DLBCL patients with rapid progression, to increase tailor therapy.

Keywords