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Multivariate analysis of prognostic factors in patients with lip squamous cell carcinoma after surgery

World Journal of Surgical Oncology volume 22, Article number: 35 (2024) Cite this article

Abstract

Background

Lip squamous cell carcinoma (LSCC) was one of the most common cancer types of head and neck tumors. This study aimed to find more predictors of the prognosis in postoperative LSCC patients.

Methods

A total of 147 LSCC patients between June 2012 and June 2018 were collected from two tertiary care institutions. There were 21 clinicopathological factors included and analyzed in our study. The univariate and multivariate Cox regression analyses were performed to find the independent prognostic factors for predicting progression-free survival (PFS) and overall survival (OS) in postoperative LSCC patients. The role of adjuvant radiotherapy in various subgroups was displayed by Kaplan–Meier plots.

Results

The 1-, 3-, and 5-year PFS of postoperative LSCC patients were 88.4%, 70.1%, and 57.8%, respectively. Similarly, the 1-, 3-, and 5-year OS of postoperative LSCC patients were 94.6%, 76.9%, and 69.4%, respectively. The results suggested that postoperative LSCC patients with age at diagnosis ≥ 70 years, grade with moderate or poor differentiate, the American Joint Committee on Cancer (AJCC) stage IV, higher systemic immune-inflammation index (SII), surgical margin < 5, and age-adjusted Charlson Comorbidity Index (ACCI) ≥ 5 tend to have a poorer PFS (all P < 0.05). Besides, postoperative LSCC patients with age at diagnosis ≥ 70 years, AJCC stage IV, higher GPS, higher SII, and ACCI ≥ 5 tend to have a worse OS (all P < 0.05). Additionally, postoperative patients with LSCC in the subgroup of ACCI < 5 and AJCC III–IV stage was more likely to benefit from adjuvant radiotherapy, but not for the other subgroups.

Conclusion

We identified a series of significant immune-inflammation-related and comorbidity-related clinicopathological factors associated with the prognosis of postoperative LSCC patients by local data from two tertiary care institutions in China, which can be helpful for patients and surgeons to pay more attention to nutrition, inflammation, and complications and finally obtained a better prognosis.

Introduction

Lip squamous cell carcinoma (LSCC) is a type of oral cancer that accounts for about 25% of all oral cancer patients [1], and its incidence has shown a downward trend in recent years [2,3,4]. The lip was the junction of oral squamous cells and skin squamous cells, and LSCC was the pathological and anatomical combination of oral mucosa squamous cell carcinoma and skin squamous cell carcinoma. The aggressiveness and prognosis of LSCC were intermediate between those of oral mucosa squamous cell carcinoma and head and neck skin squamous cell carcinoma [5]. Smoking, long-term sunlight exposure, alcohol intake, and habitual chewing of betel nuts may be important acquired causes of lip cancer [6, 7]. Generally, the choice of treatment strategy and prognosis in LSCC patients depended on the traditional TNM AJCC stage. The tumor size, lymph node status, and distant metastasis are critical prognostic factors for those resected patients with LSCC, which has been reflected by the traditional TNM AJCC stage system. Surgery was still the main treatment for patients with LSCC [8, 9]. The prophylactic cervical lymph node dissection is the common method for estimating the lymph node status in LSCC patients. Besides, sentinel lymph node biopsy before surgical resection was another new method, which was mentioned in the notes of the Chinese Society of Clinical Oncology (CSCO) diagnosis and treatment guidelines for head and neck cancer (2018 version) [10] and has attracted the attention of many surgical experts, especially in patients with early-stage lip squamous cell carcinoma (LSCC) [11, 12]. However, due to the limitations of surgical techniques and other factors, the sentinel lymph node biopsy before surgical resection has not been commonly applied in all patients with early-stage lip squamous cell carcinoma (LSCC), especially in low-resource regions [13]. Recently, more and more clinicians have found that LSCC patients with the same TNM AJCC stage had an entirely different prognosis and therapeutic schedule in practice. There are some other factors that also affect the prognosis and treatment choice of LSCC patients, such as the patient’s general condition, immune status, nutritional status, and comorbidity. Therefore, it is important for us to find out more prognostic factors for LSCC patients, which can work as a complement to the traditional TNM AJCC stage system.

At present, there were risk factor analyses for the prognosis of patients with LSCC. These risk factors include age at diagnosis, marital status, sex, race, the American Joint Committee on Cancer (AJCC) stage, surgery status, positive lymph node ratio, total protein, immunoglobulin G, factor B, blood cell count, human papillomavirus (HPV) infection, and radiotherapy status [14,15,16]. However, there were few studies on the prognostic factors of postoperative LSCC patients. Therefore, a retrospective study was designed to find more predictors of the prognosis in postoperative LSCC patients, which can provide a certain reference for clinical application.

Materials and methods

Data collection

In this study, a total of 147 LSCC patients were obtained from the First Affiliated Hospital of Xinxiang Medical University and the Affiliated Cancer Hospital of Zhengzhou University between June 2012 and June 2018. The inclusion criteria were as follows: (1) pathology confirmed, (2) age at diagnosis ≥ 16, and (3) active follow-up. The exclusion criteria include the following: (1) There was distant metastasis at the time of initial diagnosis, (2) no radical resection was performed during the whole treatment, (3) patients who had received preoperative radiotherapy or preoperative chemotherapy, (4) dead within 30 days after surgery, (5) complete clinical data were not available, (6) patients who were lost to follow-up or did not cooperate with follow-up work, and (7) Eastern Cooperative Oncology Group performance status score (ECOG-PS) ≥ 3 before surgery.

We collected clinical data through the clinical case systems of the two medical institutions. A total of 21 clinicopathological variables of LSCC patients were included in the analysis, including age at diagnosis, gender, primary site, grade, AJCC stage, perineural invasion, vascular invasion, surgical margin, extranodal extension (ENE), adjuvant chemotherapy, adjuvant radiotherapy, ECOG-PS, Glasgow prognostic score (GPS), systemic immune-inflammation index(SII), prognostic nutrition index (PNI), platelet-to-lymphocyte ratio (PLR), age-adjusted Charlson Comorbidity Index (ACCI), neutrophil-to-lymphocyte ratio (NLR), hemoglobin, multiple primary tumors, and body mass index (BMI). The adjuvant chemotherapy in this study was platinum-based chemotherapy. The adjuvant radiotherapy was delivered by intensity-modulated radiotherapy (IMRT) with doses ranging from 50.0 to 71.0 Gy. A close margin was defined as a margin within 5 mm from the tumor. Overall survival (OS) and progression-free survival (PFS) were primary study endpoints.

Calculations

ACCI is a marker implicated in comorbidity and age status. The calculation method for ACCI is shown in Table S1. Besides, BMI, GPS, PLR, PNI, NLR, and SII are indicators related to inflammation and nutrition, and the calculation formulas for those indexes are displayed in Table S2.

Statistical analysis

All statistical analyses were performed by SPSS 20.0 software. Univariate Cox regression analysis was applied to find the potential predictors of OS and PFS. Then, these potential predictors were included for further analysis to reveal the independent predictors of OS and PFS by multivariate regression analysis. Additionally, all LSCC patients were divided into four subgroups based on the AJCC stage and ACCI to illustrate the benefit of adjuvant radiotherapy specifically (Table 4). Kaplan–Meier plots were used to display the benefit of adjuvant radiotherapy in these different subgroups. P < 0.05 was considered to be statistically significant.

Results

Patient clinicopathologic characteristics

A total of 147 LSCC patients were included in the study according to the inclusion criteria and exclusion criteria, with a median age of 66 years old. The 1-, 3-, and 5-year PFS of postoperative LSCC patients were 88.4%, 70.1%, and 57.8%, respectively. Similarly, the 1-, 3-, and 5-year OS of postoperative LSCC patients were 94.6%, 76.9%, and 69.4%, respectively. Of all cases, 112 patients (76.2%) with ECOG PS score of 0–1. The main primary site was lower lip (88.4%). Very few LSCC patients were with positive perineural invasion (8.2%) and vascular invasion (13.6%). Most patients were with negative ENE (87.8%) and had a surgical margin ≥ 5 (84.4%). There were 84 (57.1%) patients with LSCC who receive adjuvant radiotherapy after surgical resection.

There were a series of immune-inflammatory-nutritional indicators selected and analyzed in this study, and the indicators of SII (median 1138 (IQR: 686–1573)), PNI (median 73 (IQR: 49–96)), PLR (median 148 (IQR: 93–202)), and NLR (median 2.42 (IQR: 1.34–3.29)) were analyzed as continuous variables. The GPS was analyzed as categorical variable, which was divided into three groups according to the score of C-reactive protein and albumin, 103 (70.1%) patients with 0 score, 24 (16.3%) patients with 1 score, and 20 (13.6%) patients with 2 score. Moreover, hemoglobin (HGB) is also a marker implicated in nutritional status, which was also included in analysis with a median of 101 g/l (IQR: 90 g/l–121 g/l). Finally, 87 (59.2%) LSCC patients were with an ACCI score of < 5, and 60 (40.8%) LSCC patients were with an ACCI score of ≥ 5. All baseline of clinicopathological characteristics was summarized in Table 1.

Table 1 Clinicopathological characteristics of postoperative LSCC patients
Full size table

There were 11 patients with multiple primary tumors: two patients had lung cancer, two had basal cell carcinoma, three had thyroid cancer, three had malignant lymphoma, and one had both oropharyngeal and breast cancer.

Univariate and multivariate Cox regression results

The clinicopathological factors associated with OS and PFS of postoperative LSCC patients were identified by the univariate and multivariate Cox regression analyses. Univariate Cox regression analysis showed that age at diagnosis, grade, AJCC stage, GPS, SII, PNI, ACCI, vascular invasion, surgical margin, and ENE were significant factors for PFS (Table 2). Besides, nine variables (age at diagnosis, AJCC stage, GPS, SII, PNI, ACCI, vascular invasion, surgical margin, and ENE) were found to be associated with OS (Table 3). Consequently, independent prognostic factors associated with PFS and OS were figured out by multivariate Cox regression analysis respectively. The independent predictors related to PFS were as follows: age at diagnosis [≥ 70 years: hazard ratio (HR) = 2.986 (95% confidential interval (CI) = 1.780–5.009), P = 0.001], grade [moderate differentiate: HR = 1.895 (95% CI = 1.078–3.332), P = 0.026; poor differentiate: HR = 2.688 (95% CI = 1.447–4.995), P = 0.002], AJCC stage [IV: HR = 3.814 (95% CI = 1.682–8.651), P = 0.001], SII [HR = 1.000 (95% CI = 1.000–1.001), P = 0.013], ACCI [≥ 5: HR = 1.731 (95% CI = 1.075–2.788), P = 0.024], surgical margin [≥ 5: HR = 0.523 (95% CI = 0.282–0.970), P = 0.04]. The independent prognostic factors related to OS include the following: age at diagnosis [≥ 70: HR = 2.334 (95% CI = 1.382–3.976), P = 0.002], AJCC stage [IV: HR = 3.841 (95% CI = 1.516–9.734), P = 0.005], GPS [1: HR = 1.986 (95% CI = 1.020–3.864), P = 0.043; 2: HR = 2.127 (95% CI = 1.070–4.229), P = 0.003], SII [HR = 1.000 (95% CI = 1.000–1.001), P = 0.003], ACCI [≥ 5: HR = 2.402 (95% CI = 1.403–4.111), P = 0.001]. The detailed result was shown in Tables 2 and 3.

Table 2 Univariate and multivariate analyses results for PFS in postoperative LSCC patients
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Table 3 Univariate and multivariate analyses results for OS in postoperative LSCC patients
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Additionally, all enrolled postoperative patients with LSCC were divided into four subgroups according to the ACCI and AJCC stage, and the benefits of adjuvant radiotherapy on OS and PFS were displayed by the Kaplan–Meier plots in Table 4, Figs. 1 and 2. Obviously, there was a considerable benefit of prognosis in the subgroup of ACCI < 5 and AJCC stages III–IV for LSCC patients who receive adjuvant radiotherapy, but not for the other subgroups.

Table 4 Impact of adjuvant radiotherapy on PFS and OS in different subgroups of postoperative LSCC patients
Full size table
Fig. 1
figure 1

The effects of adjuvant radiotherapy on OS in different subgroups by Kaplan–Meier curves. A AJCC stages I–II and ACCI 2–4. B AJCC stages III–IV and ACCI 2–4. C AJCC stages I–II and ACCI ≥ 5. D AJCC stages III–IV and ACCI ≥ 5. ACCI, age-adjusted Charlson Comorbidity Index; OS, overall survival

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Fig. 2
figure 2

The effects of adjuvant radiotherapy on PFS in different subgroups by Kaplan–Meier curves. A AJCC stages I–II and ACCI 2–4. B AJCC stages III–IV and ACCI 2–4. C AJCC stages I–II and ACCI ≥ 5. D AJCC stages III–IV and ACCI ≥ 5. ACCI, age-adjusted Charlson comorbidity index; PFS, progression-free survival

Full size image

Discussion

LSCC was a common type of oral cancer. Mostly, the AJCC stage system was commonly applied to predict the prognosis of LSCC patients [1, 17]. Previously, various studies indicate that local advanced stage LSCC patients tend to have a poorer prognosis [18, 19], which is consistent with our study. However, increasing studies suggest that other clinicopathological factors also had an important effect on the prognosis of LSCC patients except for the traditional AJCC stage system.

Age at diagnosis is a commonly used factor in assessing the general condition of cancer patients. There was a different morbidity and mortality in different age groups for most cancers. Wolfer S. et al. [20] showed that age at diagnosis had a different effect on prognosis depending on gender in oral cancer patients. However, some researchers suggest that age has little effect on prognosis or has an effect only in certain populations [21, 22]. It was controversial in the impact of age on the prognosis of LSCC patients. In this study, older patients with LSCC have shorter survival times, which was similar to the results of previous studies [14, 18, 23].

Tumor differentiation is a traditional clinical factor, which commonly have an important impact on the prognosis of patients with cancer to some extent. It has been always taken into account in the evaluation of prognosis and treatment choice in various cancers. Vesna Janevska et al. [24] found that poorer differentiation can increase the density of neoangiogenesis in lower LSCC patients. In this study, we found that LSCC patients with moderate or poor differentiate tend to have a relatively worse PFS in comparison to LSCC patients with well differentiate, which is consistent with previous studies. As is well known, OS is more likely to be affected by multiple clinical or social factors than PFS. Therefore, it is reasonable that tumor differentiation is not an important factor for predicting OS of LSCC patients according to our results.

Although the definition of “close margin” has always been a controversial topic in oral cancer surgery, there is a consensus that close margin may improve local recurrence rate and reduce long-term survival [25,26,27,28]. Our study suggested that a surgical margin distance within 5 mm from the tumor is unsafe and will predict a poor prognosis. Due to the delicate anatomical structure of the maxillofacial region, excessive surgical margins may destroy organ function and cause cosmetic defects. Further studies with a larger sample size were needed to determine the appropriate surgical margins.

Previous researchers had paid their attention to ENE and vascular invasion in oral cancer [3, 17,18,19,20]. In our study, although ENE and vascular invasion were not the independent prognostic factors, they had significantly negative effects on both OS and PFS in postoperative LSCC patients by univariate Cox analysis. If the pathological and imaging results show ENE and/or vascular invasion, the clinicians should adjust the treatment intensity and follow-up frequency.

As we all know, inflammation-related indicators generally play an important role in tumor microenvironment and treatment [29,30,31,32]. Complete blood count (FBC), C-reactive protein (CRP), and albumin can reflect the systemic inflammatory status of cancer patients and thus predict prognosis to some extent [29, 33]. SII, GPS, and PNI are indicators of systemic inflammation status calculated from the above clinical data, reflecting not only systemic inflammation but also the antitumor response and immune monitoring status of the patient. Increased neutrophil counts or neutrophilia in cancer occur due to the secretion of myeloid growth factors by tumor cells triggering neutrophil production or due to cancer-related inflammation secondary to tissue destruction or hypercytokinemia [34]. Lymphocytopenia and neutropenia are often associated with reduced antitumor response and immunosuppression [29, 35,36,37]. Numerous studies have revealed a negative correlation between SII and tumor prognosis [38,39,40,41,42]. Both GPS and PNI incorporate serum albumin levels, which reflect a patient’s nutritional, immune, and inflammatory status, and were all important prognostic factors [43,44,45,46,47]. However, the effects of SII, PNI, and GPS on the prognosis of LSCC had not been studied. In our study, higher SII was independent predictors of PFS and OS. Besides, the higher the GPS, the worse the OS in LSCC patients according to the results. PNI has some effects on the prognosis of LSCC patients, but was not the independent predictors of prognosis. All these results were an important supplement to the study of LSCC.

The ACCI is a useful comorbidity indicator, which is commonly utilized to normalize the assessment of patients of different ages and has been reported to predict the mortality of various cancers [48,49,50]. In our study, for LSCC patients who underwent adjuvant radiotherapy, the OS (P = 0.016) and PFS (P = 0.018) were significantly improved in subgroup of AJCC stages III–IV and ACCI < 5. Moreover, in the subgroup of ACCI ≥ 5 or AJCC stages I–II, adjuvant radiotherapy did not have any benefit in improving the prognosis. Therefore, it is importantly that we should not only refer to the AJCC stage system but also pay more attention to patients’ ACCI scores in choosing the optimal treatment strategy for postoperative LSCC patients.

There are also some limitations in our study. Firstly, this was a retrospective study, which had some inevitable selective bias. Secondly, due to the low incidence of LSCC, the selected cases were small and cannot reflect the situation of all LSCC patients in China. Finally, some potential prognostic factors were not included in the analysis, such as pain score, tumor markers, dietary habits, marital status, and preoperative mean platelet volume. Further research should be conducted to find more prognostic factors in LSCC patients.

Conclusion

In summary, a series of significant immune-inflammation-related and comorbidity-related clinicopathological factors associated with the prognosis of postoperative LSCC patients were identified in this study. It is helpful for patients and surgeons to pay more attention to nutrition, inflammation, and complications and finally obtained a better prognosis.

Availability of data and materials

Detailed data are available from the corresponding author on reasonable request.

Abbreviations

ACCI:

Age-adjusted Charlson comorbidity index

AJCC:

American Joint Committee on Cancer

BMI:

Body mass index

CI:

Confidential interval

CSCO:

Chinese Society of Clinical Oncology

ECOG-PS:

Eastern Cooperative Oncology Group performance status score

ENE:

Extranodal extension

GPS:

Glasgow prognostic score

HPV:

Human papillomavirus

HR:

Hazard ratio

IMRT:

Intensity-modulated radiotherapy

IQR:

Inter-quartile range

LSCC:

Lip squamous cell carcinoma

NLR:

Neutrophil-to-lymphocyte ratio

OS:

Overall survival

PFS:

Progression-free survival

PLR:

Platelet-to-lymphocyte ratio

PNI:

Prognostic nutrition index

SII:

Systemic immune-inflammation index

References

  1. Han AY, Kuan EC, Mallen-St Clair J, Alonso JE, Arshi A, St John MA. Epidemiology of squamous cell carcinoma of the lip in the United States: a population-based cohort analysis. JAMA Otolaryngol Head Neck Surg. 2016;142(12):1216–23.

    Article  PubMed  Google Scholar 

  2. Farhadi K, Rojanaworarit C, Bhurosy T, Olokunlade T, Karaye IM. Trends in lip, oral cavity, and pharyngeal cancer mortality in the United States, 1999–2019. J Oral Pathol Med. 2022;51(9):763–70.

    Article  CAS  PubMed  Google Scholar 

  3. Ellington TD, Henley SJ, Senkomago V, O’Neil ME, Wilson RJ, Singh S, Thomas CC, Wu M, Richardson LC. Trends in incidence of cancers of the oral cavity and pharynx - United States 2007–2016. MMWR Morb Mortal Wkly Rep. 2020;69(15):433–8.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Miranda-Filho A, Bray F. Global patterns and trends in cancers of the lip, tongue and mouth. Oral Oncol. 2020;102:104551.

    Article  PubMed  Google Scholar 

  5. Bota JP, Lyons AB, Carroll BT. Squamous cell carcinoma of the lip-a review of squamous cell carcinogenesis of the mucosal and cutaneous junction. Dermatol Surg. 2017;43(4):494–506.

    Article  CAS  PubMed  Google Scholar 

  6. Hashim D, Genden E, Posner M, Hashibe M, Boffetta P. Head and neck cancer prevention: from primary prevention to impact of clinicians on reducing burden. Ann Oncol. 2019;30(5):744–56.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Shrestha AD, Vedsted P, Kallestrup P, Neupane D. Prevalence and incidence of oral cancer in low- and middle-income countries: a scoping review. Eur J Cancer Care (Engl). 2020;29(2):e13207.

    Article  PubMed  Google Scholar 

  8. Unsal AA, Unsal AB, Henn TE, Baredes S, Eloy JA. Cutaneous squamous cell carcinoma of the lip: a population-based analysis. Laryngoscope. 2018;128(1):84–90.

    Article  CAS  PubMed  Google Scholar 

  9. Kerawala C, Roques T, Jeannon JP, Bisase B. Oral cavity and lip cancer: United Kingdom National Multidisciplinary Guidelines. J Laryngol Otol. 2016;130(S2):S83–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Chinese Society of Clinical Oncology (CSCO) diagnosis and treatment guidelines for head and neck cancer 2018 (English version). Chin J Cancer Res. 2019;31(1):84–98. https://doi.org/10.21147/j.issn.1000-9604.2019.01.05. PMID: 30996568.

  11. Schilling C, Stoeckli SJ, Vigili MG, de Bree R, Lai SY, Alvarez J, Christensen A, Cognetti DM, D’Cruz AK, Frerich B, et al. Surgical consensus guidelines on sentinel node biopsy (SNB) in patients with oral cancer. Head Neck. 2019;41(8):2655–64.

    Article  PubMed  Google Scholar 

  12. Giammarile F, Schilling C, Gnanasegaran G, Bal C, Oyen WJG, Rubello D, Schwarz T, Tartaglione G, Miller RN, Paez D, et al. The EANM practical guidelines for sentinel lymph node localisation in oral cavity squamous cell carcinoma. Eur J Nucl Med Mol Imaging. 2019;46(3):623–37.

    Article  PubMed  Google Scholar 

  13. Cervenka B, Pipkorn P, Fagan J, Zafereo M, Aswani J, Macharia C, Kundiona I, Mashamba V, Zender C, Moore M. Oral cavity cancer management guidelines for low-resource regions. Head Neck. 2019;41(3):799–812.

    Article  PubMed  Google Scholar 

  14. Lin YW, Kang WP, Hong CQ, Huang BL, Qiu ZH, Liu CT, Chu LY, Xu YW, Guo HP, Wu FC. Nutritional and immune-related indicators-based nomogram for predicting overall survival of surgical oral tongue squamous cell carcinoma. Sci Rep. 2023;13(1):8525.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Liu TPJ, David M, Clark JR, Low TH, Batstone MD. Prediction nomogram development and validation for postoperative radiotherapy in the management of oral squamous cell carcinoma. Head Neck. 2023;45(6):1503–10.

    Article  PubMed  Google Scholar 

  16. Jiang S, Dong Y. Human papillomavirus and oral squamous cell carcinoma: a review of HPV-positive oral squamous cell carcinoma and possible strategies for future. Curr Probl Cancer. 2017;41(5):323–7.

    Article  PubMed  Google Scholar 

  17. Sumer BD. Editorial: cancer staging in squamous cell carcinoma of the vermilion lip. Ann Surg Oncol. 2021;28(6):2944–5.

    Article  PubMed  Google Scholar 

  18. Zanoni DK, Montero PH, Migliacci JC, Shah JP, Wong RJ, Ganly I, Patel SG. Survival outcomes after treatment of cancer of the oral cavity (1985–2015). Oral Oncol. 2019;90:115–21.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Du E, Mazul AL, Farquhar D, Brennan P, Anantharaman D, Abedi-Ardekani B, Weissler MC, Hayes DN, Olshan AF, Zevallos JP. Long-term survival in head and neck cancer: impact of site, stage, smoking, and human papillomavirus status. Laryngoscope. 2019;129(11):2506–13.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Wolfer S, Kunzler A, Foos T, Ernst C, Leha A, Schultze-Mosgau S. Gender and risk-taking behaviors influence the clinical presentation of oral squamous cell carcinoma. Clin Exp Dent Res. 2022;8(1):141–51.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Fan Y, Zheng L, Mao MH, Huang MW, Liu SM, Zhang J, Li SL, Zheng L, Zhang JG. Survival analysis of oral squamous cell carcinoma in a subgroup of young patients. Asian Pac J Cancer Prev. 2014;15(20):8887–91.

    Article  PubMed  Google Scholar 

  22. Sun Q, Fang Q, Guo S. A comparison of oral squamous cell carcinoma between young and old patients in a single medical center in China. Int J Clin Exp Med. 2015;8(8):12418–23.

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Borsetto D, Higginson JA, Aslam A, Al-Qamachi L, Dhanda J, Marioni G, Franchella S, Frigo A, Praveen P, Martin T, et al. Factors affecting prognosis in locoregional recurrence of oral squamous cell carcinoma. J Oral Pathol Med. 2019;48(3):206–13.

    Article  PubMed  Google Scholar 

  24. Kakasheva-Mazhenkovska L, Kostovski M, Gjokik G, Janevska V. Assessment of density of neovascularization in lower lip squamous cell carcinoma in relation to neoplasm differentiation grade in patients with and without neck lymph nodes metastasis. Open Access Maced J Med Sci. 2019;7(1):19–23.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Bulbul MG, Zenga J, Tarabichi O, Parikh AS, Sethi RK, Robbins KT, Puram SV, Varvares MA. Margin practices in oral cavity cancer resections: survey of American Head and Neck Society members. Laryngoscope. 2021;131(4):782–7.

    Article  PubMed  Google Scholar 

  26. Tasche KK, Buchakjian MR, Pagedar NA, Sperry SM. Definition of “close margin” in oral cancer surgery and association of margin distance with local recurrence rate. JAMA Otolaryngol Head Neck Surg. 2017;143(12):1166–72.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Lin MC, Leu YS, Chiang CJ, Ko JY, Wang CP, Yang TL, Chen TC, Chen CN, Chen HL, Liao CT, et al. Adequate surgical margins for oral cancer: a Taiwan Cancer Registry national database analysis. Oral Oncol. 2021;119:105358.

    Article  PubMed  Google Scholar 

  28. Kanatas A, Walshaw EG, Wu J, Fabbroni G, Chengot P. Prognostic factors in oral cancer surgery - results from a UK tertiary centre. Eur J Surg Oncol. 2023;49(4):755–9.

    Article  PubMed  Google Scholar 

  29. Bugada D, Allegri M, Lavand’homme P, De Kock M, Fanelli G. Inflammation-based scores: a new method for patient-targeted strategies and improved perioperative outcome in cancer patients. Biomed Res Int. 2014;2014:142425.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Greten FR, Grivennikov SI. Inflammation and cancer: triggers, mechanisms, and consequences. Immunity. 2019;51(1):27–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Sautes-Fridman C, Petitprez F, Calderaro J, Fridman WH. Tertiary lymphoid structures in the era of cancer immunotherapy. Nat Rev Cancer. 2019;19(6):307–25.

    Article  CAS  PubMed  Google Scholar 

  32. Nost TH, Alcala K, Urbarova I, Byrne KS, Guida F, Sandanger TM, Johansson M. Systemic inflammation markers and cancer incidence in the UK Biobank. Eur J Epidemiol. 2021;36(8):841–8.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Gallego A, Mendiola M, Hernando B, Berjon A, Cadiz A, Chaves-Urbano B, Heredia-Soto V, Spagnolo E, Hernandez Gutierrez A, Hardisson D, et al. Prognostic markers of inflammation in endometrioid and clear cell ovarian cancer. Int J Gynecol Cancer. 2022;32(8):1009–16.

    Article  PubMed  Google Scholar 

  34. Marques P, de Vries F, Dekkers OM, van Furth WR, Korbonits M, Biermasz NR, Pereira AM. Pre-operative serum inflammation-based scores in patients with pituitary adenomas. Pituitary. 2021;24(3):334–50.

    Article  CAS  PubMed  Google Scholar 

  35. Yang T, Mao P, Chen X, Niu X, Xu G, Bai X, Xie W. Inflammatory biomarkers in prognostic analysis for patients with glioma and the establishment of a nomogram. Oncol Lett. 2019;17(2):2516–22.

    CAS  PubMed  Google Scholar 

  36. Ahmad J, Grimes N, Farid S, Morris-Stiff G. Inflammatory response related scoring systems in assessing the prognosis of patients with pancreatic ductal adenocarcinoma: a systematic review. Hepatobiliary Pancreat Dis Int. 2014;13(5):474–81.

    Article  PubMed  Google Scholar 

  37. Quail DF, Amulic B, Aziz M, Barnes BJ, Eruslanov E, Fridlender ZG, Goodridge HS, Granot Z, Hidalgo A, Huttenlocher A, et al. Neutrophil phenotypes and functions in cancer: a consensus statement. J Exp Med. 2022;219(6):e20220011.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Li J, Cao D, Huang Y, Xiong Q, Tan D, Liu L, Lin T, Wei Q. The prognostic and clinicopathological significance of systemic immune-inflammation index in bladder cancer. Front Immunol. 2022;13:865643.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Huang H, Liu Q, Zhu L, Zhang Y, Lu X, Wu Y, Liu L. Prognostic value of preoperative systemic immune-inflammation index in patients with cervical cancer. Sci Rep. 2019;9(1):3284.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Wang D, Hu X, Xiao L, Long G, Yao L, Wang Z, Zhou L. Prognostic nutritional index and systemic immune-inflammation index predict the prognosis of patients with HCC. J Gastrointest Surg. 2021;25(2):421–7.

    Article  PubMed  Google Scholar 

  41. Ji Y, Wang H. Prognostic prediction of systemic immune-inflammation index for patients with gynecological and breast cancers: a meta-analysis. World J Surg Oncol. 2020;18(1):197.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Meng L, Yang Y, Hu X, Zhang R, Li X. Prognostic value of the pretreatment systemic immune-inflammation index in patients with prostate cancer: a systematic review and meta-analysis. J Transl Med. 2023;21(1):79.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Yamamoto T, Kawada K, Obama K. Inflammation-related biomarkers for the prediction of prognosis in colorectal cancer patients. Int J Mol Sci. 2021;22(15):8002.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Toyokawa T, Muguruma K, Yoshii M, Tamura T, Sakurai K, Kubo N, Tanaka H, Lee S, Yashiro M, Ohira M. Clinical significance of prognostic inflammation-based and/or nutritional markers in patients with stage III gastric cancer. BMC Cancer. 2020;20(1):517.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Kudou K, Nakashima Y, Haruta Y, Nambara S, Tsuda Y, Kusumoto E, Ando K, Kimura Y, Hashimoto K, Yoshinaga K, et al. Comparison of inflammation-based prognostic scores associated with the prognostic impact of adenocarcinoma of esophagogastric junction and upper gastric cancer. Ann Surg Oncol. 2021;28(4):2059–67.

    Article  PubMed  Google Scholar 

  46. Wang C, He W, Yuan Y, Zhang Y, Li K, Zou R, Liao Y, Liu W, Yang Z, Zuo D, et al. Comparison of the prognostic value of inflammation-based scores in early recurrent hepatocellular carcinoma after hepatectomy. Liver Int. 2020;40(1):229–39.

    Article  PubMed  Google Scholar 

  47. Iwai N, Okuda T, Sakagami J, Harada T, Ohara T, Taniguchi M, Sakai H, Oka K, Hara T, Tsuji T, et al. Neutrophil to lymphocyte ratio predicts prognosis in unresectable pancreatic cancer. Sci Rep. 2020;10(1):18758.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Zhou S, Zhang XH, Zhang Y, Gong G, Yang X, Wan WH. The age-adjusted Charlson Comorbidity Index predicts prognosis in elderly cancer patients. Cancer Manag Res. 2022;14:1683–91.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Takahara N, Nakai Y, Saito K, Sasaki T, Suzuki Y, Inokuma A, Oyama H, Kanai S, Suzuki T, Sato T, et al. The impact of age and comorbidity in advanced or recurrent biliary tract cancer receiving palliative chemotherapy. J Gastroenterol Hepatol. 2020;35(10):1828–35.

    Article  CAS  PubMed  Google Scholar 

  50. Qu WF, Zhou PY, Liu WR, Tian MX, Jin L, Jiang XF, Wang H, Tao CY, Fang Y, Zhou YF, et al. Age-adjusted Charlson Comorbidity Index predicts survival in intrahepatic cholangiocarcinoma patients after curative resection. Ann Transl Med. 2020;8(7):487.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

All the researcher should be highly appreciated.

Funding

The article received support from the fund from the Joint Project of Henan Province and Ministry (LHGJ20200516 and LHGJ20200500).

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Author notes

  1. Hao Cheng and Jin-Hong Xu contributed equally to this work.

Authors and Affiliations

  1. Department of Radiotherapy Oncology, The First Affiliated Hospital of Xinxiang Medical University, 88 Jiankang Road, Xinxiang, Henan, 453100, China

    Hao Cheng & Xue-Lian Xu

  2. Department of Otolaryngology, Anyang District Hospital, Anyang, Henan, 455000, China

    Jin-Hong Xu

  3. Department of Radiotherapy Oncology, Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, Henan, 450000, China

    Jia-Qi He

  4. Department of Radiotherapy Oncology, Yuanyang County People’s Hospital, Xinxiang, Henan, 453500, China

    Xi-Yang Yang & Xu-Ning Shen

Authors
  1. Hao Cheng
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  3. Jia-Qi He
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  6. Xue-Lian Xu
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Contributions

Conception and design: XLX, HC. Funding: XLX, HC. Collection and assembly of data: JHX, JQH, XYY, XNS. Data analysis and interpretation: HC, JHX, XNS. Manuscript writing: HC. Final approval of manuscript: All authors.

Corresponding author

Correspondence to Xue-Lian Xu.

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Ethics approval and consent to participate

This study has been approved by the Ethics Committee of the First Affiliated Hospital of Xinxiang Medical University and the Affiliated Cancer Hospital of Zhengzhou University. All patients provided written informed consent.

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The authors declare no competing interests.

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Supplementary Information

Additional file 1: Table S1.

Age-adjusted Charlson Comorbidity Index. Table S2. Calculation formulas in this study.

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Cheng, H., Xu, JH., He, JQ. et al. Multivariate analysis of prognostic factors in patients with lip squamous cell carcinoma after surgery. World J Surg Onc 22, 35 (2024). https://doi.org/10.1186/s12957-024-03313-9

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Keywords

World Journal of Surgical Oncology

ISSN: 1477-7819

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