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ABSTRACT The aim of this study was to investigate the diagnostic value of the platelet count-to-spleen volume ratio (PSR) for diagnosing hepatic fibrosis in patients with hepatocellular

carcinoma (HCC). In this interim analysis of an on-going prospective study, 117 patients with HCC and with or without cirrhosis or fibrosis in different stages were analyzed. Fibrosis

staging negatively correlated with PSR and the liver volume-to-spleen volume ratio (LSR), while it positively correlated with aspartate aminotransferase-to-platelet ratio index (APRI),

Frons’ index, S-index and a fibrosis index based on four factors (FIB-4). The area under the receiver operating characteristic curve (AUROC) was significantly larger for PSR (0.777) than LSR

(0.633, _P_ = 0.002). Among patients with significant fibrosis, AUROC for PSR did not differ significantly from the AUROCs for APRI (0.789, _P_ = 0.825), Frons’ index (0.674, _P_ = 0.102),

FIB-4 (0.704, _P_ = 0.251) or S-index (0.696, _P_ = 0.204). Among patients with severe fibrosis, AUROC was significantly higher for PSR (0.808) than for LSR (0.685, _P_ = 0.003), Frons’

index (0.673, _P_ = 0.014), FIB-4 (0.684, _P_ = 0.029), or S-index (0.672, _P_ = 0.016); in contrast, the AUROC for PSR was not significantly different from that for APRI (0.739, _P_ = 

0.215). Among patients with cirrhosis, AUROC was significantly higher for PSR (0.814) than for LSR (0.671, _P_ = 0.001) or S-index (0.679, _P_ = 0.022), while the AUROC for PSR did not

differ significantly from those for APRI (0.711, P = 0.105), Frons’ index (0.722, _P_ = 0.061) or FIB-4 (0.708, _P_ = 0.079). Our results suggest that PSR may be a useful non-invasive model

for diagnosing liver fibrosis stage in patients with HCC in China. SIMILAR CONTENT BEING VIEWED BY OTHERS ROLE OF FIB-4 FOR REASSESSMENT OF HEPATIC FIBROSIS BURDEN IN REFERRAL CENTER Article

Open access 30 June 2021 ALBUMIN PLATELET PRODUCT AS A NOVEL SCORE FOR LIVER FIBROSIS STAGE AND PROGNOSIS Article Open access 05 March 2021 DGPRI, A NEW LIVER FIBROSIS ASSESSMENT INDEX,

PREDICTS RECURRENCE OF AFP-NEGATIVE HEPATOCELLULAR CARCINOMA AFTER HEPATIC RESECTION: A SINGLE-CENTER RETROSPECTIVE STUDY Article Open access 10 May 2024 INTRODUCTION Hepatocellular

carcinoma (HCC) is a common malignancy and the third leading cause of cancer-related mortality worldwide; it accounts for one-fifth of all cancer cases wordwide1. A leading cause of HCC as

well as cirrhosis is chronic hepatitis B, a disease caused by hepatitis B virus (HBV)2. Approximately 80% of patients with HCC in China have either cirrhosis or some degree of hepatic

fibrosis. Surgical resection remains the best treatment for HCC patients who cannot undergo liver transplantation. Preoperative assessment of liver fibrosis and cirrhosis is crucial for

optimizing patient prognosis. The severity of liver fibrosis and cirrhosis is closely related to preoperative hepatic reserve function as well as postoperative regeneration of remnant liver

volume. Thus, this severity limits how much of the liver can be removed during hepatectomy, which can jeopardize negative margins. The gold standard for diagnosing and staging hepatic

fibrosis is liver biopsy, but in fact biopsy is rarely used because of its invasiveness and complications. The accuracy of liver biopsy is also severely compromised by intra- and

inter-observer variation as well as sampling error3,4,5. This has led several studies to explore non-invasive models for diagnosing different stages of hepatic fibrosis6,7,8,9. These models

include the aspartate transaminase-to-platelet ratio index (APRI), Frons’ index, and a fibrosis index based on four factors (FIB-4). These models are already used to evaluate liver fibrosis

in patients who are chronically infected or coinfected with HBV or hepatitis C virus or who have non-alcoholic fatty liver disease (NAFLD). Indeed, the World Health Organization recommends

the APRI and FIB-4 as non-invasive tools to detect significant fibrosis in resource-limited settings. To the best of our knowledge, these models have yet to be used to diagnose hepatic

fibrosis in HCC patients scheduled to undergo hepatectomy. Although APRI and FIB-4 are calculated in a straightforward way from routine blood and serum parameters, they show low sensitivity.

They also appear to be inaccurate at diagnosing mild or moderate hepatic fibrosis10,11. Potentially more promising diagnostic indices have appeared with the advent of precise hepatectomy as

a result of the increasing application of high-resolution imaging and automated image analysis12. For example, studies13,14,15 have indicated a correlation between hepatosplenic volume and

hepatic cirrhosis. The liver-to-spleen volume ratio (LSR) has shown potential for diagnosing advanced liver fibrosis16,17. Another study18 has suggested that LSR can discriminate between

advanced and severe fibrosis in patients infected with hepatitis C virus. Whether LSR can similarly diagnose the stage of hepatic fibrosis in HCC patients does not appear to have been

reported. In our efforts to improve on existing diagnostic indices of fibrosis in HCC patients, we reasoned that spleen volume and platelet count can reflect the severity of cirrhosis, and

that spleen volume may be a more stable index than liver volume in HCC. Therefore we defined the platelet count-to-spleen volume ratio (PSR) as a novel, non-invasive fibrosis model and

assessed its ability to diagnose liver fibrosis stage in HCC patients. We compared PSR performance with that of traditional models for diagnosing liver fibrosis stage. Our results suggest

that PSR, which can be calculated more easily than other models, may be more accurate for diagnosing hepatic fibrosis stage in HCC and therefore more effective at guiding hepatectomy.

METHODS ETHICS STATEMENT This study was conducted in accordance with the Declaration of Helsinki and was approved by the Affiliated Tumor Hospital of Guangxi Medical University Ethnics

Committee. All participants gave written informed consent for their clinical records to be used in this study. PATIENTS This report is an interim analysis of an on-going prospective study

involving patients scheduled to undergo curative liver resection (defined as complete macroscopic removal of the tumor) in the Department of Hepatobiliary Surgery at the Affiliated Tumor

Hospital of Guangxi Medical University. The patients in the present study were consecutively enrolled from the start of the study in October 2015 until May 2016. To be enrolled, patients had

to satisfy the following inclusion criteria: (1) initial HCC diagnosis; (2) a single tumor in stage A of the Barcelona Clinic Liver Cancer (BCLC) system, which was confirmed as HCC based on

postoperative pathology; (3) complete hepatic fibrosis staging based on pathology; and (4) liver computed tomography within one week before hepatectomy. Patients were excluded from the

study if they (1) had another malignancy before hepatectomy; (2) received preoperative cancer treatment such as radio- or chemotherapy or transcatheter arterial chemoembolization; (3)

already had undergone previous hepatectomy; or (4) had diabetes, HIV infection, or other severe disease. CLINICAL AND LABORATORY ASSESSMENT Before hepatectomy, data on all patients were

collected from medical records regarding demographics, liver biochemistry, hepatitis virus infection status, and hematological parameters. Fasting blood samples were collected between 6:30

and 8:00 a.m. on the day before hepatectomy. Liver biochemistry tests involved total bilirubin, albumin (ALB), ferritin, aspartate aminotransferase (AST), alanine transaminase (ALT),

gamma-glutamyl transpeptidase (GGT), total cholesterol (TC), and prothrombin time (PT). Hematological tests assayed hemoglobin levels and determined counts of red blood cells (RBCs), white

blood cell (WBCs), and platelets. LIVER AND SPLEEN VOLUME Images (5 mm thick) of the contiguous artery phase, portal venous phase and delayed phase were imported into a three-dimensional

surgical simulation system (Myrian XP Liver 1.30.79.4, Intrasense, France). Portal venous phase images were adopted for image analysis and for calculation of liver and spleen volume. The

contours of the liver and spleen were delineated by hand using a computer mouse, the areas within the contours of liver and spleen were filled with different colors, and the gallbladder and

inferior vena cava were eliminated from each slice. The volumes enclosed by the liver and spleen contours were automatically calculated using the Myrian XP Liver software (Fig. 1).

HISTOLOGICAL ASSESSMENT Specimens of resected liver tissue were fixed in 10% buffered formalin, embedded in paraffin, and stained with hematoxylin and eosin (HE), Masson’s trichrome and

reticular fiber staining. Diagnosis was confirmed based on analysis of at least 1.5 cm of liver tissue containing at least five portal tracts. Two histologists independently determined the

extent of hepatic fibrosis in each sample using the METAVIR scoring system19: F0, no fibrosis; F1, expansion of portal zones; F2, expansion of most portal zones and occasional bridging; F3,

expansion of most portal zones and marked bridging and occasional modules; F4, cirrhosis. Histologists were blinded to patients’ results for hepatic fibrosis models. Disagreements between

the histologists were resolved by consensus. HEPATIC FIBROSIS MODELS Patients were assessed using the following hepatic fibrosis models7,20,21,22: $$\begin{array}{rcl}{\rm{PSR}} & =

& {\rm{platelet}}\,{\rm{count}}\,({10}^{9}/{\rm{L}})/{\rm{spleen}}\,{\rm{volume}}\,(\mathrm{ml})\\ {\rm{LSR}} & = &

{\rm{liver}}\,{\rm{volume}}\,({\rm{ml}})/{\rm{spleen}}\,{\rm{volume}}\,({\rm{ml}})\\ {\rm{APRI}} & = & 100\times

({\rm{AST}}\,({\rm{IU}}/{\rm{L}})/{\rm{upper}}\,{\rm{normal}}\,{\rm{limit}}\,{\rm{of}}\,{\rm{AST}})\\ & & /{\rm{platelet}}\,{\rm{count}}\,({10}^{9}/{\rm{L}})\\

{\rm{Frons}}\mbox{'}\,{\rm{index}} & = & 7.811-3.131\times {\rm{In}}\,(\mathrm{platelet}\,{\rm{count}}\,({10}^{9}/{\rm{L}}))+0.781\\ & & \times

\,{\rm{In}}\,({\rm{GGT}}\,(\mathrm{IU}/{\rm{L}}))+3.467\times {\rm{In}}\,(\mathrm{age}\,({\rm{year}}))-0.014\times ({\rm{TC}}).\\ {\rm{FIB}}-4 & = &

({\rm{age}}\,(\mathrm{year})\times {\rm{AST}}\,({\rm{IU}}/{\rm{L}}))/({\rm{platelet}}\,{\rm{count}}\,({10}^{9}/{\rm{L}})\\ & & \times \,{({\rm{ALT}}(\mathrm{IU}/{\rm{L}}))}^{1/2})\\

{\rm{S}}-{\rm{index}} & = & 1000\times {\rm{GGT}}\,({\rm{IU}}/{\rm{L}})/({\rm{PLT}}\,({10}^{9}/{\rm{L}})\times {({\rm{ALB}}({\rm{g}}/{\rm{L}}))}^{2})\end{array}$$ STATISTICAL

ANALYSIS Continuous variables were expressed as mean ± standard deviation, while categorical variables were expressed as number (percentage). Univariate analysis was performed using one-way

ANOVA or, in the case of continuous variables showing a skewed distribution, the nonparametric Kruskal-Wallis H test in order to identify significant differences in the ability of the six

hepatic fibrosis models (PSR, LSR, APRI, Frons’ index, FIB-4, S-index) to differentiate patients in different stages of liver fibrosis. Correlations between hepatic fibrosis models and liver

fibrosis stage were assessed using the Spearman rank correlation coefficient. These statistical analyses were performed using SPSS 23.0. Diagnostic accuracy of each hepatic fibrosis model

was assessed based on the area underneath the receiver operating characteristic curve (AUROC). The sensitivity, specificity, positive predictive value, negative predictive value and AUROC

were determined for each fibrosis model in the case of patients with significant fibrosis (defined as ≥F2), severe fibrosis (≥F3) or cirrhosis (F4). Receiver operating characteristic curves

were analyzed statistically using Medcalc 15.2.0. All P values are 2-sided, and P < 0.05 was considered statistically significant. RESULTS Table 1 shows the main demographic and clinical

characteristics of the study population of 117 patients, including 98 (83.76%) men and 19 (16.24%) women. Of all 117 patients, 96 (82.05%) were HBsAg-positive and 110 (94.02%) had Child-Pugh

class A liver function, while the remaining 7 (5.98%) had Child-Pugh class B liver function. The distribution of METAVIR scores for hepatic fibrosis was as follows: F0, 6 (5.13%) patients;

F1, 29 (24.79%) patients; F2, 25 (21.37%) patients; F3, 21 (17.95%) patients; and F4, 36 (30.77%) patients. Figure 2 shows representative pathology images from patients with the different

METAVIR scores. Given the small number of F0 patients, we pooled F0 and F1 patients into a group with “no significant fibrosis” (F0-F1). Potential correlation between liver fibrosis models

and fibrosis stage based on postoperative pathology was explored using Spearman rank correlation (Table 2). Fibrosis staging negatively correlated with PSR (r = −0.577) and LSR (r = −0.312),

while it positively correlated with APRI (r = 0.476), Frons’ index (r = 0.366), FIB-4 (r = 0.384) and S-index (r = 0.353). PSR differed significantly among the four subgroups of patients

with no significant fibrosis, significant fibrosis, severe fibrosis or cirrhosis, and it differed significantly between all pairs of these four subgroups. The other indices tested in this

study (LSR, APRI, Frons’ index, FIB-4, S-index) did not differ significantly from PSR for any of the four patient subgroups (P < 0.05, Table 3 and Fig. 3). Next we compared the models for

their ability to diagnose significant fibrosis, severe fibrosis, and cirrhosis (Table 4 and Fig. 4). AUROC was significantly higher for PSR than for LSR among patients with significant

fibrosis (0.777 vs. 0.633, Z = 3.096, _P_ = 0.002), severe fibrosis (0.808 vs. 0.685, Z = 2.992, _P_ = 0.003), or cirrhosis (0.814 vs. 0.671, Z = 3.511, _P_ < 0.001). Among patients with

significant fibrosis, AUROC for PSR (0.777) did not differ significantly from AUROCs for APRI (0.789, Z = 0.221, _P_ > 0.05), Frons’ index (0.674, Z = 1.636, _P_ > 0.05), FIB-4 (0.704,

Z = 1.147, _P_ > 0.05), or S-index (0.696, Z = 1.269, _P_ > 0.05). Among patients with severe fibrosis, AUROC for PSR (0.808) was not significantly different from that for APRI

(0.739, Z = 1.24, _P_ > 0.05), but it was significantly higher than that for Frons’ index (0.673, Z = 2.468, _P_ < 0.05), FIB-4 (0.684, Z = 2.191, _P_ < 0.05), and S-index (0.672, Z

 = 2.401, _P_ < 0.05). Among patients with cirrhosis, AUROC for PSR (0.814) was not significantly different from that for APRI (0.711, Z = 1.623, _P_ > 0.05), Frons’ index (0.722, Z = 

1.876, _P_ > 0.05), or FIB-4 (0.708, Z = 1.756, _P_ > 0.05), but it was significantly higher than that for S-index (0.679, Z = 2.286, _P_ < 0.05). Among patients with significant

fibrosis, AUROC for LSR (0.633) was significantly lower than that for APRI (0.789, Z = 2.465, _P_ = 0.014), but it was not significantly different from that for Frons’ index (0.674, Z = 

0.527, _P_ > 0.05), FIB-4 (0.704, Z = 0.355, _P_ > 0.05), or S-index (0.696, Z = 0.792, _P_ > 0.05). Among patients with severe fibrosis, AUROC for LSR (0.685) was not significantly

different from that for APRI (0.739, Z = 0.843, _P_ > 0.05), Frons’ index (0.673, Z = 0.175, _P_ > 0.05), FIB-4 (0.684, Z = 0.013, _P_ > 0.05) or S-index (0.672, Z = 0.183, _P_ 

> 0.05). Similarly, among patients with cirrhosis, AUROC for LSR (0.671) was not significantly different from that for APRI (0.711, Z = 0.578, _P_ > 0.05), Fron’s index (0.722, Z = 

0.749, _P_ > 0.05), FIB-4 (0.708, Z = 0.532, _P_ > 0.05), or S-index (0.679, Z = 0.118, _P_ > 0.05). DISCUSSION Hepatectomy remains the first choice for treating HCC in patients who

do not undergo liver transplantation, although radio-, chemo-, bio-, and immunotherapy are also widely used23. The efficacy of these various approaches is still unsatisfactory. The main

cause of perioperative death is postoperative liver failure, which is associated with degree of hepatitis or cirrhosis in many HCC patients in China. The severity of hepatitis and cirrhosis

affects preoperative liver functional reserve, the liver volume that can be safely removed during hepatectomy, and postoperative residual liver regeneration. This highlights the importance

of preoperative assessment of hepatic fibrosis stage in HCC patients. Liver biopsy remains the main method for diagnosing hepatic fibrosis stage, but its invasiveness and associated

complications make it less widely used. As non-invasive alternatives, LSR and APRI and other indices have been tested for their ability to evaluate hepatic fibrosis in patients with chronic

liver disease. Here we provide one of the few reports assessing the ability of these indices to diagnose hepatic fibrosis in HCC patients scheduled to undergo hepatectomy. Furthermore, we

describe the novel model PSR and provide evidence that it may perform even better than LSR and other indices for patients with different extents of hepatic fibrosis. The results may help

guide rational and scientific surgical planning and postoperative treatment. In our study, fibrosis stage showed a significant negative correlation with PSR and LSR, but a significant

positive correlation with APRI, Frons’ index, FIB-4, and S-index. While these results cannot be directly compared with other studies, since those studies did not examine patients with HCC,

the data are consistent with previous work showing an association between these indices and fibrosis stage in other types of patients. One study18 reported a significant negative correlation

between LSR and hepatic fibrosis stage in patients infected with hepatitis C virus. Another study17 reported a strong correlation between LSR and fibrosis stage in patients who were

suspected of having chronic liver disease or who had focal hepatic lesions. Other work8,24 reported a correlation of APRI and FIB-4 with fibrosis stage in HBeAg-negative patients with

chronic hepatitis B and ALT ≤2 (upper normal limit) as well as in patients with chronic hepatitis B and non-alcoholic fatty liver disease. In this way, our results as well as the literature

indicate that the fibrosis models in our study may be used to diagnose hepatic fibrosis stage in HCC patients. The finding in our studies and others’ work that LSR and PSR gradually diminish

with hepatic fibrosis progression may reflect reduced blood perfusion in the portal vein and hepatic venous out-flow25. Reduction in the branches of the intrahepatic portal vein and in the

hepatic vascular bed as well as expansion of the fiber matrix lead to portal hypertension and liver atrophy. Portal hypertension then leads to spleen hypertrophy, further reducing platelet

count26,27. PSR relies on routine serum and biochemical parameters and on straightforward measurement of liver and spleen volume using widely available 3D reconstruction technology and 3D

surgery simulation systems. On the other hand, the time-consuming posting requested when using 3D simulation volumetry to calculate spleen and liver volumes may be a barrier to potential

widespread use. Our finding that PSR can be used to diagnose hepatic fibrosis stage in patients with HCC is consistent with studies showing that spleen volume and platelet count are closely

related to hepatic fibrosis. When we compared PSR with other hepatic fibrosis models, we obtained different results depending in the extent of fibrosis. Among patients with significant

fibrosis, AUROC for PSR was not significantly different from that for APRI, Frons’ index, FIB-4, or S-index. Among patients with severe fibrosis, AUROC for PSR was not significantly

different from that for APRI, but it was significantly higher than that for Frons’ index, FIB-4 and S-index. Among patients with cirrhosis, AUROC for PSR was not significantly different from

that of APRI, Frons’ index, or FIB-4, but it was significantly higher than that for S-index. These results suggest that PSR may be more stable than APRI, Frons’ index, FIB-4, and S-index

for evaluating liver fibrosis and cirrhosis in HCC patients. In addition, PSR appears to show greater diagnostic value than LSR for diagnosing significant fibrosis, severe fibrosis, or

cirrhosis. This may be because LSR involves total liver volume, which is closely related to tumor size in HCC patients. In addition, HCC cells may secrete active substances to promote the

proliferation of normal liver tissue, which may help to explain why liver volume is less stable than spleen volume. The other indices tested in this study (APRI, Frons’ index, FIB-4,

S-index) may be less reliable than PSR because they rely on multiple serum and biochemical parameters (e.g. AST, ALT, GGT), which may vary with many factors such as blood drawing time,

sample delivery time, cancer treatment, tumor size, and liver functional status. We emphasize that the results reported here are interim findings in an on-going prospective trial that will

ultimately analyze a larger sample. Conclusions therefore depend on subsequent validation with a larger study population. Given the interim nature of this analysis, we chose not to correct

for potential confounding due to factors such as sex, age, or body mass index. In any event, it seems less likely that these factors affect our results. For example, we are unaware of

evidence linking spleen volume to age, sex or BMI, and studies17,18 evaluating LSR and hepatic fibrosis in patients with chronic hepatitis B do not adjust for these factors. Similarly, the

World Health Organization recommendations for using APRI to detect significant fibrosis in resource-limited settings do not involve correcting for these three factors. Nevertheless, such

confounding analysis should be performed with a larger sample. In addition to our relatively small sample, our analysis is limited by the fact that we included only patients with single

tumors in BCLC stage A. Our results should be verified in patients with multiple tumors. It will also be interesting to see whether PSR can evaluate hepatic fibrosis stage in patients in

whom the portal vein is compressed by a large tumor, causing portal hypertension that ultimately leads to spleen hypertrophy. Such work will be important for establishing PSR as an easily

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Int._ 36, 124–129 (2016). Article  PubMed  Google Scholar  Download references ACKNOWLEDGEMENTS This research was supported by Medical and Health Suitable Technology Research and Development

Projects of Guangxi (grant S201516) and Guangxi Scientific Research and Technology Development Plan (grant 1355005-3-3). AUTHOR INFORMATION Author notes * Gao-Xiong Ouyang and Yu-mei Zhang

contributed equally. AUTHORS AND AFFILIATIONS * Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, 530021, China Gao-Xiong Ouyang, 

Shao-Liang Zhu, Yuan Ren, Jia-Hao Li, Yu-Kai Liu, Bang-De Xiang, Le-Qun Li, Jian-Yong Liu & Zhi-Ming Zhang * Department of Chemotherapy, Affiliated Tumor Hospital of Guangxi Medical

University, Nanning, 530021, China Yu-mei Zhang * Department of Radiology, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, 530021, China Peng Wang * Department of

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can also search for this author inPubMed Google Scholar * Le-Qun Li View author publications You can also search for this author inPubMed Google Scholar * Jian-Yong Liu View author

publications You can also search for this author inPubMed Google Scholar * Zhi-Ming Zhang View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS

Designed the study: Zhi-Ming Zhang, Le-Qun Li, Bang-De Xiang and Jian-Yong Liu. Performed the research: Gao-Xiong Ouyang and Yu-mei Zhang. Statistical analyses: Shao-Liang Zhu, Peng Wang,

Yuan Ren, Jia-Hao Li, Yu-Kai Liu and Jun Chen. Wrote the manuscript: Gao-Xiong Ouyang and Yu-mei Zhang. All authors reviewed the manuscript. CORRESPONDING AUTHORS Correspondence to Jian-Yong

Liu or Zhi-Ming Zhang. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. ADDITIONAL INFORMATION PUBLISHER'S NOTE: Springer Nature remains neutral with

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http://creativecommons.org/licenses/by/4.0/. Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Ouyang, GX., Zhang, Ym., Zhu, SL. _et al._ A novel, non-invasive model for

diagnosing liver fibrosis stage in patients with hepatocellular carcinoma. _Sci Rep_ 8, 13074 (2018). https://doi.org/10.1038/s41598-018-31351-3 Download citation * Received: 31 January 2018

* Accepted: 16 August 2018 * Published: 30 August 2018 * DOI: https://doi.org/10.1038/s41598-018-31351-3 SHARE THIS ARTICLE Anyone you share the following link with will be able to read

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