 Red cell distribution width in cancer and kidney transplant COVID-19 patients Eur J Transl Myol 32 (2): 10582, 2022 doi: 10.4081/ejtm.2022.10582 - 1 - Red cell distribution width, a predictive factor in immunocompromised patients with COVID-19: A comparison retrospective study between cancer and kidney transplant patients Minoosh Moghimi (1), Manizheh Jozpanahi (2), Kasra Khodadadi (1), Seyede Pegah Saeed (3), Seyede Vanoushe Azimi Pirsaraie (3), Nooshin Jalili (1) (1) Department of Internal Medicine, Zanjan University of Medical Sciences, Zanjan, Iran;(2) Department of Infectious Disease, Zanjan University of Medical Sciences, Zanjan, Iran; (3) School of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran; This article is distributed under the terms of the Creative Commons Attribution Noncommercial License (CC BY-NC 4.0) which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. Abstract We aimed to review the records of cancer and kidney transplant patients of out of 1135 COVID- 19 patients, who were referred to our hospital (Valiasr) in Zanjan, from March 16th, 2020, to June 11th, 2020. This was single-center, historical cohort study. Patients were divided into different subgroups and compared of disease outcomes. The only predictor of death was lactate dehydrogenase (LDH). The rate of red cell distribution width (RDW) in patients with active cancer was higher than kidney transplant patients and was statistically significant. There was no statistically significant difference in mortality between active and non-active cancer groups. Female sex and low SpO2 has increased the chances of ICU admission. Patients with active cancer generally have severe and more complicated disease and RDW can be a predictable option. Key Words: COVID-19; kidney transplantation, cancer, immunocompromised patient. Eur J Transl Myol 32 (2): 10582, 2022 doi: 10.4081/ejtm.2022.10582 The pandemic of COVID-19 has a huge effect on public health and is still a major cause of death in Iran.1 During the COVID-19 pandemic, cancer patients are an especially vulnerable group. Because of their underlying condition and treatment complication, they are often immunosuppressed.2 Many individuals assume that cancer patients who receive systemic anticancer drugs are at a higher risk of developing the disease than patients who do not receive anticancer treatment.3 There is few information on the risk of developing COVID-19 in hematological cancer patients. Many people with hematological cancer take anti-cancer drugs that suppress bone marrow function, putting them at risk of acquiring infections in the community and hospitals.4 The epidemiology, clinical characteristics, and outcomes of COVID-19 among solid organ transplant (SOT) recipients are undefined. Few early descriptive case reports and case series of SOT recipients with COVID- 19 suggest poor outcomes; but, difference is unclear between in the SOT and non-transplant population.5 Due to chronic immunosuppression and coexisting conditions, kidney transplant recipients are particularly vulnerable to COVID-19.6 Patients with COVID-19 have hematological abnormality, such as a lower lymphocyte and platelet count but a normal white blood cell (WBC).7 Red cell distribution width (RDW) conveys the degree of anisocytosis between red blood cells. Anisocytosis is a mechanism that is highly dependent on inflammation. Many of the proinflammatory cytokines like TNF-α and interleukin-1 decrease erythropoietin synthesis during cytokine storm.8 In addition, hypoxia causes erythropoietic disturbance in COVID-19. Super infections are prevalent in COVID-19, thus increasing sepsis. RDW plays a considerable alarm in sepsis.8 In particular, several previous studies have shown that increased RDW is correlated with mortality in non- specific acute respiratory distress syndrome (ARDS) patients.9 Adding RDW at diagnosis of ARDS increased discrimination in the model using 4 clinical factors to estimate ICU mortality.10 Since the beginning of the pandemic, there have been grave concerns over the risk of developing severe COVID-19 for individuals with immunodeficiency’s or those taking immunosuppressive therapies. Two main immunosuppressant diseases are cancer and SOT. There are conflicting data about increased risk of COVID-19 in patients with a history of immunosuppressant.11,12 Type and duration of immunosuppressant are important in evaluation of Red cell distribution width in cancer and kidney transplant COVID-19 patients Eur J Transl Myol 32 (2): 10582, 2022 doi: 10.4081/ejtm.2022.10582 - 2 - susceptibility to infection. Therefore, we aimed to review the records of cancer and kidney transplant patients of out of 1135 COVID-19 patients, who were referred to our hospital (Valiasr) in Zanjan, Iran. Materials and Methods Study design This was a single-center, historical cohort study. We reviewed the records of cancer and kidney transplant patients with COVID-19 were referred to our hospital (Valiasr) in Zanjan, from March 16th, 2020, to June 11th, 2020 (Figure 1). The most prevalence between SOT patients that referred to our system was kidney transplant. Cancer (solid tumor and hematologic malignancy) and kidney transplant patients with positive COVID-19 RT- PCR (reverse-transcriptase polymerase chain reaction) were included. This study was approved by the institutional ethics review boards of our university (approval number IR.ZUMS.REC.1399.265 date: Oct 15th, 2020). The Research Ethics Committee waived the requirement informed consent before the study started because of the urgent need to collect epidemiological and clinical data. We analyzed all the data anonymously. Diagnostic methods The method of diagnosis is RT-PCR assay test using throat swab specimens collected from upper respiratory tracts. All patient aged was more than 18. Patients with a radiological or clinical diagnosis of COVID-19, without a positive RT-PCR test were not included in this analysis. Fig 1. Statistics of patients suspected to COVID-19: Cancer and kidney transplant patients with positive COVID- 19 RT-PCR were included. Fig 2. Division algorithm of patients with COVID-19, including two groups 1: Patients with cancer, 2: Patients with renal transplant. Patients with cancer were studied in two groups: active cancer and inactive cancer. Cancers were studied in 3 groups: blood malignancy, gastrointestinal cancer and non-gastrointestinal cancers. Red cell distribution width in cancer and kidney transplant COVID-19 patients Eur J Transl Myol 32 (2): 10582, 2022 doi: 10.4081/ejtm.2022.10582 - 3 - Patients with non-invasive cancers including non- melanomatous skin cancer, in-situ carcinoma, or precursor hematological neoplasms were excluded from this analysis. Patients with room air oxygen saturation (SpO2) < 90% were considered as severe COVID-19, and ≥90% were considered moderate COVID-19.13 Clinical data of each patient were collected, which included age, gender, and known comorbidities (diabetes mellitus (DM), hypertension (HTN)). Other underlying diseases were not included in the study due to their lower prevalence. Cancer stage was not chosen for the multivariable analysis as this variable was only collected in solid tumors. Patients with cancer were studied in two Table 1. Description of patients on admission. Graft patients N (%) Cancer patient’s N (%) Variables 4(80) 16(57.1) Male Sex 1(20) 12(42.9) Female M ± SD 48.60±15.14 M ± SD 62.54±14.78 Age 2(40) 11(39.3) severe Severity 3(60) 17(60.7) Non-severe 1(20) 3(10.7) DM Comorbidity 4(80) 6(21.4) HTN 22(78.5) Active Cancer activity 6(21.4) Non-active N/A 5(17.9) Hematologic Type of cancer 8(28.6) GI 15(53.6) Non-GI 5(100) 28(100) Total GI: Gastrointestinal; Non GI: Non Gastrointestinal; HTN: Hypertension; DM: Diabetes Mellitus; N: Number; SD: standard deviation Fig 3. Comparison of cancer type with mortality. GI: Gastrointestinal, Non GI: Non Gastrointestinal Red cell distribution width in cancer and kidney transplant COVID-19 patients Eur J Transl Myol 32 (2): 10582, 2022 doi: 10.4081/ejtm.2022.10582 - 4 - groups: active cancer (for which anticancer treatment (chemotherapy) had been administered in the past 6 months; or hematological cancer that is not in complete remission) and inactive cancer. Also cancer patients were studied in 3 groups: blood malignancy, gastrointestinal cancer and non-gastrointestinal cancers (Figure 2). Table 2. Patients’ laboratory tests and the type of cancer. Patient with Cancer type WBC Hb PLT RDW LDH Lymph count 1 Breast Cancer 2900 12.3 89000 13.2 403 41.6 2 Lung Cancer 15200 8.9 215000 15.3 612 6.4 3 Esophageal Cancer 3200 10.1 404000 13.4 259 9.9 4 Oral SCC 4200 12.3 252000 14.1 570 18.2 5 Hypopharyngeal Cancer 19400 7.3 276000 17.5 3.5 6 Gastric Cancer 10300 11.6 204000 16.2 587 17.1 7 CLL 116000 11.5 44000 15.2 786 0 8 Metastatic Lung Cancer 5300 10.5 256000 17.4 539 37.6 9 Prostate cancer 4300 13.4 126000 13.6 405 18.7 10 Glioblastoma multiforme 11 Prostate Cancer 5000 16.6 171000 13.5 514 23.9 12 Breast Cancer 7500 12 191000 12.4 419 10.7 13 Thyroid Cancer 4800 13.8 160000 13.1 316 16.8 14 Gastric Cancer 7.9 9.7 317 14.9 316 25.3 15 CLL 79.6 8.8 31 15.3 887 87.8 16 Ovarian Cancer 15.6 12.2 473 15.8 298 22.3 17 Non Hodgkin Lymphoma + Prostate 2.5 8.3 30 21.6 548 11.8 18 Multiple Myeloma 0.6 7 65 15.1 194 19 RCC 4 10.4 114 15.1 659 21.3 20 Laryngeal Carcinoma 254 21 Chollangiocarcinoma 0.8 11.2 167 15.1 1338 22 Hodgkin Lymphoma 6.5 12.5 90 13.5 197 10.1 23 Anal Cancer 3.2 13.6 70 14.2 408 13.4 24 Astrocytoma 3.7 13.2 149 15.3 753 35.6 25 Lung Cancer 9 10.3 211 17.8 351 14.7 26 Breast Cancer 7.9 12.1 279 13.3 416 21.8 27 Esophageal Cancer 0.3 10.1 33 16.8 445 28 Gastric Cancer 2.6 10.3 172 13.2 461 37.2 Graft patient Sex Age Underlying disease SPO2 WBC Hb PLT RDW LDH Patient 1 Male 41 HTN 93 6100 16.2 133000 12.1 319 Patient 2 Female 27 HTN 89 6500 8.4 234000 12.8 769 Patient 3 Male 50 DM HTN 82 7000 13.2 177 13.5 1145 Patient 4 Female 61 HTN 93 4800 9.8 130 12.4 477 Patient 5 Male 64 97 11300 11.8 166 14.4 209 SCC: Squamous Cell Carcinoma; CLL: Chronic Lymphocytic Leukemia; GBM: Glioblastoma Multiform; RCC: Renal Cell Carcinoma; WBC: White Blood Cell; Hb: Hemoglobin; PLT: Platelets; RDW: Red Distribution Width; LDH: Lactate Dehydrogenase; SPO2: Oxygen Saturation; HTN: Hypertension; DM: Diabetes Mellitus Red cell distribution width in cancer and kidney transplant COVID-19 patients Eur J Transl Myol 32 (2): 10582, 2022 doi: 10.4081/ejtm.2022.10582 - 5 - Indicators measurements and analysis The main outcome was patient survival during hospitalization. Measurements included RDW (elevated RDW defined as greater than 14.5%), Lymphocyte count (ALC < 1,000 cells/mm3 was defined as lymphopenia) and Platelet (PLT < 150,000 platelets/mm3 was defined as thrombocytopenia) at first day admission in hospital. Secondary outcomes were: a composite of severe illness (death, severe illness, admission to an intensive care unit (ICU), or a combination of these). Statistical analysis carried out using SPSS version 22. Significance level considered 0.05. Results We retrospectively enrolled 28 cancer (2.4%) and 5 kidney transplant patients of the 1135 patients admitted to Valiasr hospital for treatment of COVID-19. Demographic, clinical feature and underlying diseases of the patients are shown in Table 1. The mean age was 62 for cancer and 48 for kidney transplant patients (Mann- Whitney sig=0.053). The sex distribution in patients was not significantly different between cancer and kidney transplant patients (Exact sig=0.625). The most types of cancer patients were Gastric (3 patients), lung (3 patients), Breast (3 patients). Gastrointestinal cancer was the most frequent type of cancer (28.6%). The patient Table 3. Cancer and Graft patients Cancer patients Graft patients ICU admission N (%) Days of hospitalization (Med ±IQR) Mortality N (%) ICU admission N (%) Days of hospitalization (Med ±IQR) Mortality N (%) Sex Male 4(25) 7±5 5(31.3) 1(25) 8±11 1(25) Female 5(41) 5.5±5 4(33.3%) 0 4 0 Severity Severe 4(36.4%) 6±6 4(36.4%) 1(50) 18 1(50) Non severe 5(29.4%) 7±7 5(29.4%) 0 5.5±4.5 0 Cancer activity Active 7(31.8%) 6±5 8(36.4%) N/A N/A N/A Non active 2(33.3%) 7±13 1(16.7%) N/A N/A N/A Total 9(32) 6.50±6 9(32.1) 1(20) 7±10 1(20) IQR: Inter Quartile Range, N: Number, Med: Medium Table 4. Main Laboratory Findings according to clinical situation Graft patients Cancer patients RDW>14.5% N (%) PLT count<150.000 N (%) RDW>14.5 % N (%) PLT count<150.000 N (%) 0 3(75) 11(68.8%) 11(68%) Male Sex 0 1(100) 6(50%) 7(63.6%) Female N/A 0.78 0.441 1.00 Exact sig 0 1(50) 8(72.7%) 8(72.7%) Severe Severity 0 3(100) 9(52.9%) 10(62.5%) Non- severe N/A 0.04 0.435 0.692 Exact sig 15(68.2%) 15(71.4%) Active Cancer activity 2(33.3%) 3(50%) Non- active 0.174 0.305 Exact sig PLT: Platelets, RDW: Red Distribution Width, N: Number Red cell distribution width in cancer and kidney transplant COVID-19 patients Eur J Transl Myol 32 (2): 10582, 2022 doi: 10.4081/ejtm.2022.10582 - 6 - with Glioblastoma Multiform (GBM) died on the day of referral and no blood test was recorded for the patient, but the RT-PCR test came back positive later. The result of CBC taken in first day of case with laryngeal carcinoma was laboratory's missing, in which the results of the patient's tests were not entered in the system. In comparison between cancers type, gastrointestinal had higher mortality, but there was no statistically significant difference (P-Value= 0.54) (Figure 3). Among cancer patients, 9 (32.1%) patients had at least one or more underlying diseases whereas 80% kidney transplant patients had chronic comorbidity (Exact sig=0.041). In the severe cancer group, 6 of the 9 patients with the underlying disease had severe COVID-19. The patients' laboratory tests and the type of cancer in Table 2 are shown. Twenty-two (78.5%) cancer patients had active and six (21.4%) had inactive disease. Eight patients (36.3%) of active cancer and one (16.6%) inactive cancer died. Mortality of active versus inactive cancer patients was higher, but the differences was not statistically significant (Exact sig=0.63). Comparing mortality rate of cancer (32%) and graft patients (20%), the difference was not significant (Exact sig=1.000). Frequency of ICU admission was not statistically different between graft (20%) and cancer patients (32%) (Exact sig=1.000), also duration of hospitalization was not different between groups of patients (Mann-Whitney p=0.88) (Table 3). Nine (32.1%) of cancer patients needed invasive mechanical ventilation. In this study, among age, sex, diabetes mellitus, hypertension and baseline laboratory values, the only predictor of mortality was LDH level. The prevalence of thrombocytopenia (PLT<150000) and RDW> 14.5% were higher in severe patients but the difference was not statistically significant (Table 4). With each unit increase in LDH, the patient's chance of death increased by 0.5%. Patients were assessed for risk of mortality using LDH. ROC analysis with AUC = 0.750 and sig = 0.038 revealed the cut-off values of 404 with a sensitivity of 0.87 and a specificity of 0.64. To predict the need for ICU based on clinical conditions and laboratory findings, two variables of sex and O2 saturation were entered the Logistic regression model. Female sex and SpO2 <90% increased the chances of admission in ICU. None of the variables could estimate the number of days a patient will spend in the hospital based on clinical conditions and laboratory results at the time of patient admission using linear regression. Comparing active cancer and kidney transplant patients, interesting results were obtained that are shown in Table 5. Mortality and the need for hospitalization in ICU were higher in patients with active cancer, although the difference was not statistically significant (exact sig>0.05). RDW in patients with active cancer was higher than kidney transplant patients (exact sig=0.01). Discussion It was surprising for us that mortality and the need for ICU care were not significantly difference between active and inactive cancer patients. Liu study showed that the anti-tumor treatment did not lead to poorer prognosis in patients with solid tumors diagnosed with COVID- 19.14 Lee study showed that chemotherapy in the past 4 weeks had no significant effect on COVID-19 mortality.15 In our study, although the rate of mortality and admission in the ICU were higher in patients with active cancer, but there were not statistically significant. Active hematologic malignancies with COVID-19 had a similar risk of death versus non active hematologic patients.16 In Shoumariyeh study no significant difference was observed between solid tumor and hematological malignancy in overall survival.17 Our study shows same result (between GI cancer, non-GI cancer and hematologic cancer) but mortality was higher in GI malignancy without statistical significance. In this study among the cancer patients, gastrointestinal was the most frequent type of cancer. It is noteworthy that in the Ma study; the most common cancer was colorectal (29.7%), some studies indicated that lung cancer patients were the most common to be infected.18,19 Elevated LDH have been observed in the blood of patients with COVID-19, and levels of this enzyme correlate with disease severity. The findings of this study also confirmed this point.20 Men have a much greater risk of severe acute COVID-19 than women.21 While in our study, woman had increased risk of admitted to the ICU. COVID-19 is an immunosuppressant disease. An important question that has not yet been properly answered is: which patient with immunosuppression is more sensitive to COVID-19? Compared with active cancer and kidney transplant patients, interestingly high RDW was significant between the two groups, although the mortality rate was not statistically different, but it was higher in the active cancer group. In Sharma et al. study RDW in COVID-19 patients, was found to be higher than normal patients; however, it had no significant Table 5. Comparison of active cancer patients with kidney transplant patients Active Cancer Kidney Transplant p-value ICU admission 7(31.8%) 1(20%) 0.52 Mortality 8(36.4%) 1(20%) 0.44 RDW>14.5% 15(68.2%) 0 0.01 ICU: Intensive Care Unit; RDW: Red Distribution Width. Red cell distribution width in cancer and kidney transplant COVID-19 patients Eur J Transl Myol 32 (2): 10582, 2022 doi: 10.4081/ejtm.2022.10582 - 7 - association with disease severity.22 In our study, the proportion of severe COVID-19 with active cancer was 31.8% which was also significantly higher than that of the Iranian general population with severe COVID-19 (11%).23 It seems cancer patients were more likely to be immunosuppressed than kidney transplant patients included in our study and are more susceptible to COVID-19, but why there isn’t statistical difference between mortality in active cancer and kidney transplant patients? One of the reasons is the presence of associated underlying disease (hypertension and diabetes) that more predispose patients to COVID-19 in most kidney transplant patients. However, we cannot ignore the limitations of our study, the most important of which is the small number of immunosuppressed patients in each group and don’t enrolled other immunocompromised condition. In conclusion, our data suggest that patients with active cancer generally have severe and more complicated disease. But in our study, there was no higher mortality among patients with active versus inactive cancer in COVID-19. Therefore, it seems logical not to deprive cancer patients who need chemotherapy as basic treatment. The severity of COVID-19 varies in different types of immunosuppressed patients. RDW can be a predictor in these patients, but for clearer results, studies with larger statistical populations should be evaluated. List of acronyms ALC - Lymphocyte count ARDS - acute respiratory distress syndrome CBC - complete blood count CLL - Chronic Lymphocytic Leukemia DM - diabetes mellitus GBM - Glioblastoma Multiform GI - Gastrointestinal; Hb - Hemoglobin HTN - hypertension ICU - intensive care unit LDH - lactate dehydrogenase Non GI - Non Gastrointestinal PLT - platelet RCC- Renal Cell Carcinoma RDW - red cell distribution width ROC - receiver operating characteristic RT-PCR - Reverse transcription polymerase chain reaction SCC - Squamous Cell Carcinoma SOT - solid organ transplant SpO2 - oxygen saturation WBC - white blood cell Contributions of Authors Conceptualization: MM and KK; Methodology: MM, KK and MJ; Data Curation: MJ, SPS and SVAP; Analysis: NJ; Writing, MM and KK; Reviewing and Editing: MM, KK and NJ. All authors have read and agreed to the published version of the manuscript. Acknowledgments None Funding None Conflict of Interest The authors declare no conflict of interests. Ethical Publication Statement We confirm that we have read the Journal’s position on issues involved in ethical publication and affirm that this report is consistent with those guidelines. Corresponding Author Kasra Khodadadi, Internal Medicine Ward, Valiasr Hospital, Valiasr Street, Sheikh Fazlolah Blv, Zanjan, Iran, Postal code: 45157-77978. ORCID iD: 0000-0002-6192-4421 E-mail: khodadadikasra2020@gmail.com E-mails and ORCID iD of co-authors Minoosh Moghimi: mmoghimi2000@yahoo.com ORCID iD: 0000-0003-4120-5793 Manijeh Jozpanahi: dr.panahi48@gmail.com ORCID iD: 0000-0003-3008-8202 Seyede Pegah Saeed: Zmed1996@gmail.com ORCID iD: 0000-0002-8146-1081 Seyede Vanoushe Azimi Pirsaraie: Venosheh.a@gmail.com ORCID iD: 0000-0002-3701-6431 Nooshin Jalili: dr.nooshinjalili@zums.ac.ir ORCID iD: 0000-0002-6799-8923 References 1. Moradzadeh R, Jamalian SM, Nazari J, Kamali A, Sadeghi B, Hosseinkhani Z, Sofian M, Zamanian M. 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Submission: April 30, 2022 Revision received: May 21, 2022 Accepted for publication: May 21, 2022 Results