Purpose: The aim of this study was to establish a risk-stratification model integrating posttreatment metabolic response using the Deauville score and the pretreatment National Comprehensive Cancer Network-International Prognostic Index (NCCN-IPI) in nodal PTCLs. Methods: We retrospectively analysed 326 patients with newly diagnosed nodal PTCLs between January 2005 and June 2016 and both baseline and posttreatment PET/CT data. The final model was validated using an independent prospective cohort of 79 patients. Results: Posttreatment Deauville score (1/2, 3, and 4/5) and the NCCN-IPI (low, low-intermediate, high-intermediate, and high) were independently associated with progression-free survival: for the Deauville score, the hazard ratios (HRs) were 1.00 vs. 2.16 (95% CI 1.47–3.18) vs. 7.86 (5.66–10.92), P < 0.001; and for the NCCN-IPI, the HRs were 1.00 vs. 2.31 (95% CI 1.20–4.41) vs. 4.42 (2.36–8.26) vs. 7.09 (3.57–14.06), P < 0.001. Based on these results, we developed a simplified three-group risk model comprising a low-risk group (low or low-intermediate NCCN-IPI with a posttreatment Deauville score of 1 or 2, or low NCCN-IPI with a Deauville score of 3), a high-risk group (high or high-intermediate NCCN-IPI with a Deauville score of 1/2 or 3, or low-intermediate NCCN-IPI with a Deauville score of 3), and a treatment failure group (Deauville score 4 or 5). This model was significantly associated with progression-free survival (5-year, 70.3%, 31.4%, and 4.7%; P < 0.001) and overall survival (5-year, 82.1%, 45.5%, and 14.7%; P < 0.001). Similar associations were also observed in the independent validation cohort. Conclusion: The risk-stratification model integrating posttreatment Deauville score and pretreatment NCCN-IPI is a powerful tool for predicting treatment failure in patients with nodal PTCLs.
|Number of pages||11|
|Journal||European Journal of Nuclear Medicine and Molecular Imaging|
|Publication status||Published - 2018 Dec 1|
- International prognostic index
- Peripheral T-cell lymphoma
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging