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. 2021 Sep 23;16(9):e0257775. doi: 10.1371/journal.pone.0257775

Repurposing FIB-4 index as a predictor of mortality in patients with hematological malignancies and COVID-19

Noorwati Sutandyo 1,*, Sri Agustini Kurniawati 1, Achmad Mulawarman Jayusman 2, Anisa Hana Syafiyah 3, Raymond Pranata 4, Arif Riswahyudi Hanafi 2
Editor: Senthilnathan Palaniyandi5
PMCID: PMC8459998  PMID: 34555104

Abstract

Background

In this study, we aimed to investigate whether FIB-4 index is useful in predicting mortality in patients with concurrent hematological malignancies and COVID-19. We also aimed to determine the optimal cut-off point for the prediction.

Methods

This is a single-center retrospective cohort study conducted in Dharmais National Cancer Hospital, Indonesia. Consecutive sampling of adults with hematological malignancies and COVID-19 was performed between May 2020 and January 2021. COVID-19 screening test using the reverse transcriptase polymerase chain reaction (RT-PCR) of nasopharyngeal samples were performed prior to hospitalization for chemotherapy. FIB-4 index is derived from [age (years) × AST (IU/L)]/[platelet count (109/L) × √ALT (U/L)]. The primary outcome of this study is mortality, defined as clinically validated death/non-survivor during a 3-months (90 days) follow-up.

Results

There were a total of 70 patients with hematological malignancies and COVID-19 in this study. Median FIB-4 Index was higher in non-survivors (13.1 vs 1.02, p<0.001). FIB-4 index above 3.85 has a sensitivity of 79%, specificity of 84%, PLR of 5.27, and NLR of 0.32. The AUC was 0.849 95% CI 0.735–0.962, p<0.001. This cut-off point was associated with OR of 16.70 95% CI 4.07–66.67, p<0.001. In this study, a FIB-4 >3.85 confers to 80% posterior probability of mortality and FIB-4 <3.85 to 19% probability. FIB-4 >3.85 was associated with shorter time-to-mortality (HR 9.10 95% CI 2.99–27.65, p<0.001). Multivariate analysis indicated that FIB-4 >3.85 (HR 4.09 95% CI 1.32–12.70, p = 0.015) and CRP> 71.57 mg/L (HR 3.36 95% CI 1.08–10.50, p = 0.037) were independently associated with shorter time-to-mortality.

Conclusion

This study indicates that a FIB-4 index >3.85 was independent predictor of mortality in patients with hematological malignancies and COVID-19 infection.

Introduction

Coronavirus Disease-2019 (COVID-19) manifest with different clinical presentations which might be asymptomatic, mild-moderate, and severe, which may cause multi-organ failure and death [1]. The severity of COVID-19 is affected by the presence of comorbidities [2–4]. During the pandemic, healthcare system is often overloaded with COVID-19 patients and risk stratification is of paramount importance for optimum resource allocation. Liver enzymes and platelets are often altered in patients with hematological malignancies; and might be useful for predicting outcome. Thrombocytopenia in also often encountered in patients with COVID-19 and signifies poor prognosis [5].

Fibrosis-4 (FIB-4) index is derived from the calculation of age, liver enzymes, and platelets, which are often evaluated in patients with hematological malignancies, thus is cost-effective and efficient. Moreover, FIB-4 index has also been shown to be associated with mortality in patients with COVID-19, even in the absence of previously known liver disease [6–8]. To the best of the authors knowledge, this is the first study to describe the use of FIB-4 index in patients with hematological malignancies, with or without COVID-19. In this study, we aimed to investigate whether FIB-4 index is useful in predicting mortality in patients with concurrent hematological malignancies and COVID-19. We also aimed to determine the optimal cut-off point for the prediction.

Materials and methods

Study design

This is a single-center retrospective cohort study conducted in Dharmais National Cancer Hospital, Indonesia. Consecutive sampling of adults who were tested positive for COVID19 while undergoing chemotherapy for hematological malignancy was performed between May 2020 and January 2021. The baseline characteristics and admission laboratory values were obtained from medical records. Hematological malignancies were defined as patients diagnosed with acute myelogenous leukemia (AML), acute lymphocytic leukemia (ALL), chronic myelogenous leukemia (CML), chronic lymphocytic leukemia (CLL), multiple myeloma (MM), non-Hodgkins lymphoma (NHL), or Hodgkins lymphoma (HL). COVID-19 screening test using the reverse transcriptase polymerase chain reaction (RT-PCR) of nasopharyngeal samples were performed prior to hospitalization for chemotherapy. COVID-19 diagnosis was based on the positive RT-PCR examination. The study was performed in accordance with the ethical standards of the 1964 Helsinki Declaration and its later amendments. Ethical clearance was provided by Ethical Research Committee of Dharmais National Cancer Hospital, Indonesia (Number: 0149/KEPK/X/2020). Ethics committee waived the requirement for informed consent due to retrospective observational nature of the study.

COVID-19 medications

The patients were given favipiravir (2 x 1600 mg) followed by maintenance (2 x 600 mg), azithromycin 1 x 500 mg, oseltamivir 2x75 mg, vitamin D3 1 x 1000 IU, vitamin C 2 x 500 mg, zinc 1 x 20 mg, betadine gargle 3 x 15 ml, and iodine nasal spray 3 x 1 for COVID-19 treatment. The risk of potential mechanisms or drug-to-drug interaction that may aggravate cancer progression with the use of these medications is low.

FIB-4 index

FIB-4 index is derived from [age (years) × AST (IU/L)]/[platelet count (109/L) × √ALT (U/L)]. This variable was calculated in the form of continuous data and categorized based on the optimal ROC curve determined cut-off point and a cut-off value of 1.45, which is commonly used to rule out certain outcomes.

Outcome

The primary outcome of this study is mortality, defined as clinically validated death/non-survivor during a 3-months (90 days) follow-up. The outcome was ascertained from the medical record confirmed by death certificate. The statistical analysis was performed by a researcher that is not involved in data collection or patient care.

Statistical analysis

Statistical analysis was performed using SPSS 25.0 and STATA 14.0. The continuous data was tested for normal distribution; t-test was used for normally distributed data and Mann-Whitney test was used for abnormally distributed data. Normally distributed data was reported as mean and standard deviation (SD); while abnormally distributed data was reported as median and interquartile range (IRQ). The continuous variables that significantly differ in non-survivors vs. survivors were then categorized. ROC curve analysis was performed to determine the optimal cut-off points for FIB-4 index and C-reactive protein (CRP). For FIB-4 index, a cut-off value of 1.45 was also analyzed because it is commonly used to rule out poor prognosis. The sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and area under the curve (AUC) were calculated for the respective cut-off points. Fagan’s nomogram was plotted to determine the posterior probability of mortality in the event of FIB-4 index elevation above the cut-off point. Chi-square was used to calculate the odds ratio (OR) and its 95% confidence interval (95% CI) if the requirements are met. Cox-regression was performed to obtain the hazard ratio (HR) and survival curve based on the optimal FIB-4 index. Multivariable Cox-regression analysis was initially performed by including FiB-4 index, hemoglobin <10 g/dL, and CRP >71.57 mg/L to find the independent predictors. The number of variables were limited to three for the multivariable analysis to avoid model-overfitting. Multivariable analysis was only performed for HR to minimize the familywise error rate. Subgroup analysis for acute and chronic types of malignancies were performed, we obtained the ORs but not HRs, because chronic subgroup has spuriously high hazard ratio.

Results and discussion

There were a total of 70 patients with hematological malignancies and COVID-19 in this study. The baseline characteristics of the study can be seen in Table 1. Severe COVID-19 was higher in non-survivors. The mean hemoglobin, platelets, and FIB-4 Index were lower in non-survivors; while CRP was higher in non-survivors. The mortality rate was 43% and the median follow-up length was 33 days (IQR 64).

Table 1. Baseline characteristics.

Non-Survivor (n = 28) Survivor (n = 42) p-value
Age (years) 44.9 ± 12.8 42.7 ± 14.6 0.339
Gender (Male) 15 (53.6%) 23 (54.8%) 0.922
BMI (kg/m 2 ) 22.4 (6.68) 21.2 (3.65) 0.172
Severe COVID-19 23 (82.1%) 4 (9.5%) <0.001
Cancer Type 0.180
AML 10 (35.7%) 10 (23.8%) 0.280
ALL 4 (14.3%) 3 (7.1%) 0.426
CML 1 (3.6%) 3 (7.1%) 0.645
CLL 2 (7.1%) 2 (4.8%) 1.000
MM 4 (14.3%) 2 (4.8%) 0.209
NHL 7 (25.0%) 16 (38.1%) 0.253
HL 0 (0%) 6 (14.3%) 0.074
Rituximab Use in CLL and NHL 5 (100%) 9 (75%) 0.515
Remission and Relapse Status
Remission 2 (7.1%) 3 (7.1%) 1.000
Relapse 2 (7.1%) 6 (14.3%) 1.000
Neither 24 (85.8) 33 (78.6%) 0.329
Proliferation 0.301
Fast 13 (46.4%) 12 (28.6%) 0.127
Moderate 12 (42.9%) 25 (59.5%) 0.171
Slow 3 (10.7%) 5 (11.9%) 1.000
Laboratory Values
Hemoglobin (g/dL) 8.5 ± 1.7 10.5 ± 2.1 <0.001
Leukocyte (x 10 9 /L) 12.6 (15.8) 14.5 (100.9) 0.607
Platelets (x 10 9 /L) 60.0 (573) 69.0 (334) <0.001
Ureum (mg/dL) 38 (31) 32 (28) 0.011
Creatinine (mg/dL) 0.60 (0.42) 0.63 (0.52) 0.317
AST (U/L) 30 (60) 21 (25) 0.752
ALT (U/L) 51.5 (77) 16.0 (38) 0.239
FIB-4 Index 13.1 (12.1) 1.02 (2.53) <0.001
FIB-4 Index <3.85 6 (27.3%) 16 (72.7%) <0.001
FIB-4 Index >3.85 25 (86.2%) 4 (13.8%) <0.001
PT 17.4 ± 4.6 19.8 ± 18.0 0.585
aPTT 35.0 ± 13.9 52.0 ± 77.2 0.297
D-Dimer (mg/dL) 2662 ± 1564 2163 ± 1617 0.317
CRP (mg/L) 87.1 (123.2) 28.6 (58.2) <0.001
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The survivors and non-survivors are based on 3 months (90 days) mortality.

Continuous variables were presented in mean ± standard deviation or median (interquartile range)

AST: aspartate aminotransferase, ALT: alanine aminotransferase, AML: acute myelogenous leukemia, ALL: acute lymphocytic leukemia, CML: chronic myelogenous leukemia, CLL: chronic lymphocytic leukemia, MM: multiple myeloma, NHL: non-Hodgkins lymphoma, or HL: Hodgkins lymphoma, CRP: c-reactive protein, FIB-4 index: fibrosis-4 index, PT: Prothrombin Time, aPTT: Activated Partial Thromboplastin Time

FIB-4 index >3.85 and mortality

Median FIB-4 Index was higher in non-survivors (13.1 vs 1.02, p<0.001). Through the ROC curve analysis, the optimal cut-off point for FIB-4 index was determined to be 3.85, which has a sensitivity of 79%, specificity of 84%, PLR of 5.27, and NLR of 0.32. The AUC was 0.849 95% CI 0.735–0.962, p<0.001 [Fig 1]. This cut-off point was associated with OR of 16.70 95% CI 4.07–66.67, p<0.001. In this study, a FIB-4 >3.85 confers to 80% posterior probability of mortality and FIB-4 <3.85 to 19% probability [Fig 2]. FIB-4 >3.85 was associated with shorter time-to-mortality (HR 9.10 95% CI 2.99–27.65, p<0.001) [Fig 3].

Fig 1. Receiver operating characteristic curve for FIB-4 and mortality.

Fig 1

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Fig 2. Fagan’s nomogram for FIB-4 >3.85 and mortality.

Fig 2

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Fig 3. Time-to-event analysis for FIB-4 >3.85 and mortality (3-months survival).

Fig 3

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All of the events occurred at or before the 34th day.

FIB-4 >1.45 and mortality

FIB-4 >1.45 was associated with higher mortality (OR 12.05 95% CI 2.86–50, p<0.001) with a sensitivity of 84%, specificity of 59%, PLR of 2.50, and NLR of 0.21. In this study, a FIB-4 >1.45 confers to 65% posterior probability of mortality and FIB-4 <1.45 to 14% probability [Fig 4]. FIB-4 >1.45 was associated with shorter time-to-mortality (HR 5.43 95% CI 1.58–18.70, p = 0.007) [Fig 5].

Fig 4. Fagan’s nomogram for FIB-4 >1.45 and mortality.

Fig 4

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Fig 5. Time-to-event analysis for FIB-4 >1.45 and mortality (3-months survival).

Fig 5

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All of the events occurred at or before the 34th day.

Other markers

Hemoglobin <10 g/dL (HR 8.13 95% CI 2.44–27.03, p = 0.001) and CRP >71.57 mg/L (HR 4.98 95% CI 1.86–13.3, p = 0.001) were associated with shorter time-to-mortality. CRP >71.57 mg/L was derived from ROC curve and has sensitivity of 80% and specificity of 75%, PLR of 3.20, NLR of 0.27, and AUC of 0.782 95% CI 0.649–0.914, p = 0.001.

Multivariable analysis

Multivariate analysis indicated that FIB-4 >3.85 (HR 4.09 95% CI 1.32–12.70, p = 0.015) and CRP >71.57 mg/L (HR 3.36 95% CI 1.08–10.50, p = 0.037) were independently associated with shorter time-to-mortality [Table 2]. Hemoglobin <10 g/dL was not statistically significant in the multivariable model.

Table 2. The univariable and multivariable cox-regression analysis.

Unadjusted HR Adjusted HR
FIB-4 >3.85 9.10 95% CI 2.99–27.65, p<0.001 4.09 95% CI 1.32–12.70, p = 0.015
Hemoglobin <10 g/dL 8.13 95% CI 2.44–27.03, p = 0.001 3.65 95% CI 0.82–16.18, p = 0.088
CRP >71.57 (mg/L) 4.98 95% CI 1.86–13.3, p = 0.001 3.36 95% CI 1.08–10.50, p = 0.037
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CRP: c-reactive protein, FIB-4 index: fibrosis-4 index; HR: hazard ratio

Subgroup analysis based on acute and chronic types

FIB-4 >3.85 was associated with mortality in both acute (OR 8.77 95% CI 1.24–62.25, p = 0.018) and chronic (OR 6.67 95% CI 2.35–18.87, p<0.001) types of malignancies.

This study indicates that a FIB-4 index >3.85 was independent predictor of mortality in patients with hematological malignancies and COVID-19 infection. Subgroup analysis for acute and chronic types of malignancies indicates that the index was applicable in both types of malignancies. Only ORs were obtained for subgroup analysis, because subgroup analysis for HR resulted in spuriously high HR for chronic type of malignancies. FIB-4 >3.85 was significantly associated with mortality in all of these analyses, OR and HR, in both acute and chronic types of malignancies.

Although initially used as a marker of liver fibrosis, FIB-4 index has been repurposed for prognostication in patients with COVID-19, with or without liver disease [7, 9–11]. Age, liver injury, and thrombocytopenia have been shown to increase mortality in COVID-19 [1, 5, 6, 12]. However, in Table 1, only platelets is significantly lower in patients with COVID-19. Although the mean age and median AST ALT were higher in non-survivors, they were not statistically significant. It is possible that due to small sample size, the differences were not noted. This further emphasizes the importance of prediction tool that is more sensitive and specific, combining these factors into FIB-4 index may enhance its performance. FIB-4 index above 3.85 has 79% sensitivity, 84% specificity resulting in 80% posterior probability for mortality in this study. In the multivariate cox-regression model, only FIB-4 >3.85 and CRP >71.57 mg/L independently predicted mortality; with FIB-4 being a stronger predictor. Pro-inflammatory markers such as CRP have been previously shown to be associated with mortality [13]. FIB-4 >1.45 has 84% sensitivity and 59% specificity, thus it may be used to rule-out the poor prognosis. However, other clinical parameters should be considered.

Platelets are an important component of FIB-4 index. COVID-19 induced thrombocytopenia may be caused by altered platelet production and accelerated consumption/destruction [14]. Through the CD13 receptor, SARS-CoV-2 may invade bone marrow cells and platelets which results in growth inhibition and apoptosis [15–17]. Inflammation cytokines may cause inhibition of the hematopoietic stem cells, suppressed thrombopoietin production, and megakaryocyte maturation [18]. Additionally, supplementary hematopoietic progenitor in the pulmonary vessels was reduced by the lung damage associated with COVID-19 [19]. Accelerated platelet consumption or destruction due to inflammation and coagulopathy may further reduce platelets [14]. Another important condition is secondary hemophagocytic lymphohistiocytosis, in which widespread engulfment of blood cells occurred, further reducing platelets [16, 20]. Through molecular mimicry, antibodies generated by the host may specifically bind to platelet antigens causing destruction of platelets [15, 16, 21]. In brief, thrombocytopenia may reflect a higher inflammatory response and greater viral load of SARS-CoV-2, signifying poor prognosis. Thus, COVID-19 synergizes with the inherent hematopoietic abnormalities caused by hematological malignancies, which may further aggravates the disease. In this study, platelets were considerably lower in non-survivors.

Liver enzyme is another important component of FIB-4 Index. Direct viral invasion, medication-induced hepatotoxicity, and inflammation may cause liver injury in patients with COVID-19 [22, 23]. Bile duct epithelial cells and liver endothelial cells express a high amount of angiotensin-converting enzyme II (ACE2) which is the target for SARS-CoV-2 spike protein [24]. This resulted in increased AST and ALT, followed by increased bilirubin to some extent [25–31]. Most cases are transient and reversible, nevertheless some developed advanced liver injury [24, 32]. In patients with hematological malignancies, increased liver enzyme might be caused by drug toxicity or leukemic cell invasion [33].

Limitations

This study has several caveats. Despite being the national referral center and the largest hospital for cancer, the sample size is small, nevertheless this study represents the real world data. We are unable to provide stratified analysis based on the types of hematological malignancies or their properties such as resistance/relapse due to small sample size. Additional inflammatory markers such as interleukins were not measured. It would be interesting to see how FIB-4 index fare compared to these variables. Finally, the reasoning for the formula is because one of the authors (Pranata R) published a meta-analysis on the use of FIB-4 Index in patients with COVID-19 [8]. Many of the studies included in the meta-analysis were conducted in patients without liver diseases and FIB-4 Index was shown to be associated with mortality. Thus this is a simple repurposing of a widely used scoring method which include several important variables in patients with hematological malignancies. Familiar score that has been used widely can be applied with relative ease to clinical practice. The model is not based on meticulous formula derived from rigorous evaluation. Since the study is based on limited sample size, this study serves as a basis for further investigation, it will be interesting if other studies in the future are conducted to confirm or debate the findings of the present study. FIB-4 index is yet to be investigated in hematological malignancies without COVID-19, it will be interesting to know how this index fare in future studies.

Conclusion

FIB-4 index was independently associated with mortality in patients with hematological malignancies and COVID-19. A FIB-4 index cut-off value of 3.85 is optimal for predicting mortality.

Supporting information

S1 File

(DOCX)

Click here for additional data file. (11.8KB, docx)

Acknowledgments

The COVID-19 mitigation team; Department of research and development, Dharmais National Cancer Center, Jakarta, Indonesia.

Data Availability

Data cannot be shared publicly because the data contain potentially identifying or sensitive patient information. The Ethical Research Committee of Dharmais National Cancer Hospital, Indonesia imposes strict restriction regarding patients’ confidentiality. However, all reasonable data access requests may be sent to the Ethical Research Committee of Dharmais National Cancer Hospital, Indonesia (email: kepkdharmais@gmail.com) or to the address at Jl. Letjen S. Parman No.84-86, Kota Bambu Selatan, Kec. Palmerah, Kota Jakarta Barat, Daerah Khusus Ibukota Jakarta 11420.

Funding Statement

The author(s) received no specific funding for this work.

References

  • 1.Lim MA, Pranata R, Huang I, Yonas E, Soeroto AY, Supriyadi R. Multiorgan Failure With Emphasis on Acute Kidney Injury and Severity of COVID-19: Systematic Review and Meta-Analysis. Can J Kidney Heal Dis. 2020;7. doi: 10.1177/2054358120938573 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Pranata R, Henrina J, Raffaello WM, Lawrensia S, Huang I. Diabetes and COVID-19: The Past, The Present, and The Future. Metabolism. 2021; 154814. doi: 10.1016/j.metabol.2021.154814 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Tuty Kuswardhani RA, Henrina J, Pranata R, Anthonius Lim M, Lawrensia S, Suastika K. Charlson comorbidity index and a composite of poor outcomes in COVID-19 patients: A systematic review and meta-analysis. Diabetes Metab Syndr Clin Res Rev. 2020;14: 2103–2109. doi: 10.1016/j.dsx.2020.10.022 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.July J, Pranata R. Prevalence of dementia and its impact on mortality in patients with coronavirus disease 2019: A systematic review and meta-analysis. Geriatr Gerontol Int. 2021;21: 172–177. doi: 10.1111/ggi.14107 [DOI] [PubMed] [Google Scholar]
  • 5.Pranata R, Lim MA, Yonas E, Huang I, Nasution SA, Setiati S, et al. Thrombocytopenia as a prognostic marker in COVID-19 patients: Diagnostic test accuracy meta-analysis. Epidemiol Infect. 2021;149: e40. doi: 10.1017/S0950268821000236 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Pranata R, Yonas E, Huang I, Lim MA, Nasution SA, Kuswardhani RAT. Fibrosis-4 index and mortality in coronavirus disease 2019. Eur J Gastroenterol Hepatol. 2021;Publish Ah. doi: 10.1097/meg.0000000000002091 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Park JG, Kang MK, Lee YR, Song JE, Kim NY, Kweon YO, et al. Fibrosis-4 index as a predictor for mortality in hospitalised patients with COVID-19: A retrospective multicentre cohort study. BMJ Open. 2020;10: e041989–e041989. doi: 10.1136/bmjopen-2020-041989 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Pranata R, Yonas E, Huang I, Lim MA, Nasution SA, Kuswardhani RAT. Fibrosis-4 index and mortality in coronavirus disease 2019: a meta-analysis. Eur J Gastroenterol Hepatol. 2021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Sterling RK, Oakes T, Gal TS, Stevens MP, Dewit M, Sanyal AJ. The Fibrosis-4 Index Is Associated with Need for Mechanical Ventilation and 30-Day Mortality in Patients Admitted with Coronavirus Disease 2019. J Infect Dis. 2020;222: 1794–1797. doi: 10.1093/infdis/jiaa550 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Li Y, Regan J, Fajnzylber J, Coxen K, Corry H, Wong C, et al. Liver Fibrosis Index FIB‐4 Is Associated With Mortality in COVID‐19. Hepatol Commun. 2021;5: 434–445. doi: 10.1002/hep4.1650 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Lopez-Mendez I, Aquino-Matus J, Gall SMB, Prieto-Nava JD, Juarez-Hernandez E, Uribe M, et al. Association of liver steatosis and fibrosis with clinical outcomes in patients with SARS-CoV-2 infection (COVID-19). Ann Hepatol. 2021;20: 100271. doi: 10.1016/j.aohep.2020.09.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Pranata R, Henrina J, Lim MA, Lawrensia S, Yonas E, Vania R, et al. Clinical frailty scale and mortality in COVID-19: A systematic review and dose-response meta-analysis: Clinical Frailty Scale in COVID-19. Arch Gerontol Geriatr. 2021;93: 104324. doi: 10.1016/j.archger.2020.104324 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Huang I, Pranata R, Lim MA, Oehadian A, Alisjahbana B. C-reactive protein, procalcitonin, D-dimer, and ferritin in severe coronavirus disease-2019: a meta-analysis. Ther Adv Respir Dis. 2020;14. doi: 10.1177/1753466620937175 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Zhang Y, Zeng X, Jiao Y, Li Z, Liu Q, Yang M, et al. Mechanisms involved in the development of thrombocytopenia in patients with COVID-19. Thromb Res. 2020;193: 110–115. doi: 10.1016/j.thromres.2020.06.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Amgalan A, Othman M. Exploring possible mechanisms for COVID-19 induced thrombocytopenia: Unanswered questions. J Thromb Haemost. 2020/05/06. 2020;18: 1514–1516. doi: 10.1111/jth.14832 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Xu P, Zhou Q, Xu J. Mechanism of thrombocytopenia in COVID-19 patients. Ann Hematol. 2020/04/15. 2020;99: 1205–1208. doi: 10.1007/s00277-020-04019-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Yang X, Yang Q, Wang Y, Wu Y, Xu J, Yu Y, et al. Thrombocytopenia and its association with mortality in patients with COVID-19. J Thromb Haemost. 2020;18: 1469–1472. doi: 10.1111/jth.14848 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Prompetchara E, Ketloy C, Palaga T. Immune responses in COVID-19 and potential vaccines: Lessons learned from SARS and MERS epidemic. Asian Pacific J Allergy Immunol. 2020;38: 1–9. doi: 10.12932/AP-200220-0772 [DOI] [PubMed] [Google Scholar]
  • 19.Lefrançais E, Ortiz-Muñoz G, Caudrillier A, Mallavia B, Liu F, Sayah DM, et al. The lung is a site of platelet biogenesis and a reservoir for haematopoietic progenitors. Nature. 2017;544: 105–109. doi: 10.1038/nature21706 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Iba T, Levy JH, Levi M, Thachil J. Coagulopathy in COVID-19. J Thromb Haemost. 2020;18: 2103–2109. doi: 10.1111/jth.14975 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Ahmed MZ, Khakwani M, Venkatadasari I, Horgan C, Giles H, Jobanputra S, et al. Thrombocytopenia as an initial manifestation of COVID-19; case series and literature review. Br J Haematol. 2020;189: 1057–1058. doi: 10.1111/bjh.16769 [DOI] [PubMed] [Google Scholar]
  • 22.Zhang C, Shi L, Wang FS. Liver injury in COVID-19: management and challenges. Lancet Gastroenterol Hepatol. 2020;5: 428–430. doi: 10.1016/S2468-1253(20)30057-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Chai X, Hu L, Zhang Y, Han W, Lu Z, Ke A, et al. Specific ACE2 expression in cholangiocytes may cause liver damage after 2019-nCoV infection. bioRxiv. 2020. doi: 10.1101/2020.02.03.931766 [DOI] [Google Scholar]
  • 24.Xu L, Liu J, Lu M, Yang D, Zheng X. Liver injury during highly pathogenic human coronavirus infections. Liver Int. 2020;40: 998–1004. doi: 10.1111/liv.14435 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical characteristics of 2019 novel coronavirus infection in China. medRxiv. 2020; 2020.02.06.20020974. doi: 10.1101/2020.02.06.20020974 [DOI] [Google Scholar]
  • 26.Fan Z, Chen L, Li J, Tian C, Zhang Y, Huang S, et al. Clinical features of COVID-19-related liver damage. medRxiv. 2020; 2020.02.26.20026971. doi: 10.1101/2020.02.26.20026971 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Cai Q, Huang D, Ou P, Yu H, Zhu Z, Xia Z, et al. COVID-19 in a designated infectious diseases hospital outside Hubei Province, China. medRxiv. 2020; 2020.02.17.20024018. doi: 10.1101/2020.02.17.20024018 [DOI] [PubMed] [Google Scholar]
  • 28.Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395: 497–506. doi: 10.1016/S0140-6736(20)30183-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Shi H, Han X, Jiang N, Cao Y, Alwalid O, Gu J, et al. Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study. Lancet Infect Dis. 2020;20: 425–434. doi: 10.1016/S1473-3099(20)30086-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Yang X, Yu Y, Xu J, Shu H, Xia J, Liu H, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med. 2020;8: 475–481. doi: 10.1016/S2213-2600(20)30079-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395: 507–513. doi: 10.1016/S0140-6736(20)30211-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Zhang C, Shi L, FS W. Liver injury in COVID-19: management and challenges. PG—428–430 LID—S2468-1253(20)30057-1 [pii] LID— 10.1016/S2468-1253(20)30057-1 [doi] LID—FAU—Zhang, Chao. Treatment and Research Center for Infectious Diseases, The Fifth Medical Center of PLA General Hospital, National Clinical Research Center for Infectious Diseases, Beijing 100039, China. FAU—Shi, Lei; [DOI]
  • 33.Bigildeev AE, Shipounova IN, Svinareva DA, Drize NJ. Leukemia cells invading the liver express liver chemokine receptors and possess characteristics of leukemia stem cells in mice with MPD-like myeloid leukemia. Exp Hematol. 2011;39: 187–194. doi: 10.1016/j.exphem.2010.11.005 [DOI] [PubMed] [Google Scholar]

Decision Letter 0

Senthilnathan Palaniyandi

21 Jun 2021

PONE-D-21-11387

Repurposing FIB-4 Index as a Predictor of Mortality in Patients with Hematological Malignancies and COVID-19

PLOS ONE

Dear Dr. Sutandyo,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

We have revived the opinions of expert reviewers as agree with reviewers comments raised a few concerns about this study. We invite you to submit a revised version of the manuscript, please consider and address each of the comments raised by the reviewers.  

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We look forward to receiving your revised manuscript.

Kind regards,

Senthilnathan Palaniyandi, Ph.D

Academic Editor

PLOS ONE

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[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

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 #1: Partly

Reviewer #2: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

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.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. 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 #1: Knowledge of COVID-19 pathogenesis in cancer patients is very limited but accumulating steadily. Any efforts in the direction are useful and extremely important. Data has to be examined carefully prior to any conclusions considering all the possibilities and probabilities within the scope of the study.

Studies correlating FIB-4 index with COVID-19 infections in the context of fibrosis and type II diabetes milletus have already been published. In the current study authors propose a correlation between FIB-4 index and mortality in hematological malignancies.

In addition to the caveats listed by the authors there are more questions that need to be addressed.

1.Is there correlation between COVID -19 negative or low load infection to heavy load of the infection in cancer patients.

2. Are there any insights in to possible treatment regimen so as to reduce the viral load and not aggravate cancer progression.

3. The sample size is limited. It would be interesting to observe data from multiple studies to be able to establish a correlation between FIB-4 index and mortality in hematological malignancies and COVID-19.

Reviewer #2: The authors evaluated the prognostic value of FIB-4 in patients with various hematologic malignancies. FIB-4 is calculated by AST, ALT, platelet and age, and was originally developed for the assessment of chronic liver disease. There have been some previous publication highlighting the value of FIB-4 in patients with acute illness like COVID19. The hypothesis is FIB-4 is prognostic in this population. The analysis seems to be reasonable, though the clinically more important question “what is the impact of underlying hematologic malignancy in patients with COVID19” was not assessed in this study, as there is no COVID19 patient data without hematologic malignancy presented.

The table 1 shows grouping of patients only by “survivor” and “non-survivor”. For this kind of analysis, sufficient follow up duration for all patients is important. The authors state the median follow up duration of 33 days but no range. If “mortality” is the endpoint, it is best to provide a specified time mortality (i.e. 30-day mortality etc) using Kaplan-Meyer estimate. The Table 2 is evaluated for “time to mortality”, which seems appropriate.

Remission and relapse information are provided but majority were “neither”. It is not clear what exactly it means. If it indicates that the patient was undergoing the initial therapy for the primary malignancy, it should be clarified. The implication is significantly different if they were on treatment versus not. The research would be valuable if this study was focused on patients who were undergoing treatment for hematologic malignancy or those who experienced COVID during therapy or within 30 (or whatever number) days from the completion of treatment. Or, the complete opposite would be to focus on those who were in remission and not receiving treatment. In any case, such full analyses may not be necessarily feasible due to limited number of patients.

The timing that FIB-4 was calculated based on the value at the time of admission. It is possible that the FIB-4 reflects the severity of the disease as it worsens, but not necessarily prognostic as one single parameter at diagnosis. It is worth mentioning the time from the onset of symptoms to admission (FIB-4 assessment) or time from diagnosis to admission (FIB-4 assessment). Or FIB-4 at the time of diagnosis, if available, would be also valuable.

At last, but not least, FIB-4 formula was “borrowed” from other studies (originally from chronic liver scarring) but there is no rigorous evaluation of the formula itself in this context. Why ALT needs to be square rooted and placed in the denominator? The impact of age (e.g. 1 vs 10 vs 50) is appropriately reflected in this formula? Such discussion or consideration, or to state the limitation of the current study in this regard would strengthen the paper.

**********

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Reviewer #2: No

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PLoS One. 2021 Sep 23;16(9):e0257775. doi: 10.1371/journal.pone.0257775.r002

Author response to Decision Letter 0

3 Jul 2021

Reviewer #1: Knowledge of COVID-19 pathogenesis in cancer patients is very limited but accumulating steadily. Any efforts in the direction are useful and extremely important. Data has to be examined carefully prior to any conclusions considering all the possibilities and probabilities within the scope of the study.

Studies correlating FIB-4 index with COVID-19 infections in the context of fibrosis and type II diabetes milletus have already been published. In the current study authors propose a correlation between FIB-4 index and mortality in hematological malignancies.

In addition to the caveats listed by the authors there are more questions that need to be addressed.

Response: Thank you very much for reviewing our paper and providing constructive feedbacks for our article.

1.Is there correlation between COVID -19 negative or low load infection to heavy load of the infection in cancer patients.

Response: Thank you very much for the question, we are sure that it will be an interesting analysis. Unfortunately, the data on patients’ viral load are unavailable. Thus we are unable to perform the analysis.

2. Are there any insights in to possible treatment regimen so as to reduce the viral load and not aggravate cancer progression.

Response: Thank you very much for the question, in the Dharmais National Cancer hospital of Indonesia, we used

1. Avigan (Favipiravir) 2 x 1600 mg followed by 2 x 600 mg maintenance

2. Azithromycin 1 x 500 mg

3. Oseltamivir 2x75 mg

4. Vitamin D3 1x1000 IU

5. Vitamin C 2x500 mg

6. Zinc 1x20 mg

7. Betadine gargle 3x15 ml

8. Iodine nasal spray 3x1

Theoretically, we observe no potential mechanisms or drug-to-drug interaction that may aggravate cancer progression with the use of these medications. Although control group with other medications are required to sufficiently conclude.

3. The sample size is limited. It would be interesting to observe data from multiple studies to be able to establish a correlation between FIB-4 index and mortality in hematological malignancies and COVID-19.

Response: Thank you very much for the suggestion, to the best of the authors’ knowledge, this is the first study evaluating the use of FIB-4 index as prognostication tool in patients with hematological malignancies with COVID-19. There are others in different type of population. Thus, this study serve as a basis for further investigation, it will be interesting if other studies in the future are conducted to confirm or debate the findings of the present study. We have added this in the limitation section.

Reviewer #2: The authors evaluated the prognostic value of FIB-4 in patients with various hematologic malignancies. FIB-4 is calculated by AST, ALT, platelet and age, and was originally developed for the assessment of chronic liver disease. There have been some previous publication highlighting the value of FIB-4 in patients with acute illness like COVID19. The hypothesis is FIB-4 is prognostic in this population. The analysis seems to be reasonable, though the clinically more important question “what is the impact of underlying hematologic malignancy in patients with COVID19” was not assessed in this study, as there is no COVID19 patient data without hematologic malignancy presented.

Response: Thank you very much for reviewing our paper and providing constructive feedbacks for our article.

The table 1 shows grouping of patients only by “survivor” and “non-survivor”. For this kind of analysis, sufficient follow up duration for all patients is important. The authors state the median follow up duration of 33 days but no range. If “mortality” is the endpoint, it is best to provide a specified time mortality (i.e. 30-day mortality etc) using Kaplan-Meyer estimate. The Table 2 is evaluated for “time to mortality”, which seems appropriate.

Response: Thank you very much for the suggestion, the patients were followed-up for 90 days and the Table 1 is for 3-months survival, we have added details in the methods and table. However, the event (mortality) occurred from one to 34 days. The Kaplan Meier estimate was for 90 days, however, the graph ended at the 34th day since all of the events occurred at or before the 34th day; we have revised the figure caption to add the details.

Remission and relapse information are provided but majority were “neither”. It is not clear what exactly it means. If it indicates that the patient was undergoing the initial therapy for the primary malignancy, it should be clarified. The implication is significantly different if they were on treatment versus not. The research would be valuable if this study was focused on patients who were undergoing treatment for hematologic malignancy or those who experienced COVID during therapy or within 30 (or whatever number) days from the completion of treatment. Or, the complete opposite would be to focus on those who were in remission and not receiving treatment. In any case, such full analyses may not be necessarily feasible due to limited number of patients.

Response: Thank you very much for the question, this study is conducted in patients undergoing chemotherapy for the primary malignancy. Thus all patients are currently receiving chemotherapy. We have added this to the methods section, we would like to apologize for the vague statement.

The timing that FIB-4 was calculated based on the value at the time of admission. It is possible that the FIB-4 reflects the severity of the disease as it worsens, but not necessarily prognostic as one single parameter at diagnosis. It is worth mentioning the time from the onset of symptoms to admission (FIB-4 assessment) or time from diagnosis to admission (FIB-4 assessment). Or FIB-4 at the time of diagnosis, if available, would be also valuable.

Response: Thank you very much for the suggestion, all patients in this study are patients undergoing chemotherapy for hematological malignancies. COVID-19 screening test using RT-PCR of nasopharyngeal samples are performed prior to hospitalization for chemotherapy, thus, the time from diagnosis to admission is within a few hours. We have added this to the methods section. As for the onset of symptoms to admission, we cannot provide adequate/clear documentation because many of symptoms overlap with those of malignancies and many patients display no COVID-19 related symptoms (24 patients).

At last, but not least, FIB-4 formula was “borrowed” from other studies (originally from chronic liver scarring) but there is no rigorous evaluation of the formula itself in this context. Why ALT needs to be square rooted and placed in the denominator? The impact of age (e.g. 1 vs 10 vs 50) is appropriately reflected in this formula? Such discussion or consideration, or to state the limitation of the current study in this regard would strengthen the paper.

Response: Thank you very much for the suggestion. Unfortunately, the reasoning for the formula is because one of the authors (Pranata R) published a paper on the use of FIB-4 Index in patients with COVID-19 (meta-analysis), many of the included studies are conducted in patients without liver diseases. Thus this is a simple repurposing of a widely used scoring method (so it can be directly used without creating an additional model to an already congested pool of prediction models), which include several important variables in patients with hematological malignancies. It turns out to be a good prediction model. Thus the model is not based on meticulous formula derived from rigorous evaluation, we have added this to the limitation section.

Decision Letter 1

Senthilnathan Palaniyandi

2 Sep 2021

PONE-D-21-11387R1

Repurposing FIB-4 Index as a Predictor of Mortality in Patients with Hematological Malignancies and COVID-19

PLOS ONE

Dear Dr. Sutandyo,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

We have received the opinions of expert reviewer and we invite you to submit a revised version of the manuscript. 

Please submit your revised manuscript by Oct 17 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Senthilnathan Palaniyandi, Ph.D

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments (if provided):

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

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 #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

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 #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

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.

Reviewer #2: 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 #2: The authors addressed points that were raised by the reviewers adequately.

The only minor point is, in Page 8, "Consecutive sampling of adults who were tested positive for COVID19 while undergoing chemotherapy for hematological malignancy" would be a better description of the population analyzed.

**********

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.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

[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.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2021 Sep 23;16(9):e0257775. doi: 10.1371/journal.pone.0257775.r004

Author response to Decision Letter 1

4 Sep 2021

Reviewer #2: The authors addressed points that were raised by the reviewers adequately.

The only minor point is, in Page 8, "Consecutive sampling of adults who were tested positive for COVID19 while undergoing chemotherapy for hematological malignancy" would be a better description of the population analyzed.

Response: Thank you very much for the suggestion, we have revised accordingly.

Attachment

Submitted filename: Response to Reviewer 2.docx

Click here for additional data file. (11.9KB, docx)

Decision Letter 2

Senthilnathan Palaniyandi

10 Sep 2021

Repurposing FIB-4 Index as a Predictor of Mortality in Patients with Hematological Malignancies and COVID-19

PONE-D-21-11387R2

Dear Dr. Sutandyo,

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.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. 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.

Kind regards,

Senthilnathan Palaniyandi, Ph.D

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

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 #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

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 #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #2: No

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Reviewer #2: No

Acceptance letter

Senthilnathan Palaniyandi

14 Sep 2021

PONE-D-21-11387R2

Repurposing FIB-4 Index as a Predictor of Mortality in Patients with Hematological Malignancies and COVID-19

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

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    Submitted filename: Response to Reviewer 2.docx

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    Data Availability Statement

    Data cannot be shared publicly because the data contain potentially identifying or sensitive patient information. The Ethical Research Committee of Dharmais National Cancer Hospital, Indonesia imposes strict restriction regarding patients’ confidentiality. However, all reasonable data access requests may be sent to the Ethical Research Committee of Dharmais National Cancer Hospital, Indonesia (email: kepkdharmais@gmail.com) or to the address at Jl. Letjen S. Parman No.84-86, Kota Bambu Selatan, Kec. Palmerah, Kota Jakarta Barat, Daerah Khusus Ibukota Jakarta 11420.

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