SARS-CoV-2 Infection in Patients With Hematological Malignancies: the Italian Hematology Alliance
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 250
- 试验地点
- 78
- 主要终点
- To evaluate mortality.
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Other
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •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.
排除标准
- •Hematological diseases, other than hematological malignancies.
- •SARS-CoV-2 negative test.
结局指标
主要结局
To evaluate mortality.
时间窗: At 2 months from study initiation
The percentage of HM patients with COVID-19 who died.
To evaluate potential predictive biochemical parameters of mortality.
时间窗: 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.
To evaluate COVID severity as predictive parameter of mortality.
时间窗: 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
To evaluate potential predictive HM-related parameters of mortality.
时间窗: 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.
次要结局
- Evolution of HM(At 2 months from study initiation)
- To evaluate admission to ICU requiring mechanical ventilation or death per characteristics(At 2 months from study initiation)
- Epidemiology of patients with HM infected by SARS-CoV-2with any spectrum of illness severity(At 6 months from study initiation)
- Definition of complete clinical picture of COVID-19 in HM(At 2 months from study initiation)
- Viral dynamics in infected HM patients(At 12 months from study initiation)
研究者
Francesco Passamonti
Principal Investigator
Ospedale di Circolo - Fondazione Macchi