A Clinical Prognostic Model Based on Machine Learning from the Fondazione Italiana Linfomi (FIL) MCL0208 Phase III Trial

BACKGROUND Multicenter clinical trials are producing growing amounts of clinical data. Machine Learning (ML) might facilitate the discovery of novel tools for prognostication and disease-stratification. Taking advantage of a systematic collection of multiple variables, we developed a model derived from data collected on 300 patients with mantle cell lymphoma (MCL) from the Fondazione Italiana Linfomi-MCL0208 phase III trial (NCT02354313). METHODS We developed a score with a clustering algorithm applied to clinical variables. The candidate score was correlated to overall survival (OS) and validated in two independent data series from the European MCL Network (NCT00209222, NCT00209209); Results: Three groups of patients were significantly discriminated: Low, Intermediate (Int), and High risk (High). Seven discriminants were identified by a feature reduction approach: albumin, Ki-67, lactate dehydrogenase, lymphocytes, platelets, bone marrow infiltration, and B-symptoms. Accordingly, patients in the Int and High groups had shorter OS rates than those in the Low and Int groups, respectively (Int→Low, HR: 3.1, 95% CI: 1.0-9.6; High→Int, HR: 2.3, 95% CI: 1.5-4.7). Based on the 7 markers, we defined the engineered MCL international prognostic index (eMIPI), which was validated and confirmed in two independent cohorts; Conclusions: We developed and validated a ML-based prognostic model for MCL. Even when currently limited to baseline predictors, our approach has high scalability potential

A Clinical Prognostic Model Based on Machine Learning from the Fondazione Italiana Linfomi (FIL) MCL0208 Phase III Trial

SIMPLE SUMMARY: The interest in using Machine-Learning (ML) techniques in clinical research is growing. We applied ML to build up a novel prognostic model from patients affected with Mantle Cell Lymphoma (MCL) enrolled in a phase III open-labeled, randomized clinical trial from the Fondazione Italiana Linfomi (FIL)—MCL0208. This is the first application of ML in a prospective clinical trial on MCL lymphoma. We applied a novel ML pipeline to a large cohort of patients for which several clinical variables have been collected at baseline, and assessed their prognostic value based on overall survival. We validated it on two independent data series provided by European MCL Network. Due to its flexibility, we believe that ML would be of tremendous help in the development of a novel MCL prognostic score aimed at re-defining risk stratification. ABSTRACT: Background: Multicenter clinical trials are producing growing amounts of clinical data. Machine Learning (ML) might facilitate the discovery of novel tools for prognostication and disease-stratification. Taking advantage of a systematic collection of multiple variables, we developed a model derived from data collected on 300 patients with mantle cell lymphoma (MCL) from the Fondazione Italiana Linfomi-MCL0208 phase III trial (NCT02354313). Methods: We developed a score with a clustering algorithm applied to clinical variables. The candidate score was correlated to overall survival (OS) and validated in two independent data series from the European MCL Network (NCT00209222, NCT00209209); Results: Three groups of patients were significantly discriminated: Low, Intermediate (Int), and High risk (High). Seven discriminants were identified by a feature reduction approach: albumin, Ki-67, lactate dehydrogenase, lymphocytes, platelets, bone marrow infiltration, and B-symptoms. Accordingly, patients in the Int and High groups had shorter OS rates than those in the Low and Int groups, respectively (Int→Low, HR: 3.1, 95% CI: 1.0–9.6; High→Int, HR: 2.3, 95% CI: 1.5–4.7). Based on the 7 markers, we defined the engineered MCL international prognostic index (eMIPI), which was validated and confirmed in two independent cohorts; Conclusions: We developed and validated a ML-based prognostic model for MCL. Even when currently limited to baseline predictors, our approach has high scalability potential

Anti-Lymphoma Activity of Interferon-Free Antiviral Treatment in Patients with Indolent B-Cell Lymphomas Associated with Hepatitis C Virus Infection

Background: The regression of hepatitis C virus (HCV)-associated lymphoma with antiviral treatment (AT) is the strongest argument in favour of an etiological link between lymphoma, especially marginal zone lymphoma (MZL), and HCV infection. In addition, the favourable impact of AT on overall survival of these patients has been reported (Arcaini 2014, Michot 2015). Although there is a clear association across the studies between the lymphoma regression and the clearance of HCV, the direct anti-lymphoma activity of interferon (IFN) cannot be ruled out. AT is undergoing a revolution: new antiviral drugs, including direct-acting antiviral (DAA) like sofosbuvir (SOF) cure more than 90% of infections. However, data on new IFN-free regimens in HCV-associated lymphoproliferative disorders are scanty and based on clinical reports (Rossotti 2015; Sultanik 2015; Carrier 2015). Patients and Methods: We analyzed virological and hematological response of 26 patients (pts) with indolent B-cell non-Hodgkin lymphomas (NHL) or chronic lymphocytic leukemia (CLL) and HCV infection treated with an IFN- free AT. We included the 5 cases reported in literature (Rossotti 2015; Sultanik 2015; Carrier 2015) with updated follow up. Results: Histological, virological and hematological features are summarized    in Table 1. Histology distribution was as follows: 12 splenic MZL, 6 extranodal MZL of MALT, 2 leukemic MZL, 2 nodal MZL, 2 CLL/SLL, 1 lymphoplasmacytic lymphoma (LPL) and 1 low grade NHL NOS. Cryoglobulins were present in 13 (symptomatic cryoglobulinemia in 5). HCV genotype was 1 in 15 pts, 2 in 4 pts, 3 in 3 pts and 4 in 2 pts, NA in 2 pts. Three pts previously received chemotherapy and 4 underwent IFN-based therapy before. Twenty-four pts received a SOF-based regimens (SOF + simeprevir in 10, SOF + ribavirin in 5, SOF + daclatasvir in 8, SOF + ledipasvir in 1) and 2 pts other regimens (ombitasvir + paritaprevir + ritonavir + ribavirin and faldaprevir + deleobuvir + ribavirin). In one pt with renal MZL 4 rituximab (R) doses have been added to SOF + simeprevir. Median AT duration was 12 weeks (range: 6-24). At time of present analysis, virological response is available in 21 pts while hematological response has been assessed in 20 pts. A sustained virological response has been obtained in 20 pts; hematological response has been observed only in pts with HCV clearance: in particular 8 pts (all MZL) achieved a complete response and 4 (all MZL) a partial response (comprising one treated also with R) while 5 had stable disease (response by histology is summarized in Table 1). In 7 pts response duration is +1 mo (in 2 pts), +2 mo (in 1 pt), +6 mo (in 3 pts), and +22 mo (in 1 pt); 6 pts (60%) cleared cryoglobulins after AT. After a median follow-up of 6 mo (range: 1- 28), 2 pts progressed: one pt shifted to DLBCL and one pt without virological response progressed and died of lymphoma; another pt with hematological CR died of metastatic hepatocellular carcinoma 8 mo after AT. Complete data for all pts will be presented at the meeting. Conclusions: Our study shows that a significant rate of hematological response can be achieved in HCV-associated MZL also with IFN-free AT. These data are a strong rationale for planning prospective trials with DAA in this setting

Interferon-free compared to interferon-based antiviral\ua0regimens as first-line therapy for B-cell lymphoproliferative disorders associated with hepatitis C virus infection

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Interferon-free antiviral treatment in B-cell lymphoproliferative disorders associated with hepatitis C virus infection

Regression of hepatitis C virus (HCV)-associated lymphoma with interferon-based antiviral treatment supports an etiological link between lymphoma and HCV infection. In addition, a favorable impact of antiviral treatment on overall survival of patients with HCV-related lymphoma has been reported. Data on IFN-free regimens combining direct-acting antivirals (DAAs) in HCV-associated lymphoproliferative disorders are scanty. We analyzed virological and lymphoproliferative disease response (LDR) of 46 patients with indolent B-cell non-Hodgkin lymphomas (NHL) or chronic lymphocytic leukemia (CLL) and chronic HCV infection treated with DAAs. Histological distribution was: 37 marginal zone lymphomas (MZL), 2 lymphoplasmacytic lymphomas, 2 follicular lymphomas, 4 CLL/small lymphocytic lymphoma (SLL), 1 low-grade NHL not otherwise specified. Thirty-nine patients received a Sofosbuvir-based regimen and 7 patients other DAAs. Median duration of DAA therapy was 12 weeks (range 6-24 weeks). A sustained virological response at week 12 after finishing DAAs was obtained in 45 patients (98%); overall LDR rate was 67% including 12 patients (26%) achieving a complete response. LDR rate was 73% among patients with MZL while no response was observed in CLL/SLL patients. Seven patients cleared cryoglobulins out of 15 initially positive. After a median follow up of 8 months, 1-year progression-free and overall survival were 75% [95% confidence interval: 51% - 88%] and 98% [86-100%], respectively. DAA therapy induces a high LDR rate in HCV-associated indolent lymphomas. These data provide a strong rationale for prospective trials with DAAs in this setting