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Baseline total metabolic tumor volume may predict outcomes in follicular lymphoma
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Baseline total metabolic tumor volume served as a robust independent predictor of survival outcomes for patients with high-tumor–burden follicular lymphoma, according to a pooled analysis of clinical trials.
Follicular lymphoma represents approximately 20% to 25% of non-Hodgkin lymphomas diagnosed in the United States and Western Europe.
“Approaches that use rituximab [Rituxan; Genentech, Biogen] combined with chemotherapy have led to a remarkable improvement in survival over the last decade,” Michel Meignan, MD, PhD, professor of nuclear medicine at Henri Mondor University Hospitals in Créteil, France, and colleagues wrote. “However, despite the advances in prolonging remission overall, 20% of those treated with immunochemotherapy have disease progression within 2 years and a 5-year OS of only 50%.”
Current prognostic tools — such as the Follicular Lymphoma International Prognostic Index (FLIPI), FLIPI2 and conventional CT scanning — have proven insufficient in identifying patients with high-tumor–burden follicular lymphoma, a subset associated with a high risk for progression and death.
Meignan and colleagues sought to determine whether total metabolic tumor volume at baseline could serve as a prognostic indicator for this patient population.
The researchers conducted a pooled analysis of three multicenter trials that used 18[F]fluorodeoxyglucose PET–CT scans to measure tumor volume prior to immunochemotherapy.
These trials included data from 185 patients (median age, 55 years; range, 47-65; 50% women), 92% (n = 166) of whom had stage III or stage IV disease.
Thirty-seven percent of patients (n = 67) had a FLIPI score of 3 to 5, and 31% (n = 50) had a FLIPI2 score of 3 to 5.
Median follow-up was 63.5 months. The 5-year PFS rate was 55%, and the 5-year OS rate was 92%.
The study population had a median total metabolic tumor volume of 297 cm3 (interquartile range, 135-567). The researchers identified an optimal PFS and OS cutoff of 510 cm3.
Factors associated with a high total metabolic tumor volume included stage III or stage IV disease; high nodal, extranodal, and bone marrow involvement; and higher FLIPI and FLIPI2 scores.
Twenty-nine percent (n = 53) of patients had a total metabolic tumor volume greater than 510 cm3. When compared with patients with a lower tumor volume, these patients had significantly poorer 5-year PFS (32.7% vs. 65.1%; P < .001) and OS (84.8% vs. 94.7%; P = .013).
High total metabolic tumor volume remained a significant independent predictor for poorer outcomes after the researchers adjusted for induction treatments (PFS, P < .001; OS, P = .0141).
A multivariate analysis showed that total metabolic tumor volume (HR = 2.3; P = .002) and FLIPI2 score (HR = 2.2; P = .002) served as independent PFS predictors.
Based on these data, the researchers identified three risk categories:
- high total metabolic tumor volume and intermediate-to-high FLIPI2 score (5-year PFS, 20%; P < .001);
- high total metabolic tumor volume or intermediate-to-high FLIPI2 score (5-year PFS, 46%; P = .007); and
- low total metabolic tumor volume and low FLIPI2 score (5-year PFS, 69%).
“Because total metabolic tumor volume and metabolic response are both independent predictors of PFS, they may provide a platform for study of PET–adapted approaches and contribute to development of risk-adapted individualized care, avoiding both over- and undertreatment of all patients with follicular lymphoma,” Meignan and colleagues wrote.
Potential limitations to this pooled analysis, due to its retrospective nature, should be noted, Heiko Schröder, MD, deputy chief of molecular imaging and therapy at Memorial Sloan Kettering Cancer Center, and Craig Moskowitz, MD, Steven A. Greenberg chair of hematology at Memorial Sloan Kettering Cancer Center and a HemOnc Today Editorial Board member, wrote in an accompanying editorial.
“For instance, the vast majority of patients (1,634 of 1,819) from the three clinical trials were not eligible for analysis, presumably because baseline staging PETs had not been performed or were not available for electronic volumetric analysis,” Schröder and Moskowitz wrote.
Further, three different drug regimens were used and 16 patients stayed on 2-year maintenance therapy, Schröder and Moskowitz wrote. They noted calculations of standardized uptake values and total metabolic tumor volume may have been affected by the use of different generations of scanners from three vendors for PET scans.
It might be too early to classify total metabolic tumor volume as a prognostic biomarker for follicular lymphoma outcomes.
“As a single parameter, total metabolic tumor volume remains far from perfect for prognostication,” Schröder and Moskowitz wrote. “In the [Meignan] study, added prognostic information was derived when total metabolic tumor volume was used in combination with the Follicular Lymphoma International Prognostic Index score.”
Other studies have led to better segregation of prognostic groups through interim PET imaging assessments of total metabolic tumor volume and treatment response.
“Quantitatively, the situation also seems less clear; all proposed so-called optimal total metabolic tumor volume cutoffs were derived retrospectively, varied from study to study, and will require prospective validation,” they wrote.
Cutoffs only indicate probability — such as the probability of poor PFS in the Meignan study — and there is a trade-off between sensitivity and specificity.
“Cutoffs may also vary depending on the specific patient population, the range of tumor volumes in this population and, possibly, the drug regimen used,” Schröder and Moskowitz wrote. – by Cameron Kelsall
Disclosure: Meignan reports travel expenses from Roche. Please see the full study for a list of all other researchers’ relevant financial disclosures. Schröder and Moskowitz report no relevant financial disclosures.
Perspective
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Brad S. Kahl
Metabolic tumor burden is a measurement that integrates the tumor volume with the standard uptake value noted on 18-FGD PET imaging. Meignan and colleagues — a group of imaging experts and lymphoma specialists — analyzed PET imaging data and outcome data in patients with follicular lymphoma who received standard therapy on three different prospective clinical trials. The goal of this project was to see if metabolic tumor burden could identify patients who are at high risk for early progression and at higher risk for early death. Historically, this has been a challenge in follicular lymphoma. We commonly use tools such as the GELF criteria, the Follicular Lymphoma International Prognostic Index (FLIPI) or the FLIPI 2. Each of these tools has limitations, and none of these strategies are able to identify a truly high-risk group of patients.
In this study, researchers pooled and analyzed data from 185 patients. All patients had high tumor burden by GELF criteria. The median age was 55 years, which were relatively young for a follicular lymphoma population. The median total metabolic tumor volume (TMTV) was 297 cm3. Using statistical methods, they determined the optimal cutoff was identified at 510 cm3. Patients above that threshold had markedly inferior survival. Twenty-nine percent of patients fell into that category; 5-year PFS was 33% for this group, compared with 65% for patients below that threshold. Five-year OS was 85% for patients with high TMTV and 95% for patients with low TMTV. The discriminatory ability of the TMTV methodology could be further enhanced by integrating results with FLIPI scores, which then could be used to create three risk categories. This methodology then generated a more reliable high-risk category comprising 14% of patients with a high TMTV and an intermediate to high FLIPI-2 score. This group of patients had a median PFS of only 19 months.
This is an exciting new technique that may allow investigators and treating clinicians a reproducible way to categorize a patient’s disease burden and risk at diagnosis. Current methods — such as Ann Arbor stage, GELF criteria and FLIPI scores — are relatively inadequate for accomplishing these goals. The TMTV technique, however, still struggles to identify patients at high risk for death from follicular lymphoma and does not show the kind of discriminatory power that length of first remission demonstrated in earlier work. Clearly, further work is needed along these lines to identify the truly high-risk group of patients with follicular lymphoma. Perhaps the answer will come with a combination of TMTV and genomic risk predictors, such as the M7-FLIPI. I expect there will be more to come in this promising area of research. Stay tuned.
Disclosure: Kahl reports no relevant financial disclosures.
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