Study of the significance of the combination of the fibrinogen-albumin ratio and sarcopenia in predicting the prognosis of laryngeal cancer patients undergoing radical surgery

Abstract

Objective

This study aims to investigate how the impact of preoperative sarcopenia and inflammatory markers for laryngeal cancer patients and develop a new scoring system to predict their prognosis.

Materials and methods

Patients who underwent laryngectomy for laryngeal cancer (LC) from December 2015 to December 2020 at the Second Affiliated Hospital of Fujian Medical University were included. Independent prognostic factors were determined using univariate and multivariate analyses. A new scoring system (SFAR) was established based on FAR and preoperative sarcopenia, and statistically analyzed.

Results

198 cases included in this study that met the admission criteria. Multivariate analysis shown that preoperative sarcopenia, pTNM stage, and FAR were independent prognostic factors for laryngeal cancer. Based on these three indicators, we developed the SFAR scoring system. Multivariate analysis showed that SFAR was an independent predictor of laryngeal cancer (p < 0.001). SFAR was then incorporated into a prognostic model that included T-stage and N-stage, and a column-line graph was generated to accurately predict its survival.

Conclusion

Systemic inflammation and sarcopenia are significantly associated with postoperative prognosis in laryngeal cancer. A new scoring system (SFAR) had implications for improving the prognosis of patients undergoing surgery for laryngeal cancer.

Introduction

The incidence of laryngeal cancer(LC) has been steadily increasing, making it one of the most prevalent malignancies among head and neck tumors [1, 2]. While early-stage laryngeal cancer has a cure rate of 80–90%, the prognosis for late-stage laryngeal cancer remains disappointingly poor, with survival rates hovering around 60% [3]. Therefore, identifying laryngeal cancer patients with poor prognosis or risk of premature death is a key focus of oncology research [4], and relevant studies have focused on exploring biomarkers for cancer progression [5]. Recent scientific investigations have increasingly underscored the significant interplay between systemic inflammation and muscle atrophy, contributing to adverse outcomes in patients with malignancies. These studies emphasize the link between inflammation and cancer progression, as well as the impact of muscle health on disease trajectory and complications [6–11]. Sarcopenia, characterized by a pervasive decline in skeletal muscle mass and strength, has been associated with unfavorable surgical outcomes [12]. Cancer patients are particularly susceptible to sarcopenia, with approximately one-third to one-half of head and neck squamous cell carcinoma (HNSCC) patients affected by this condition [13–16]. The presence of sarcopenia has been strongly correlated with prolonged postoperative hospitalization, increased complication risk, and slower recovery [13].

A growing body of evidence suggests that nutritional deficiencies, hemostatic factors, and inflammation play pivotal roles in the pathogenesis of human malignancies [17, 18]. Inflammation has been causally linked to cancer development and progression through multiple pathways, including aberrant tissue repair, genotoxicity, proliferative responses, and tumor metastasis and invasion [19–22]. Several studies have highlighted the potential role of fibrinogen and serum albumin in prognostic assessments of various cancers, with evidence suggesting that decreased serum albumin and elevated plasma fibrinogen are significantly associated with shortened survival in cancer patients [23–28].

This study aims to comprehensively evaluate the impact of preoperative sarcopenia and inflammatory markers on the prognosis of patients with laryngeal cancer. Additionally, it seeks to develop a novel scoring system incorporating these factors to enhance the prediction of patient outcomes in laryngeal cancer.

Patients, study design, and study measures

Study design and patients

We conducted a retrospective analysis of data from a group of patients who had undergone laryngectomy for laryngeal cancer between December 2015 and December 2020 at the Second Affiliated Hospital of Fujian Medical University. Inclusion criteria: (a) pathological diagnosis of LC; (b) life expectancy > 3 months; (c) no distant metastasis. Exclusion criteria: (a) malignancy in combination with other sites; (b) Cases with incomplete clinical information; (c) Cases of lost visits. The information collected included important clinical characteristics of the patients as well as relevant test parameters, including gender, age, height, weight, degree of differentiation, tumor depth, lymph nodes, clinical stage, inflammatory markers, and CT.

The cases in this study were treated according to AJCC guidelines and NCCN guidelines. The research involved 198 patients in total. Ethical approval for the study was obtained from the Ethics Committee of the Second Hospital of Fujian Medical University.

Assessment of sarcopenia and BMI

We select the CT level of the third cervical (C3) vertebra as the reference point for the CT scan of the head and neck [29, 30]. The cross-sectional area (CSA) of the paravertebral muscles (PVM) and sternoclavicular commissure-like muscles (SCM) were measured separately at this level and resulting in a composite CSA of the paravertebral and sternoclavicular commissure-like muscles (Fig. 1A). The conversion formulae as well as the diagnostic criteria are as follows [31]:

Fig. 1.

(A) Representative images of computed tomography (CT) scan in sarcopenia and non-sarcopenia patients

CSA at L3(cm²) =24.078 + 2.789×CSA at C3(cm²).

SMI = CSA at L3/height².

Sarcopenia was defined as having an SMI < 40.86 cm²/m² in men and a SMI < 30.71 cm²/m² in women.

Based on the calculation of the body mass index (BMI) in kg/m², and the patients were classified into the following categories [32]: BMI < 18.45 kg/m² as underweight; 18.5 to 24.9 kg/m² as normal weight; 25.0 to 29.9 kg/m² as overweight; and ≥ 30.0 kg/m² as obese.

Collection of inflammatory markers and follow-up investigation

We collected the patient’s hematology and laboratory results a week ahead of the procedure. And these consisted of lymphocyte count, neutrophil count, γ-glutamyltransferase, fibrinogen, platelet count, and albumin levels. The GLR (Gamma-Glutamyltransferase to Lymphocyte Ratio) is calculated by dividing the count of gamma-glutamyltransferase by the value of lymphocytes. The GAR is a calculation that involves dividing the gamma-glutamyltransferase count by the albumin count. The Fibrinogen Albumin Ratio (FAR) is calculated by dividing the count of fibrinogen by the count of albumin. The platelet albumin ratio (PAR) was also determined by dividing the count of platelet by the count of albumin. The FAR is a calculation that involves dividing the count of fibrin by the count of albumin. The best critical values for GLR, GAR, FAR, and PAR were identified using X-tile software [33] (the cutoff point corresponding to the maximum chi-square value obtained by the log-rank test, which is generally considered to be the best threshold for distinguishing high-risk and low-risk groups), and they were 18.1, 1.5, 0.083, and 6.9, individually.

Patients were scheduled to visit our center for follow-up appointments every three months for the first two years, every six months for the third year, and once a year thereafter. Overall survival (OS) was calculated from the date of surgery to the date of death, or the date of exclusion at last follow-up.

Statistical analysis

To summarize the characteristics of preoperative sarcopenia, systemic inflammatory indicators, and other cohort data, we employed descriptive statistics. Categorical variables were analyzed using the chi-square test or Fisher’s exact test, whereas continuous variables were assessed with the Student’s t-test. Additionally, we utilized univariate and multivariate logistic regression models to determine the association between preoperative sarcopenia and systemic inflammation.

To analyze differences in survival curves, we utilized the Kaplan-Meier method along with the log-rank test. Multivariate analysis was conducted using the Cox regression model to identify variables that significantly impacted survival. The nomogram was generated using the ‘rms’ package in R software. Calibration plots were employed to evaluate the performance of the predictive nomogram, while prediction accuracy was assessed using Harrell’s concordance index (C-index) and decision curve analyses (DCA).

All tests were conducted at a two-sided significance level, with a p-value of less than 0.05 considered statistically significant. Statistical analyses were performed using SPSS for Windows, version 20.0 (SPSS Inc., Chicago, IL), and R version 3.1.2 (R Foundation for Statistical Computing, Vienna, Austria). For t-ROC analysis, we utilized the R package ‘time ROC’.

Results

Clinical features

There were 198 cases included in this study that met the admission criteria, of which 57 were in the supraglottic region and 141 were in the glottic and subglottic regions. The tumor pathology report showed the highest percentage of grade I and II tumors (185 cases (93.4%)), followed by grade III (13 cases (6.7%)). Most patients were in the early stage of TNM classification, specifically stage I-II, accounting for 139 cases (70.2%). The percentage of patients in this stage was 148 (74.7%) patients had a BMI ≥ 25 kg/m², and 50(25.3%)patients with BMI < 25 kg/m². According to the EWGSOP recommendations, 45 individuals (22.7%) were diagnosed with sarcopenia in this study (Table 1).

Table 1.

Clinical and pathological information of included studies and Univariate and multivariate analysis

Clinicopathological features	n(%)	Univariate analysis		Multivariate analysis
		HR(95%CI)	P value	HR(95%CI)	P value
Age
≤ 61	105(53.0%)	Reference
>61	93(47.0%)	1.222(0.748–1.998)	0.423
Lymph node metastasis
0	165(83.3%)	Reference
1–2	33(16.7%)	3.067(1.814–5.186)	0.000		0.521
pTNM stage
I-II	139(70.2%)	Reference
III-IV	59(29.8%)	2.962(1.804–4.861)	0.000	2.238(1.170–4.281)	0.015
Tumor location
Glottic/Subglottic	141(71%)	Reference	0.607
Supraglottic	57(29%)	1.150(0.676–1.955)
Differentiation
Well/Moderate	185(93.4%)	Reference
Poor	13(6.7%)	2.245(0.999–5.046)	0.050
BMI
<25	148(74.7%)	Reference
≥ 25	50(25.3%)	0.742(0.415–1.327)	0.315
Sarcopenia
No	153(77.27%)	Reference
Yes	45(22.7%)	2.536(1.541–4.175)	0.000	2.813(1.666–4.750)	0.000
GLR
<18.1	137(69.2%)	Reference
≥ 18.1	61(30.8%)	1.749(1.060–2.885)	0.029	1.619(0.944–2.778)	0.080
GAR
<1.5	178(89.9%)	Reference
≥ 1.5	20(10.1%)	1.755(0.866–3.558)	0.118
FAR
<0.083	124(62.6%)	Reference
≥ 0.083	74(37.3%)	2.169(1.322–3.559)	0.002	2.462(1.397–4.340)	0.002
PAR
<6.9	155(78.2%)	Reference
≥ 6.9	43(21.7%)	1.747(1.020–2.990)	0.042	1.216(0.652–2.268)	0.540

Abbreviations: HR, hazard ratio; CI, confidence interval; pTNM, pathologic TNM; BMI, body mass index; GLR, gamma-glutamyltransferase to lymphocyte ratio; GAR, gamma-glutamyltransferase to albumin ratio; FAR, fibrinogen-to-albumin ratio; PAR, the platelet albumin ratio

Survival analysis

In this study, patients’ onset dates spanned 2015–2020. The 3-year survival rate was 76.4%. The 5-year survival rate was 78%. The median follow-up period in our study is 41 months. Univariate and multivariate analyses regarding the prediction of survival in LC patients are presented in Table 1. Uunivariate analysis showed that preoperative sarcopenia, pTNM stage, lymph node metastasis, sarcopenia, GLR, FAR and PAR were associated with OS (all p < 0.05, Table 1). Multifactorial analysis indicated that lymph node positivity rate, GLR, and PAR were not independent prognostic factors for laryngeal cancer, but preoperative sarcopenia, pTNM stage, and FAR were still independent prognostic factors for laryngeal cancer (Table 1).

Associations between Sarcopenia and systemic inflammation in LC

We conducted further studies using logistic regression to analyze whether FAR was associated with sarcopenia. Based on the findings of univariate analysis, tumor location, the degree of pathological differentiation, GAR, GLR, PAR and BMI, were not associated with preoperative sarcopenia, while age, pTNM, and FAR were significantly associated with preoperative sarcopenia. And the results of multifactorial analysis suggested that age, pTNM, and high FAR were independent predictors of preoperative sarcopenia (Table 2).

Table 2.

The relationship between the clinical and pathological indicators included in the study and sarcopenia

Clinicopathological features	Odds ratio for sarcopenia(95%CI)
	Univariate analysis	p value	Multivariate analysis	p value
Age
≤ 61	Reference
>61	2.230(1.127–4.413)	0.021	2.631(1.284–5.390)	0.008
pTNM stage
I-II	Reference
III-IV	2.338(1.171–4.668)	0.016	2.744(1.320–5.704)	0.007
Tumor location
Supraglottic	Reference
Glottic/Subglottic	1.507(0.743–3.058)	0.256
Differentiation
Well/Moderate	Reference
Poor	0.600(0.128–2.814)	0.517
BMI
<25	Reference
≥ 25	1.931(0.940–3.966)	0.073
GLR
<18.1	Reference
≥ 18.1	1.019(0.497–2.089)	0.960
GAR
<1.5	Reference
≥ 1.5	1.527(0.551–4.237)	0.416
FAR
<0.083	Reference
≥ 0.083	0.397(0.183–0.860)	0.019	0.314(0.153–0.761)	0.009
PAR
<6.9	Reference
≥ 6.9	0.482(0.189–1.230)	0.127

Abbreviations: CI, confidence interval; pTNM, pathologic TNM; BMI, body mass index; GLR, gamma-glutamyltransferase to lymphocyte ratio; GAR, gamma-glutamyltransferase to albumin ratio; FAR, fibrinogen-to-albumin ratio; PAR, the platelet albumin ratio

Establishment of a new prognostic scoring system SFAR

To more precisely differentiate patients with sarcopenia and their respective prognosis, we integrated sarcopenia and FAR levels into four subgroups. The group with sarcopenia and FAR > 0.083 had the worst survival, while the group without sarcopenia and FAR ≤ 0.083 had the longest survival (p < 0.05, Fig. 2A and C). In contrast, patients without sarcopenia and FAR > 0.083 had similar survival to those with sarcopenia with FAR ≤ 0.083 (p > 0.05, Fig. 2C), with no statistically significant difference. To further distinguish between the different prognostic outcomes, we regrouped the subgroups. We grouped the two groups with similar survival and scored them, defined as follows: Patients with both sarcopenia and FAR > 0.083 were scored as 2; patients with either sarcopenia or FAR > 0.083 were scored as 1; and patients neither sarcopenia nor FAR ≤ 0.083 were scored as 0. Table 3 shows the relationship between SFAR and clinicopathological factors. There were 89 cases in the SFAR = 0 group, 99 cases in the SFAR = 1 group and 10 cases in the SFAR = 2 group. Our findings suggest that elevated SFAR is distinctly related to age and T stage (Table 3).

Fig. 2.

(A-D) Kaplan-Meier analysis based on FAR and sarcopenia in overall survival (OS) of laryngeal cancer patients. Kaplan‐Meier analysis for (A) sarcopenia vs. nosarcopenia, (B) FAR ≤ 0.083 vs. FAR>0.083, (C) combination of FAR and sarcopenia, and (D) SFAR

Table 3.

Relationship between SFAR and clinicopathological characteristics of patients included in the study

Clinicopathological features	SFAR, n(%)			p value
	0	1	2
Case	89	99	10
Age
≤ 61	57(54.3%)	43(41.0%)	5(4.8%)	0.018
>61	32(34.4%)	56(60.2%)	5(5.4%)
T stage
T1,T2	72(49.7%)	68(49.9%)	5(3.4%)	0.039
T3,T4	17(32.1%)	31(58.5%)	5(9.4%)
pTNM
I, II	69(49.6%)	65(46.8%)	5(3.6%)	0.074
III, IV	20(33.9%)	34(57.6%)	5(8.5%)
Location
Supraglottic	64(45.4%)	70(49.6%)	7(5.0%)	0.980
Glottic/Srbglottic	25(43.9%)	29(50.9%)	3(5.3%)
BMI
<25	70(47.3%)	71(48.0%)	7(4.7%)	0.517
≥ 25	19(38.0%)	28(56.0%)	3(6.0%)

Abbreviations: pTNM, pathologic TNM; BMI, body mass index

Influence of the SFAR on OS

We analyzed the Kaplan-Meier curve of the 5-year OS rate and divided it into three groups based on the SFAR score (Fig. 2D). These groups were SFAR = 0 (44.9%), SFAR = 1 (50%), and SFAR = 2 (5.1%). According to the multifactorial analysis results, SFAR was an independent prognostic factor that affected patient survival (OS, Table 4). Our findings also showed that patients with sarcopenia and FAR ≥ 0.083 had more than a two-fold increased risk of death from any cause compared to patients with SFAR = 0 (Table 4). In addition, pTNM stage was also one of its independent risk factors (p < 0.001).

Table 4.

Multivariate analysis of clinical information of included studies and overall survival of patients included in the study

Clinicopathological features	Multivariate analysis
	HR(95%CI)	P value
pTNM stage
I-II	Reference
III-IV	2.600(1.573–4.297)	0.000
SFAR
0	Reference
1	3.062(1.639–5.720)	0.000
2	8.386(3.523–19.965)	0.000

Abbreviations: CI, confidence interval; HR, hazard ratio; pTNM, pathologic TNM; SFAR, Sarcopenia and the fibrinogen-to-albumin ratio

Predictive nomogram based on SFAR

We included an external validation cohort consisting of patients who underwent laryngectomy at Shaowu Hospital in Fujian Province between January 2017 and December 2020 to assess the predictive accuracy of the SFAR system. These patients met the same inclusion and exclusion criteria as those in the original study, and identical data collection procedures were followed. A total of 160 patients were included in this cohort.

To enhance the predictive accuracy, we developed a nomogram that incorporated SFAR, T stage, and N stage (Fig. 3 C). The calibration plots for the nomogram’s predictions of 3-year and 5-year survival rates demonstrated strong correlations between predicted and actual outcomes in both the training and validation cohorts (Figs. 3A and B and 4A and B). Decision curves were drawn to compare the nomogram’s performance with that of traditional staging systems (Figs. 3D and 4D), and the nomogram provided the highest net benefit. The C-index values for the two nomograms were 0.796 and 0.830, respectively.

Fig. 3.

(A-D) Nomogram based on T-stage, N-stage, and SFAR in 198 patients with postoperative laryngeal cancer. Calibration plot of the nomogram for (A) 3-year and (B) 5‐year survival. (C): Nomograms predicting 3- and 5-year postoperative OS in LC patients. (D): Decision Curve Analysis for SFAR systems for Laryngeal cancer. Abbreviation: SFAR, sarcopenia and fibrinogen-to-albumin ratio

Fig. 4.

(A-D) Nomogram based on T-stage, N-stage, and SFAR in 160 patients with postoperative laryngeal cancer. Calibration plot of the nomogram for (A) 3-year and (B) 5‐year survival. (C): Nomograms predicting 3- and 5-year postoperative OS in LC patients. (D): Decision Curve Analysis for SFAR systems for Laryngeal cancer. Abbreviation: SFAR, sarcopenia and fibrinogen-to-albumin ratio

In conclusion, the calibration plots for the nomogram’s 3-year and 5-year survival predictions showed excellent performance, demonstrating high predictive accuracy and reliability. This nomogram, therefore, offers strong guidance for clinical practice.

Discussion

The tolerance of adult cancer patients to treatment varies significantly due to individual differences, even among patients with identical TNM staging and treatment regimens. Consequently, prognostic outcomes can differ substantially. Traditional prognostic indicators, including the tumor-node-metastasis system, histological subtype, and carcinoembryonic antigen (CEA), are widely recognized as key references for assessing cancer prognosis. However, the clinical application of these conventional prognostic factors is limited by their invasiveness and high cost. Therefore, the identification of economical, simple, and effective cancer biomarkers is crucial for improving prognostic evaluations.

Increasing evidence suggests that inflammation and sarcopenia are associated with the progression of various tumors [17, 31, 34]. Although the precise relationship between sarcopenia and inflammation and their potential predictive value remains unclear, some studies indicate a possible link among these factors. Céline M. Op den Kamp et al. found elevated levels of inflammatory markers in the serum of patients with malignant lung cancer compared to healthy controls [35]. Riccardi and colleagues demonstrated differences in systemic inflammatory markers between patients with malignant tumors and weight-stable cancer patients [36]. Their findings revealed higher levels of pro-inflammatory cytokines and altered fatty acid lipid profiles in patients with malignant gastrointestinal cancers [36]. Further analysis identified dietary intake and serum CRP concentrations as significant independent variables influencing weight loss in gastroesophageal cancer patients. Abbass et al. also observed differences in systemic inflammatory markers between patients with malignant tumors and those with stable body weight [37], establishing a strong correlation between systemic inflammation and low skeletal muscle index in cancer patients. This suggests a potential link between sarcopenia and inflammation in cancer cachexia, with significant implications for the development of treatment strategies and prognostic assessments in cancer patients. Based on our results, we found that sarcopenia and FAR (inflammatory markers) are independent prognostic indicators for laryngeal cancer. Laryngeal cancer patients with sarcopenia and FAR ≥ 0.083 before surgery tend to have a poor prognosis. In addition, we found that patients could be divided into three groups based on sarcopenia and FAR (inflammatory markers) in subgroup analysis. So, we developed the SFAR scoring system for evaluation of patient prognosis. And we further validated the accuracy of the SFAR scoring system through internal and external queues. In summary, we believe that sarcopenia and FAR (inflammatory markers) are may important factors in assessing patient prognosis. In the future, we may strengthen patient nutrition and regulate inflammatory indicators such as FAR to improve patient survival prognosis.

Moreover, TNM staging remains an independent prognostic factor for OS in LC patients, consistent with current consensus. However, univariate and multivariate statistical analyses consistently indicate that age is not an independent prognostic factor. The impact of age on LC prognosis remains controversial [38–40].

Research on sarcopenia in head and neck cancer (HNC) patients is currently limited [41]. Malnutrition exacerbates cancer progression by impairing immunity, anatomical barriers, and other defense mechanisms [42]. The prevalence of sarcopenia in HNC patients may be associated with tumor location, as these patients often experience pain and difficulty swallowing due to the tumor, leading to inadequate nutritional intake, metabolic abnormalities, and malnutrition. These factors further compromise the immune system, making patients more susceptible to infections and other complications [43]. One study found that sarcopenia is common among HNC patients, with the incidence of sarcopenia nearly doubling post-radiotherapy compared to pre-treatment levels, and overall survival rates being relatively low in sarcopenic patients [44, 45]. Our study confirmed that sarcopenic patients had poorer OS than non-sarcopenic patients, highlighting the importance of early detection and intervention in cancer patients with concurrent sarcopenia.

Recent studies have shown that inflammation, hypercoagulability, and malnutrition can promote tumor development, progression, recurrence, and metastasis, contributing to the deterioration of malignancies [46, 47]. Although the specific mechanisms involved are still being explored, emerging research suggests that tumor-associated inflammation is a hallmark of cancer and plays a critical role in tumorigenesis and progression [48, 49]. Cancer cells may interact with the stroma and inflammatory cells via inflammation-induced factors, such as interleukin-2, affecting catabolic pathways and triggering high levels of fib expression, which leads to muscle breakdown [50–52]. Evidence also indicates that inflammatory cytokines can activate the ubiquitin-proteasome pathway, leading to muscle atrophy and insulin resistance, with systemic inflammation further promoting fibrinogen release [53]. Consequently, a vicious cycle may exist between inflammatory cytokines and muscle wasting, exacerbating insulin resistance and fostering a pro-tumorigenic environment [54]. Fibrinogen is not only a key element in the coagulation cascade but also plays a pivotal role in the acute phase response of systemic inflammation [55]. Additionally, fibrinogen appears to promote chronic low-grade inflammation. It facilitates cancer metastasis by influencing leukocyte and platelet migration and serves as a scaffold that supports cancer growth, invasion, and metastasis. Beyond its role in acute phase response and inflammatory activity, fibrinogen contributes to tumorigenesis through involvement in epithelial-mesenchymal transition, angiogenesis, and cellular proliferation [50, 56–59]. Multiple studies have demonstrated that elevated fibrinogen levels are associated with shorter survival in patients with advanced pancreatic cancer [60–62].Our research also indicates a correlation between systemic inflammation and muscle wasting, which may adversely affect the prognosis of patients with laryngeal cancer. Malnutrition or hypoalbuminemia, often observed in cancer cachexia, are common in patients with advanced-stage disease [50]. Albumin, an important parameter for assessing nutritional status, possesses anti-inflammatory and antioxidant properties and is closely correlated with systemic inflammation [42]. For example, certain factors, such as tumor necrosis factor-alpha, can inhibit albumin synthesis through various pathways, leading to hypoalbuminemia [63]. In addition to these characteristics, albumin has been utilized as a prognostic indicator of cancer survival [64]. Numerous studies have shown that low albumin levels are negatively correlated with prognosis in patients with diffuse large B-cell lymphoma and hepatocellular carcinoma [60–62].

Researchers have extensively studied the potential of albumin and fibrinogen as cancer biomarkers, finding them effective in evaluating the coagulation, nutritional, and inflammatory status of cancer patients [65]. An elevated FAR suggests a hypercoagulable state, hypoalbuminemia, cachexia, and malnutrition in cancer patients. Consequently, assessing this ratio may provide insights into cancer progression and the interplay between inflammation, nutrition, and disease status. Several studies have identified high FAR (> 0.083) as a negative prognostic factor in malignancy [65–68]. Claps et al. found that patients with lower AFR had poorer overall and cancer-specific survival, consistent with previous findings [68, 69]. Our study further demonstrated that FAR is an independent prognostic factor in laryngeal cancer.

Moreover, this study reveals that regardless of tumor origin or TNM stage, patients with sarcopenia and high FAR exhibit significantly lower OS compared to their counterparts. We developed a novel prognostic scale, the SFAR, based on the correlation between preoperative sarcopenia and FAR, identifying SFAR as an independent prognostic factor in LC patients. Additionally, patients with sarcopenia and a low SFAR (SFAR = 2) faced nearly double the risk of mortality compared to those without these conditions. Our research team believes that the SFAR scoring system can effectively complement the TNM staging system, helping to identify patient groups with poorer prognoses. This insight can inform future clinical practices by emphasizing the importance of preoperative rehabilitation and nutritional therapies. These interventions can improve patients’ muscle quality and function, thereby enhancing surgical success rates and postoperative recovery outcomes.

The National Cancer Action Team in the UK stipulates that the first treatment should occur within 31 days of the decision, which plays a significant role in minimizing disease progression. This also implies that preoperative treatments should be completed within this timeframe. Therefore, research has increasingly focused more on employing multimodal prehabilitation strategies aimed at evaluating through systematic methods and, guided by evidence-based medicine, combining measures such as nutritional support to achieve optimal preoperative preparation effects in the short term [70]. Despite this, there is still no consensus regarding effective evaluation methods, optimal prehabilitation plans, and ideal therapeutic effect assessment criteria [71].

Optimizing preoperative nutrition is an important measure. Clinicians work together with registered dietitians to develop individualized dietary plans and provide nutritional supplements to ensure patients receive adequate energy and protein [3, 72–76]. For patients who cannot consume sufficient amounts orally, feeding tubes or percutaneous endoscopic gastrostomy (PEG) and parenteral nutrition may be considered. Research by Lopes et al. indicates that strictly controlling dietary intake can improve functional outcomes such as grip strength and mobility [77, 78]. Additionally, it is recommended to take products containing branched-chain amino acids after exercise [79], and provide appropriate pharmacological treatments based on the patient’s condition, such as vitamin D and calcium supplementation for older adults to maintain bone health, and anti-inflammatory drugs for patients with chronic inflammation [3, 77, 80–85].

During the preoperative phase, exercise training should be an integral part of prehabilitation programs, including muscle strengthening exercises for upper and lower limbs under the guidance of specialized therapists, as well as standing, stretching exercises, and coughing postoperatively [86]. Appropriate resistance training can enhance muscle mass and strength, while aerobic activities such as walking and swimming can improve cardiopulmonary function [70, 87]. Moreover, balance and flexibility training can increase the ability to perform daily activities and reduce the risk of falls. Muscle conditions can be assessed using bioelectrical impedance analysis (BIA) and muscle function tests, and these assessments can guide adjustments to nutritional and exercise plans [88].

Patients with malignant tumors often experience significant emotional distress, a psychological state that often does not receive adequate attention. Therefore, we recommend involving family members in rehabilitation plans to provide emotional and social support to the patient. At the same time, education about the disease should be provided to both patients and their families, guiding them on how to monitor symptom changes and developments [89], explaining the impact of sarcopenia and the importance of preventive measures. In addition, patients are advised to quit smoking and alcohol consumption to reduce inflammation and oxidative stress, and to ensure they get adequate sleep to promote muscle recovery, all of which are essential [3, 77, 80–84].

Through the application of these preventive measures, we hope to improve the nutritional status and physical function of preoperative patients, thereby enhancing surgical success rates and accelerating postoperative recovery. We believe that these comprehensive interventions will contribute to improved overall treatment outcomes for patients.

Limitations

Our study had some limitations that are worth noting. Firstly, it was conducted in a single center and the sample size was limited. This could have resulted in selection bias, which is a limitation of the study. Secondly, we were unable to determine if all patients were in the same state before blood collection. Thirdly, the sarcopenia threshold used in our study was based on previous research and may not be applicable to our subgroup. However, despite these limitations, our study confirms the close association of sarcopenia with systemic inflammation, each of which is an important indicator of LC prognosis.

Conclusions

Our research has discovered a clear correlation between preoperative systemic inflammation, sarcopenosis, and postoperative prognosis in patients with laryngeal cancer. Based on these findings, we have developed a new prognostic scoring index (SFAR) that can effectively predict the outcomes of laryngeal cancer and is a valuable complement to TNM staging’s prognostic value. This development can lead to the creation of new treatments that can improve cancer prognosis.

Author contributions

Conceptualisation, methodology, software, validation, ZM and YZ; surveys and resources, ML and SR; data collation, JZ; writing-review and editing, MZ; writing-original draft preparation, YH and KC and XL; data collation and software, writing-review and editing, CX; access to funding, project management, writing-review and editing, CZ.All authors have read and agreed to the published version of the manuscript.No potential conflicts of interest were disclosed.

Funding

This study was supported by the Provincial Natural Science Foundation of Fujian Provincial Department of Science and Technology (Grant No. 2023J01722), Quanzhou City High-level Talents Innovation and Entrepreneurship Project of Quanzhou Municipal Bureau of Science and Technology in 2022 (Grant No. 2022C033R), Medical Innovation Subject of Science and Technology Programme Project of Fujian Provincial Commission of Health Planning (Grant No. 2023CXA033), and the Natural Science Foundation of Nanping (Grant no: N2023J046) were funded.

Data availability

The datasets used and analysed during the current study available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This study is based on the current version of the Helsinki Declaration and good clinical practice guidelines. Ethical approval for this study was obtained from the Ethical Review Board for Human Research of the Second Affiliated Hospital of Fujian Medical University, Fujian, China (approval No. 517, 2023). Informed consent was obtained from all participants. All authors have read and agreed to the published version of the manuscript. No potential conflicts of interest were disclosed.

Consent for publication

Not Applicable.

Competing interests

The authors declare no competing interests.