Personalized Medicine Program on Myelodysplastic Syndromes: Characterization of the Patient's Genome for Clinical Decision Making and Systematic Collection of Real World Data to Improve Quality of Health Care

MDS (Myelodysplastic Syndrome) Clinical Trial

— FISiM-NGS-MDS  

Official title:

Personalized Medicine Program on Myelodysplastic Syndromes: Characterization of the Patient's Genome for Clinical Decision Making and Systematic Collection of Real World Data to Improve Quality of Health Care

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04212390
• Other study ID #: FISIMMDS2020
• Status: Recruiting
• Start date: June 3, 2020
• Est. completion date: March 31, 2025

Study information

• Verified date: February 2024
• Source: Fondazione Italiana Sindromi Mielodisplastiche-ETS
• Contact: Matteo Della Porta, MD
• Phone: +39 02 8224 7668
• Email: matteo.della_porta[@]hunimed.eu
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

BACKGROUND Myelodysplastic syndromes (MDS) typically occur in elderly people and with time, a portion of the patients evolve into acute myeloid leukemia (AML). Therefore a risk-adapted treatment strategy is mandatory. Current prognostic scores present limitations, and in most cases fail to capture reliable prognostic information at individual level. STATE OF THE ART Important steps forward have been made in defining the molecular architecture of MDS and gene mutations have been reported to influence survival and risk of disease progression in MDS. Evaluation of the mutation status may add significant information to currently used prognostic scores and a comprehensive analyses of large, prospective patient populations is warranted to correctly estimate the independent effect of each mutation on clinical outcome and response to treatments. AIMS In this project, the investigators will develop a research platform by integrating genomic mutations, clinical variables and patient outcome derived from real-world data obtained from FISiM (Fondazione Italiana Sindromi Mielodisplastiche) clinical network, including 72 hematological centers. This will allow the investigators to: 1. define the clinical utility of mutational screening in the diagnostic work-up and classification of MDS 2. assess the implementation of diagnostic and therapeutic guidelines (appropriateness) in the real-life 3. evaluate the impact of specific interventions (treatments) on clinical outcomes, long-term complications and costs 4. identify predictors of response to specific treatments, and develop precision medicine programs in hematology based on Real World Evidence RWD 5. measure patient-reported outcomes (PRO) and quality of life (QoL) in a real world MDS setting

Description:

Myelodysplastic syndromes (MDS) typically occur in elderly people. Patients present peripheral blood cytopenia, and with time a portion of these subjects evolve into acute myeloid leukemia (AML). MDS are heterogeneous ranging from conditions with a near-normal life expectancy to forms close to AML and therefore a risk-adapted treatment strategy is mandatory. Current prognostic scores present limitations, and in most cases fail to capture reliable prognostic information at individual level. Several therapeutic tools have been proposed for MDS but only few survived the evidence-based criteria of efficacy. Lenalidomide improves anemia in patients with 5q deletion. Allogeneic transplantation (HSCT) is the only potentially curative treatment for high risk patients; however, an accurate selection of candidate patients is needed. Hypomethylating agents (HMA) may improve survival in MDS not eligible HSCT, while predictive factors for clinical response remain to be defined. Important steps forward have been made in defining the molecular architecture of MDS. The MDS associated with 5q deletion derives from the haploinsufficiency of RPS14 gene. The investigators and others identified genes encoding for spliceosome components in a high proportion of MDS. The investigators found a close relationship between ring sideroblasts and SF3B1 mutations, which is consistent with a causal relationship. In addition, an increasing number of genes have been found to carry recurrent mutations in MDS, involved in DNA methylation (DNMT3A, TET2, IDH1/2), chromatin modification (EZH2, ASXL1), transcriptional regulation (RUNX1), signal transduction. Gene mutations have been reported to influence survival and risk of disease progression in MDS, and the evaluation of the mutation status may add significant information to currently used prognostic scores. Moreover, mutation screening may affect clinical decision making : a) in MDS with 5q-, subjects carrying TP53 mutations have a higher risk of leukemic progression and a lower probability of response to lenalidomide; b) in patients receiving HSCT, TP53 mutations predict high probability of relapse; c) SF3B1 mutations are associated with increased probability of erythroid response to TGFb inhibitors Despite these findings, caution is needed against immediately adopting such mutational testing in clinical practice. Most of scientific evidence derive from retrospective analyses of selected patient populations. In addition, in patients with MDS genetic abnormalities explain only a proportion of the total hazard for overall survival and outcome associated with specific treatments, meaning that a large percentage is still associated with clinical and non-mutational factors. Comprehensive analyses of large, prospective patient populations are warranted to correctly estimate the independent effect of each mutation on clinical outcome and response to treatments. Real World Evidence (RWE) is information on health care that is derived from multiple sources outside typical clinical research settings, including electronic health records (EHRs), claims and billing data, product and disease registries, and data gathered through personal devices and health applications National healthcare systems of advanced countries, including Italy, widely agree on the approach whereby public healthcare decisions should be driven by available evidence on effectiveness and safety of therapeutics. It is equally accepted that randomized controlled clinical trials (RCTs), although universally recognized as the most robust "evidence generators", are insufficient for guiding the decision-making process since they are intrinsically unsuited to capture the impact of treatments in routine clinical practice. The complexity of treatments, as well as the demographic and clinical heterogeneity of patients receiving the treatments, and the long period of many treatments, explain the gap between the evidence generated in the controlled, but artificial, setting of RCTs and their current impact in the real world. This explains the growing interest in the development of methods able to produce evidence on the real-world impact of care pathways (i.e., real-world evidence). Among them, those based on the Electronic Healthcare Records (EHRs), are becoming established and receiving increasing attention from the scientific community and healthcare decision-makers. In addition, real world data (RWD) are currently used during drug development to examine aspects such as the natural history of a disease, delineating treatment pathways in clinical practice, and determining the costs and resource use associated with treatment interventions In this project, the investigators will develop a research platform by integrating genomic mutations, clinical variables and patient outcome derived from real-world data obtained from FISiM (Fondazione Italiana Sindromi Mielodisplastiche) clinical network, including 72 hematological centers. In this context, there is clearly a need to develop effective solutions to analyze and integrate molecular and clinical data of large patient populations, in order to fully understand the relationship between genotype and the clinical expression of a disease. In this area, a solution of excellence has been developed by the research center i2b2 (Informatics for Integrating Biology and the Bedside, University of Harvard, Boston - www.i2b2.org). This center developed an open-source software based on a data-warehouse able to integrate and to exploit all data coming from clinical practice and hospital admissions, making them available and easily accessible by researchers. FISiM network is based on a platform to specifically support hematological research, called i2b2Hematology (www.biomeris.com/index.php/it/tasks/i2b2-hematology-pv-it), allowing researchers to explore and analyze three types of data: (i) the clinical data available in all hematological centers belonging to the clinical network, (ii) the information related to the samples stored in biobanks, and (iii) NGS sequencing data in terms of genomic variants. Relying on this national clinical network and on an innovative informatics infrastructure, in this project the investigators will analyze the interactions among driver mutations clinical variables and patient outcome of specific treatments. At the same time the investigators will render NGS analysis of somatic mutations available for the FISiM centers that need support for this technique. The investigators will address strategical needs in MDS (i.e., standardization and improvement of diagnostic work-up, clinical relevance of mutational screening, adherence to evidence-based guidelines, drug safety and efficacy, clinical relevance of patient-reported outcomes, PRO and quality of life,QoL) in a real world MDS setting with the final objective to propose a personalized approach for the individual patient.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 1000
• Est. completion date: March 31, 2025
• Est. primary completion date: March 31, 2024
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 100 Years

Eligibility

Inclusion Criteria:

Newly diagnosed patients affected with MDS:

• age = 18 years
• written informed consent

Exclusion Criteria:

• Lack of written informed consent
• Lack of biological samples (peripheral blood, bone marrow aspirate)

Related Conditions & MeSH terms

• MDS (Myelodysplastic Syndrome)
• Myelodysplastic Syndromes
• Preleukemia
• Syndrome

Locations

Country	Name	City	State
Italy	Elena Crisà	Candiolo	Torino
Italy	IRCCS Humanitas Research Hospital	Rozzano	Milano

Sponsors (1)

Lead Sponsor	Collaborator
Fondazione Italiana Sindromi Mielodisplastiche-ETS

Country where clinical trial is conducted

Italy, 

References & Publications (19)

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Berger ML, Sox H, Willke RJ, Brixner DL, Eichler HG, Goettsch W, Madigan D, Makady A, Schneeweiss S, Tarricone R, Wang SV, Watkins J, Daniel Mullins C. Good practices for real-world data studies of treatment and/or comparative effectiveness: Recommendatio — View Citation

Cazzola M, Della Porta MG, Malcovati L. The genetic basis of myelodysplasia and its clinical relevance. Blood. 2013 Dec 12;122(25):4021-34. doi: 10.1182/blood-2013-09-381665. Epub 2013 Oct 17. — View Citation

Della Porta MG, Alessandrino EP, Bacigalupo A, van Lint MT, Malcovati L, Pascutto C, Falda M, Bernardi M, Onida F, Guidi S, Iori AP, Cerretti R, Marenco P, Pioltelli P, Angelucci E, Oneto R, Ripamonti F, Bernasconi P, Bosi A, Cazzola M, Rambaldi A; Gruppo — View Citation

Della Porta MG, Galli A, Bacigalupo A, Zibellini S, Bernardi M, Rizzo E, Allione B, van Lint MT, Pioltelli P, Marenco P, Bosi A, Voso MT, Sica S, Cuzzola M, Angelucci E, Rossi M, Ubezio M, Malovini A, Limongelli I, Ferretti VV, Spinelli O, Tresoldi C, Poz — View Citation

Fenaux P, Mufti GJ, Hellstrom-Lindberg E, Santini V, Finelli C, Giagounidis A, Schoch R, Gattermann N, Sanz G, List A, Gore SD, Seymour JF, Bennett JM, Byrd J, Backstrom J, Zimmerman L, McKenzie D, Beach C, Silverman LR; International Vidaza High-Risk MDS — View Citation

Ford I, Norrie J. Pragmatic Trials. N Engl J Med. 2016 Aug 4;375(5):454-63. doi: 10.1056/NEJMra1510059. No abstract available. — View Citation

Fralick M, Kesselheim AS, Avorn J, Schneeweiss S. Use of Health Care Databases to Support Supplemental Indications of Approved Medications. JAMA Intern Med. 2018 Jan 1;178(1):55-63. doi: 10.1001/jamainternmed.2017.3919. — View Citation

Franklin JM, Schneeweiss S. When and How Can Real World Data Analyses Substitute for Randomized Controlled Trials? Clin Pharmacol Ther. 2017 Dec;102(6):924-933. doi: 10.1002/cpt.857. Epub 2017 Sep 25. — View Citation

Gerstung M, Papaemmanuil E, Martincorena I, Bullinger L, Gaidzik VI, Paschka P, Heuser M, Thol F, Bolli N, Ganly P, Ganser A, McDermott U, Dohner K, Schlenk RF, Dohner H, Campbell PJ. Precision oncology for acute myeloid leukemia using a knowledge bank ap — View Citation

Greenberg PL, Tuechler H, Schanz J, Sanz G, Garcia-Manero G, Sole F, Bennett JM, Bowen D, Fenaux P, Dreyfus F, Kantarjian H, Kuendgen A, Levis A, Malcovati L, Cazzola M, Cermak J, Fonatsch C, Le Beau MM, Slovak ML, Krieger O, Luebbert M, Maciejewski J, Ma — View Citation

Grinfeld J, Nangalia J, Baxter EJ, Wedge DC, Angelopoulos N, Cantrill R, Godfrey AL, Papaemmanuil E, Gundem G, MacLean C, Cook J, O'Neil L, O'Meara S, Teague JW, Butler AP, Massie CE, Williams N, Nice FL, Andersen CL, Hasselbalch HC, Guglielmelli P, McMul — View Citation

Hemkens LG, Contopoulos-Ioannidis DG, Ioannidis JP. Agreement of treatment effects for mortality from routinely collected data and subsequent randomized trials: meta-epidemiological survey. BMJ. 2016 Feb 8;352:i493. doi: 10.1136/bmj.i493. Erratum In: BMJ. — View Citation

https://www.ctti-clinicaltrials.org/files/recommendations/registrytrials-recs.pdf

Jaiswal S, Fontanillas P, Flannick J, Manning A, Grauman PV, Mar BG, Lindsley RC, Mermel CH, Burtt N, Chavez A, Higgins JM, Moltchanov V, Kuo FC, Kluk MJ, Henderson B, Kinnunen L, Koistinen HA, Ladenvall C, Getz G, Correa A, Banahan BF, Gabriel S, Kathire — View Citation

Wang SV, Schneeweiss S, Berger ML, Brown J, de Vries F, Douglas I, Gagne JJ, Gini R, Klungel O, Mullins CD, Nguyen MD, Rassen JA, Smeeth L, Sturkenboom M; joint ISPE-ISPOR Special Task Force on Real World Evidence in Health Care Decision Making. Reporting — View Citation

* Note: There are 19 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Type and frequency of recurrent gene mutations in MDS patients at diagnosis	Polymorphonuclear granulocytes (PMN)/mononucleated cells (MNC) will be isolated from peripheral blood (PB) and/or bone marrow (BM) samples. Separated cells will be frozen locally and sent to the central lab to perform DNA extraction and NGS screening every 4 months.In all cases, a NGS screening will be performed by targeted approach to sequence all coding exons of 60 candidate genes.; As a result of this approach, the investigators will describe type and frequency of recurrent gene mutations in MDS patients.	0-24 months
Primary	Prognostic significance of gene mutations in MDS patients	A research platform will be developped by combining FISiM data on genetic and molecular characterization of hematological malignancies together with the national platform (REDCAP database), where clinical data are kept in a protected environment .; The investigators will analyze the prognostic effect of gene mutations on MDS patients' outcome (overall survival) by multivariable analysis.	12-36 months
Primary	Measure of quality of life (QoL) in MDS patients	The investigators will use QOL-E questionnaire to measure QoL in MDS patients. QOL-E is a specific tool to evaluate patient reported outcomes in patients with Myelodysplastic Syndromes. It evaluates the impact of the disease and treatment on 4 general dimensions (physical, functional, social and sexual well-being) and on one specific MDS-related dimension and also fatigue (https://qol-e.it/). Each item is rescaled so that a better response corresponds to a higher numerical value and better QoL.Transformation of raw scores into a 0-100 scale will be carried out to generate the standardized scores for each domain.; Questionnaire will be completed by the patients upon study entry. Follow-up measurements will be performed every 6 months for patients receiving supportive care (including RBC transfusions), before and after disease modifying treatments (every 4 months) and at the time of disease progression.	0-24 months
Primary	Measure of patient-reported outcomes (PRO) in MDS patients.	The investigators will use HM-PRO questionnaire (Hematology specific patient-reported outocome measure) to measure PRO in MDS patients.; The HM-PRO is a composite measure consisting of two scales: Part A (mesures the impact of MDS and its treatment on a patient's quality of life; Part B (signs and symptoms, SS) captures the severity of different disease symptoms and treatment side effects (https://www.futuremedicine.com/doi/10.2217/cer-2018-0108?url_ver=Z39.88-2003&rfr_id=ori%3Arid%3Acrossref.org&rfr_dat=cr_pub%3Dwww.ncbi.nlm.nih.gov&). Both scales have linear scoring system ranging from 0 to 100, with higher scores representing greater impact on QoL and symptom burden.; Questionnaire will be completed by the patients upon study entry. Follow-up measurements will be performed every 6 months for patients receiving supportive care (including RBC transfusions), before and after disease modifying treatments (every 4 months) and at the time of disease progression.	0-24 months