Retrospective cohort study on prognostic factors of malignant pleural effusion secondary to pleural mesothelioma

Introduction

Mesothelioma is a highly aggressive tumor which originates in pleura, pericardium, peritoneum and tunica vaginalis (1). Pleural mesothelioma, which accounts for 90% of cases, is usually diagnosed at an advanced stage and has a median survival ranging between 8.0–34.6 months (1-5). Incidence rates of pleural mesothelioma for males and females are 7 and 3 per million persons in the United States and 17 and 4 in Europe, respectively (6). Mortality rates of pleural mesothelioma for males and females are 24.9 and 4.7 deaths per million persons in the United States in 1999–2015 (7), and 63.6 and 13.1 deaths per million in Great Britain in 2018–2020 (8), respectively. Studies have shown that all forms of asbestos are carcinogenic to human and may cause mesothelioma. Also, the asbestos consumption trend correlates positively with the mortality of pleural mesothelioma. As the leading consumers of asbestos, China should give particular attention to the research on pleural mesothelioma which currently lacks relevant data (9).

The main treatment options for pleural mesothelioma include surgery, chemotherapy, radiation therapy, and checkpoint inhibition therapy. Although current studies have found that the above treatment options are associated with improved survival, therapeutic for mesothelioma remains palliative for most patients. Progress in improving survival for patients with mesothelioma has been slow. Extensive heterogeneity among patient is another major obstacle, requiring stratified treatment, and interventions must carefully strike a balance between life expectancy and quality of life. Multiple prognostic factors of pleural mesothelioma have been described, including age, sex, chest pain, weight loss (10), performance status (PS), histologic subtype, platelet (PLT), hemoglobin (Hb), serum albumin (ALB), the neutrophil-to-lymphocyte ratio (NLR), the platelet-to-lymphocyte ratio (PLR), the lymphocyte-to-monocyte ratio (LMR), C-reactive protein (CRP), tumor volume (TV), tumor-node-metastasis (TNM) stage, response to chemotherapy, type of surgery, etc. (10-18). But validated prognostic indicators for pleural mesothelioma that can identify appropriate treatment and minimize patient discomfort during the final stages of life are still lacking.

Existing prognostic models for malignant pleural effusion (MPE), such as the LENT and PROMISE scores, were derived from cohorts with mixed etiologies (lung cancer, breast cancer, mesothelioma, etc.) and may not capture the unique biological behavior of mesothelioma (18). Pleural mesothelioma has distinct pathophysiological features, including a strong tendency for locoregional spread and a rich inflammatory microenvironment within the pleural fluid. Whether pleural fluid parameters have prognostic value specifically in mesothelioma-associated MPE remains unclear. Controversies exist regarding the use of pleural fluid lactate dehydrogenase (LDH) as a prognostic marker, as levels can be influenced by the duration of effusion, prior thoracentesis, and infection.

Mesothelioma has a strong tendency to spread along the pleural surface. Studies have shown that most (>90%) patients with pleural mesothelioma present with MPE (15). MPE in pleural mesothelioma is often the first clinical manifestation of the disease. Therefore, it is the main presenting symptom. The most common symptoms were dyspnea, progressive breathlessness, weight loss, fatigue, chest pain and cough. The severity of dyspnea is related to the volume and rate of pleural effusion, but is also influenced by underlying cardiac and respiratory comorbidities. MPE is also associated with life quality of patient. Indicators in pleural fluid can be used for the diagnosis of pleural mesothelioma (19), but its prognostic value in pleural mesothelioma is less studied. When a patient presents with pleural effusion, less invasive drainage is often required for symptom relief and diagnosis. Therefore, parameters in pleural fluid are also easily obtained.

In our study, we comprehensively evaluated the prognostic value of clinical and laboratory characteristics in patients with MPE secondary to pleural mesothelioma in China before the anti-tumor therapy was taken, especially the parameters in pleural fluid, determine the median survival time, and evaluate the prognostic parameters related to overall survival (OS) in patients with MPE secondary to pleural mesothelioma. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0776/rc) (20).

Methods

Study design

This was a single-center, retrospective cohort study conducted in the Department of Respiratory and Critical Care Medicine, Tianjin Chest Hospital, and all statistical analyses were based on the intention-to-treat principle.

Patients and data collection

Diagnostic criteria and classification were adopted in line with relevant clinical guidelines (6,21,22). Diagnoses of pleural mesothelioma were established in accordance with the European Society for Medical Oncology (ESMO) clinical practice guidelines (6). Definitive pathological confirmation was required via thoracoscopic pleural biopsy or cell block preparation from drained pleural effusion specimens, supported by targeted immunohistochemical staining including calretinin, WT-1, CK5/6, and mesothelin. This cohort included patients aged over 18 years diagnosed and treated in Tianjin Chest Hospital from January 2015 to May 2025. Patients were excluded from the analysis for any of the following reasons: active concomitant infectious disease, incomplete baseline clinical or laboratory datasets, or prior receipt of antitumor treatments (chemotherapy, immunotherapy, or surgical resection) before study enrollment. Clinically significant infection was defined as infectious manifestations necessitating systemic antimicrobial therapy, including fever exceeding 38.5 ℃, leukocytosis >12×10⁹/L, or positive microbiological cultures. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Ethics Committee of Tianjin Chest Hospital (No. 2023-KY-022-01). Only the clinical information of the patients was collected retrospectively, and any characters with the subjects’ identities were deleted from the research results to ensure that personal privacy was not disclosed. Consequently, the Ethics Committee granted a waiver for the requirement of written informed consent.

Patient characteristics including age, gender, Eastern Cooperative Oncology Group PS (ECOG PS), smoking status, weight loss, asbestos exposure history, pleural fluid location, histological subtype, all peripheral blood laboratory indicators collected at initial diagnosis (including routine blood cell counts, liver and renal function, inflammatory markers, fibrinogen and tumor markers), together with pleural fluid test indicators from the first diagnostic thoracentesis, were extracted from the hospital’s electronic medical record system. Owing to the extended timeframe of patient data collection, TNM staging information was unavailable for a subset of patients and therefore not documented. All blood and pleural fluid samples were collected within 24 hours of admission. Pleural fluid samples were obtained from the first diagnostic thoracentesis. LDH levels were measured within 2 hours of collection with the rate method using a fully automated clinical chemistry analyzer (Roche Cobas c501, Roche Diagnostics, Switzerland) at the hospital’s central laboratory. There was no missing data of key variables [pleural fluid LDH, mean platelet volume (MPV), lymphocyte count, and fibrinogen (FIB)] in this study; for individual non-key variables with missing data (<5%), the complete case analysis method was used.

The primary outcome was OS, calculated as the time interval from the date of pathological diagnosis to the date of death from any cause or the date of last follow-up for censored patients. Follow-up was conducted by telephone using a standardized questionnaire that included: date of last hospital visit, current symptoms, and survival status. For deceased patients, the date and cause of death were obtained from hospital records or family report. If a patient could not be reached after three attempts within two weeks, the last known contact date was used for censoring. During the first 6 months after diagnosis, follow-up was routine every month, and thereafter every 3 months for at least 1 year.

Statistical analysis

Continuous data were expressed as mean ± standard deviation. Categorical data were expressed by the frequency and percentage. Continuous data were analyzed by using student’s t test or one-way analysis, and categorical data were analyzed by using χ² test. The cutoff values of variables that yield the joint maximum sensitivity and specificity are determined by constructing a receiver operating characteristic (ROC) curve analysis using the Youden index (maximum of sensitivity + specificity − 1) with OS status as the classification endpoint. This data-dependent approach is known to potentially inflate hazard ratios (HRs) and increase type I error; therefore, results should be interpreted as exploratory. Continuous variables were then transformed into categorical variables using the optimal cut-off point. Survival curves were analyzed by the Kaplan-Meier method, and differences were compared by log-rank test. Univariable and multivariable analyses were performed by Cox regression analysis. Indicators that were found to be clearly associated with OS and all statistically significant (P<0.2) univariates were included in the multivariable model. Univariate and multivariate Cox regression models had provided HRs and 95% confidence interval (CI), respectively. A Cox proportional hazards model was used to fit all individual prognostic variables to determine their independent factors. All statistical tests were two-sided, and a P value <0.05 was considered statistically significant. SPSS 25.0 software was used for statistical analysis.

We acknowledge the absence of a priori sample size calculation. A total of 53 all-cause deaths were observed, corresponding to an events per variable (EPV) ratio of 13.25 (53/4). This meets the recommended minimum of 10 EPV. Nevertheless, our analysis is exploratory, and formal internal validation (bootstrapping, cross-validation) was not implemented.

Results

Baseline characteristics

A total of 93 patients with a diagnosis of pleural mesothelioma combined with MPE were initially identified from the electronic medical record system. After screening: 7 patients were excluded due to anti-tumor therapy before enrollment, 12 due to incomplete clinical/laboratory data, and 3 due to combined other primary tumors. Finally, 71 eligible patients were included in the analysis. The mean follow-up duration was 37 months (range, 34–40 months). Baseline characteristics of population in this study are shown in Table 1. OS for the overall population was 30 months (range, 16–44 months). Median age of the patients was 67 years (range, 60–74 years), and there are 43 (60.6%) males and 28 (39.4%) females. A total of 22.5% of the patients had a clear history of asbestos exposure. The majority of patients present that ECOG PS is 0–1 (80.3%), were never smokers (59.2%), exhibited epithelioid histology (62.0%), and have no weight loss (73.2%).

Association of clinicopathological factors and OS

Univariate associations between clinicopathologic factors and OS are shown in Table 2. ECOG PS, sarcomatoid type histology, low level of lymphocyte and alanine aminotransferase (ALT), high level of, MPV, FIB, cytokeratin 19 fragment (CYFRA), and LDH in pleural fluid were significantly related to worse outcomes (all P<0.2). As shown in Table 3, variables with P values <0.2, along with variables that were found to be associated with OS including, NLR, Hb and ALB were further fitted into a multivariate Cox’s proportional hazard model, pleural fluid LDH ≥361 U/L (HR 4.373; 95% CI: 1.903–10.049; P=0.001), FIB ≥3.82 g/L (HR 3.592; 95% CI: 1.683–7.666; P=0.001), MPV ≥12.50 fL (HR 2.507; 95% CI: 1.125–5.586; P=0.03), and absolute lymphocyte count ≥1.48×10⁹/L (HR 0.423; 95% CI: 0.204–0.877; P=0.02) were identified as independent indicators of OS in patients with MPE secondary to pleural mesothelioma.

The Kaplan-Meier survival curves are shown in Figure 1.

Figure 1 Kaplan-Meier curves for overall survival stratified by each of the four baseline variables. Cum, cumulative; FIB, fibrinogen; L, lymphocyte; LDH, lactate dehydrogenase; MPV, mean platelet volume; PF, pleural fluid.

Discussion

In our study, we extensively screened routinely available demographic, clinical, hematological, and pleural fluid parameters in patients with MPE secondary to pleural mesothelioma, and identified raised LDH in pleural fluid, raised MPV and FIB, and decreased lymphocyte count as markers of poor prognosis in these patients. This information has direct clinical relevance in adjusting treatment strategies based on individual predicted survival.

The inflammatory response is closely related to the occurrence and development of cancers (23). Growing evidence has supported potential effects of the local and systemic inflammatory response on cancer patient prognosis (24). Previous studies have shown that semiquantitative assessment of inflammatory response in tumor and stroma by hematoxylin and eosin (H&E) stained sections can predict survival in patients with pleural mesothelioma (24). As mentioned before, most patients with pleural mesothelioma present with MPE, which arises from plasma extravasation from leaky vessels in the visceral and parietal pleura and contains rich amounts of inflammatory mediators. The pleural fluid biological tests may predict patients’ survival or chemotherapy response. High pleural fluid LDH levels which reflect localized, acute inflammation, necrosis and cell death within the pleural cavity are associated with a poor prognosis in MPE (25). The LENT prognostic score also found that LDH in pleural fluid is an independent predictor of prognosis in MPE (26). However, parameters in pleural fluid are rarely used as predictors for survival in patients with MPE secondary to pleural mesothelioma. Our finding that LDH in pleural fluid was an independent prognostic factor for OS in patients with MPE secondary to pleural mesothelioma is consistent with these discoveries.

Existing validated prognostic models for MPE, such as the LENT score (which includes pleural fluid LDH, ECOG PS, serum CRP, and tumor type), have been established in larger cohorts. Our study identified pleural fluid LDH as a prognostic factor, consistent with LENT. However, we did not directly compare our identified factors with these models in terms of discrimination or calibration, which is a limitation. Future studies should benchmark any new prognostic factors against established scores.

Plenty of studies have explored the most commonly used indicators of the inflammatory response, such as leukocytes, leukocyte subtypes, CRP, PLT, Hb, serum albumin and the ratio between some indicators and their potential effects on the prognosis of pleural mesothelioma or MPE patients (27). In previous studies, MPV has been clearly shown to be associated with systemic inflammation and thromboembolism (28). Studies have shown that in patients with colon, esophagus, ovary, and breast cancer, MPV in peripheral blood can be used as an indicator of cancer progression and inflammation before surgery or systemic therapy (29,30). Lymphocytes, as an indicator of host inflammatory status, have been reported to help predict prognosis in a variety of cancers. The relationship between lymphocyte in peripheral blood and prognosis of lung cancer has been extensively studied, such as lymphocyte percentage (31), absolute lymphocyte count (32), lymphocyte subsets (33), neutrophil-lymphocyte ratio (32), etc. We also found that MPV, absolute lymphocyte counts were associated with prognosis of patients with MPE secondary to pleural mesothelioma.

Previous studies have suggested that in patients with cancer, FIB is significantly increased, and blood viscosity is also increased, which makes cancer patients more likely to form cancer thrombus (34). At the same time, the abnormal increase of FIB causes the smooth disorder of the fibrinolytic system, and the fibrinolytic substances are activated to hydrolyze the vascular intima and basement membrane, thus promoting the spread of cancer. Consistent with these results, we found that high FIB was associated with poor prognosis.

Surprisingly, variables associated with prognostic outcomes, such as age, gender, PS, histological subtype, were not found to be significant, which may be explained by differences in disease stages of enrolled participants between previous studies and our study. And it may also imply that the findings vary with the diversity of the study population, with racial differences likely playing a role. Specifically, the high proportion (28.2%) of patients with unclassified histology is a major limitation. Histological subtype is among the strongest prognostic factors in pleural mesothelioma, and its absence in over a quarter of our cohort likely introduced residual confounding that may have affected the multivariable analysis. This study has several important limitations. First, it is a retrospective, single-center study with a relatively small sample size (n=71). The number of events (53 deaths) yields an EPV of 13.25, which meets the minimum recommendation but is still modest. No internal validation (e.g., bootstrapping or cross-validation) was performed, and the findings are exploratory. Second, there is no external validation; generalizability to other populations remains unknown. Third, TNM stage was not available for the majority of patients, and disease stage is a well-known prognostic factor in pleural mesothelioma. Our inability to adjust for stage may introduce residual confounding. Fourth, the high proportion of patients with unclassified histology (28.2%) is a major source of confounding, as histological subtype is among the strongest prognostic factors. Fifth, the use of data-dependent ROC cutoffs for continuous variables can inflate HRs and increase type I error rates. Sixth, although immunotherapy has been incorporated into standard systemic therapy for pleural mesothelioma in recent years, we could not assess its impact due to lack of relevant data in our cohort (the study period ended before routine use of checkpoint inhibitors at our center). Finally, the LENT and PROMISE scores were not directly compared; therefore, we cannot determine whether our identified factors add value beyond these established models. Despite these limitations, our analysis extends previous studies on prognostic factors in MPE secondary to pleural mesothelioma, specifically highlighting the potential role of pleural fluid biomarkers. More studies are needed to further confirm the effectiveness of these factors and to identify other sensitive biomarkers in pleural fluid.

Conclusions

In this retrospective cohort study, pleural fluid LDH, peripheral blood MPV, absolute lymphocyte count, and FIB were independently associated with OS in patients with MPE secondary to pleural mesothelioma. These four routinely available baseline parameters may serve as potential prognostic indicators. However, due to the modest sample size, lack of external validation, and other methodological limitations, these findings should be considered exploratory. Multicenter, prospective, large-sample studies with external validation are needed to confirm the prognostic value and generalizability of these factors.

Acknowledgments

The authors thank all the patients who participated in this study.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0776/rc

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0776/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0776/prf

Funding: This work was supported by Tianjin Key Medical Discipline Construction Project (No. TJYXZDXK-3-032C), National Clinical Key Specialty Construction Project (No. ZC20076), and grants from the Tianjin Health Science and Technology Project (grant No. MS20015).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0776/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Tianjin Chest Hospital (No. 2023-KY-022-01) and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Janes SM, Alrifai D, Fennell DA. Perspectives on the Treatment of Malignant Pleural Mesothelioma. N Engl J Med 2021;385:1207-18. [Crossref] [PubMed]
2. Scherpereel A, Opitz I, Berghmans T, et al. ERS/ESTS/EACTS/ESTRO guidelines for the management of malignant pleural mesothelioma. Eur Respir J 2020;55:1900953. [Crossref] [PubMed]
3. Scherpereel A, Astoul P, Baas P, et al. Guidelines of the European Respiratory Society and the European Society of Thoracic Surgeons for the management of malignant pleural mesothelioma. Eur Respir J 2010;35:479-95. [Crossref] [PubMed]
4. Rusch VW, Giroux D, Kennedy C, et al. Initial analysis of the international association for the study of lung cancer mesothelioma database. J Thorac Oncol 2012;7:1631-9. [Crossref] [PubMed]
5. Harris EJA, Kao S, McCaughan B, et al. Prediction modelling using routine clinical parameters to stratify survival in Malignant Pleural Mesothelioma patients undergoing cytoreductive surgery. J Thorac Oncol 2019;14:288-93. [Crossref] [PubMed]
6. Popat S, Baas P, Faivre-Finn C, et al. Malignant pleural mesothelioma: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up Ann Oncol 2022;33:129-42. [Crossref] [PubMed]
7. Mazurek JM, Syamlal G, Wood JM, et al. Malignant Mesothelioma Mortality - United States, 1999-2015. MMWR Morb Mortal Wkly Rep 2017;66:214-8. [Crossref] [PubMed]
8. Mesothelioma deaths by Geographical Area, 2022. Available online: https://www.ukata.org.uk
9. Gariazzo C, Gasparrini A, Marinaccio A. Asbestos Consumption and Malignant Mesothelioma Mortality Trends in the Major User Countries. Ann Glob Health 2023;89:11. [Crossref] [PubMed]
10. Gunatilake S, Lodge D, Neville D, et al. Predicting survival in malignant pleural mesothelioma using routine clinical and laboratory characteristics. BMJ Open Respir Res 2021;8:e000506. [Crossref] [PubMed]
11. Tanrikulu AC, Abakay A, Komek H, et al. Prognostic value of the lymphocyte-to-monocyte ratio and other inflammatory markers in malignant pleural mesothelioma. Environ Health Prev Med 2016;21:304-11. [Crossref] [PubMed]
12. Zhuo M, Zheng Q, Chi Y, et al. Survival analysis via nomogram of surgical patients with malignant pleural mesothelioma in the Surveillance, Epidemiology, and End Results database. Thorac Cancer 2019;10:1193-202. [Crossref] [PubMed]
13. Billé A, Krug LM, Woo KM, et al. Contemporary Analysis of Prognostic Factors in Patients with Unresectable Malignant Pleural Mesothelioma. J Thorac Oncol 2016;11:249-55. [Crossref] [PubMed]
14. Yeap BY, De Rienzo A, Gill RR, et al. Mesothelioma Risk Score: A New Prognostic Pretreatment, Clinical-Molecular Algorithm for Malignant Pleural Mesothelioma. J Thorac Oncol 2021;16:1925-35. [Crossref] [PubMed]
15. Brims F. Epidemiology and Clinical Aspects of Malignant Pleural Mesothelioma. Cancers (Basel) 2021;13:4194. [Crossref] [PubMed]
16. Vigneri P, Martorana F, Manzella L, et al. Biomarkers and prognostic factors for malignant pleural mesothelioma. Future Oncol 2015;11:29-33. [Crossref] [PubMed]
17. Sinn K, Mosleh B, Hoda MA. Malignant pleural mesothelioma: recent developments. Curr Opin Oncol 2021;33:80-6. [Crossref] [PubMed]
18. Mounsey CA, Kanellakis NI, Addala DN, et al. External validation of the LENT and PROMISE prognostic scores for malignant pleural effusion. ERJ Open Res 2025;11:01019-2024. [Crossref] [PubMed]
19. Eccher A, Girolami I, Lucenteforte E, et al. Diagnostic mesothelioma biomarkers in effusion cytology. Cancer Cytopathol 2021;129:506-16. [Crossref] [PubMed]
20. von Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol 2008;61:344-9. [Crossref] [PubMed]
21. Roca E, Aujayeb A, Astoul P. Diagnosis of Pleural Mesothelioma: Is Everything Solved at the Present Time? Curr Oncol 2024;31:4968-83. [Crossref] [PubMed]
22. WHO Classification of Tumours Editorial Board. Thoracic Tumours (5th ed), International Agency for Research on Cancer. Lyon, France; 2021.
23. Maiorino L, Daßler-Plenker J, Sun L, et al. Innate Immunity and Cancer Pathophysiology. Annu Rev Pathol 2022;17:425-57. [Crossref] [PubMed]
24. Suzuki K, Kadota K, Sima CS, et al. Chronic inflammation in tumor stroma is an independent predictor of prolonged survival in epithelioid malignant pleural mesothelioma patients. Cancer Immunol Immunother 2011;60:1721-8. [Crossref] [PubMed]
25. Bielsa S, Salud A, Martínez M, et al. Prognostic significance of pleural fluid data in patients with malignant effusion. Eur J Intern Med 2008;19:334-9. [Crossref] [PubMed]
26. Clive AO, Kahan BC, Hooper CE, et al. Predicting survival in malignant pleural effusion: development and validation of the LENT prognostic score. Thorax 2014;69:1098-104. [Crossref] [PubMed]
27. Psallidas I, Kanellakis NI, Gerry S, et al. Development and validation of response markers to predict survival and pleurodesis success in patients with malignant pleural effusion (PROMISE): a multicohort analysis. Lancet Oncol 2018;19:930-9. [Crossref] [PubMed]
28. Omar M, Tanriverdi O, Cokmert S, et al. Role of increased mean platelet volume (MPV) and decreased MPV/platelet count ratio as poor prognostic factors in lung cancer. Clin Respir J 2018;12:922-9. [Crossref] [PubMed]
29. Afsar CU, Gunaldi M, Kum P, et al. Pancreatic carcinoma, thrombosis and mean platelet volume: single center experience from the southeast region of Turkey. Asian Pac J Cancer Prev 2014;15:9143-6. [Crossref] [PubMed]
30. Kemal Y, Demirağ G, Ekiz K, et al. Mean platelet volume could be a useful biomarker for monitoring epithelial ovarian cancer. J Obstet Gynaecol 2014;34:515-8. [Crossref] [PubMed]
31. Huang H, Li L, Luo W, et al. Lymphocyte percentage as a valuable predictor of prognosis in lung cancer. J Cell Mol Med 2022;26:1918-31. [Crossref] [PubMed]
32. Punjabi A, Barrett E, Cheng A, et al. Neutrophil-Lymphocyte Ratio and Absolute Lymphocyte Count as Prognostic Markers in Patients Treated with Curative-intent Radiotherapy for Non-small Cell Lung Cancer. Clin Oncol (R Coll Radiol) 2021;33:e331-8. [Crossref] [PubMed]
33. Dai S, Ren P, Ren J, et al. The Relationship between Lymphocyte Subsets and the Prognosis and Genomic Features of Lung Cancer: A Retrospective Study. Int J Med Sci 2021;18:2228-34. [Crossref] [PubMed]
34. Zhang Y, Liu N, Liu C, et al. High Fibrinogen and Platelets Correlate with Poor Survival in Gastric Cancer Patients. Ann Clin Lab Sci 2020;50:457-62.