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FLEX – A New Predictive Model for Assessing Follicular Lymphoma Risks

14. 11. 2020

Overall survival of patients with advanced-stage follicular lymphoma (FL) who experience early disease progression after chemotherapy remains low. Currently used clinical prognostic models do not provide optimal sensitivity and specificity for identifying this patient subgroup. The presented study by an international team of authors introduced a new assessment index that achieves better outcomes.

The Challenges of Identifying Patients with Poor Prognosis

Despite recent advances in FL immunochemotherapy, patients who experience early disease progression after the first line of therapy remain among the high-risk patients with poor prognosis. Identifying patients from this group at diagnosis before treatment initiation would provide the opportunity to choose alternative therapies tailored to the high risk of recurrence.

Currently, there are several clinical prognostic models useful for predicting treatment outcomes; however, they have relatively low sensitivity for predicting disease progression. These models include the Follicular Lymphoma International Prognostic Index (FLIPI) and its newer version FLIPI-2. However, these models were developed before the availability of the most modern treatments, and their application to current immunochemotherapy regimens is unclear. Even the latest prognostic index PRIMA (PRIMA-PI) does not include data from patients treated with bendamustine and obinutuzumab.

The Development of a New Model for Predicting Early Disease Progression

The authors of the presented study thus decided to create a model based solely on clinical variables that could predict early progression in patients treated with currently recommended therapies. For the development and validation of the model, they used data from two large phase III clinical trials, on the basis of which they identified nine clinical variables applicable for stratifying progression-free survival (PFS), overall survival (OS), and disease progression within 2 years of therapy completion (POD24).

In the GALLIUM clinical trial, chosen as the initial dataset for creating the model, patients (n = 1004) were treated with obinutuzumab or rituximab in combination with chemotherapy. For validation of the model, the authors used a dataset from the SABRINA clinical trial, where patients (n = 410) were treated with rituximab in combination with chemotherapy.

Index for Assessing FL

The new FLEX model (Follicular Lymphoma Evaluation Index) includes the following variables:

  • Male gender
  • Value of the sum of the products of the perpendicular diameters of the largest lesions (SPD) in the highest quartile
  • Histological stage 3A
  • > 2 extranodal lesions
  • ECOG performance status score > 1
  • Hemoglobin level < 120 g/l
  • β-microglobulin level above the reference range of the institution
  • Total number of NK cells in peripheral blood < 100/μl
  • Lactate dehydrogenase level above the reference range of the institution

A score of 1 point is assigned for each parameter, and patients are stratified into low-risk (0–2 points) or high-risk (3–9 points) groups.

The sensitivity of a high FLEX score for predicting POD24 was 60% for the GALLIUM study data, compared to 53% for FLIPI and FLIPI-2 and 69% for PRIMA-PI. The specificity of the prediction was 68% for FLEX score, 58% for FLIPI, 59% for FLIPI-2, and 48% for PRIMA-PI. The prognostic value of the FLEX score during validation using the SABRINA clinical trial data was comparable to the FLIPI model.

Conclusion

The FLEX score appears to yield better results than existing prognostic models in patients with untreated FL, especially in light of modern therapeutic regimens.

(este)

Source: Mir F., Mattiello F., Grigg A. et al. Follicular Lymphoma Evaluation Index (FLEX): a new clinical prognostic model that is superior to existing risk scores for predicting progression-free survival and early treatment failure after frontline immunochemotherapy. Am J Hematol 2020 Aug 20, doi: 10.1002/ajh.25973 [Epub ahead of print].



Labels
Paediatric clinical oncology Haematology Clinical oncology
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