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COVID19-hematological Malignancies: the Italian Hematology Alliance

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ClinicalTrials.gov Identifier: NCT04352556
Recruitment Status : Recruiting
First Posted : April 20, 2020
Last Update Posted : May 18, 2021
Sponsor:
Information provided by (Responsible Party):
Francesco Passamonti, Ospedale di Circolo - Fondazione Macchi

Study Description
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Brief Summary:

This is a retrospective/prospective, cohort, non-interventional observational study. This means that all patients with documented COVID and HM diagnosed between February 2020 and study initiation will compose the retrospective part, while those diagnosed after study approval will enter prospective part.

The total duration of the study will be 12 months.

The study population will must be older than 18 years of age with HM and SARS-CoV-2 infection. All patients with documented SARS-CoV-2 infection (COVID) and history or active hematological malignancies, who refer to any Hematological Unit will be included.


Condition or disease
SARS-CoV-2 Infection Hematological Malignancies

Detailed Description:

This is a retrospective/prospective, cohort, non-interventional observational study. An informed consensus for the participation is available. In this section we provide informations on sample size and statistical analysis.

In Italy, the projected estimate of complete HM prevalence at Jan 1, 2020 has been established as 48,254 cases for Hodgkin lymphoma, 110.715 cases for non Hodgkin Lymphomas, 67,301 for leukemias, and 25,066 for multiple myeloma (Guzzinati et al, BMC Cancer 2018). The Italian Dipartimento della Protezione Civile website reported (March 23, 2020) that 63,927 cases are currently infected with SARS-CoV-2. No formal sample size calculation was made for this project but, on the basis of data available to date, considering the prevalence of hematological patients in Italy (0.4%) and assuming that these patients have the same risk of contracting COVID-19 as the general population, we supposed to enroll at least 250 patients (at March 24, 2020).

Statistical analyses All data collected will be summarized using appropriate descriptive statistics: absolute and relative frequencies for discrete variables; mean, standard deviation, median and interquartile range for continuous ones. To identify factors significantly associated with composite endpoint, log-binomial regression will be used for modelling risk ratio together with 95% confidence interval estimated.

The least absolute shrinkage and selection operator (LASSO) method will be applied for selecting the factors able to independently predict primary end-point. LASSO selects variables correlates to the measured outcome by shrinking coefficients weights, down to zero for the ones not correlated to outcome. In addition, machine learning techniques will be used for validating results from LASSO. A weight will be assigned to each coefficient of the selected predictors and weights will be summed to produce a total aggregate score. Predictive performance will be assessed through discrimination and calibration. Discrimination indicates how well the model can distinguish individuals with the outcome from those without the outcome. Two, the net reclassification improvement (NRI) will be calculated for assessing the 'net' number of individuals correctly reclassified using "the new model" over a comparator index [i.e., CCI (Charlson Comorbidity Score) or MCS (Multisource Comorbidity Score), or HM-disease specific]. Calibration ascertains the concordance between the model's predictions and observed outcomes, which we evaluated using a calibration plot. Cartographic and geostatistical methods will be used to exploring the spatial patterns of disease. An Exploratory Spatial Data Analysis (ESDA) and the Kriging method will be also applied to describe and model spatial (geographical) pattern.

Study Design
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Study Type : Observational
Estimated Enrollment : 250 participants
Observational Model: Cohort
Time Perspective: Other
Official Title: SARS-CoV-2 Infection in Patients With Hematological Malignancies: the Italian Hematology Alliance
Actual Study Start Date : April 7, 2020
Estimated Primary Completion Date : April 30, 2022
Estimated Study Completion Date : April 30, 2022

Resource links provided by the National Library of Medicine


Groups and Cohorts
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Outcome Measures
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Primary Outcome Measures :
  1. To evaluate mortality. [ Time Frame: At 2 months from study initiation ]
    The percentage of HM patients with COVID-19 who died.

  2. To evaluate potential predictive biochemical parameters of mortality. [ Time Frame: At 2 months from study initiation ]
    We will assess the correlation between some biochemical parameters at diagnosis of COVID (i.e. hemoglobin, platelets, lymphocytes, clotting tests, CRP), each on the basis of its specific unit of measure, and mortality.

  3. To evaluate potential predictive HM-related parameters of mortality. [ Time Frame: At 2 months from study initiation ]
    We will assess the correlation between HM-related parameters at diagnosis of COVID [i.e. disease type (leukemia, lymphomas, myeloma), disease status (remission / stable / progression), therapy status (on / off therapy)] and mortality.

  4. To evaluate COVID severity as predictive parameter of mortality. [ Time Frame: At 2 months from study initiation ]
    We will assess the correlation between COVID severity [mild (non-pneumonia and mild pneumonia), severe (dyspnea, respiratory frequency ≥ 30/min, SpO2 ≤ 93%, PaO2/FiO2 < 300 and/or lung infiltrates > 50%) and critical (respiratory failure, septic shock, and/or multiple organ disfunction or failure)] and mortality


Secondary Outcome Measures :
  1. Epidemiology of patients with HM infected by SARS-CoV-2with any spectrum of illness severity [ Time Frame: At 6 months from study initiation ]
    Description of the different types of hematological malignancies (WHO criteria) in patients with SARS-CoV-2 infection. All aggregated data will be stratified on the basis of COVID severity: mild (non-pneumonia and mild pneumonia), severe (dyspnea, respiratory frequency ≥ 30/min, SpO2 ≤ 93%, PaO2/FiO2 < 300 and/or lung infiltrates > 50%) and critical disease (respiratory failure, septic shock, and/or multiple organ disfunction or failure)

  2. Definition of complete clinical picture of COVID-19 in HM [ Time Frame: At 2 months from study initiation ]
    Characterization of clinical and biochemical profile of patients with SARS-CoV-2 positivity.

  3. Evolution of HM [ Time Frame: At 2 months from study initiation ]
    Assessment of HM status post SARS-CoV-2 infection stratified as no implication, loss of response, progression of the hematological disease.

  4. To evaluate admission to ICU requiring mechanical ventilation or death per characteristics [ Time Frame: At 2 months from study initiation ]
    Percentage of HM patients being admitted to ICU requiring mechanical ventilation, or death stratified per disease type, status, per off-therapy/on-therapy, per type of therapy (chemo, immunotherapy, cell therapy, stem cell transplant).

  5. Viral dynamics in infected HM patients [ Time Frame: At 12 months from study initiation ]

Eligibility Criteria
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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
The study population will must be older than 18 years of age with Hematological malignancies and SARS-CoV-2 infection.
Criteria

Inclusion Criteria:

  • Age equal to or greater than 18 years of age.
  • History of hematological malignancies (acute leukemias, myelodysplastic syndromes, myeloproliferative neoplasms, lymphomas, myeloma).
  • Active hematological malignancies (acute leukemias, myelodysplastic syndromes, myeloproliferative neoplasms, lymphomas, myeloma) at any stage/status.
  • SARS-CoV-2 positive test (nasopharyngeal, BAL, fecal), documented by Real-Time Reverse Transcriptase (RT)-PCR Diagnostic Panels.

Exclusion Criteria:

  • Hematological diseases, other than hematological malignancies.
  • SARS-CoV-2 negative test.
Contacts and Locations
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Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04352556


Contacts
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Contact: Francesco Passamonti, MD +39-0332-393648 francesco.passamonti@asst-settelaghi.it
Contact: Marco Salvini, MD marco.salvini@asst-settelaghi.it

Locations
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Sponsors and Collaborators
Ospedale di Circolo - Fondazione Macchi
Investigators
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Principal Investigator: Francesco Passamonti, MD Ospedale di Circolo e Fondazione Macchi, ASST Sette Laghi, Varese, Italy
More Information
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Publications:

Publications automatically indexed to this study by ClinicalTrials.gov Identifier (NCT Number):
Visco C, Marcheselli L, Mina R, Sassone M, Guidetti A, Penna D, Cattaneo C, Bonuomo V, Busca A, Ferreri AJM, Bruna R, Petrucci L, Cairoli R, Salvini M, Bertù L, Ladetto M, Pilerci S, Pinto A, Ramadan S, Marchesi F, Cavo M, Arcaini L, Coviello E, Romano A, Musto P, Massaia M, Fracchiolla N, Marchetti M, Scattolin A, Tisi MC, Cuneo A, Della Porta M, Trentin L, Turrini M, Gherlinzoni F, Tafuri A, Galimberti S, Bocchia M, Cardinali V, Cilloni D, Corso A, Armiento D, Rigacci L, La Barbera EO, Gambacorti-Passerini C, Visani G, Vallisa D, Venditti A, Selleri C, Conconi A, Tosi P, Lanza F, Candoni A, Krampera M, Corradini P, Passamonti F, Merli F; ITA-HEMA-COV investigators. A prognostic model for patients with lymphoma and COVID-19: a multicentre cohort study. Blood Adv. 2022 Jan 11;6(1):327-338. doi: 10.1182/bloodadvances.2021005691.
Passamonti F, Cattaneo C, Arcaini L, Bruna R, Cavo M, Merli F, Angelucci E, Krampera M, Cairoli R, Della Porta MG, Fracchiolla N, Ladetto M, Gambacorti Passerini C, Salvini M, Marchetti M, Lemoli R, Molteni A, Busca A, Cuneo A, Romano A, Giuliani N, Galimberti S, Corso A, Morotti A, Falini B, Billio A, Gherlinzoni F, Visani G, Tisi MC, Tafuri A, Tosi P, Lanza F, Massaia M, Turrini M, Ferrara F, Gurrieri C, Vallisa D, Martelli M, Derenzini E, Guarini A, Conconi A, Cuccaro A, Cudillo L, Russo D, Ciambelli F, Scattolin AM, Luppi M, Selleri C, Ortu La Barbera E, Ferrandina C, Di Renzo N, Olivieri A, Bocchia M, Gentile M, Marchesi F, Musto P, Federici AB, Candoni A, Venditti A, Fava C, Pinto A, Galieni P, Rigacci L, Armiento D, Pane F, Oberti M, Zappasodi P, Visco C, Franchi M, Grossi PA, Bertù L, Corrao G, Pagano L, Corradini P; ITA-HEMA-COV Investigators. Clinical characteristics and risk factors associated with COVID-19 severity in patients with haematological malignancies in Italy: a retrospective, multicentre, cohort study. Lancet Haematol. 2020 Oct;7(10):e737-e745. doi: 10.1016/S2352-3026(20)30251-9. Epub 2020 Aug 13.

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Responsible Party: Francesco Passamonti, Principal Investigator, Ospedale di Circolo - Fondazione Macchi
ClinicalTrials.gov Identifier: NCT04352556    
Other Study ID Numbers: HM-COVID19-Italy
First Posted: April 20, 2020    Key Record Dates
Last Update Posted: May 18, 2021
Last Verified: May 2021
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No
Keywords provided by Francesco Passamonti, Ospedale di Circolo - Fondazione Macchi:
Hematological Malignancies
Covid-19
SARS-CoV-2
Italian Hematology Alliance
 Leukemia
Lymphoma
Multiple Myeloma
Additional relevant MeSH terms:
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Infections
COVID-19
Neoplasms
Hematologic Neoplasms
Respiratory Tract Infections
Pneumonia, Viral
Pneumonia
Virus Diseases
 Coronavirus Infections
Coronaviridae Infections
Nidovirales Infections
RNA Virus Infections
Lung Diseases
Respiratory Tract Diseases
Neoplasms by Site
Hematologic Diseases