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

Multiple Myeloma Treatment in Real-world Clinical Practice : Results of a Prospective, Multinational, Noninterventional Study

Funding Information: The authors would like to thank all patients and their families and all the EMMOS investigators for their valuable contributions to the study. The authors would like to acknowledge Robert Olie for his significant contribution to the EMMOS study. Writing support during the development of our report was provided by Laura Mulcahy and Catherine Crookes of FireKite, an Ashfield company, a part of UDG Healthcare plc, which was funded by Millennium Pharmaceuticals, Inc, and Janssen Global Services, LLC. The EMMOS study was supported by research funding from Janssen Pharmaceutical NV and Millennium Pharmaceuticals, Inc. Funding Information: The authors would like to thank all patients and their families and all the EMMOS investigators for their valuable contributions to the study. The authors would like to acknowledge Robert Olie for his significant contribution to the EMMOS study. Writing support during the development of our report was provided by Laura Mulcahy and Catherine Crookes of FireKite, an Ashfield company, a part of UDG Healthcare plc, which was funded by Millennium Pharmaceuticals, Inc, and Janssen Global Services, LLC. The EMMOS study was supported by research funding from Janssen Pharmaceutical NV and Millennium Pharmaceuticals, Inc. Funding Information: M.M. has received personal fees from Janssen, Celgene, Amgen, Bristol-Myers Squibb, Sanofi, Novartis, and Takeda and grants from Janssen and Sanofi during the conduct of the study. E.T. has received grants from Janssen and personal fees from Janssen and Takeda during the conduct of the study, and grants from Amgen, Celgene/Genesis, personal fees from Amgen, Celgene/Genesis, Bristol-Myers Squibb, Novartis, and Glaxo-Smith Kline outside the submitted work. M.V.M. has received personal fees from Janssen, Celgene, Amgen, and Takeda outside the submitted work. M.C. reports honoraria from Janssen, outside the submitted work. M. B. reports grants from Janssen Cilag during the conduct of the study. M.D. has received honoraria for participation on advisory boards for Janssen, Celgene, Takeda, Amgen, and Novartis. H.S. has received honoraria from Janssen-Cilag, Celgene, Amgen, Bristol-Myers Squibb, Novartis, and Takeda outside the submitted work. V.P. reports personal fees from Janssen during the conduct of the study and grants, personal fees, and nonfinancial support from Amgen, grants and personal fees from Sanofi, and personal fees from Takeda outside the submitted work. W.W. has received personal fees and grants from Amgen, Celgene, Novartis, Roche, Takeda, Gilead, and Janssen and nonfinancial support from Roche outside the submitted work. J.S. reports grants and nonfinancial support from Janssen Pharmaceutical during the conduct of the study. V.L. reports funding from Janssen Global Services LLC during the conduct of the study and study support from Janssen-Cilag and Pharmion outside the submitted work. A.P. reports employment and shareholding of Janssen (Johnson & Johnson) during the conduct of the study. C.C. reports employment at Janssen-Cilag during the conduct of the study. C.F. reports employment at Janssen Research and Development during the conduct of the study. F.T.B. reports employment at Janssen-Cilag during the conduct of the study. The remaining authors have stated that they have no conflicts of interest. Publisher Copyright: © 2018 The AuthorsMultiple myeloma (MM) remains an incurable disease, with little information available on its management in real-world clinical practice. The results of the present prospective, noninterventional observational study revealed great diversity in the treatment regimens used to treat MM. Our results also provide data to inform health economic, pharmacoepidemiologic, and outcomes research, providing a framework for the design of protocols to improve the outcomes of patients with MM. Background: The present prospective, multinational, noninterventional study aimed to document and describe real-world treatment regimens and disease progression in multiple myeloma (MM) patients. Patients and Methods: Adult patients initiating any new MM therapy from October 2010 to October 2012 were eligible. A multistage patient/site recruitment model was applied to minimize the selection bias; enrollment was stratified by country, region, and practice type. The patient medical and disease features, treatment history, and remission status were recorded at baseline, and prospective data on treatment, efficacy, and safety were collected electronically every 3 months. Results: A total of 2358 patients were enrolled. Of these patients, 775 and 1583 did and did not undergo stem cell transplantation (SCT) at any time during treatment, respectively. Of the patients in the SCT and non-SCT groups, 49%, 21%, 14%, and 15% and 57%, 20%, 12% and 10% were enrolled at treatment line 1, 2, 3, and ≥ 4, respectively. In the SCT and non-SCT groups, 45% and 54% of the patients had received bortezomib-based therapy without thalidomide/lenalidomide, 12% and 18% had received thalidomide/lenalidomide-based therapy without bortezomib, and 30% and 4% had received bortezomib plus thalidomide/lenalidomide-based therapy as frontline treatment, respectively. The corresponding proportions of SCT and non-SCT patients in lines 2, 3, and ≥ 4 were 45% and 37%, 30% and 37%, and 12% and 3%, 33% and 27%, 35% and 32%, and 8% and 2%, and 27% and 27%, 27% and 23%, and 6% and 4%, respectively. In the SCT and non-SCT patients, the overall response rate was 86% to 97% and 64% to 85% in line 1, 74% to 78% and 59% to 68% in line 2, 55% to 83% and 48% to 60% in line 3, and 49% to 65% and 36% and 45% in line 4, respectively, for regimens that included bortezomib and/or thalidomide/lenalidomide. Conclusion: The results of our prospective study have revealed great diversity in the treatment regimens used to manage MM in real-life practice. This diversity was linked to factors such as novel agent accessibility and evolving treatment recommendations. Our results provide insight into associated clinical benefits.publishersversionPeer reviewe

HLA class I and II diversity contributes to the etiologic heterogeneity of non-Hodgkin lymphoma subtypes

A growing number of loci within the human leukocyte antigen (HLA) region have been implicated in non-Hodgkin lymphoma (NHL) etiology. Here, we test a complementary hypothesis of "heterozygote advantage" regarding the role of HLA and NHL, whereby HLA diversity is beneficial and homozygous HLA loci are associated with increased disease risk. HLA alleles at class I and II loci were imputed from genome-wide association studies (GWAS) using SNP2HLA for: 3,617 diffuse large B-cell lymphomas (DLBCL), 2,686 follicular lymphomas (FL), 2,878 chronic lymphocytic leukemia/small lymphocytic lymphomas (CLL/SLL), 741 marginal zone lymphomas (MZL), and 8,753 controls of European descent. Both DLBCL and MZL risk were elevated with homozygosity at class I HLA-B and -C loci (OR DLBCL=1.31, 95% CI=1.06-1.60; OR MZL=1.45, 95% CI=1.12-1.89) and class II HLA-DRB1 locus (OR DLBCL=2.10, 95% CI=1.24-3.55; OR MZL= 2.10, 95% CI=0.99-4.45). Increased FL risk was observed with the overall increase in number of homozygous HLA class II loci (p-trend<0.0001, FDR=0.0005). These results support a role for HLA zygosity in NHL etiology and suggests that distinct immune pathways may underly the etiology of the different NHL subtypes

Graft-<i>versus</i>-leukemia effects after allogeneic bone marrow transplantation are active also in the presence of clones with chromosomal anomalies in addition to the Ph chromosome

Two male patients with Philadelphia-chromosome (Ph+) chronic myelogenous leukemia (CML) underwent allogeneic bone marrow transplantation (ABMT) in the first chronic phase after busulfan treatment. In both cases, the donor was a sister, and engrafting was demonstrated by chromosome analyses which showed only donor cells in the BM. Cytogenetic relapse occurred 29 and 30 months after ABMT, respectively, when host cells reappeared: in both cases, the Ph and additional anomalies typical of the blastic phase of CML were evident. We then monitored the chromosome picture for 52 and 39 months, respectively: no striking evolution occurred, and cells with the Ph and additional anomalies persisted together with donor cells, which were a minority in the first patient and a great majority in the second throughout the observation period. A clinical relapse was observed in the first patient, but the disease never progressed to a blastic phase, whereas the second patient has not relapsed 7 years after ABMT. We reviewed data from the literature on cytogenetic relapse after ABMT in CML without clinical relapse, especially the 12 patients in whom cytogenetic relapse included chromosome anomalies in addition to the Ph, as in our patients. We suggest that graft-versus-leukemia (GVL) reactions in such patients are able to arrest progression of the leukemic blastic clone and prevent a possible relapse in blastic phase

A genome-wide association study by ImmunoChip reveals potential modifiers in myelodysplastic syndromes

Because different findings suggest that an immune dysregulation plays a role in the pathogenesis of myelodysplastic syndrome (MDS), we analyzed a large cohort of patients from a homogeneous Sardinian population using ImmunoChip, a genotyping array exploring 147,954 single-nucleotide polymorphisms (SNPs) localized in genomic regions displaying some degree of association with immune-mediated diseases or pathways. The population studied included 133 cases and 3,894 controls, and a total of 153,978 autosomal markers and 971 non-autosomal markers were genotyped. After association analysis, only one variant passed the genome-wide significance threshold: rs71325459 (p = 1.16 × 10−12), which is situated on chromosome 20. The variant is in high linkage disequilibrium with rs35640778, an untested missense variant situated in the RTEL1 gene, an interesting candidate that encodes for an ATP-dependent DNA helicase implicated in telomere-length regulation, DNA repair, and maintenance of genomic stability. The second most associated signal is composed of five variants that fall slightly below the genome-wide significance threshold but point out another interesting gene candidate. These SNPs, with p values between 2.53 × 10−6 and 3.34 × 10−6, are situated in the methylene tetrahydrofolate reductase (MTHFR) gene. The most associated of these variants, rs1537514, presents an increased frequency of the derived C allele in cases, with 11.4% versus 4.4% in controls. MTHFR is the rate-limiting enzyme in the methyl cycle and genetic variations in this gene have been strongly associated with the risk of neoplastic diseases. The current understanding of the MDS biology, which is based on the hypothesis of the sequential development of multiple subclonal molecular lesions, fits very well with the demonstration of a possible role for RTEL1 and MTHFR gene polymorphisms, both of which are related to a variable risk of genomic instability

The Engineered MIPI (e-MIPI), a Candidate Data-Mining Based Mantle Cell Lymphoma Prognostic Index Developed from the Dataset of the Fondazione Italiana Linfomi (FIL) MCL0208 Phase III Trial

The amount of clinical and biological data stored within clinical trials is growing exponentially. Data warehousing (DW) is useful for systematic global evaluation of information collected in trials: the highly translational FIL (Fondazione Italiana Linfomi)-MCL0208 trial has been used to test DW to improve data quality and to discover putative associations [Zaccaria, ASH ‘17]. In this study we developed an engineered prognostic model, focusing on easily accessible clinical variables. For this purpose, we exploited hierarchical clustering with the aim of seeking hidden patterns of interest in large datasets. Hence, these tools allowed us to develop a novel prognostic model: the engineered MIPI index (e-MIPI). Herein we present the first results, on baseline clinical characteristics: 1) clustering analysis and definition of a signature of predictive variables 2) construction of the e-MIPI to detect patients’ risk of relapse 3) comparison with known prognostic indexes for MCL 4) validation of the signature on an independent subset of patients

Pegaspargase-modified risk-oriented program for adult acute lymphoblastic leukemia: results of the GIMEMA LAL1913 trial

: Pediatric-inspired chemotherapy is the standard of care for younger adults with Philadelphia-negative acute lymphoblastic leukemia/lymphoma (Ph- ALL/LL). The GIMEMA LAL1913 trial tested a modified regimen adding pegaspargase 2000 IU/m2 to courses 1, 2, 5 and 6 of an eight-block protocol for patients 18-65 years, with dose reductions in patients &gt;55 years. Responders were risk-stratified to allogeneic hematopoietic stem cell transplantation (HCT) or maintenance according to clinical characteristics and minimal residual disease (MRD). Out of 203 study patients (median age 39.8 years, 68.5% B-lineage), 185 (91%) achieved a complete remission (CR). The 3-year overall survival (OS), event-free (EFS) and disease-free (DFS) survival rates were 66.7% (95% confidence intervals, 64.4-60.1%), 57.7% (51.0-65.3%) and 63.3% (56.3-71.1%), respectively, fulfilling the primary study endpoint of a 2-year DFS &gt;55%. While by intention-to-treat DFS was 74% and 50% in the chemotherapy (n=94) and HCT (n=91) assigment cohorts, a time-dependent analysis proved the value of HCT in eligible patients (DFS HCT 70% vs. no HCT 26%, P&lt;0.0001). In multivariate analysis, age and MRD (n=151) were independent prognostic factors associated with DFS rates of 86% (age less/equal to 40/MRD-negative, n=66), 65% (age &gt;40/MRD-negative, n=48), 64% (age less/equal to 40/MRD-positive, n=17) and 25% (age &gt;40/MRD-positive, n=20) (P&lt;0.0001). Grade 2/greater pegaspargase toxicity was mainly observed at course 1 (41 episodes in 32 patients), contributing to induction death in 2 patients, but was rare and milder thereafter. This pegarspargase-containing risk-oriented program was feasible and improved outcome of Ph- ALL/LL patients up to 65 years in a multicenter national setting. ClinicalTrials.gov #NCT02067143