Europe PMC

This website requires cookies, and the limited processing of your personal data in order to function. By using the site you are agreeing to this as outlined in our privacy notice and cookie policy.

Abstract 


Background

Follicular lymphoma is a clinically and genetically heterogeneous disease, but the prognostic value of somatic mutations has not been systematically assessed. We aimed to improve risk stratification of patients receiving first-line immunochemotherapy by integrating gene mutations into a prognostic model.

Methods

We did DNA deep sequencing to retrospectively analyse the mutation status of 74 genes in 151 follicular lymphoma biopsy specimens that were obtained from patients within 1 year before beginning immunochemotherapy consisting of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). These patients were recruited between May 4, 2000, and Oct 20, 2010, as part of a phase 3 trial (GLSG2000). Eligible patients had symptomatic, advanced stage follicular lymphoma and were previously untreated. The primary endpoints were failure-free survival (defined as less than a partial remission at the end of induction, relapse, progression, or death) and overall survival calculated from date of treatment initiation. Median follow-up was 7·7 years (IQR 5·5-9·3). Mutations and clinical factors were incorporated into a risk model for failure-free survival using multivariable L1-penalised Cox regression. We validated the risk model in an independent population-based cohort of 107 patients with symptomatic follicular lymphoma considered ineligible for curative irradiation. Pretreatment biopsies were taken between Feb 24, 2004, and Nov 24, 2009, within 1 year before beginning first-line immunochemotherapy consisting of rituximab, cyclophosphamide, vincristine, and prednisone (R-CVP). Median follow-up was 6·7 years (IQR 5·7-7·6).

Findings

We established a clinicogenetic risk model (termed m7-FLIPI) that included the mutation status of seven genes (EZH2, ARID1A, MEF2B, EP300, FOXO1, CREBBP, and CARD11), the Follicular Lymphoma International Prognostic Index (FLIPI), and Eastern Cooperative Oncology Group (ECOG) performance status. In the training cohort, m7-FLIPI defined a high-risk group (28%, 43/151) with 5-year failure-free survival of 38·29% (95% CI 25·31-57·95) versus 77·21% (95% CI 69·21-86·14) for the low-risk group (hazard ratio [HR] 4·14, 95% CI 2·47-6·93; p<0·0001; bootstrap-corrected HR 2·02), and outperformed a prognostic model of only gene mutations (HR 3·76, 95% CI 2·10-6·74; p<0·0001; bootstrap-corrected HR 1·57). The positive predictive value and negative predictive value for 5-year failure-free survival were 64% and 78%, respectively, with a C-index of 0·80 (95% CI 0·71-0·89). In the validation cohort, m7-FLIPI again defined a high-risk group (22%, 24/107) with 5-year failure-free survival of 25·00% (95% CI 12·50-49·99) versus 68·24% (58·84-79·15) in the low-risk group (HR 3·58, 95% CI 2·00-6·42; p<0.0001). The positive predictive value for 5-year failure-free survival was 72% and 68% for negative predictive value, with a C-index of 0·79 (95% CI 0·69-0·89). In the validation cohort, risk stratification by m7-FLIPI outperformed FLIPI alone (HR 2·18, 95% CI 1·21-3·92), and FLIPI combined with ECOG performance status (HR 2·03, 95% CI 1·12-3·67).

Interpretation

Integration of the mutational status of seven genes with clinical risk factors improves prognostication for patients with follicular lymphoma receiving first-line immunochemotherapy and is a promising approach to identify the subset at highest risk of treatment failure.

Funding

Deutsche Krebshilfe, Terry Fox Research Institute.

References 


Articles referenced by this article (35)


Show 10 more references (10 of 35)

Citations & impact 


Impact metrics

Jump to Citations
Jump to Data

Citations of article over time

Alternative metrics

Altmetric item for https://www.altmetric.com/details/4373241
Altmetric
Discover the attention surrounding your research
https://www.altmetric.com/details/4373241

Smart citations by scite.ai
Smart citations by scite.ai include citation statements extracted from the full text of the citing article. The number of the statements may be higher than the number of citations provided by EuropePMC if one paper cites another multiple times or lower if scite has not yet processed some of the citing articles.
Explore citation contexts and check if this article has been supported or disputed.
https://scite.ai/reports/10.1016/s1470-2045(15)00169-2

Supporting
Mentioning
Contrasting
20
425
5

Article citations


Go to all (316) article citations

Data 


Similar Articles 


To arrive at the top five similar articles we use a word-weighted algorithm to compare words from the Title and Abstract of each citation.