|Ahead of print publication
Prognostic impact of the 18F-fluorodeoxyglucose positron-emission tomography/computed tomography metabolic parameters and correlation with hematological inflammatory markers in lung cancer
Sibel Goksel1, Arzu Cengiz2, Hakan Ozturk3, Yakup Yurekli2
1 Department of Nuclear Medicine, Graduate School of Medical Sciences, Recep Tayyip Erdogan University, Rize, Turkey
2 Department of Nuclear Medicine, Graduate School of Medical Sciences, Adnan Menderes University, Aydin, Turkey
3 Department of Biostatistic, Graduate School of Istatistic, Adnan Menderes University, Aydin, Turkey
|Date of Submission||21-Aug-2020|
|Date of Acceptance||25-Dec-2020|
|Date of Web Publication||16-Jul-2021|
Department of Nuclear Medicine, Recep Tayyip Erdogan University Training and Research Hospital Rize
Source of Support: None, Conflict of Interest: None
Introduction: Hematological inflammatory markers and metabolic parameters in positron-emission tomography/computed tomography (PET/CT) are important indicators predicting the prognosis of the disease in lung cancer as in many cancers. This study aimed to evaluate the correlation between pretreatment hematological inflammatory markers and PET/CT metabolic parameters in nonsmall cell lung cancer (NSCLC) patients and to predict the prognostic value of these parameters.
Materials and Methods: A total of 132 patients with diagnosed NSCLC who underwent PET/CT at staging were retrospectively evaluated. Hematological parameters were obtained from the hemogram taken no more than 2 weeks prior to PET/CT. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and mean platelet volume (MPV) were recorded. Maximum standard uptake value, SUVmean, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were calculated. Clinical stage, tumor pathology, and overall survival were analyzed with these parameters.
Results: NLR and PLR were significantly positively correlated with MTV and TLG (all P < 0.001), MPV was negatively correlated with TLG (P = 0.021). While TLG, MTV, NLR, and PLR were increased in advanced stage disease, MPV was decreased. Univariate Cox-regression analysis demonstrated that greater age (P = 0.015), advanced stage (P < 0.001), low MPV (P = 0.017), high NLR (P < 0.001), PLR (P < 0.001), MTV (P = 0.004), TLG (P = 0.001) values, multivariate Cox-regression analysis revealed that NLR (P < 0.001) and advanced stage (P < 0.001) were significant predictors of poor prognosis in patients with NSCLC.
Conclusions: There were significant associations between hematological inflammatory markers and PET/CT metabolic parameters in the patients with NSCLC at the time of diagnosis. These indicators can contribute to predicting prognosis in patients with NSCLC.
Keywords: Hematological parameter, metabolic tumor volume, nonsmall cell lung cancer, prognosis, total lesion glycolysis
|How to cite this URL:|
Goksel S, Cengiz A, Ozturk H, Yurekli Y. Prognostic impact of the 18F-fluorodeoxyglucose positron-emission tomography/computed tomography metabolic parameters and correlation with hematological inflammatory markers in lung cancer. J Can Res Ther [Epub ahead of print] [cited 2021 Jul 29]. Available from: https://www.cancerjournal.net/preprintarticle.asp?id=321679
| > Introduction|| |
Lung cancer is the leading cause of cancer-related deaths in both sexes, and the incidence of lung cancer is increasing with time. The stage of the disease is still the most important prognostic factor.,,,
18F-fluorodeoxyglucose positron-emission tomography/computed tomography (18F-FDG PET/CT) is useful for staging in patients with nonsmall cell lung cancer (NSCLC) and contributes to predicting prognosis by providing information about the metabolic activity of the tumors. Many studies have suggested that metabolic parameters, such as maximum standard uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG), are important factors in determining the clinical course and prognosis in several types of cancers such as NSCLC.,,,,,,
Systemic inflammation is known to be important in carcinogenesis., Studies have shown that mean platelet volume (MPV), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) are indicators of systemic inflammation and were recently recognized as the indicators of prognosis in patients with various cancers.,, Although the relationship between systemic inflammation and cancer importance is increasing in recent years, MPV, NLR, and PLR have been used as predictive parameters in cancer prognosis and survival in many cancer types.,,,,,,,,
Although many studies show that both metabolic PET/CT parameters and hematological parameters predict the prognosis in many cancers, there are limited studies evaluating their relationship with each other.
This study aimed to evaluate the prognostic impact of NLR, PLR, MPV, SUVmax, MTV, and TLG of primary tumor during initial PET/CT and to investigate the correlation between systemic hematological inflammatory markers with the PET/CT metabolic parameters of a primary tumor in patients with NSCLC.
| > Materials and Methods|| |
A total of 204 patients diagnosed with NSCLC between March 2013 and December 2017 who underwent PET/CT for initial staging were retrospectively evaluated and 132 patients (10 females and 122 males) were included in this study. Exclusion criteria from the study were received neoadjuvant or adjuvant therapy, underwent surgery, had any sign of inflammatory or infectious disease or leukocytosis (≥10,000/μL), recently received blood transfusion, or those with the presence of hematological or autoimmune disease or a secondary malignancy.
Patients' clinical data were retrieved from the hospital's electronic medical records. Tumor stage was classified according to the eighth edition of the tumor-node-metastasis 8 classification system. Hematological markers including absolute neutrophil count, absolute lymphocyte count, absolute platelet count, and MPV value were obtained from the complete blood count, which were obtained within 2 weeks of the baseline PET/CT scan. NLR, PLR, and MPV were recorded for all the patients. Overall survival (OS) was calculated as the time between the initial PET/CT scan and death or the last follow-up. The flowchart of the study design is shown in [Figure 1].
The study was started after obtaining local ethical committee of Adnan Menderes University permission dated December 20, 2018, with numbers 2018/1546.
18F-fluorodeoxyglucose positron-emission tomography/computed tomography and measurement (maximum standard uptake value, metabolic tumor volume, and total lesion glycolysis)
All the patients fasted for at least 6 h before PET/CT. The fasting blood glucose levels of all the patients were <200 mg/dL prior to scanning. Approximately 220–370 MBq 18F-FDG was PET/CT. Oral contrast agent was given to all patients. The patients were subjected to the PET/CT (Siemens Biograph mCT, 16 slices) with 3D mode and TOF features, following a resting period of 50–60 min in the waiting room. Images were acquired from the head to the upper thigh region. Low-dose CT data were collected at an average of 120 kV and 50 mAs. The PET acquisition was obtained at a rate of 2 min per bed position.
All PET/CT images were visually and semi-quantitatively evaluated by two nuclear medicine physicians. SUVmax, SUVmean, and MTV values were calculated for only primary tumor. Lymph node and distant organ metastasis lesions were not included in the calculation. MTV was calculated by total tumor volume of 40% SUVmax or greater, and TLG was calculated by the following formula: TLG = MTV × SUVmean.
Statistical analysis was performed using the statistical package SPSS 22.0. Kolmogorov–Smirnov test was conducted to determine whether the quantitative variables were normally distributed in the groups. The dependence between the qualitative variables was determined by the Chi-square analysis. Mann–Whitney U-test was used for independent two-group comparisons. Kruskal–Wallis H-test was used for more than two independent group comparisons. Descriptive statistics on quantitative variables were given as median (25th–75th percentile), and qualitative variables were given as number (n) and percentage (%). The correlation between continuous variables was analyzed by the Spearman correlation test. Linear regression analysis was used to determine the correlation between hematological inflammatory markers and SUVmax, MTV, and TLG values of the primary tumor.
The predictors of survival were analyzed by the Kaplan–Meier method. The prognostic significance of the variables for OS was assessed by univariate and multivariate analyses, using the Cox proportional-hazard regression model (Forward procedure, Wald method). P < 0.05 was considered statistically significant.
| > Results|| |
Clinical–demographic characteristics and laboratory and PET/CT metabolic parameters of all the patients are given in [Table 1]. The median age was 69 years (range 32–91 years). The majority of patients (67.4%) had squamous cell carcinoma diagnosis. Most patients had an advanced disease. The stage distribution of the patients is given in [Table 1].
Based on the study conducted by Jeong et al., the 75th percentile of cutoff value was applied to these parameters, and high-low PET/CT metabolic parameters and hematological inflammatory markers were detected. The cutoff values were 19.5 for SUVmax, 79.3 cm3 for MTV, 674.6 g for TLG, 6.3 for NLR, 291.6 for PLR, and 10.5 fL for MPV.
Median OS was 9.8 months (range 0.5–68 month), and 117 (88.6%) patients died during the follow-up period. Mean OS was found to be 15.26 ± 15.14 months. Relationship of OS with the PET/CT metabolic parameters and hematological inflammatory markers of patients is shown in [Table 2]. OS was found to be shorter in patients with higher MTV (P = 0.003), TLG (P = 0.001), NLR (P < 0.001), PLR (P < 0.001), and lower MPV (P = 0.014) according to these high and low cutoff values. However, SUVmax had no prognostic significance in OS. Kaplan–Meier survival analyses of MTV and TLG are shown in [Figure 2] and [Figure 3].
|Table 2: Relationship of overall survival with high/low cutoff values of positron-emission tomography/computed tomography metabolic parameters and hematological inflammatory markers|
Click here to view
|Figure 3: Kaplan–Meier overall survival curve of total lesion glycolysis|
Click here to view
Prognostic factors of the disease were analyzed using univariate and multivariate Cox-regression analyses. Locally advanced and advanced stage; age (each 1-year increase); high MTV (≥79.3 cm3), TLG (≥674.6 g), NLR (≥6.34), and PLR (≥291.6) values; and lower MPV (<10.5 fL) values were associated with poor prognosis in univariate Cox-regression analysis [Table 3]. Multivariate Cox-regression analysis revealed that only NLR level (P < 0.001, hazard ratio [HR] = 2.672, 95% confidence interval [CI] = 1.746–4.088) and locally advanced/advanced stage disease (P < 0.001, HR = 7.770, 95% CI = 2.617–23.073) were significant independent risk factors for poor prognosis.
When the association between the stage of disease and PET/CT metabolic parameters – hematological inflammatory markers – was analyzed, statistically significant differences were found between these parameters. While NLR (P < 0.001), PLR (P < 0.001), MTV (P = 0.009), and TLG (P = 0.024) levels were found to be increased in advanced-stage disease, MPV (P = 0.029) was found to be decreased. Moreover, there was no significant relationship between the SUVmax and the stage of the disease.
In the correlation analysis, it was found that the MTV and TLG were positively correlated with the hematological inflammatory markers. However, SUVmax had no correlation with these markers. The MTV and TLG showed positive correlation with NLR (for MTV, r = 0.524, P < 0.001; for TLG, r = 0.540, P < 0.001) and PLR (for MTV, r = 0.445, P < 0.001; for TLG, r = 0.460, P < 0.001). Moreover, there was a negative correlation between the MPV and TLG (r = −0.201, P = 0.021). Linear regression analyses are shown in [Figure 4] and [Figure 5].
|Figure 4: Linear regression analyses between metabolic tumor volume with neutrophil-to-lymphocyte ratio (a) and platelet-to-lymphocyte ratio (b)|
Click here to view
|Figure 5: Linear regression analyses between total lesion glycolysis with neutrophil-to-lymphocyte ratio (a) and platelet-to-lymphocyte ratio (b)|
Click here to view
| > Discussion|| |
NSCLC is one of the most aggressive malignant tumors. Although the most important prognostic factor is still the stage of the disease, it has many prognostic indicators. Identification of the indicators that contribute to predict prognosis is clinically important in patients with NSCLC. The importance of PET/CT metabolic parameters and hematological inflammatory markers is increasing to predict prognosis in NSCLC, as in other malignancies.
Our study demonstrated that MTV and TLG at initial PET/CT are associated with systemic inflammatory markers and are significant prognostic factors in patients with NSCLC. According to recent literature, there are rare reports about the relationship between hematological inflammatory markers and PET/CT metabolic parameters in patients with NSCLC.
In many studies, PET/CT metabolic parameters were investigated as additional prognostic parameters.,, Similar to our study, Davison et al. showed that MTV and TLG were significantly greater in patients who died than in those who survived, and there was no relationship between SUVmax and OS. Similar to these results, recent studies showed that the volume-based PET/CT metabolic parameters such as the MTV and TLG are better prognostic indicators than SUVmax, in NSCLC patients.,
The relationship between high NLR and PLR values with a poor prognosis has been demonstrated in many cancers including NSCLC.,, In accordance with the literature, our study showed that NLR and PLR correlated with the stage of the disease in patients with NSCLC. In addition, we demonstrated in this study that low MPV value is a poor prognostic factor in NSCLC patients. Similar to our study, Kumagai et al. concluded that low MPV was associated with poor prognosis in patients with NSCLC. In addition, another study showed that MPV was decreased in patients with advanced stage NSCLC, similar to our study.
However, contrary to these results, Omar et al. showed that increased MPV was an important prognostic factor, indicative of poor prognosis in patients with NSCLC. The difference in the results in the literature may be due to the low number of patients, different stages of patients, and the inclusion of different histopathological subtypes in these studies. Studies have shown that the relationship between MPV and prognosis is not clear yet in patients with NSCLC. These clinical results should be evaluated with a larger number of patients and in homogeneous patient groups.
There are a limited number of studies investigating the relation between PET/CT metabolic parameters and hematological inflammatory markers in malignancies. Tatsumi et al. showed that there was a positive correlation between TLG and neutrophil count in esophageal cancer, at the time of diagnosis. In another study, the authors reported that there was a significant positive correlation between NLR and MTV in patients with esophageal cancer. Mirili et al. investigated the relationship between PET/CT metabolic parameters and hematological inflammatory markers in small cell lung cancer. Although MTV and TLG were significantly correlated with NLR, there was no correlation between MPV and PET/CT metabolic parameters in this study. Another study reported that there were significant positive correlations between NLR with MTV-SUVmax-TLG values, and PLR with MTV-TLG values in patients with colorectal cancer.
Jeong et al. investigated the relationship between SUVmax and hematological inflammatory markers in lung cancer. There was a significant positive correlation between SUVmax and neutrophil count in this study. On the contrary, there was no relationship between SUVmax and hematological inflammatory markers, in our study. The difference in the results may be justified by the differences between the distribution of the histopathological subtypes and stages of the disease. Jeong et al. included only stage 1 lung cancers in their study; but in our study, patients irrespective of the stage were included. In our study, the patient population had stage 4 disease predominantly. This is one of the limitations of our study.
In addition, SUVmax cannot represent glucose metabolism, tumor growth, and progression potential of the whole tumor. Metabolic volumetric parameters such as MTV and TLG are more reliable in the glucose metabolism of primary tumor and progression potential of disease than the SUVmax.
| > Conclusions|| |
MTV and TLG of the primary tumor provide metabolic and volumetric information. Systemic hematological inflammation markers such as NLR and PLR are prognostic factors in various malignancies. High hematological inflammatory markers and high MTV and TLG values at initial staging may be useful to predict advanced stage and poor prognosis in patients with NSCLC. The relation between PET/CT metabolic parameters and hematological inflammatory markers suggests that the evaluation of pretreatment metabolic tumor parameters, with hematological markers, together is more useful to detect clinical course, prognosis, and survival. Studies with a larger number of homogeneous patient groups are needed to understand the relation between these parameters and prognosis.
Financial support and sponsorship
Conflict of Interest
The authors declare no conflict of interest.
| > References|| |
Siegel R, Naishadham D, Jemal A. Cancer statistics, 2013. CA Cancer J Clin 2013;63:11-30.
Myrdal G, Lambe M, Gustafsson G, Nilsson K, Ståhle E. Survival in primary lung cancer potentially cured by operation: Influence of tumor stage and clinical characteristics. Ann Thorac Surg 2003;75:356-63.
Brundage MD, Davies D, Mackillop WJ. Prognostic factors in non-small cell lung cancer: A decade of progress. Chest 2002;122:1037-57.
Grivaux M, Zureik M, Marsal L, Asselain B, Peureux M, Chavaillon JM, et al
. Five year survival for lung cancer patients managed in general hospitals. Rev Mal Respir 2009;26:37-44.
Siegel RL, Miller KD, Jemal A. Cancer statistics, 2015. CA Cancer J Clin 2015;65:5-29.
Liao S, Penney BC, Zhang H, Suzuki K, Pu Y. Prognostic value of the quantitative metabolic volumetric measurement on 18F-FDG PET/CT in Stage IV nonsurgical small-cell lung cancer. Acad Radiol 2012;19:69-77.
Liao S, Penney BC, Wroblewski K, Zhang H, Simon CA, Kampalath R, et al
. Prognostic value of metabolic tumor burden on 18F-FDG PET in nonsurgical patients with non-small cell lung cancer. Eur J Nucl Med Mol Imaging 2012;39:27-38.
Lee P, Bazan JG, Lavori PW, Weerasuriya DK, Quon A, Le QT, et al
. Metabolic tumor volume is an independent prognostic factor in patients treated definitively for non-small-cell lung cancer. Clin Lung Cancer 2012;13:52-8.
Dosani M, Yang R, McLay M, Wilson D, Liu M, Yong-Hing CJ, et al
. Metabolic tumour volume is prognostic in patients with non-small-cell lung cancer treated with stereotactic ablative radiotherapy. Curr Oncol 2019;26:e57-e63.
Li X, Wang D, Yu L. Prognostic and predictive values of metabolic parameters of 18
F-FDG PET/CT in patients with non-small cell lung cancer treated with chemotherapy. Mol Imaging 2019;18:1-12.
Chang H, Lee SJ, Lim J, Lee JS, Kim YJ, Lee WW. Prognostic significance of metabolic parameters measured by 18
F-FDG PET/CT in limited-stage small-cell lung carcinoma. J Cancer Res Clin Oncol 2019;145:1361-7.
Ganem J, Thureau S, Gouel P, Dubray B, Salaun M, Texte E, et al
. Prognostic value of post-induction chemotherapy 18F-FDG PET-CT in stage II/III non-small cell lung cancer before (chemo-) radiation. PLoS One 2019;14:e0222885.
Hanahan D, Weinberg RA. Hallmarks of cancer: The next generation. Cell 2011;144:646-74.
Mantovani A. Cancer: Inflaming metastasis. Nature 2009;457:36-7.
Nakaya A, Kurata T, Yoshioka H, Takeyasu Y, Niki M, Kibata K, et al
. Neutrophil-to-lymphocyte ratio as an early marker of outcomes in patients with advanced non-small-cell lung cancer treated with nivolumab. Int J Clin Oncol 2018;23:634-40.
Marchioni M, Primiceri G, Ingrosso M, Filograna R, Castellan P, De Francesco P, et al
. The clinical use of the neutrophil to lymphocyte ratio (NLR) in urothelial cancer: A systematic review. Clin Genitourin Cancer 2016;14:473-84.
Shen XM, Xia YY, Lian L, Zhou C, Li XL, Han SG, et al
. Mean platelet volume provides beneficial diagnostic and prognostic information for patients with resectable gastric cancer. Oncol Lett 2016;12:2501-6.
Yodying H, Matsuda A, Miyashita M, Matsumoto S, Sakurazawa N, Yamada M, et al
. Prognostic significance of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in oncologic outcomes of esophageal cancer: A systematic review and meta-analysis. Ann Surg Oncol 2016;23:646-54.
Kim JH, Lee JY, Kim HK, Lee JW, Jung SG, Jung K, et al
. Prognostic significance of the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in patients with stage III and IV colorectal cancer. World J Gastroenterol 2017;23:505-15.
Sun X, Liu X, Liu J, Chen S, Xu D, Li W, et al
. Preoperative neutrophil-to-lymphocyte ratio plus platelet-to-lymphocyte ratio in predicting survival for patients with stage I-II gastric cancer. Chin J Cancer 2016;35:57.
Gong W, Yang S, Yang X, Guo F. Blood preoperative neutrophil-to-lymphocyte ratio is correlated with TNM stage in patients with papillary thyroid cancer. Clinics (Sao Paulo) 2016;71:311-4.
Jia J, Zheng X, Chen Y, Wang L, Lin L, Ye X, et al
. Stage-dependent changes of preoperative neutrophil to lymphocyte ratio and platelet to lymphocyte ratio in colorectal cancer. Tumour Biol 2015;36:9319-25.
Hu L, Li M, Ding Y, Pu L, Liu J, Xie J, et al
. Prognostic value of RDW in cancers: A systematic review and meta-analysis. Oncotarget 2017;8:16027-35.
Wang L, Liang D, Xu X, Jin J, Li S, Tian G, et al
. The prognostic value of neutrophil to lymphocyte and platelet to lymphocyte ratios for patients with lung cancer. Oncol Lett 2017;14:6449-56.
Mirili C, Guney IB, Paydas S, Seydaoglu G, Kapukaya TK, Ogul A, et al
. Prognostic significance of neutrophil/lymphocyte ratio (NLR) and correlation with PET-CT metabolic parameters in small cell lung cancer (SCLC). Int J Clin Oncol 2019;24:168-78.
Jeong E, Hyun SH, Moon SH, Cho YS, Kim BT, Lee KH. Relation between tumor FDG uptake and hematologic prognostic indicators in stage I lung cancer patients following curative resection. Medicine (Baltimore) 2017;96:e5935.
Yan H, Wang R, Zhao F, Zhu K, Jiang S, Zhao W, et al
. Measurement of tumor volume by PET to evaluate prognosis in patients with advanced non-small cell lung cancer treated by non-surgical therapy. Acta Radiol 2011;52:646-50.
Davison J, Mercier G, Russo G, Subramaniam RM. PET-based primary tumor volumetric parameters and survival of patients with non-small cell lung carcinoma. AJR Am J Roentgenol 2013;200:635-40.
Lin Y, Lin WY, Kao CH, Yen KY, Chen SW, Yeh JJ. Prognostic value of preoperative metabolic tumor volumes on PET-CT in predicting disease-free survival of patients with stage I non-small cell lung cancer. Anticancer Res 2012;32:5087-91.
Hyun SH, Choi JY, Kim K, Kim J, Shim YM, Um SW, et al
. Volume-based parameters of (18)F-fluorodeoxyglucose positron emission tomography/computed tomography improve outcome prediction in early-stage non-small cell lung cancer after surgical resection. Ann Surg 2013;257:364-70.
Kumagai S, Tokuno J, Ueda Y, Marumo S, Shoji T, Nishimura T, et al
. Prognostic significance of preoperative mean platelet volume in resected non-small-cell lung cancer. Mol Clin Oncol 2015;3:197-201.
Omar M, Tanriverdi O, Cokmert S, Oktay E, Yersal O, Pilancı KN, 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.
Tatsumi M, Isohashi K, Watabe T, Kato H, Hatazawa J. Association of hematological inflammatory markers with texture features or volumetric parameters on FDG PET in patients with esophageal cancer receiving neoadjuvant chemotherapy and surgery. J Nucl Med 2018;59:159.
Sürücü E, Demir Y, Şengöz T. The correlation between the metabolic tumor volume and hematological parameters in patients with esophageal cancer. Ann Nucl Med 2015;29:906-10.
Xu J, Li Y, Hu S, Lu L, Gao Z, Yuan H. The significant value of predicting prognosis in patients with colorectal cancer using 18F-FDG PET metabolic parameters of primary tumors and hematological parameters. Ann Nucl Med 2019;33:32-8.
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
[Table 1], [Table 2], [Table 3]