Abstract.
– OBJECTIVE: This study aimed to compare the mortality rate between ad- vanced-stage non-small cell lung cancer patients (NSCLC) with and without COVID-19. This study also explores the possible laboratory character- istics used for prognostication in patients with NSCLC and COVID-19. Additionally, this study evaluated potential differences in laboratory val- ues between the case and control groups.PATIENTS AND METHODS: This is a sin- gle-center retrospective cohort study conduct- ed in Dharmais National Cancer Hospital, Indo- nesia, enrolling patients with NSCLC undergoing chemotherapy or targeted therapy between May 2020 and January 2021. All patients with NSCLC and COVID-19 in these periods were enrolled in- to the case group. The control group was age- matched NSCLC patients without COVID-19 that was derived from the NSCLC cohort through randomization.
RESULTS: There were 342 patients with NS- CLC between May 2020 and January 2021. Twen- ty-seven (7.9%) of the patients were infected by COVID-19. To facilitate comparison, thirty-five age-matched controls with NSCLC were select- ed from the cohort.
The mortality rate in patients with COVID-19 was 46.2%. Eleven patients (40.7%) had severe COVID-19, of which none survived. NLR >8.35 has a sensitivity of 83.3%, specificity of 92.9%, LR+ of 12, and LR- of 0.18. The AUC was 0.946 (95% CI 0.867-1.000), p<0.001. PLR >29.14 has a sensitivity of 75.0%, specificity of 71.4%, LR+
2.62, LR- 0.35, and AUC 0.851 (95% CI 0.706- 0.996), p=0.002. Both NLR and PLR were associ-
ated with shorter time-to-mortality in the unad- justed and adjusted model
CONCLUSIONS: NLR and PLR are indepen- dent predictors of mortality in COVID-19 patients with NSCLC.
Key Words:
Lung cancer, COVID-19, Mortality, Neutro- phil-to-Lymphocyte Ratio, Platelet-to-Lymphocyte ratio.
Introduction
Coronavirus disease 2019 (COVID-19) is cur- rently one of the most common diseases global- ly, causing a considerable death toll
1. Although most patients have mild-moderate clinical man- ifestations, a significant proportion developed life-threatening complications
2-4. This is espe- cially true in patients with comorbidities
5-14. The cases of COVID-19 remain high and threaten to overwhelm the healthcare system; thus, risk strat- ification for prudent resource allocation is need- ed. Several biomarkers have been evaluated or repurpose to attain this objective
15,16.
Cancer is prevalent and remains the second lead- ing cause of death in the world
17. COVID-19 patients with cancer had a higher mortality rate compared to those without
18,19. This study aimed to compare the mortality rate between advanced-stage non-
N. SUTANDYO
1, A.M. JAYUSMAN
2, L. WIDJAJA
3, F. DWIJAYANTI
3, P. IMELDA
4, A.R. HANAFI
21
Lung Cancer Teamwork, Department of Medical Hematology-Oncology, Dharmais National Cancer Center, Jakarta, Indonesia
2
Lung Cancer Teamwork, Department of Pulmonology, Dharmais National Cancer Center, Jakarta, Indonesia
3
Department of Research and Development, Dharmais National Cancer Center, Jakarta, Indonesia
4
Lung Cancer Research Team, Dharmais National Cancer Center, Jakarta, Indonesia
Neutrophil-to-lymphocyte ratio and
platelet-to-lymphocyte ratio as mortality
predictor of advanced stage non-small cell lung
cancer (NSCLC) with COVID-19 in Indonesia
small cell lung cancer (NSCLC) patients with and without COVID-19. This study also explores the possible laboratory characteristics that might be used for prognostication in patients with NSCLC and COVID-19. Additionally, this study evaluated potential differences in laboratory values between the case and control groups.
Patients and Methods Study Design
This is a single-center retrospective cohort study conducted in the Dharmais National Can- cer Hospital, Indonesia. There were 342 consec- utive patients with NSCLC undergoing chemo- therapy or targeted therapy between May 2020 and January 2021. All patients with NSCLC and COVID-19 in these periods were enrolled into the case group. The control group was age-matched NSCLC patients without COVID-19 that was derived from the NSCLC cohort through ran- domization. COVID-19 diagnosis was based on reverse transcriptase polymerase chain reaction (RT-PCR) examination performed before che- motherapy/targeted therapy regimen. Data on baseline characteristics and admission laborato- ry values were extracted from medical records.
The study was performed following the ethical standards of the Helsinki Declaration. Informed consent was not obtained because the study was retrospective observational in nature.
Outcome
The primary outcome of this study is mor- tality, defined as clinically validated death/
non-survivor. The outcome was ascertained from the medical record confirmed by the death certificate. A research that was independent of the data collection process or patient care per- formed the statistical analysis. We compared the mortality rate between the case and control groups. This study also explores the possible laboratory characteristics that might be used for prognostication in patients with NSCLC and COVID-19. Additionally, this work evalu- ated potential differences in laboratory values between the case and control groups.
Statistical Analysis
Statistical analysis was performed using SPSS 25.0 (IBM SPSS Statistics for Windows, Armonk, NY, USA) and STATA 14.0 (College Station, TX, USA). We test continuous data for normal distri-
bution; a t-test was used for normally distributed data, and the Mann-Whitney test was used for abnormally distributed data. Normally distribut- ed continuous data were presented as mean and standard deviation (SD), while abnormally dis- tributed continuous data were reported as median and interquartile range (IRQ). ROC curve analy- sis was performed to determine the optimal cut- off points for the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), which were found to be significantly different in non-survivors compared to survivors. The sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), and area under the curve (AUC) were calculated. Fagan’s nomogram was plotted to determine the posteri- or probability of mortality for the cut-off points determined by ROC curve analysis. Chi-square test or Fischer-Exact test was performed for cate- gorical variables. To obtain the hazard ratio (HR) and survival curve, we performed Cox-regression analysis. Multivariable Cox-regression analysis was performed by adjusting for age. The number of variables for adjustment was limited to avoid model-overfitting.
Results
There were 342 patients with NSCLC be- tween May 2020 and January 2021. Twen- ty-seven (7.9%) of the patients were infected by COVID-19. To facilitate comparison, thirty-five age-matched controls with NSCLC were select- ed from the cohort.
Cases and Controls
In this case-control study, there were 62 pa- tients. There were 27 patients in the COVID-19 positive group and 35 patients in the COVID-19 negative group. There is no significant difference observed in laboratory values between the cases and controls (Table I). The mortality rate between the case and control groups did not significantly differ (44.4% vs. 42.9%, p=0.901).
Patients With NSCLC and COVID-19 The mortality rate in patients with COVID-19 was 44.4%. Among the sixteen patients (59.3%) with mild-moderate COVID-19, nine (33.3%) were asymptomatic, four (14.8%) have mild symp- toms, and three (11.1%) have moderate symptoms.
Eleven patients (40.7%) had severe COVID-19.
All patients with severe COVID-19 did not sur-
vive, in contrast to only one patient (6.3%) with mild-moderate illness. Non-survivors have sig- nificantly higher numbers of leukocytes, NLR, and PLR (Table II). NLR >8.35 has a sensitivity of 83.3%, specificity of 92.9%, LR+ of 12, and LR- of 0.18. The AUC was 0.946 (95% CI 0.867- 1.000), p<0.001 (Figure 1). Patients with NLR
>8.35 has 91% posterior probability of mortality.
An NLR <8.35 has 13% posterior probability of mortality (Figure 2). NLR >8.35 was associated with shorter time-to-mortality in unadjusted (HR 10.53 (95% CI 2.29-50), p=0.003) (Figure 3) and
age-adjusted model (HR 14.50 (95% CI 2.84- 76.9), p=0.001).
PLR >29.14 has a sensitivity of 75.0%, specific- ity of 71.4%, LR+ 2.62, LR- 0.35, and AUC 0.851 (95% CI 0.706-0.996), p=0.002. Patients with PLR
>29.14 has 69% posterior probability of mortality.
An PLR <29.14 has 23% posterior probability of mortality (Figure 4). PLR >29.14 was associated with shorter time-to-mortality in unadjusted (HR 4.41 (95% CI 1.18-16.40), p=0.027) (Figure 5) and adjusted model (HR 4.41 (95% CI 1.18-16.40), p=0.027).
Table I. Baseline Characteristics of cases and controls.
COVID-19 (+) n=27 COVID-19 (-) n=35 p-value
Age (years) 59.89±9.5 59±9.2 0.713
Gender 20 (44.4) 25 (55.6) 0.817
BMI (kg/m2) 20.8±3.1 20.1±4.4 0.511
Lung Cancer Type
Undetermined 5 (18.5%) 0 (0%)
Adenocarcinoma 18 (66.7%) 29 (82.9%)
Squamous Cell Carcinoma 4 (14.8%) 6 (17.1%)
Cancer Stage
Undetermined 4 (14.8%) 1 (2.9%)
Stage III (a,b) 4 (14.8%) 9 (21.0%)
Stage IV 19 (70.4%) 25 (71.4%)
Laboratory Values
Hemoglobin (g/dL) 11.5±1.5 11.9±1.7 0.425
Leukocyte (x 109/L) 12.0 (8.8) 10.6 (13.3) 0.804
Platelets (x 109/L) 349.1±141.3 316.8±135.3 0.368
ALC (103 cells/microL) 9.7±5.8 8.1±4.9 0.260
ANC (103 cells/microL) 8.6 (7.8) 8.7 (12.1) 0.694
NLR 5.5 (14.3) 9.0 (17.6) 0.137
PLR 29.1 (57.1) 38.3 (45.2) 0.457
Ureum (mg/dL) 28.5±9.3 36.8±32.8 0.163
Creatinine (mg/dL) 0.7 (0.6) 0.6 (1.3) 0.710
AST (U/L) 20 (15) 21 (13) 0.705
ALT (U/L) 14 (13) 16.5 (15) 0.640
Protein Total (g/dL) 6.5±0.9 6.3±1.0 0.273
Albumin (g/dL) 3.3±0.6 3.6±0.7 0.417
Globulin (g/dL) 3.2±0.7 3.7±4.4 0.520
PT (s) 14±1.5 16.5±9.3 0.145
aPTT (s) 29.5 (5.5) 28.9 (4.9) 0.976
Fibrinogen (mg/dL) 506.3±169.9 469.8±167.9 0.479
D-Dimer (mg/dL) 1410 (2163) 1460 (1915) 0.759
CRP (mg/L) 52.1±35.2 46.0±42.5 0.705
Mortality 12 (44.4%) 15 (42.9%) 0.901
AST: aspartate aminotransferase, ALT: alanine aminotransferase, ALC: Absolute Lymphocyte Count, ANC: Absolute Neutrophil Count, aPTT: Activated Partial Thromboplastin Time, BMI: Body Mass Index, CRP: C-Reactive Protein, NLR: Neutrophil-to- Lymphocyte Ratio, PLR: Platelet-to-Lymphocyte Ratio, PT: Prothrombin Time.
Discussion
In this study, we found no significant differ- ence in mortality and laboratory parameters such as d-dimer between NSCLC patients with COVID-19 compared to those without. The mor- tality rate in patients with NSCLC and severe COVID-19 was 100%. We found that NLR >8.35 and PLR >29.14 were predictors of mortality in NSCLC patients with COVID-19.
This cohort showed that the rate of severe COVID-19 was 40.7% in patients with NSCLC and COVID-19. In which death occurs in 100%
of patients with severe COVID-19. This trans- lates to a 40.7% mortality in NSCLC patients with COVID-19, which is higher compared to the 2.2% in the general population1. It should be noted that the RT-PCR performed in this study was not based on symptoms, but rather a screen- ing prior to chemotherapy. This is supported by the fact that 33.3% of the patients have no COVID-19 related symptoms. Thus, this study may represent the rate of severe COVID-19 among patients with NSCLC undergoing che- motherapy or targeted therapy. Considering these facts, vaccination should be provided to the caregiver or close relatives of the patients.
Nevertheless, we observed no statistically sig- nificant difference between the mortality rate in those with and without COVID-19. Hence, the high mortality in the case group might also be due to the natural course of NSCLC. Regard-
less, chemotherapy for these patients should not be deferred; we have seen reduced hospital ad-
Figure 2. Fagan’s nomogram for neutrophil-to-lympho- cyte ratio.
Figure 1. Receiver operating characteris- tics curve for neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and mortality.
missions due to fear of contracting COVID-19 in other diseases
22-26, and this issue needs to be addressed.
Biomarkers derived from laboratory examina- tions or imaging are important for risk stratifica- tion in COVID-19 patients
15,16,27-37. NLR was pre- viously shown to be an independent predictor of mortality in patients with cancer
38,39. In patients with COVID-19, NLR was also shown to be an important predictor of mortality
40-42. Although we observed no significant difference between NSCLC patients with and without COVID-19 in terms of NLR, we found that NLR >8.35 was an independent predictor of mortality in patients
with NSCLC and COVID-19, with 83.3% sensi- tivity and 92.9% specificity. Due to the limited number of events (deaths), we only adjust age for the cox-regression analysis. This is because age is an important predictor of mortality (directly and indirectly through comorbidities/associated medications), and older age is associated with im- munosenescence which may impair the immune response to COVID-1911
43-49. Since NLR is pri- marily related to the immune response, consider- ing age as a covariate for adjusted model is im- portant. There are several hypotheses that explain the underlying mechanism between increased NLR and poor prognosis. NLR indicates endothe-
Table II. Baseline characteristics of patients with COVID-19.
COVID-19 non-Survivor n=12 COVID-19 survivor n=15 p-value
Age (years) 59.0±10.3 60.6±9.2 0.678
Gender (Male) 10 (83.3%) 10 (66.7%) 0.408
BMI (kg/m2) 21.0±3.4 20.6±3.0 0.785
Severe COVID-19 11 (91.7%) 0 (0%) <0.001
Lung Cancer Type
Undetermined 3 (25.0%) 2 (13.3%)
Adenocarcinoma 6 (50.0%) 12 (80.0%)
Squamous Cell Carcinoma 3 (25.0%) 1 (6.7%)
Cancer Stage
Undetermined 2 (16.7%) 2 (13.3%)
Stage III (a,b) 1 (8.3%) 3 (20.0%)
Stage IV 9 (75.0%) 10 (75.0%)
Laboratory Values
Hemoglobin (g/dL) 11.8±1.7 11.4±1.3 0.526
Leukocyte (x 109/L) 17.6±7.7 9.9±4.5 0.017
Platelets (x 109/L) 307.9±128.9 382.1±146.4 0.174
ALC (103 cells/microL) 5.7±3.7 12.8±5.2 <0.001
ANC (103 cells/microL) 11.4 (9.2) 8.1 (2.3) 0.004
NLR 15.7 (37.9) 3.4 (5.3) <0.001
PLR 72.7 (104.7) 21.7 (30.1) 0.002
Ureum (mg/dL) 34.8±7.8 23.9±7.5 0.002
Creatinine (mg/dL) 0.7±0.4 0.8±0.2 0.704
AST (U/L) 28 (21) 16.5 (12) 0.235
ALT (U/L) 14 (6) 16 (26) 0.845
Protein Total (g/dL) 6.7 (1.05) 7.0 (1.1) 0.478
Albumin (g/dL) 3.6±0.6 3.0±0.5 0.043
Globulin (g/dL) 3.4±0.8 3.0±0.6 0.196
PT (s) 14±1.7 13.5±1.1 0.060
aPTT (s) 28.8 (5.3) 29.9 (5.3) 0.437
Fibrinogen (mg/dL) 552.3±175.1 472.9±166.0 0.335
D-Dimer (mg/dL) 5543.3±8613.6 3316.2 (7481.6) 0.499
CRP (mg/L) 57.2±40.0 44.5±30.5 0.586
AST: aspartate aminotransferase, ALT: alanine aminotransferase, ALC: Absolute Lymphocyte Count, ANC: Absolute Neutrophil Count, aPTT: Activated Partial Thromboplastin Time, BMI: Body Mass Index, CRP: C-Reactive Protein, NLR: Neutrophil-to- Lymphocyte Ratio, PLR: Platelet-to-Lymphocyte Ratio, PT: Prothrombin Time.
lial dysfunction, which may cause cellular dam- age and endothelial cell damage
42. In predisposed individuals with endothelial dysfunction, such as patients with cancer undergoing chemothera- py
50, COVID-19 induced endothelial dysfunction will further aggravate the pathology and causes more pronounced inflammation. Hence, patients with cancer and COVID-19 are expected to have a poorer prognosis
51, and the risk can be strati- fied by measuring NLR. Increased neutrophils may indicate the degree of the inflammatory re- sponse, and the decreased lymphocytes indicate the degree of immune imbalance
52. Rapid coro- navirus replication causes delayed IFN response and causes T cells apoptosis; neutrophils are then recruited and infiltrate the lungs
53,54. Additionally, a direct viral infection of lymphocytes may cause lymphocyte loss
55. In which, NLR may also indi- rectly reflect the viral load.
In addition to lymphocytes, platelets also play an important role in patients with COVID-19. It is shown that thrombocytopenia was associated with a poor prognosis in patients with COVID-19
15,56. Altered platelet production and accelerated con- sumption/destruction in patients with COVID-19 may cause thrombocytopenia
57. SARS-CoV-2 may invade bone marrow cells and platelets via CD13 receptor, causing growth inhibition and apopto- sis
58-60. Inhibition of the hematopoietic stem cells, suppressed thrombopoietin production, and mega- karyocyte maturation might be caused by inflam- matory cytokines
61. COVID-19 associated lung damage may reduce supplementary hematopoietic progenitor in the pulmonary vessels
62. Accelerated platelet consumption or destruction due to inflam-
mation, coagulopathy, and secondary hemophago- cytic lymphohistiocytosis may further reduce platelets
57,59,63. Antibodies may bind to platelet an-
Figure 3. The survival curve based on neu- trophil-to-lymphocyte ratio >8.35.
Figure 4 Fagan’s nomogram for platelet-to-lymphocyte ratio.
tigens and cause platelet destruction via molecu- lar mimicry
58,59,64. However, we did not observe a difference in platelet levels between survivors and non-survivors. PLR, which takes both platelets and lymphocytes into account may be more sensitive to changes related to COVID-19 induced inflam- mation. PLR has been shown to be associated with mortality in patients with NSCLC
65-67. Platelet and lymphocyte function are closely related, platelet factor-4 may prevent agglutinin-A from inhibit- ing lymphocyte generation, and activated platelets enhance lymphocyte adhesion to the endothelium, which promotes lymphocyte homing in endothe- lial veins and migration to inflammatory sites
68. PLR reflects both aggregation and inflammatory pathways and might be more useful than platelet or lymphocyte counts alone
68,69. In this study, PLR
>29.14 was an independent predictor of mortality with 75% sensitivity and 74.1% specificity.
There are several limitations in this study. First is the retrospective nature of the study, which is more prone to biases. Second, despite being the national referral center for cancer, the sample size for patients with COVID-19 was small. Thirdly, inflammatory markers such as interleukins were not measured in most of the patients.
Conclusions
The mortality rate in patients with NSCLC and COVID-19 is high; however, the overall mortali- ty does not significantly differ from those without COVID-19. The mortality rate in patients with NS-
CLC and severe COVID-19 was 100%. NLR >8.35 and PLR >29.14 were independent predictors of mortality in NSCLC patients with COVID-19.
Conflict of Interest
The Authors declare that they have no conflict of interests.
Acknowledgement
The COVID-19 mitigation team; Department of Research and Development, Dharmais National Cancer Center, Ja- karta, Indonesia.
Ethical Approval
This study has approved by The Research Ethics Commis- sion of the Dharmais Cancer Hospital, with The Ethical clearance, No. 149/KEPK/X/2020..
Data Availability
The Authors declare that they have no conflict of interests.
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