"Outcomes of COVID-19 infection in patients with hematological malignancies- A multicenter analysis from Pakistan".

PURPOSE: COVID-19 infection resulting from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began to spread across the globe in early 2020. Patients with hematologic malignancies are supposed to have an increased risk of mortality from coronavirus disease of 2019 (COVID-19) infection. From Pakistan, we report the analysis of the outcome and interaction between patient demographics and tumor subtype and COVID-19 infection and hematological malignancy. PATIENTS AND METHODS: This multicenter, retrospective study included adult patients with a history of histologically proven hematological malignancies who were tested positive for COVID-19 via PCR presented at the oncology department of 5 tertiary care hospitals in Pakistan from February to August 2020. A patient with any known hematological malignancy who was positive for COVID-19 on RT-PCR, was included in the study. Chi-square test and Cox-regression hazard regression model was applied considering p ≤ 0.05 significant.
RESULTS: A total of 107 patients with hematological malignancies were diagnosed with COVID-19, out of which 82 (76.64%) were alive, and 25 (23.36%) were dead. The significant hematological malignancy was B-cell Lymphoma in dead 4 (16.00%) and alive group 21 (25.61%), respectively. The majority of the patients in both the dead and alive group were on active treatment for hematological malignancy while they came positive for COVID-19 [21 (84.00%) & 48 (58.54%) p 0.020]. All patients in the dead group were admitted to the hospital 25 (100.00%), and among these, 14 (56.00%) were admitted in ICU with a median 11 (6-16.5) number of days. Among those who had contact exposure, the hazard of survival or death in patients with hematological malignancies and COVID-19 positive was 2.18 (CI: 1.90-4.44) times and 3.10 (CI: 2.73-4.60) times in patients with travel history compared to no exposure history (p 0.001).
CONCLUSION: Taken together, this data supports the emerging consensus that patients with hematologic malignancies experience significant morbidity and mortality resulting from COVID-19 infection.

Introduction

The SARS-Cov-2 or COVID-19, known as novel coronavirus, has become a global threat and healthcare concern. Since its outbreak in China at the end of 2019, the pandemic has affected more than 100 million people worldwide [1]. Although the outbreak is likely to have started from a zoonotic spread, it soon became apparent that person-to-person transmission occurs mainly through respiratory droplets and direct contact with a diseased person or indirect contact with fomites in the environment [2, 3]. Many people have mild symptoms. In contrast, others have no symptoms at all but still, actively carry and transmit the virus. However, some do develop severe symptoms such as respiratory failure, cytokine release syndrome, and multi-organ failure [4].

Since COVID-19 began to spread across the globe in early 2020, patients with comorbidities and cancer are more susceptible to marked complications of viral infection. Cancer patients are more prone to increased risk of infections than individuals without cancer because of immunosuppression by the malignancy itself and anticancer treatments, such as chemotherapy or surgery [5, 6] and have a poorer prognosis. Cao et al. have reported that patients with metastatic disease, hematological malignancy, or lung cancer are at particularly high risk of severe complications, requiring intensive care unit (ICU) admission, invasive mechanical ventilation, and even death. Furthermore, active treatment such as surgery and immunotherapy is associated with a significantly increased risk (hazard ratios of 6.22 and 4.82) respectively, for poor outcomes [7], Zhang et al. reported a higher rate of adverse events (53.6%) and mortality (28.6%) in those who had their last anti-tumor treatment within 14 days of the infection (HR = 4.079, 95% CI 1.086–15.322, P = 0.037). We do know that patients with hematological malignancies can have an underlying immune dysfunction and are vulnerable to viral and other infections [9]. Additionally, treatments which include cytotoxic agents, immunomodulators, hematopoietic stem cell transplantation, and chimeric antigen receptor T-cell therapy, are profoundly immunosuppressive. In addition, patients with hematologic malignancies have multiple risk factors of particular concern in the context of COVID-19 infection such as advanced age, underlying or treatment-induced comorbid illnesses like hypertension and diabetes, and chronic lymphopenia. These factors make this patient population particularly susceptible to an adverse outcome.

Public health measures are universally instituted to control the disease spread and aim to decrease preventable hospital admissions. In addition, it is recommended that patients receiving anticancer treatment should have vigorous screening for COVID-19 [8]. However, cancer care encompasses a diverse array of primary tumor types and stages, affecting all age groups of patients, with different prognosis and outcomes. Therefore, labeling all patients with cancer as susceptible to COVID-19 is probably neither reasonable nor informative.

For patients with hematologic malignancies, the overall risk of morbidity and mortality resulting from COVID-19 infection, as well as how this risk varies as a function of age, disease status, type of malignancy, and cancer therapy is being studied [9]. However, data from low- and middle-income countries is sparse. It is hypothesized that lower rates of testing and contact tracing and dearth of medical facilities adequately equipped to manage complicated covid infections can potentially result in higher morbidity and mortality in this high-risk population.

From Pakistan, we report the analysis of the interaction between patient demographics and tumor subtype and COVID-19 infection and outcomes in patients with hematological malignancy. This is a multicenter analysis from five tertiary care hospitals in Pakistan, all of whom have an established cancer center.

Materials and methods

We retrospectively collected data on all the patients with a history of histologically proven hematological malignancies that tested positive for COVID-19 by RT-PCR and present at the oncology department of 5 tertiary care hospitals in Pakistan: Aga Khan University Hospital Karachi, Armed Forces Bone Marrow Transplant Centre Rawalpindi, Hameed Latif Hospital Lahore, Shifa International Hospital Islamabad, and Shaukat Khanum Memorial Cancer Hospital Lahore from February to August 2020. Data was collected using a standard Performa developed for this study. Demographic, clinical, treatment, and laboratory data and serial samples for viral RNA detection were extracted from the medical records of 107 patients.

Patient with any known hematological malignancy who was positive for COVID-1f on RT-PCR was included in the study. Patients with a clinical or radiological diagnosis of COVID-19 without a positive RT-PCR test, were not included in this analysis.

Operational definition

Leukemia is cancer of the body’s blood-forming tissues, including the bone marrow and the lymphatic system [10].

Lymphoma is a cancer of the lymphatic system, which is part of the body’s germ-fighting network. The lymphatic system includes the lymph nodes (lymph glands), spleen, thymus gland, and bone marrow [11].

Multiple myeloma is a cancer of plasma cells. Normal plasma cells are found in the bone marrow and are an important part of the immune system [12].

Myelodysplastic syndromes (MDS) are conditions that can occur when the blood-forming cells in the bone marrow become abnormal. This leads to low numbers of one or more types of blood cells [12].

Clinical classification of suspected or confirmed COVID-19 patients in Pakistan

Asymptomatic SARS CoV-2 infection but with no symptoms. Some asymptomatic patients may be pre-symptomatic if tested early (e.g., as part of contact tracing) [13].

Non-Severe Oxygen saturation of 94% or greater and respiratory rate of less than 25 breaths/minute [14].

Severe Oxygen saturation < 94% and respiratory rate greater than 25 breaths/minute.

Oxygen saturation is maintained by nasal cannulation or simple facemask, no need for non-invasive or invasive mechanical ventilation [14].

Critical Respiratory compromise severe enough requiring invasive and non-invasive mechanical ventilation [13].

Variables

Age, Sex, Hospital, Co-morbidities, Hematological malignancy, treatment, chemotherapy, COVID-19 exposure, presenting complaint, hospital admission, COVID-19 status at death or discharge were the covariates.

Outcome

Mortality—the number of deaths in patients with hematological malignancy diagnosed with COVID-19 infection.

Statistical analysis

The data was entered and analyzed by using STATA version 16. Calculated medians for all continuous skewed variables. The normality of data was checked through density plots—frequencies with percentages for categorical variables. A Chi-square test was performed to check the association between the covariates and mortality. For survival analysis, a multivariable Cox-regression hazard regression model was applied, and the Kaplan Meir survival curve was used to check the overall survival. P-value ≤0.05 was considered significant.

Ethical approval

Ethical approval was obtained from the Ethical Review Committee of the Aga Khan University Hospital, Karachi, Pakistan. Data were retrospectively collected through chart review, so there was no need for the informed written consent.

Results

Baseline characteristics

A total of 107 patients with hematological malignancies were diagnosed with COVID-19, out of which 82 (76.64%) were alive, and 25 (23.36%) were dead. Among the dead, 12 (48.00%) of the participants were greater than 50 years of age (p 0.027). Most of the participants were males in both the dead and alive group [18 (72.00%) & 54 (68.85%)]. Hypertension was the common comorbidity in both groups [8 (32.00%) & 8 (9.76%) p 0.021]. The significant hematological malignancy was B-cell Lymphoma in dead 4 (16.00%) and alive group 21 (25.61%), respectively (Table 1). The majority of the patients in both the dead and alive group were on active treatment for hematological malignancy while they came positive for COVID-19 [21 (84.00%) & 48 (58.54%) p 0.020]. IV chemotherapy was the common treatment 15 (71.43%) from the dead group, and 29 (61.70%) in the alive group received IV chemotherapy moreover Idarubicin + cytarabine was the common IV chemo-regimen given to patients in both groups [5 (23.81%) & 5 (12.20%)] (Table 2). The presenting complaint in patients with hematological malignancies who catch COVID-19 among the dead group were fever (52.00%) followed by respiratory symptoms 11 (44.00%). However, in the alive group, 18 (21.95%) were asymptomatic, 22 (26.83) presented with fever, 33 (40.24%) presented with respiratory symptoms (p 0.029). There was a contact exposure in 3 (12.00%) and travel history in 8 (32.00%) of patients in the dead group while 13 (15.85%) had contact exposure and 9 (10.98%) had travel history among the alive group (p 0.042). All patients in the dead group were admitted in the hospital 25 (100.00%) and among these, 14 (56.00%) were admitted in ICU with a median 11 (6–16.5) number of days while 24 (29.27%) alive patients were admitted to hospital and only 4 (4.88%) admitted in ICU (p <0.001). At discharge or death, 4 (16.00%) dead patients were COVID positive, and 30 (36.59) alive patients were positive (p 0.008) (Table 3).

Table 1

Baseline and clinical characteristics of patients with hematological malignancies and COVID-19 stratified on the outcome (n = 107).

Characteristic	Outcome n (%)		P-value
	Dead [25 (23.36%)]	Alive [82 (76.64%)]
Age (years)			0.027
10–30	7 (28.00)	34 (41.46)
31–50	6 (24.00)	31 (37.80)
>50	12 (48.00)	17 (20.73)
Sex			0.566
Male	18 (72.00)	54 (68.85)
Female	7 (28.00)	28 (34.15)
Hospital			0.012
AKUH	8 (32.00)	9 (10.98)
SKMCH	6 (24.00)	48 (58.54)
Shifa Hospital	6 (24.00)	16 (19.51)
AFBMTC	5 (20.00)	7 (8.54)
HLH	0 (0.00)	2 (2.44)
Co-morbidities			0.021
None	8 (32.00)	50 (60.98)
HTN	8 (32.00)	8 (9.76)
Diabetes	2 (8.00)	7 (8.54)
Other	7 (28.00)	17 (20.73)
Malignancy			0.222
ALL	3 (12.00)	11 (13.41)
AML	7 (28.00)	6 (7.32)
CML	1 (4.00)	4 (4.88)
CLL	2 (8.00)	5 (6.10)
Hodgkins	2 (8.00)	17 (20.73)
B- cell lymphoma	4 (16.00)	21 (25.61)
T- cell lymphoma	1 (4.00)	3 (3.66)
Others	5 (20.00)	15 (18.29)

Table 2

Treatment and management of patients with hematological malignancies and COVID-19 stratified on outcome (n = 107).

Characteristic	Outcome		P-value
	Dead [25 (23.36%)]	Alive [82 (76.64%)]
Active treatment			0.020
Yes	21 (84.00)	48 (58.54)
No	4 (16.00)	34 (41.46)
Treatment			0.797
Chemoimmunotherapy	5 (23.81)	13 (27.66)
IV chemotherapy	15 (71.43)	29 (61.70)
TKI	1 (4.76)	4 (8.51)
Radiation	0 (0.00)	1 (2.13)
Chemo regimen			0.551
R-CHOP	2 (9.52)	7 (17.07)
R- Bendamustine	0 (0.00)	2 (4.88)
R-ICE	1 (4.76)	2 (4.88)
R-CEOP	0 (0.00)	1 (2.44)
R-EPOCH	1 (4.76)	1 (2.44)
Rituximab	1 (4.76)	0 (0.00)
CVP	0 (0.00)	1 (2.44)
Idarubicin + cytarabine	5 (23.81)	5 (12.20)
BFM protocol	1 (4.76)	3 (7.32)
HyperCVAD	4 (19.05)	5 (12.20)
ABVD	3 (14.29)	7 (17.07)
Bendamustine	0 (0.00)	2 (4.88)
VRD	3 (14.29)	1 (2.33)
Cyclophoshamide +bortezomib	0 (0.00)	2 (4.88)
Lenalodomide + carfilzomib	0 (0.00)	2 (4.88)

Table 3

COVID-19 exposure and status at death/discharge among hematological malignancies patients stratified on outcome (n = 107).

Characteristic	Outcome		P-value
	Dead [25 (23.36%)]	Alive [82 (76.64%)]
Presenting complaint			0.029
Fever	13 (52.00)	22 (26.83)
Respiratory symptoms	11 (44.00)	33 (40.24)
GI symptoms	1 (4.00)	4 (4.88)
Other	0 (0.00)	5 (6.10)
Asymptomatic	0 (0.00)	18 (21.95)
COVID-19 exposure			0.042
No	14 (56.00)	60 (73.17)
Contact exposure	3 (12.00)	13 (15.85)
Travel	8 (32.00)	9 (10.98)
Hospital admission			<0.001
No	0 (0.00)	58 (70.73)
Yes	25 (100.00)	24 (29.27)
In hospital stay			<0.001
No admission	0 (0.00)	58 (70.73)
Ward	5 (20.00)	16 (19.51)
SCU	6 (24.00)	4 (4.88)
ICU	14 (56.00)	4 (4.88)
If yes, Number of days			0.003*
(Median, IQR)	11 (6–16.5)	0 (0–4)
Recovered & discharged			<0.001
No	25 (0.00)	2 (2.44)
Yes	0 (0.00)	35 (42.68)
Home isolation	0 (0.00)	45 (54.88)
COVID status at death/discharge			0.008
Not done	9 (36.00)	37 (45.12)
Negative	12 (48.00)	15 (18.29)
Positive	4 (16.00)	30 (36.59)

Overall survival and multivariable regression

The median overall survival among patients with hematological malignancies and COVID-19 positive was 33 (IQR 15–60) days (Fig 1). Upon applying multivariable Cox-proportional hazard regression, age (categorical), malignancy treatment, COVID-19 exposure, and COVID-19 status at death or discharge were significant (Table 4). The hazard ratio of survival or death in patients with hematological malignancies and COVID-19 positive in the age group 10–30 years was 1.81 times (CI: 1.40–2.72) and 1.22 times among age group 31–50 years (CI: 1.14–2.00) compared to age greater than 50 years (p 0.019). The hazard ratio of survival or death in patients with hematological malignancies and COVID-19 positive in patients receiving IV chemotherapy was 1.51 (CI: 1.26–2.47) times and 1.46 times who received chemoimmunotherapy (CI: 1.30–2.39) compared to those who received TKI (p 0.031). Among those who had contact exposure, the hazard of survival or death in patients with hematological malignancies and COVID-19 positive was 2.18 (CI: 1.90–4.44) times and 3.10 (CI: 2.73–4.60) times in patients with travel history compared to no exposure history (p 0.001). Moreover, the hazards were higher in patients who did not test for COVID or were positive at discharge or death 2.28 (CI: 1.43–5.63) and 3.41 (CI: 2.12–6.38) compared to those who were negative at discharge or death (p 0.001).

Fig 1

Graph representing overall survival in patients with hematological malignancies and COVID-19.

Table 4

Univariate and multivariable Cox-proportional hazard model reporting crude and adjusted ratios (n = 107).

Characteristic	Crude HR (95% CI)	p-value	Adjusted HR (95% CI)	p-value
Age (years)
>50	1		1
10–30	1.91 (1.84–2.37)	0.081*	1.81 (1.40–2.72)	0.019
31–50	1.17 (1.03–1.56)		1.22 (1.14–2.00)
Sex
Female	1	0.107*	-	-
Male	1.84 (1.38–3.05)
Active treatment
Yes	1	0.596	-	-
No	1.19 (0.61–2.33)
Treatment
TKI	1		1
IV chemotherapy	1.19 (1.05–2.85)	0.084*	1.51 (1.26–2.47)	0.031
Chemoimmunotherapy	1.36 (1.10–3.50)		1.46 (1.30–2.69)
COVID-19 exposure
No	1		1
Contact exposure	1.49 (1.19–3.17)	0.058*	2.18 (1.90–4.44)	0.001
Travel	1.77 (1.61–5.12)		3.10 (2.73–4.60)
Hospital admission
No	1
Yes	1.16 (0.62–2.20)	0.628	-	-
COVID status at death/discharge
Negative	1		1
Not done	1.80 (1.49–2.38)	0.024*	2.28 (1.43–5.63)	0.001
Positive	1.88 (1.58–4.16)		3.41 (2.12–6.38)

Discussion

Worldwide, healthcare systems are in an uphill task of dealing with the COVID-19 pandemic, a situation that is going to remain a challenge to all clinicians. The incidence of COVID-19 and outcomes in cancer patients is a topic of great interest. It is evident now that the COVID-19 will be a global health care issue for the foreseeable future, and it is imperative that clinicians understand the complexity of presentations and outcomes of patients with concomitant health issues that make them vulnerable to severe complications. Our study has mainly focused on outcomes of COVID-19 with hematological malignancies in a resource-constrained environment, and it’s the first multicenter analysis from Pakistan.

American Society for Hematology (ASH) Research Collaborative COVID-19 Registry analysis states that patients with hematologic malignancies have higher mortality resulting from COVID-19 than in the general population. They reported an overall mortality of 28%, increasing to 42% in patients with moderate to severe infection [15-17]. However, in the general population, it ranges from 9–29.6%. In the white Hispanic group, the mortality was less than 10%, while in Black and Hispanic groups, it was less than 30% in the general population [18]. Recently published study from Italy stated mortality of 37% patients with hematological malignancy and COVID-19, with higher risk amongst those with older age, progressive disease, or severe infection [19, 20]. Another multicenter study, analyzing outcomes in cancer patients from China reported mortality of 20%, with 41% mortality in the 22 patients with hematologic malignancies [21]. UK Myeloma Forum published their results of 75 patients with COVID-19 and multiple myeloma, with mortality of 55% [22, 23]. In our study, the overall mortality mirrors the data of these studies with an overall mortality of 23% and increasing to approximately 51% in the hospitalized patients and 86% in ICU patients. 50% of deaths were seen in patients younger than 50 years. This is most likely due to the fact that approximately 70% of our patients were in that age group. Therefore, this is likely over-represented. It was interesting to note the relatively low numbers of patients of older age admitted to the hospital in our cohort. It could be hypothesized that treatment was deferred for the older patients with multiple co-morbidities in the initial months of the pandemic if they had a relatively stable clinical course. However, it would be interesting to study the outcomes of patients who had their treatment deferred.

Several other findings from our cohort are noteworthy. We analyzed the demographics of COVID-19 patients with hematological malignancy and explored the effect of cytotoxic chemotherapy and various chemoimmunotherapy and targeted treatments on the trajectory of COVID-19. The incidence of COVID-19 was found to be more frequent in acute leukemias (29%), followed by non-Hodgkin’s lymphoma (27%) and Hodgkin’s lymphoma (18%) [24]. Furthermore, an increase in mortality has been reported in myeloid malignancies (MDS/AML/MPN) than lymphoid neoplasms (NHL/CLL/ALL/MM/HL) (43% vs. 35%) [25, 26], which is similar to that seen in our study population. The majority of our study patients were on active treatment and reported a mortality rate of 19.6%, in contrast to 10% among patients on surveillance. Interestingly a higher mortality rate (14%) was seen in patients receiving chemotherapy alone compared to a 4.6% receiving chemoimmunotherapy.

The most common COVID-19–specific therapies in our dataset were symptomatic treatment with steroids and anticoagulation, tocilizumab (6.5%), remdesivir (2.8%), hydroxychloroquine (3.7%). The use of tocilizumab and remdesivir in our cohort as low compared to other studies [10]. One reason is that our data collection started in the early days of the pandemic when these drugs were not used regularly. Additionally, the availability of the drugs was sparse until the mid of 2020. Remdisivir was given emergency use authorization in May 2020 and gained full FDA approval in October 2020. It only then has this drug become widely available for use.

Morbidity rates from COVID-19 in patients with cancer admitted to the hospital are high, particularly in older patients and those with hematological malignancies. But not all cancer patients are affected equally. These findings allow clinicians to risk-stratify their patients; whether symptomatic or not, and make decisions on social isolation and shielding at appropriate levels. Our data and many other studies demonstrate that patients with hematological malignancies, particularly acute leukemias, are at high risk for severe COVID-19 infection and mortality. Therefore, preemptive testing, early recognition of infections, and prompt management at a facility with expertise to manage complications are paramount. In addition, protective measures such as universal masks, social distancing, and shielding this susceptible population from COVID-19 exposure are mandatory. Many sites have implemented telemedicine to on-site physical distancing, and these practices should continue if COVID-19 prevalence remains high.

Our study has some limitations. Our analyses are based on patients with hematological malignancy who sought help from centers receiving their treatment. Therefore, this cohort did not capture the outcomes of patients who presented for management at a different hospital. This is particularly true for patients who live in cities or towns and most likely obtained treatment closer to home. Also, we likely missed patients on long-term follow-up who approached their local general physician (GP) or hospital. We, too, were unable to capture asymptomatic patients and found to have COVID-19 positive on screening. In addition, patients on hospice care were not reported or included in this study. Therefore, it is impossible to accurately quantify the burden of infection in patients with hematological malignancy.

Nonetheless, this dataset provides a glimpse of outcomes of patients who presented to a tertiary care hospital in Pakistan where both states of art management for covid infection and the primary malignancy was available. The majority of our patients were on active treatment, and these results help prognosticate; patients who require intensive care carry a very grim prognosis. Data such as ours are especially important in formulating country/region region-specific guidelines regarding the management of covid infections in a specific subset of patients. This is important in guiding management decisions when resources are limited and medical care is not covered by private insurance.

The expertise in managing COVID-19 infection has evolved over the last year. Early use of dexamethasone, remdesivir, and anticoagulation has improved outcomes.

Conclusion

In summary, this study of patients with hematological malignancy and COVID-19 accentuates several significant considerations for clinical care and emphasizes the urgent need for more data. Longer-term follow-up and larger sample sizes are needed to understand the effect of SARS-CoV-2 on outcomes in patients with hematological malignancy.

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27 Dec 2021

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Reviewer #1: The authors investigated the outcome of patients with hematological malignancies and Covid-19 infection in a multicenter retrospective cohort in Pakistan. I agree with the authors, that more research in the management of patients with severe immune-suppression and Covid-19 infection is urgently needed.

The collected data in this study are scarce and do not allow any new conclusion.

Unfortunately, this study does not provide any new insights in the field of Covid-19 infection in patients with hematological malignancies.

Reviewer #2: The current study describes 107 patients with COVID-19 and HM retrospectively collected from Pakistan (multicenter). I suggest the following changes to the manuscript:

- Needs extensive English editing.

- What is the rationale for not starting the inclusion criteria from the day of the epidemic start and choosing almost a year after this to start?

- Include the methodology (test details) of the COVID-19 diagnosis.

- The methodology section lacks important details (definitions [disease, variables, outcomes, severity classifications] and detail the statistical analysis.

- Add details of COVID-19 severity and severity classification.

- I suggest including a univariable and a multivariable analysis on the mortality and including important predictors in these analyses.

Reviewer #3: In the manuscript, PONE-D-21-33433, Zaki et al reported the COVID-19 infection outcomes of 107 patients with history of hematological malignancies that were presented at the Oncology Department of 5 tertiary care hospitals in Pakistan from February 2020 to August 2020. The authors summarized the overall clinical outcome, the patient characteristics, clinical presentations, treatments administered, and mortality rate stratified by age, type of malignancy and oncological treatment status for COVID19 in patients with hematological malignancy.

Specific concerns:

1. The authors concluded that their data supports the emerging consensus that patients with hematologic malignancies experience significant morbidity and mortality resulting from COVID-19 infection. However, there is no matched control cases in this study to compare with.

2. No statistical significance (P value) was assessed in the mortality rate analyses.

3. The calculation of mortality rate in Table 2 is wrong, which is the reason why the mortality rate in each group is lower than the overall mortality rate of the study cohort (28%). For example, when stratified for age, the authors said the mortality rate was 7.4%, 5.6% and 10.2% in the age groups 10-30 years, 31-50 years, and 51-70 years respectively. However, the true death rate should be 19.5% (8/41), 17.6 (6/34), and 37.9% (11/29), respectively.

4. Table 1 should be divided into multiple tables.

5. It might be better to present the data in Table 2 by one or more figures.

6. There are sporadic grammar errors throughout the manuscript.

Reviewer #4: Peer-review report

Title: “Outcomes of COVID‐19 infection in patients with hematological malignancies- A multicenter analysis from Pakistan”

Manuscript number: PONE-D-21-33433

Reviewer comment

- Thank you for inviting me to review this paper. I congratulate the authors for writing this research article. Based on their study, the authors describe the outcome of COVID-19 infection in patients with hematological malignancy. However, the document needs revision in the methodology and analysis section before considering the paper for publication.

Abstract

- Please expand the term COVID-19 and SARS-CoV-2

- In the method part, explain how the data is and analyzed and presented

- Replace …‘from February 2020 to August 2020’ with … from February to August 2020’.

- Please spell out numbers when they occur at the beginning of a sentence.

- The authors said that mortality rate is high in patients aged 50 and above without putting any statistical indicator (e.g. p-value). Accordingly, the information seems invalid.

- The conclusion of the study support the knowledge in the existing literature, but it seems relevant to add recommendation. //

Introduction

-explained fairly.

Method

Needs major revision considering the following points

- Clear description of the study setting, study populations, eligibility criteria (inclusion and exclusion criteria), data collection procedure, operational definition (if applicable), and ethical approval of the study (even a little is stated in the declaration section).

- In the statistical analysis part, why the authors preferred to use median over mean? Do the authors check the distribution of the data?

- Similarly, the chi-square test is performed. However, it is unclear where they put the report of this test in the result part.

- With the existing data on your hand, you can consider identifying the factor (s) associated with the COVID-19 outcome (optional).

Result

-Revise based on previous comment on the analysis part. You have to put the chi-square (optional) and the p-value in the stratification of mortality table.

Discussion

-Be consistent on the use of the word COVID-19. You have written as covid 19, COVID-19,...

-Expand the term ASH

- At the end of the discussion part please give a separate sub-heading and label as ‘conclusion’. In this part you can put your conclusion and recommendation (s).

- Revise the lists of abbreviation

Reviewer #5: In this study, Zaki et al, carried out a multicenter, retrospective, cohort study including 107 patients (aged ≥14 years) with diagnosis of hematological malignancy admitted to 5 tertiary care hospitals with laboratory-confirmed and symptomatic COVID-19.

As the authors rightly point out, the value of the study lies in being the first multicenter analysis from Pakistan and aimed at investigating outcome of patients with hematological malignancies and COVID-19 in a context with limited health care resources.

The outcomes in COVID- 19 cancer patients is a topic of great interest, and for this reason, a deeper characterization of the study population is recommended. In particular, the author should specify:

- the duration of follow-up

- the criteria used to define the severity of COVID-19 at admission

- patients with progressive disease, remission or in active therapy

Although in this study, the overall mortality mirrors data from studies carried out in other countries, suggesting a high risk for severe COVID-19 infection and mortality also in these patients, the author should discuss results comparing data with:

- mortality estimates for COVID-19 in the general population, possibly according to sex and stratified for age

- mortality estimates for pre-covid cohort with hematological malignancies, possibly stratified according to sex, age, type of hematological malignancy.

In order to make data analysis clearer to readers, characteristics of the study population should be reported in a table, with information on age/age groups, sex, comorbidities, type of hematological malignancy, disease status and therapy, COVID-19 severity, referred for all patients, survivors and non-survivors. And the results should be discussed accordingly. In particular, the features of the cohort study can be compared according to COVID-19 severity and outcome

Although the sample size makes this study not sufficiently robust to assess events and risk factors that can predict death in this clinical setting, a deeper statistical analysis evaluating association with overall survival of variable such as age, sex, comorbidity, type and status of neoplasia, etc., would help to objectively characterize these patients

Reviewer #6: The article captures data from the real world but has certain limitations, some of which have been highlighted. The comparative mortality and hospitalization statistics in the general population without hematological malignancies should be mentioned for the reader to make a fair comparison. The English should be brushed up. Have edited some of the errors in the attached pdf, but there are more.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes: Zhijun Duan

Reviewer #4: No

Reviewer #5: No

Reviewer #6: Yes: Prantar Chakrabarti

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

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Submitted filename: PONE-D-21-33433_reviewer.pdf

Click here for additional data file.

16 Feb 2022

Response to comments

Reviewer #1: The authors investigated the outcome of patients with hematological malignancies and Covid-19 infection in a multicenter retrospective cohort in Pakistan. I agree with the authors, that more research in the management of patients with severe immune-suppression and Covid-19 infection is urgently needed.

The collected data in this study are scarce and do not allow any new conclusion.

Unfortunately, this study does not provide any new insights in the field of Covid-19 infection in patients with hematological malignancies.

Response: This is a first ever multicenter local study conducted in Pakistan, we are presenting the data that we have collected from different settings in Pakistan which represents the local population, and it is highly generalizable to the Cancer patients with COVID-19. The findings may not be new but significant for the country and reflects the patient’s outcomes in an LMIC.

Reviewer #2: The current study describes 107 patients with COVID-19 and HM retrospectively collected from Pakistan (multicenter). I suggest the following changes to the manuscript:

- Needs extensive English editing.

Response: We have made changes and corrected English errors. See track changes.

- What is the rationale for not starting the inclusion criteria from the day of the epidemic start and choosing almost a year after this to start?

Response: We have thought of this study since very beginning but as it is a multicenter study it took some time to get the permissions from Departmental and Institutional review boards for data collection and analysis.

- Include the methodology (test details) of the COVID-19 diagnosis.

Response: tested positive for COVID-19 by RT-PCR (page # 6 line # 16)

- The methodology section lacks important details (definitions [disease, variables, outcomes, severity classifications] and detail the statistical analysis.

Response: Added (page # 7 line # 18-23 page # 8 line # 1-25)

Operational definition

Disease

Leukemia is cancer of the body's blood-forming tissues, including the bone marrow and the lymphatic system

Lymphoma is a cancer of the lymphatic system, which is part of the body's germ-fighting network. The lymphatic system includes the lymph nodes (lymph glands), spleen, thymus gland and bone marrow.

Multiple myeloma is a cancer of plasma cells. Normal plasma cells are found in the bone marrow and are an important part of the immune system.

Myelodysplastic syndromes (MDS) are conditions that can occur when the blood-forming cells in the bone marrow become abnormal. This leads to low numbers of one or more types of blood cells.

- Add details of COVID-19 severity and severity classification.

Response:

Clinical classification of suspected or confirmed COVID-19 patients in Pakistan

Asymptomatic SARS CoV-2 infection but with no symptoms. Some asymptomatic patients may be pre-symptomatic if tested early (e.g. as part of contact tracing).

Non-Severe Oxygen saturation of 94% or greater and respiratory rate of less than 25 breaths/minute.

Severe Oxygen saturation < 94 % and respiratory rate greater than 25 breath/minute.

Oxygen saturation is maintained by nasal cannulation or simple facemask, no need for non-invasive or invasive mechanical ventilation.

Critical Respiratory compromise severe enough requiring invasive and non- invasive mechanical ventilation.

Variables

Age, Sex, Hospital, Co-morbidities, Hematological malignancy, treatment, chemotherapy, COVID-19 exposure, presenting complaint, hospital admission, COVID-19 status at death or discharge were the covariates.

Statistical analysis

The data was entered and analyzed by using STATA version 16. Calculated medians for all continuous variables and frequencies with percentages for categorical variables. Chi-square test was performed to check the association between the covariates and mortality. For survival analysis multivariable Cox-regression hazard regression model was applied and Kaplan Meir survival curve was used to check the overall survival. P-value ≤0.05 was considered significant.

I suggest including a univariable and a multivariable analysis on the mortality and including important predictors in these analyses.

Response: Univariable and a multivariable analysis on the mortality is done see page # 22 table 4

Reviewer #3: In the manuscript, PONE-D-21-33433, Zaki et al reported the COVID-19 infection outcomes of 107 patients with history of hematological malignancies that were presented at the Oncology Department of 5 tertiary care hospitals in Pakistan from February 2020 to August 2020. The authors summarized the overall clinical outcome, the patient characteristics, clinical presentations, treatments administered, and mortality rate stratified by age, type of malignancy and oncological treatment status for COVID19 in patients with hematological malignancy.

1.The authors concluded that their data supports the emerging consensus that patients with hematologic malignancies experience significant morbidity and mortality resulting from COVID-19 infection. However, there is no matched control cases in this study to compare with.

Response: Thanks for the comment. This is a retrospective observational study where we just have taken the data of patients with hematological malignancy and were COVID-19 positive. We can do matched case control study in future for comparison.

2. No statistical significance (P value) was assessed in the mortality rate analyses.

Response: Tables are revised. P-value added in the tables by applying chi-square.

3. The calculation of mortality rate in Table 2 is wrong, which is the reason why the mortality rate in each group is lower than the overall mortality rate of the study cohort (28%). For example, when stratified for age, the authors said the mortality rate was 7.4%, 5.6% and 10.2% in the age groups 10-30 years, 31-50 years, and 51-70 years respectively. However, the true death rate should be 19.5% (8/41), 17.6 (6/34), and 37.9% (11/29), respectively.

Response: The analysis tables are changed to basic tables with chi-square & multivariable survival regression and calculated overall survival.

4. Table 1 should be divided into multiple tables.

Response: Table 1 is changed to baseline characteristics and is stratified on outcome (alive/ dead) and p-values taken out with chi-square.

5. It might be better to present the data in Table 2 by one or more figures.

Response: The table 2 is changed to treatment and management of patient stratified on outcome (alive/ dead) and p-values taken out with chi-square.

6. There are sporadic grammar errors throughout the manuscript.

Response: Grammatical errors rectified.

Reviewer #4: Peer-review report

Title: “Outcomes of COVID‐19 infection in patients with hematological malignancies- A multicenter analysis from Pakistan”

Manuscript number: PONE-D-21-33433

Reviewer comment

- Thank you for inviting me to review this paper. I congratulate the authors for writing this research article. Based on their study, the authors describe the outcome of COVID-19 infection in patients with hematological malignancy. However, the document needs revision in the methodology and analysis section before considering the paper for publication.

Abstract

- Please expand the term COVID-19 and SARS-CoV-2

Response: Explained with detail page #7

- In the method part, explain how the data is and analyzed and presented

Response: The data was entered and analyzed by using STATA version 16. Calculated medians for all skewed continuous variables. Normality of data was check through density plots. Frequencies with percentages for categorical variables. Chi-square test was performed to check the association between the covariates and mortality. For survival analysis multivariable Cox-regression hazard regression model was applied and Kaplan Meir survival curve was used to check the overall survival. P-value ≤0.05 was considered significant. Page # 8.

- Replace …‘from February 2020 to August 2020’ with … from February to August 2020’.

Response: changed from February to August 2020

- Please spell out numbers when they occur at the beginning of a sentence.

Response: Changed.

- The authors said that mortality rate is high in patients aged 50 and above without putting any statistical indicator (e.g. p-value). Accordingly, the information seems invalid.

Response: The results are changed completely. The baseline details and clinical details are stratified on outcome (alive/dead) and p-value are taken through chi-square. Moreover multivariable analysis was done using Cox-regression.

- The conclusion of the study support the knowledge in the existing literature, but it seems relevant to add recommendation. //

Introduction

-explained fairly.

Method

Needs major revision considering the following points

- Clear description of the study setting, study populations, eligibility criteria (inclusion and exclusion criteria), data collection procedure, operational definition (if applicable), and ethical approval of the study (even a little is stated in the declaration section).

Response: Data was collected using a standard Performa developed for this study. Demographic, clinical, treatment and laboratory data and serial samples for viral RNA detection were extracted from medical records of 107 patients. Patient with any known hematological malignancy who was positive for COVID-19 on RT-PCR was included in the study. Patients with a clinical or radiological diagnosis of COVID-19, without a positive RT-PCR test were not included in this analysis. Ethical approval was obtained from Ethical Review Committee of the Aga Khan University Hospital, Karachi, Pakistan. Data was retrospectively collected through chart review so there was no need of the informed written consent.

- In the statistical analysis part, why the authors preferred to use median over mean? Do the authors check the distribution of the data?

Response: Normality of data was check through density plots. For skewed data Median & IQR was calculated.

- Similarly, the chi-square test is performed. However, it is unclear where they put the report of this test in the result part.

Response: Chi-square test was performed to check the association between the covariates and mortality. P-values reported.

- With the existing data on your hand, you can consider identifying the factor (s) associated with the COVID-19 outcome (optional).

Response: Thanks for suggestion it can be done in a prospective study.

Result

-Revise based on previous comment on the analysis part. You have to put the chi-square (optional) and the p-value in the stratification of mortality table.

Response: Chi-square test was performed to check the association between the covariates and mortality. P-values reported.

Discussion

-Be consistent on the use of the word COVID-19. You have written as covid 19, COVID-19,...

Response: changed to COVID-19 in whole manuscript

-Expand the term ASH

Response: American Society for Hematology (ASH) page #24

- At the end of the discussion part please give a separate sub-heading and label as ‘conclusion’.

Response: Added a separate section

In this part you can put your conclusion and recommendation (s).

- Revise the lists of abbreviation

Response: Revised abbreviations

Reviewer #5: In this study, Zaki et al, carried out a multicenter, retrospective, cohort study including 107 patients (aged ≥14 years) with diagnosis of hematological malignancy admitted to 5 tertiary care hospitals with laboratory-confirmed and symptomatic COVID-19.

As the authors rightly point out, the value of the study lies in being the first multicenter analysis from Pakistan and aimed at investigating outcome of patients with hematological malignancies and COVID-19 in a context with limited health care resources.

The outcomes in COVID- 19 cancer patients is a topic of great interest, and for this reason, a deeper characterization of the study population is recommended. In particular, the author should specify:

- the duration of follow-up

Response: There was no follow-up as it’s a retrospective study. The suggestion is nice a prospective follow-up study can be done in future.

- the criteria used to define the severity of COVID-19 at admission

Response: patients with a history of histologically proven hematological malignancies that tested positive for COVID-19 by RT-PCR

- patients with progressive disease, remission or in active therapy

Patients with active therapy/ treatment are included (see table 2). Progressive disease or remission were not recorded.

Although in this study, the overall mortality mirrors data from studies carried out in other countries, suggesting a high risk for severe COVID-19 infection and mortality also in these patients, the author should discuss results comparing data with:

- mortality estimates for COVID-19 in the general population, possibly according to sex and stratified for age

Response: Mortality recorded in age groups & sex refer to table 1.

- mortality estimates for pre-covid cohort with hematological malignancies, possibly stratified according to sex, age, type of hematological malignancy.

Response: Results are revised characteristics such as age, gender, malignancy & others were check with outcome alive/dead and chi-square test was run to see the significance.

In order to make data analysis clearer to readers, characteristics of the study population should be reported in a table, with information on age/age groups, sex, comorbidities, type of hematological malignancy, disease status and therapy, COVID-19 severity, referred for all patients, survivors and non-survivors. And the results should be discussed accordingly. In particular, the features of the cohort study can be compared according to COVID-19 severity and outcome

Response: Results are revised characteristics such as age, gender, malignancy & others were check with outcome alive/dead and chi-square test was run to see the significance. Moreover multivariable analysis was performed using Cox-regression to see the survival by regressing all independent variables again outcome alive/dead.

Although the sample size makes this study not sufficiently robust to assess events and risk factors that can predict death in this clinical setting, a deeper statistical analysis evaluating association with overall survival of variable such as age, sex, comorbidity, type and status of neoplasia, etc., would help to objectively characterize these patients

Response: Multivariable analysis was performed using Cox-regression to see the survival by regressing all independent variables again outcome alive/dead.

Reviewer #6: The article captures data from the real world but has certain limitations, some of which have been highlighted. The comparative mortality and hospitalization statistics in the general population without hematological malignancies should be mentioned for the reader to make a fair comparison. The English should be brushed up. Have edited some of the errors in the attached pdf, but there are more.

Response: Grammatical editing has been done.

Submitted filename: Response to multicenter outcomes comments.docx

Click here for additional data file.

9 Mar 2022

17 Mar 2022

Reviewer #1: The authors of the manuscript "Outcomes of COVID‐19 infection in patients with hematological malignancies- A multicenter analysis from Pakistan“ have partially addressed previous comments. The manuscript still needs intensive language editing.

Response: Grammatical corrections are made, see track changes

Reviewer #3: The authors have addressed most of the concerns from the 1st-round review, and this reviewer is satisfied with the improved quality of the revised manuscript. However, the English language skill still needs to be improved.

Response: Grammatical corrections are made, see track changes

Reviewer #4: Dear /sir, most of the comments given were addressed correctly. I have a few suggestions to improve the readability of this manuscript before publication is commenced. My concerns are:-

- Please expand the term COVID-19 and SARS-CoV-2 at the beginning of the abstract page 3 line 3

Response: Changed to Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Coronavirus disease of 2019 (COVID-19) page #3 line #3-4

- Replace …‘from February 2020 to August 2020’ with … from February to August 2020’ page 3 line 11.

Response: Changed to February to August 2020

- The information included in the operational definition must be cited with appropriate literature/s.

Response: Cited all operational definitions

- Authors should check for typos and grammatical errors throughout the manuscript which need to be edited after careful reading.

Response: Grammatical corrections are made, see track changes

Reviewer #5: I suggest the authors to keep the first 3 paragraph of Baseline characteristics, taking care to integrate the information added in the revised version to avoid repetitions.

Response: Made two sections added first 3 paragraphs with their tables in baseline characteristics and rest in multivariable analysis.

The comparative mortality and hospitalization statistics in the general population should be mentioned for the reader to make a fair comparison.

Response: However, in the general population it range from 9-29.6%. In white Hispanic group the morality was less than 10% while in Black and Hispanic groups it was less than 30% in the general population. Page 18 line# 6-8

Submitted filename: Response to reviewer comments multicenter.docx

Click here for additional data file.

4 Apr 2022

Outcomes of COVID‐19 infection in patients with hematological malignancies​- A multicenter analysis from Pakistan

PONE-D-21-33433R2

Dear Dr. Zaki,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Sinan Kardeş, M.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

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Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #3: All comments have been addressed

Reviewer #4: All comments have been addressed

Reviewer #5: All comments have been addressed

**********

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The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Yes

**********

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Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: N/A

**********

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Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Yes

**********

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PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

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Reviewer #4: Yes

Reviewer #5: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #3: (No Response)

Reviewer #4: (No Response)

Reviewer #5: The authors of the manuscript "Outcomes of COVID‐19 infection in patients with hematological malignancies- A multicenter analysis from Pakistan“ have addressed previous comments.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

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Reviewer #3: No

Reviewer #4: No

Reviewer #5: No

6 Apr 2022

PONE-D-21-33433R2

“Outcomes of COVID‐19 infection in patients with hematological malignancies​- A multicenter analysis from Pakistan”

Dear Dr. Zaki:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

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on behalf of

Dr. Sinan Kardeş

Academic Editor

PLOS ONE