Mortality and prognostic Factors in COVID-19 Patients with Hematologic Malignancies: A Retrospective Cohort Study in two Syrian centers

doi:10.21203/rs.3.rs-4944463/v1

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Research Article

Mortality and prognostic Factors in COVID-19 Patients with Hematologic Malignancies: A Retrospective Cohort Study in two Syrian centers

https://doi.org/10.21203/rs.3.rs-4944463/v1

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Background

Patients with hematologic malignancies (HM) have poor outcomes from coronavirus disease (COVID-19), but data are limited, especially from low-income regions. This study analyzed mortality rates, clinical outcomes, and prognostic factors associated with COVID-19 infection in HM patients in Syria.

Methods

This retrospective cohort study enrolled 150 HM patients aged 16–78 years with confirmed COVID-19 at two hospitals in Damascus during 2021–2022. Patients were diagnosed based on RT-PCR or clinical/radiological findings with Chest computed tomography (CT) scans being the primary diagnostic modality. Data on demographics, cancer type, symptoms, comorbidities, CT findings, and outcomes were collected through medical records.

Results

The median age was 52.68 (± 18.49) years, with 64% of patients’ ≥50 years old. Acute lymphoblastic leukemia (18%) and acute myeloid leukemia (16.7%) were the most common HM types. The overall mortality rate was 61.4%. Mortality was significantly associated with older age (p = 0.001), cancer type (100% for acute leukemias, p = 0.001), Presence of dyspnea, cough, or digestive symptoms (p = 0.001), severe CT lung infiltrates (p = 0.001), and Pre-existing medical conditions (p = 0.001). Nearly, 37.3% of patients required ICU admission. All patients with non-Hodgkin's lymphoma survived, while all acute leukemia patients died.

Conclusion

Advanced age, specific cancer types, symptomatic presentation, CT severity, and presence comorbidities were identified as prognostic factors for COVID-19 mortality in HM patients. These high-risk patients warrant vigilant screening and preventive measures. Additional research is urgently needed to guide protection and clinical management in this vulnerable population.

Oncology

Hematology

Virology

Hematological malignancies

COVID-19

Mortality

Risk factors

Cohort study

A new coronavirus called SARS-CoV-2 emerged in Wuhan, China, in late 2019 (1, 2). This led to a disease known as COVID-19, which caused severe symptoms such as fever, respiratory problems, and lung damage. The World Health Organization declared it a pandemic on March 11, 2020, and it spread worldwide, resulting in over 3 million deaths that year. Elderly individuals and those with underlying health conditions such as diabetes, hypertension, and heart problems are more likely to experience severe COVID-19 infections (3, 4). Cancer patients also face a higher risk of adverse outcomes, such as ICU admission, mechanical ventilation, or death, compared to non-cancer patients (5). Approximately 2% of COVID-19 cases involve individuals with cancer, and 3.7% of patients exhibit signs of a compromised immune system (6–8). The increased risk observed in cancer patients with COVID-19 can be attributed to factors such as immunosuppression caused by ongoing chemotherapy, radiotherapy, or immunosuppressive medications, as well as the presence of additional medical conditions or lung infiltration by the primary tumor or its metastases (5). Patients with hematological malignancies may be particularly vulnerable due to compromised immune system functionality (5).

The aim of this study is to assess the impact of COVID-19 infection on the clinical progression and overall survival of patients with malignant hematological diseases and to identify factors that may contribute to mortality among these patients. To our knowledge, this study is the first of its kind in Syria.

Study Design and participants:

We conducted a retrospective cohort study in two hospitals, namely Al-Assad and Al-Mouwasat University hospitals, situated in Damascus, Syria. The study spanned a duration of one year from 2021 to 2022. A total of 150 individuals, ranging from 16 to 78 years old, who had previously been diagnosed with hematological malignancies and were recently referred for further management, confirmed by laboratory, clinical, radiological, or nasopharyngeal swabs, were recruited for participation. The study excluded patients with non-hematologic cancers and those below the age of thirteen who had COVID-19.

Data collection and procedures:

Prior to initiating the study, cases were collected through departmental surveillance which flagged hematology patients who tested positive for SARS-CoV‐2 or who were suspected of having COVID‐19 based on evaluations in outpatient clinics and the emergency department. This diagnosis was established through either laboratory-confirmed results from a positive reverse-transcriptase polymerase chain reaction (RT-PCR) test on nasopharyngeal swab specimens or by relying on compelling clinical evidence. This evidence included radiologic features of pneumonia and symptoms resembling influenza-like illness, all without any identifiable cause other than COVID-19 even when testing for SARS-CoV-2 PCR yielded negative results. We categorized the patients based on disease severity using chest CT scans, which have been shown to be more sensitive than RT-PCR in detecting early lesions and assessing recovery according to previous studies. Therefore, we then collected relevant clinical and demographic information for each patient, including age, cancer type, respiratory and gastric symptoms (e.g. fever, dry cough, dyspnea, diarrhea), laboratory test results upon admission (ALT, AST, LDH, WBCs, lymphocytes), accompanied diseases, chest CT scan results, and whether the patient was hospitalized in an isolation ward or admitted for intensive care. After treatment, patients were classified into four outcome categories: Patients who showed clinical improvement, who achieved full recovery and were discharged, who deteriorated and died during hospitalization, and lastly who died shortly after admission.

Data Analysis:

Descriptive analysis encompassing frequency and percentage calculations was conducted on all study variables. Measures of central tendency, such as mean, standard deviation, and range, were employed for continuous variables. Furthermore, Chi-Square and T-test analyses were conducted to investigate relationships between the variables under study. For all purposes, statistical significance was determined as a p < 0.05. All analyses were performed using the Statistical Package for Social Sciences (SPSS) software version 25.

Ethics:

Prior to initiation, this study protocol underwent thorough review and received approval from the hospitals' ethics committee. In adherence with ethical principles, all patients were fully informed about the study. They were told that participation was voluntary and that they could withdraw at any time. We emphasized that refusing or accepting participation would not impact their medical care during hospitalization. Written informed consent was obtained from each participant before any study procedures were conducted. Throughout the study, we strictly followed the principles outlined in the Declaration of Helsinki and its amendments, as well as the Good Clinical Practice guidelines from the International Conference on Harmonization.

Sample Size:

The sample size of 150 participants was determined using the following formula to achieve a 95% confidence level with a margin of error not exceeding 5%. Where Z = Z-score for desired confidence level (1.96 for 95% confidence) and p = expected proportion or prevalence.

Sociodemographic characteristics, medical history, clinical/radiological findings, and outcomes of patients (Table 1):

The study enrolled a total of 150 patients, with a median age of 52.68 (± 18.49) years. The majority of participants (64%) were aged 50 years or older. The most prevalent cancer types among the patients were acute lymphoblastic leukemia (ALL), accounting for 18%, followed by acute myeloid leukemia (AML), accounting for 16.7%. Respiratory symptoms, particularly dry cough with dyspnea, were the most commonly reported, while only 4 patients (2.7%) experienced dyspnea accompanied by diarrhea. Analysis of thoracic CT scans revealed that 14 patients (9.3%) exhibited infiltrates reaching 80%, while the most frequently observed level of infiltrates (50%) was seen in 42 patients (28%). In terms of comorbidities, 67.3% of patients had no pre-existing conditions, while the remaining individuals had renal insufficiency (8.7%) or concurrent heart and kidney failure (6.7%). During hospitalization, approximately 62.7% of patients were admitted to the isolation ward, while 37.3% required intensive care unit (ICU) admission. Treatment outcomes varied, 13.3% of patients showed clinical improvement, 25.3% experienced full recovery and were subsequent discharge, 39.4% deteriorated and died during hospitalization, and 22% died shortly after admission. The nasopharyngeal swab results revealed that 52.7% of the patients tested negative for SARS-CoV-2, while 47.3% had positive test results.

Key associations:

The study findings revealed significant differences based on disease state and age. Specifically, the results indicated that the proportion of patients who died was higher among older individuals compared to younger age groups (p = 0.001) (Table 2.1).

Disease outcome also differed by hematological malignancy type. All patients with non-Hodgkin's lymphoma improved, while all patients with acute lymphoblastic leukemia, acute myeloid leukemia, and acute myeloid leukemia M4 deteriorated and died (p = 0.001) (Table 2.2).

Furthermore, Clinical symptoms were predictive of disease outcome. Patients presenting with shortness of breath, cough, or digestive symptoms died (p = 0.001) (Table 2.3). In addition, severity of infiltrates on CT scans correlated with disease outcome. Patients with high infiltrate levels deteriorated and died (p = 0.001) (Table 2.4). Lastly, disparities were observed in disease states based on the presence of accompanying medical conditions. Patients with pre-existing medical history did not exhibit improvement in their health status (p = 0.001) (Table 2.5).

The occurrence rate of COVID-19 infection among individuals with hematological malignancies (HM) varies from 1–3.9% (9). The high rates of illness and death related to COVID-19 in patients with HM, along with the additional difficulties caused by treatment delays or changes in chemotherapy schedules, pose significant obstacles for both patients and healthcare providers around the world, including Syria. Since randomized clinical trials were not feasible during the pandemic, observational studies can play a crucial role in helping us comprehend the various risk factors associated with COVID-19. These studies enable the implementation of suitable preventive measures and treatments more effectively in HM patients.

This study evaluated 150 hematology patients aged 16 to 78 years to determine their risk of acquiring COVID-19. It is important to highlight that in this sample, patients were mainly diagnosed with COVID-19 based on chest CT scan results, despite nearly half of them (52.7%) were negative for SARS-CoV-2 through RT-PCR laboratory tests. Several studies have demonstrated the high diagnostic accuracy of chest CT scans in identifying both typical and relatively atypical presentations of COVID-19, resulting in a minimal number of missed diagnoses (10). Additionally, research has shown that chest CT scans exhibit high accuracy in symptomatic patients suspected of having COVID-19 (11, 12). According to the previous literature, mild or asymptomatic presentations are common with COVID-19, with cough, fever, and dyspnea as the most frequent symptoms (13, 14). Likewise, the symptom profile in our hematologic malignancy cohort was dyspnea, being the most predominant, affecting 74% of patients - exceeding rates from prior studies in Italy (61%) and Turkey (33%) (15, 16). Meanwhile, less common symptoms such as diarrhea affected a smaller proportion (< 10%) of our hospitalized hematology patients, which is consistent with diarrhea rates reported in the general COVID-19 population (17). In contrast to general population studies that find 56–58% of infections to be asymptomatic, 100% of our cases were symptomatic (18).

During the COVID-19 pandemic, individuals with HM are considered to be at a higher risk due to factors such as inherent frailty, immunosuppressive treatments, and frequent hospital visits for treatment administration. In our research, we observed a mortality rate of 61.4% (92 out of 150 patients). This mortality rate is within the range of those reported in the literature among HM, ranging from 32–61% (9, 15, 19–22). Furthermore, a recent Italian study of 563 patients found that the mortality rate for patients with HM and COVID-19 was 41 times higher than for matched patients with hematological malignancies but without SARS-CoV-2 infection (20).

Our findings revealed a noteworthy correlation between patient age and the overall mortality rate, emphasizing that older individuals (those aged 50 years and above) with HM face a heightened risk of mortality. These results are consistent with previous studies (20, 23, 24). Moreover, a meta-analysis of 3,377 patients with HM and COVID-19 found that patients aged 60 years and older had a significantly higher risk of death than patients under 60 years, supporting our finding (25). This highlights the need of more protective measures in this group of age.

Furthermore, our data have revealed a profound clinical impact and the highest mortality rate among patients with acute leukemia, including AML (acute myeloid leukemia), ALL (acute lymphoblastic leukemia), and AML M4. Alarmingly, all patients in this subgroup succumbed to the infection. These findings align with previous studies (26–28), which reported increased morbidity and mortality associated with SARS-CoV-2 infection in individuals with acute HM, particularly AML. The high death rate in acute leukemia patients may stem from advanced age, profound immunodeficiency from disease and treatments, and the impossibility of delaying urgent therapy initiation. Delaying therapy has been suggested as a way to potentially improve COVID-19 survival in these patients, underscoring the need to balance competing health risks (26, 29). Notably, all 24 patients in our study with non-Hodgkin lymphoma survived, in contrast to the acute leukemia groups. This finding warrants further investigation to determine if non-Hodgkin lymphoma may confer a relatively lower mortality risk from COVID-19 versus other hematologic malignancies such as acute leukemias.

Moreover, we discovered higher mortality among those with more severe pulmonary infiltrate patterns on CT scans. This result aligns with other research linking abnormal radiographic findings and mortality, especially when ICU care is needed (16, 20). In our cohort, 37.3% required ICU admission. Regarding comorbid conditions, 67.3% of our patients had no pre-existing illnesses, with renal failure being the most common issue otherwise. This finding diverges from some literature indicating cardiovascular disease as the predominant COVID-19 comorbidity (19, 20). It is noteworthy that none of our hematology patients with underlying medical problems survived. However, Prior studies have conflicted on whether comorbidities influence COVID-19 mortality. Some studies (20) found no significant association, while others reported increased mortality risk with comorbidities (2, 16). Our findings suggest pre-existing conditions may contribute to poorer prognoses in HM patients infected with COVID-19.

In summary, the main findings of this study revealed that increased mortality rates were related to advanced age, severe infiltrates observed on CT scans, the presence of other medical conditions, and the specific type of HM. Ultimately, patients with HM still need special care, and protective measures must be maintained.

Strengths and limitations of the study:

This study represents the first investigation to examine the prevalence, risk factors, and outcomes among COVID-19 patients with hematological malignancies in Syrian population. Study limitations include missing data on cancer treatments and hematological malignancy details. Besides, the single-arm design prevented comparisons with non-COVID-19 hematologic cancer patients. Lastly, the relatively small sample size limits generalizability.

In conclusion:

This retrospective cohort study provides valuable real-world insights into the clinical characteristics and outcomes of COVID-19 infection in patients with hematologic malignancies. Our findings reveal a notably high mortality rate of 61.4% among 150 patients in Syria, highlighting the elevated risk faced by this population. Identifying key risk factors allows healthcare professionals to closely monitor patients, implement additional precautions, and make informed treatment decisions. Thorough COVID-19 screening and access to high-quality supportive care are crucial, given the unavailability of vaccines and antiviral treatments. It is imperative to prioritize preventive measures and maintain a vigilant approach in clinical practice. Continued research is essential for refining risk stratification and ensuring evidence-based care. Collaborative efforts across specialties and countries are necessary for addressing COVID-19 and comorbid conditions like hematologic cancers.

Hematological Malignancies

COVID-19

Coronavirus Disease 2019

RT-PCR

Reverse-Transcriptase Polymerase Chain Reaction

Computed Tomography

ICU

Intensive Care Unit

SARS-CoV-2

Severe Acute Respiratory Syndrome Coronavirus 2

ALL

Acute Lymphoblastic Leukemia

AML

Acute Myeloid Leukemia

ALT

Alanine Aminotransferase

AST

Aspartate Aminotransferase

LDH

Lactate Dehydrogenase

WBCs

White Blood Cells

SPSS

Statistical Package for Social Sciences

Authors' contributions:

Baraah Mohamad is the first author, contributed to drafting, data collecting and analyzing, reviewing and editing, corresponding, and bibliography.

Nafiza Martini is the second author, contributed to drafting, reviewing and editing, corresponding, and bibliography.
Majd Hanna contributed to drafting, reviewing and editing, corresponding, and bibliography.

Naji Alhamid, Ameen Sulaiman and Hussam Al bardan, contributed to reviewing, editing, and supervising.
All authors read and approved the final manuscript
Ethics approval and consent to participate:
The Ethical Committee approved this study in the Faculty of Medicine at Damascus University, Syria.

Availability of data and materials:

The datasets collected and analyzed during the current study are not publicly available. Some

restrictions apply to the availability of these data but are available from the corresponding

author on reasonable request.

Competing interests:

The authors declare no financial or non-financial conflicts of interest.

Funding:
Not applicable.

Provenance and peer review:
Not commissioned, externally peer-reviewed.

Acknowledgments:

We wish to show our appreciation to Stemosis for Scientific Research, a Syria-based scientific research youth association managed by Nafiza Martini, for the scientific environment they provided.

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Table1. Sociodemographic characteristics, medical history, clinical/radiological findings, and outcomes of HM patients with COVID-19

Variable	Sub-groups	frequency	Percentage
Age	Less than 30 years	29	19.3%
	From 30 to 50 years	25	16.7%
	50 years and above	96	64%
	Total	150	100%

Cancer type	CML	22	14.7%
	All	27	18%
	AML	25	16.7%
	AML M4	9	6%
	CLL	15	10%
	MDS	16	10.7%
	MM	12	8%
	Non-Hodgkin	24	16%
	Total	150	100%

Clinical symptoms	Digestive symptoms	10	6.7%
	Diarrhea/abdominal pain	9	6.0%
	Dyspnea/Diarrhea	4	2.7%
	Dyspnea/cough	107	71.3%
	Dry cough	20	13.3%
	Total	150	100%

CT scan Infiltrates	Infiltrate 20%	17	11.3%
	Infiltrate 30%	45	30%
	Infiltrate 40%	8	5.3%
	Infiltrate 50%	42	28%
	Infiltrate 70%	24	16%
	Infiltrate 80%	14	9.3%
	Total	150	100%

Comorbidities	COPD, Cardiac ischemia	5	3.3%
	Cirrhosis, renal failure	4	2.7%
	Atrial fibrillation, cardiac failure	4	2.7%
	Diabetes	4	2.7%
	Diabetes, Hypertension	5	3.3%
	Cardiac failure	4	2.7%
	Cardiac & renal failure	10	6.7%
	Renal failure	13	8.7%
	No comorbidities	101	67.3%
	Total	150	100%

Treatment	Isolation ward	94	62.7%
	Intensive care unit	56	37.3%
	Total	150	100%

PCR Result	Negative	79	52.7%
	Positive	71	47.3%
	Total	150	100%

Outcome	Improvement	20	13.3%
	Recovery and discharge	38	25.3%
	Died during hospitalization	59	39.4
	Died upon admission	33	22%
	Total	150	100%

Table 2.1, Relationship between outcome and age in HM patients with COVID-19.

Age		Outcome				Chi-Square	P-Value
Age		Clinical Improvement	Discharge	Death during Hospitalization	Death shortly after admission	Chi-Square	P-Value
Less than 30	Frequency	0	0	16	13	-0.270	0.001
Less than 30	percentage	0.0%	0.0%	27.1%	39.4%
From 30 to 50	Frequency	12	0	9	4
From 30 to 50	percentage	60.0%	0.0%	15.3%	12.1%
50 or above	Frequency	8	38	34	16
50 or above	Percentage	40.0%	100.0%	57.6%	48.5%
Total	Frequency	20	38	59	33
Total	Percentage	100.0%	100.0%	100.0%	100.0%

Table2.2, Relationship between outcome and blood cancer types in HM patients with COVID-19.

Blood Cancer types		Outcome				Chi-Square	P_Value
Blood Cancer types		Clinical Improvment	Discharge	Death during hospitalization	Death shortly after admission	Chi-Square	P_Value
CML	Frequency	0	4	14	4	231.371	0.001
CML	النسبة المئوية	0.0%	10.5%	23.7%	12.1%
ALL	Frequency	0	0	19	8
ALL	percentage	0.0%	0.0%	32.2%	24.2%
AML	Frequency	0	0	12	13
AML	percentage	0.0%	0.0%	20.3%	39.4%
AMLM4	Frequency	0	0	9	0
AMLM4	percentage	0.0%	0.0%	15.3%	0.0%
CLL	Frequency	0	10	5	0
CLL	percentage	0.0%	26.3%	8.5%	0.0%
MDS	Frequency	0	8	0	8
MDS	percentage	0.0%	21.1%	0.0%	24.2%
MM	Frequency	0	12	0	0
MM	percentage	0.0%	31.6%	0.0%	0.0%
Non-Hodgkin Lymphoma	Frequency	20	4	0	0
Non-Hodgkin Lymphoma	percentage	100.0%	10.5%	0.0%	0.0%
Total	Frequency	20	38	59	33
Total	percentage	100.0%	100.0%	100.0%	100.0%

Table 2.3, Relationship between outcome and clinical symptoms in HM patients with COVID-19.

Clinical Symptoms		Outcome				Chi-Square	P_Value
Clinical Symptoms		Clinical Improvement	Discharge	Death during hospitalization	Death shortly after admission	Chi-Square	P_Value
Digestive symptoms	Frequency	0	0	5	5	79.063	0.001
Digestive symptoms	Percentage	0.0%	0.0%	8.5%	15.2%
Diarrhea/abdominal pain	Frequency	0	9	0	0
Diarrhea/abdominal pain	Percentage	0.0%	23.7%	0.0%	0.0%
Dyspnea/ Diarrhea	Frequency	4	0	0	0
Dyspnea/ Diarrhea	Percentage	20.0%	0.0%	0.0%	0.0%
Dyspnea/cough	Frequency	12	21	54	20
Dyspnea/cough	Percentage	60.0%	55.3%	91.5%	60.6%
Dry cough	Frequency	4	8	0	8
Dry cough	Percentage	20.0%	21.1%	0.0%	24.2%
Total	Frequency	20	38	59	33
Total	Percentage	100.0%	100.0%	100.0%	100.0%

Table2.4, Relationship between outcome and CT-scan infiltrates in HM patients with COVID-19.

CT-Scan Infiltrates		Outcome				Chi-Square	P_Value
CT-Scan Infiltrates		Clinical improvement	Discharge	Death during hospitalization	Death shortly after admission	Chi-Square	P_Value
Infiltrate 20%	Frequency	4	13	0	0	109.499	0.001
Infiltrate 20%	Percentage	20.0%	34.2%	0.0%	0.0%
Infiltrate 30%	Frequency	8	25	8	4
Infiltrate 30%	Percentage	40.0%	65.8%	13.6%	12.1%
Infiltrate 40%	Frequency	4	0	4	0
Infiltrate 40%	Percentage	20.0%	0.0%	6.8%	0.0%
Infiltrate 50%	Frequency	4	0	22	16
Infiltrate 50%	Percentage	20.0%	0.0%	37.3%	48.5%
Infiltrate 70%	Frequency	0	0	15	9
Infiltrate 70%	Percentage	0.0%	0.0%	25.4%	27.3%
Infiltrate 80%	Frequency	0	0	10	4
Infiltrate 80%	Percentage	0.0%	0.0%	16.9%	12.1%
Total	Frequency	20	38	59	33
Total	Percentage	100.0%	100.0%	100.0%	100.0%

Table 2.5, Relationship between outcome and comorbidities in HM patients with COVID-19.

Comorbidities		Outcome				Chi-Square	P_Value
Comorbidities		Clinical Improvement	Discharge	Death during Hospitalization	Death shortly after admission	Chi-Square	P_Value
Presence of comorbidities	Frequency	0	0	33	16	46.412	0.001
Presence of comorbidities	Percentage	0.0%	0.0%	55.9%	48.5%
No comorbidities	Frequency	20	38	26	17
No comorbidities	Percentage	100.0%	100.0%	44.1%	51.5%
Total	Frequency	20	38	59	33
Total	Percentage	100.0%	100.0%	100.0%	100.0%

The authors declare no competing interests.

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Mortality and prognostic Factors in COVID-19 Patients with Hematologic Malignancies: A Retrospective Cohort Study in two Syrian centers

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Abstract

Background

Methods

Results

Conclusion

Background

Methods and Materials

Study Design and participants:

Data collection and procedures:

Data Analysis:

Ethics:

Sample Size:

Results

Sociodemographic characteristics, medical history, clinical/radiological findings, and outcomes of patients (Table 1):

Key associations:

Discussion

Strengths and limitations of the study:

In conclusion:

Abbreviations

Declarations

References

Tables

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