DOI: 10.1007/s00259-018-4093-1Pages: 1-11

A risk stratification model for nodal peripheral T-cell lymphomas based on the NCCN-IPI and posttreatment Deauville score

1. Chonbuk National University Medical School, Department of Internal Medicine

2. Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk National University Hospital

3. Korea University Anam Hospital College of Medicine, Department of Internal Medicine

4. Chonbuk National University Hospital, Department of Nuclear Medicine

5. Korea University Anam Hospital, Department of Nuclear Medicine

6. Chonnam National University Hwasun Hospital, Department of Nuclear Medicine

7. Kyungpook National University Hospital, Department of Internal Medicine

8. Kyungpook National University Hospital, Department of Nuclear Medicine

9. Pusan National University Hospital, Department of Internal Medicine

10. Pusan National University Hospital, Department of Nuclear Medicine and Biomedical Research Institute

11. Chungnam National University Hospital, Department of Internal Medicine

12. Chungnam National University Hospital, Department of Nuclear Medicine

13. Yeungnam University College of Medicine, Department of Internal Medicine

14. Yeungnam University College of Medicine, Department of Nuclear Medicine

15. Korea University Guro Hospital College of Medicine, Department of Internal Medicine

16. Korea University Guro Hospital College of Medicine, Department of Nuclear Medicine

17. Dong-A University College of Medicine, Department of Internal Medicine

18. Dong-A University College of Medicine, Department of Nuclear Medicine

19. Inje University College of Medicine, Inje University Busan Paik Hospital, Department of Internal Medicine

20. Inje University Busan Paik Hospital, Department of Nuclear Medicine, Inje University College of Medicine

21. Keimyung University School of Medicine, Department of Internal Medicine, Dongsan Medical Center

22. Sungkyunkwan University School of Medicine, Department of Medicine

23. Sungkyunkwan University School of Medicine, Department of Nuclear Medicine, Samsung Medical Center

24. Chonnam National University Hwasun Hospital, Department of Internal Medicine

Correspondence to:
Deok-Hwan Yang
Tel: +82-61-379-7636
Email: drydh1685@hotmail.com

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Abstract

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.

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  • Accepted: Jul 11, 2018
  • Online: Jul 28, 2018

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