Our results confirm the strong prognostic value of baseline TMTV in patients with PTCL, and patients with a TMTV greater than 228.8 cm3 had lower survival. This result is consistent with the results of published studies .[11–12] In the study of Cottereau et al, the baseline TMTV (cutoff value of 230 cm3) was found to be the only significant independent predictor for both PFS (P = 0.0013) and OS (P = 0.021).[11] Mehta-Shah et al.’s study also showed that a high baseline TMTV (cutoff value is 125 cm3) predicted worse OS (HR, 6.025; P = 0.022) and EFS (HR, 3.861; P = 0.005).[12] TMTV is a measure of the viable tumor fraction and may better represent the metabolic burden of tumors. The discrepancy between the optimal thresholds in Mehta-Shah et al.’s study compared to those in our present study can be explained by the different therapy regimens that patients in. their studies received CHOP or CHOEP regimen with autologous transplant as consolidation. SUVmax is the most commonly used semiquantitative index of 18F-FDG uptake, reflecting the tumor glucose metabolism of the most aggressive cell component, and previous studies have suggested an association between SUVmax and tumor aggressiveness.[13–14] However, SUVmax was not found to be associated with outcome in our study, probably because FDG avidity at baseline is variable in patients with PTCL.[15–16]
Initially designed for risk stratification in aggressive lymphomas, the IPI is the most commonly used prognostic score system for patients with aggressive PTCL.[17] However, the usefulness of the IPI in PTCL has been questioned in some studies .[18–19] To better define the clinical outcome, several prognostic score systems, including the PIT and IPTCLP were built for PTCL patients. The predictive capacity of the PIT score has been verified in PTCL-NOS in a manner similar to that seen in diffuse large B-cell lymphoma.[4] More recently, the IPTCL was developed and reported to have a better performance than PIT scores to predict the outcome of PTCL patients in Garcĺa et al.’s study.[6] Although all three scores demonstrated their ability to predict the outcome of patients with PTCL in our study, no dramatic differences were observed among the indexes in our study, and the IPTCL was shown to be better than the other two scores to predict survival outcomes in the multivariate analysis.
The treatment outcome of patients with PTCL was worse than that of those with aggressive B-cell lymphomas, with early relapse, PFS of less than 1 year, and OS of less than 2 years.[15, 20] Moreover, a small proportion of patients who can survive for long periods of time or even be cured was also reported.[21–22] Therefore, an accurate prognostic assessment is urgently needed for PTCL patients to better select high-risk patients as well as potentially curable patients. Some studies have reported that pretreatment PET/CT parameters can give added prognostic value to prognostic score systems to better stratify the progression risk of lymphoma patients.[23–24] Cottereau et al found that the addition of TMTV to PIT could identify different risk categories of PTCL patients.[11] In the present study, we added a baseline TMTV into the IPTCLP to stratify patients into three distinct prognostic groups. This resulted in the identification of three groups of patients with significantly different outcomes. This study demonstrated that baseline TMTV could be used for further precise prediction of PTCL patient prognosis when combined with IPTCLP scores.
The results among studies might be inconsistent due to the different thresholds used for delineating tumors. In some studies, the absolute threshold of an SUV ≥ 3.0 or 2.5 was used to calculate MTV[12, 25–26] and proved to be easiest to apply in clinical setting.[27] However, we calculated MTV using an 41% SUVmax as the ROI absolute threshold, as in previous studies.[28–29] Actually, 41% SUVmax threshold method has been recommended by European Association of Nuclear Medicine due to the better interobserver agreement.[10] However, a consensus on the MTV calculation method is still lacking, and an accurate and normalized method for defining metabolic volume is needed in the future.
This study was constrained by its retrospective nature. Because of the limited number of patients in the present study, we considered patients with PTCL as a whole, and the histological subtypes were not further evaluated. Although sharing a common T-cell origin and aggressive behavior with poor outcome, subtypes have a particular clinico-biological personality. In addition, various first-line treatments used in the patients may cause bias that confounded the analysis of our results. Therefore, a prospective clinical trial with a larger sample size of PTCL patients is needed to provide a more reliable prediction of survival in such patients.