Enhancement of the Follicular Lymphoma International Prognostic Index (FLIPI) with lymphopenia (FLIPI-L): a predictor for overall survival and histologic transformation

Yang, Guang; Mills, Matthew; Kim, Young‐Chul; Figura, Nicholas; Doyle, Catherine M.; Oliver, Daniel; Grass, G. Daniel; Robinson, Timothy J.; Chávez, Julio C.; Kim, Sungjune

doi:10.1038/s41408-019-0269-6

Cited by 13 publications

(5 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The integration of this tool with m7-FLIPI enabled the identification of a patient subgroup at high risk of death in the first 5 years after first line immunochemotherapy. In contrast with other approaches ( 4 – 8 ), IAC-FL has been designed to directly predict overall survival rather than progression-free survival.…”

Section: Discussionmentioning

confidence: 99%

“…Notably, PRIMA-PI was correlated with progression of disease in the 24 months from first line treatment (POD24), which is a strong predictor of short overall survival ( 7 ). Recently, a modified version of FLIPI that includes lymphopenia as a covariate improved the original score and enhanced the capacity to detect POD24 patients ( 8 ).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Personally Tailored Survival Prediction of Patients With Follicular Lymphoma Using Machine Learning Transcriptome-Based Models

et al. 2022

View full text Add to dashboard Cite

Follicular Lymphoma (FL) has a 10-year mortality rate of 20%, and this is mostly related to lymphoma progression and transformation to higher grades. In the era of personalized medicine it has become increasingly important to provide patients with an optimal prediction about their expected outcomes. The objective of this work was to apply machine learning (ML) tools on gene expression data in order to create individualized predictions about survival in patients with FL. Using data from two different studies, we were able to create a model which achieved good prediction accuracies in both cohorts (c-indexes of 0.793 and 0.662 in the training and test sets). Integration of this model with m7-FLIPI and age rendered high prediction accuracies in the test set (cox c-index 0.79), and a simplified approach identified 4 groups with remarkably different outcomes in terms of survival. Importantly, one of the groups comprised 27.35% of patients and had a median survival of 4.64 years. In summary, we have created a gene expression-based individualized predictor of overall survival in FL that can improve the predictions of the m7-FLIPI score.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Personally Tailored Survival Prediction of Patients With Follicular Lymphoma Using Machine Learning Transcriptome-Based Models

et al. 2022

View full text Add to dashboard Cite

show abstract

“…In iNHL, we also assessed baseline clinicopathological risk factors associated with aggressive transformation, such as Ann-Arbor stage III to IV, elevated LDH and nodal sites >4. 11 , 13 , 14 , 15 , 16 , 17 For patients with grade 1 to 3A FL, Follicular Lymphoma International Prognostic Index (FLIPI) score was also calculated.…”

Section: Methodsmentioning

confidence: 99%

Utility of FDG-PET in predicting the histology of relapsed or refractory lymphoma

Wai,

Lee,

Cliff

et al. 2024

Blood Advances

View full text Add to dashboard Cite

18F- fluorodeoxyglucose-positron emission tomography (FDG-PET) is a valuable prognostic tool in modern lymphoma care. In this study, we explored the utility of quantitative FDG-PET parameters in predicting the histology of suspected relapsed/refractory (R/R) lymphoma. We retrospectively analyzed 290 FDG-PET scans performed for suspected R/R lymphoma. FDG-PET parameters measured were maximum and mean Standardized Uptake Value (SUVMax, SUVMean), Total Metabolic Tumor Volume and Total Lesion Glycolysis (TLG). Receiver operating characteristic curve analysis was used to obtain the optimal thresholds that best discriminate 1) benign versus R/R lymphoma, 2) indolent versus aggressive non Hodgkin lymphoma (NHL) and 3) aggressive transformation of indolent NHL. We found that while all four FDG-PET parameters discriminated R/R lymphoma from benign histology, TLG was the best performing parameter (optimal cut-off ≥245, sensitivity 63%, specificity 86%, PPV 97%, NPV 30%, AUC 0.798, P<0.001). SUVMax discriminated aggressive from indolent NHL with modest accuracy (optimal threshold ≥15, sensitivity 46%, specificity 79%, PPV 82%, NPV 38%, AUC 0.638, P<0.001). In patients with prior indolent NHL, SUVMax was a modest predictor of transformation (optimal cut-off 12, sensitivity 71%, specificity 61%, PPV 50%, NPV 78%, AUC 0.676, P 0.006). Additionally, SUVMax ≥25 and an increase in SUVMax from baseline ≥150% were highly specific (96% and 94% respectively). These FDG-PET thresholds can aid identification of suspected R/R lymphoma cases with higher likelihood of R/R disease and aggressive transformation of indolent NHL, guiding the necessity and urgency of biopsy.

show abstract

“…8 In this regard, some peripheral blood (PB) parameters, such as the absolute lymphocyte count (ALC) or the lymphocyte-to-monocyte ratio (LMR), have been interpreted as a quantitative measure of their tissue counterparts, and associated with prognosis in FL and other malignancies. 9,10 In 2019, Yang and colleagues proposed an enhancement of FLIPI, the so-called FLIPI-L, 11 by the consideration of lymphopenia (ALC <1 � 10 9 /L, which they found in 31% of patients) as an additional factor to those included in the original FLIPI score. In their series of 736 FL patients diagnosed from 1999 to 2016, 72% had advanced-stage disease, 84% had histological grade 1-2, and patient distribution according to FLIPI score was 36%, 35% and 29% for low-(LR), intermediate-(IR), and high-risk (HR) categories, respectively.…”

Section: Introductionmentioning

confidence: 99%

First external validation of the FLIPI‐L score in a single‐center series of patients with follicular lymphoma

Mozas¹,

Rivero²,

Rivas‐Delgado³

et al. 2021

Hematological Oncology

View full text Add to dashboard Cite

The FLIPI-L has recently been proposed as a novel prognostic index in follicular lymphoma (FL), combining FLIPI and the presence of lymphopenia. In our single-center validation in 381 FL patients, lymphopenia was less frequent than in the original publication and thus the distribution of risk categories was different. Although it was not able to properly predict time to first treatment, FLIPI-L performed slightly better than FLIPI alone in the prediction of response, early relapse, progression-free and overall survival, and histological transformation.

show abstract

Enhancement of the Follicular Lymphoma International Prognostic Index (FLIPI) with lymphopenia (FLIPI-L): a predictor for overall survival and histologic transformation

Cited by 13 publications

References 15 publications

Personally Tailored Survival Prediction of Patients With Follicular Lymphoma Using Machine Learning Transcriptome-Based Models

Personally Tailored Survival Prediction of Patients With Follicular Lymphoma Using Machine Learning Transcriptome-Based Models

Utility of FDG-PET in predicting the histology of relapsed or refractory lymphoma

First external validation of the FLIPI‐L score in a single‐center series of patients with follicular lymphoma

Contact Info

Product

Resources

About