
==== Front
BMC Cancer
BMC Cancer
BMC Cancer
1471-2407
BioMed Central London

12872
10.1186/s12885-024-12872-9
Research
The controlling nutritional status score as a new prognostic predictor in patients with cervical cancer receiving radiotherapy: a propensity score matching analysis
Fu Juan 1
Xu Xintian 2
Tian Mengxing 3
Wang Hongbing 4
Jin Xin jinxinrd@alumni.hust.edu.cn

3
1 grid.460060.4 Department of Clinical Nutrition, Wuhan Third Hospital, Tongren Hospital of Wuhan University, Wuhan, China
2 grid.33199.31 0000 0004 0368 7223 Department of Pharmacy, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei China
3 grid.33199.31 0000 0004 0368 7223 Department of Clinical Nutrition, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei China
4 grid.33199.31 0000 0004 0368 7223 Department of Gynecology and Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei China
3 9 2024
3 9 2024
2024
24 10931 1 2024
28 8 2024
© The Author(s) 2024
2024
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Background

As assessment tools of nutritional status, the controlling nutritional status (CONUT) and modified controlling nutritional status (mCONUT) score are associated with survival in various cancers. We aimed to investigate the association between the CONUT/mCONUT score’s prognostic value and survival time in patients with FIGO stage IIB–IIIB cervical cancer treated with radiotherapy.

Methods

In this retrospective study, 165 patients between September 2013 and September 2015 were analyzed, and the optimal CONUT/mCONUT score cut-off values were determined using receiver operating characteristic curves. Propensity score matching (PSM) was used to minimize selection bias. The Kaplan–Meier method and a Cox proportional hazard model were used to assess the CONUT/mCONUT score’s predictive value linked to survival time. Two nomograms were created to predict the overall survival (OS) and progression-free survival (PFS).

Results

The cut-off values for CONUT and mCONUT score were both 2. Five-year OS and PFS rates were higher in a low CONUT score group than in a high CONUT score group (OS: 81.1% vs. 53.8%, respectively, P < 0.001; PFS: 76.4% vs. 48.2%, respectively; P < 0.001). A high CONUT score was associated with decreased OS (hazard ratio (HR) 2.93, 95% CI 1.54–5.56; P = 0.001) and PFS (HR 2.77, 95% CI 1.52–5.04; P < 0.001). High CONUT scores influenced OS in the PSM cohort. A high mCONUT score was not associated with decreased OS and PFS in Cox regression analysis.

Conclusion

The CONUT score is a promising indicator for predicting survival in patients with cervical cancer receiving radiotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-024-12872-9.

Keywords

Cervical cancer
Controlling nutritional status score
CONUT
Radiotherapy
Survival time
Wuhan Municipal Health Commission scientific research projectWG20B01 Hubei province natural science foundation of China2024AFB1030 issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2024
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pmcBackground

Cervical cancer remains a global health challenge in women, with more than half a million women diagnosed yearly [1]. It is the fourth most common cancer in women and its mortality rate is considerably higher in developing countries. It is estimated that 90% of cervical cancer-related deaths occur in middle-income countries [2]. With the promotion of cervical cancer preventive strategies, such as completion of recommended vaccination series and standardized screening, the incidence of cervical cancer is decreasing [3]. Nevertheless, in developing countries, cervical cancer is frequently diagnosed at a late stage and has a poor prognosis [4]. Radiotherapy and chemoradiotherapy are both recommended for women with advanced-stage cervical cancer. However, the five-year survival rate of patients with locally advanced cervical cancer treated with concurrent chemoradiotherapy is only 70% [5]. Moreover, the response to treatment varies significantly among patients. Prognostic models, such as the FIGO staging system and histological subtypes are used to predict the survival of patients with cervical cancer; however, these models alone do not apply to all patients [6, 7]. Furthermore, the prognoses of different pathological types of cervical cancer at the same stage can also differ. Therefore, a new prognostic evaluation method is needed to predict survival time across different stages and histological subtypes.

Malnutrition, which has a high incidence in patients with cancer, has a negative effect on prognosis [8]. The incidence of malnutrition in patients with cancer is reported to range from 20–70% [9]. Cancer-related malnutrition leads to adverse clinical outcomes, poor prognosis, and increased healthcare costs [8]. In previous studies, the prevalence of malnutrition in patients with cervical cancer ranges from 17.4–38.79% [10, 11]. Our previous results also indicate that malnutrition is associated with short overall survival (OS) and progression-free survival (PFS) in patients with cervical cancer [12].

Nutrition assessment tools such as the Global Leadership Initiative on Malnutrition (GLIM) [13], Patient-Generated Subjective Global Assessment (PG-SGA) [14] and Mini-Nutritional Assessment (MNA) [15] have been developed in clinical settings to evaluate the nutritional status of patients with cancer. However, these tools often require evaluation of indicators such as weight loss and muscle mass, which are challenging to implement quickly in clinical practice. Moreover, certain measurements involve a degree of subjectivity. The controlling nutritional status (CONUT) score, developed by Ignacio et al. in 2005, is used for early detection of hospital undernutrition [16]. Calculating the CONUT score only requires data in relation to lymphocyte counts, and albumin and serum total cholesterol levels. Data can be quickly and easily obtained from standard laboratory test results to evaluate the nutritional status of patients. The prognostic value of the CONUT score has also been verified in other cancer types, including gastric [17], ovarian, cervical [18], and renal cancers [19], and hematological malignancies [20]. A high CONUT score has been shown to significantly correlate with decreased OS. A high pre-operative CONUT score also indicates a high rate of postoperative and severe complications [21, 22]. One study has investigated the value of the CONUT score as a risk factor for predicting para-aortic lymph node recurrence in patients with cervical cancer treated with prophylactic extended-field irradiation [23]. The modified controlling nutritional status (mCONUT) by introducing C-reactive protein also predicted survival time in patients with cancer cachexia [24]. To our knowledge, no study has explored the effect of the CONUT score and mCONUT score on survival in patients with stage IIB–IIIB cervical cancer receiving radiotherapy. Therefore, we aimed to investigate the association between the CONUT/ mCONUT score’s prognostic value and survival time in patients with FIGO stage IIB–IIIB cervical cancer treated with radiotherapy.

Materials and methods

Study patients

The clinical records of 183 hospitalized patients with cervical cancer who had been treated with radiotherapy between September 2013 and September 2015 at the Hubei Cancer Hospital were retrieved retrospectively. Inclusion criteria comprised patients: (i) with pathologically confirmed cervical cancer, (ii) aged 18–80 years, and (iii) who had undergone radiotherapy. The exclusion criteria included patients: (i) with a history of other malignancies and diseases that seriously affect nutritional status, such as chronic obstructive pulmonary disease, acquired immunodeficiency syndrome, chronic renal failure, and severe liver cirrhosis, and (ii) those with incomplete clinical data. This study was approved by the Ethics Committee of the Hubei Cancer Hospital of Huazhong University of Science and Technology. All procedures were performed in accordance with the principles of the Declaration of Helsinki. The requirement for informed consent was waived owing to the study’s retrospective design by Ethics Committee of the Hubei Cancer Hospital of Huazhong University of Science and Technology (LLHBCH2021YN-049). Data from 165 patients were collected to investigate the association between pretreatment CONUT/mCONUT scores and OS and PFS in patients with cervical cancer.

Measurements

All data were extracted from the patients’ electronic medical records. Demographic data, such as age, were collected. Blood samples were collected from all patients within one week of radiotherapy. Laboratory measurements of serum albumin and total cholesterol levels were also performed using the Sysmex XN-9000 Hematology System (Sysmex Corporation, Shanghai, China), ADVIA 2400 Clinical Chemistry System (Siemens Healthineers, Erlangen, Germany), and Cobas e 801 analytical unit (Roche Diagnostics International AG, Rotkreuz, Switzerland). The CONUT scores and mCONUT scores were calculated according to previously published literature [16, 24] (Additional file 1). The optimal cut-off values for the CONUT score/mCONUT score were determined using receiver operating characteristic (ROC) curves.

Radiotherapy approach

All patients with FIGO stage IIB–IIIB cervical cancer had been treated with radiotherapy after diagnosis. Intensity-modulated radiotherapy (IMRT) and conventional radiotherapy were administered in accordance with Radiation Therapy Oncology Group guidelines. The radiotherapy dose ranged from 45.0 to 50.4 Gy as planned. IMRT and conventional radiotherapy were delivered at 1.8 Gy per fraction, once daily for five days/week. After whole-pelvic irradiation, high-dose 192Ir brachytherapy was administered to all patients. If a patient could tolerate chemotherapy, they also received chemotherapy with cisplatin in conjunction with radiotherapy.

Follow‑up visits

Following radiotherapy, each patient was followed up every three months. Follow-up examinations were conducted via telephone calls and during outpatient visits. The last follow-up period in this retrospective study was December 2019. OS was defined as the time from radiotherapy to death from any cause or the last follow-up. PFS was defined as the time from radiotherapy to the first instance of disease progression, the last follow-up, or death.

Data analysis

All data were analyzed using R version 4.1.1 software. A P-value < 0.05 was considered statistically significant. The mean ± standard deviation or median (interquartile range) was used to present continuous variables. Categorical variables were expressed as frequencies (percentages). A t-test was used to compare continuous variables, and a chi-square test was used to compare categorical variables between the two patient groups. Propensity score matching (PSM) analysis was used to minimize selection bias and increase comparability between the low and high CONUT score groups. Factors that were significantly different between the two groups were used for matching. A cumulative survival curve was created using the Kaplan–Meier method, and the differences between the two patient groups in terms of OS and PFS were analyzed using a log-rank test. Univariate and multivariate analyses were conducted using a Cox proportional hazard model to verify the effect of CONUT/mCONUT scores on OS and PFS. Variables with P-values < 0.2 in the univariate analysis were used in multivariable Cox regression models. In this study, nomograms were created to visualize the prognostic strength of the variables for predicting OS and PFS in multivariate analyses. Model performance was assessed using the C-index.

Results

Baseline characteristics

Patient characteristics are shown in Table 1. In total, 165 patients with cervical cancer were enrolled in this study (median patient age, 52 years; mean body mass index [BMI], 23.6 kg/m2). According to the FIGO 2009 clinical staging system, 87 (52.7%) patients had stage II tumors and 78 (47.3%) had stage III tumors. Of these, 29 had > 2 positive metastatic lymph nodes. The optimal cut-off values for the CONUT score and mCONUT score were determined using ROC curves with the OS time as an endpoint (Additional file 2). The cut-off values for the CONUT and mCONUT score were both 2, and a low pretreatment CONUT score was observed in 127 patients. Among the 38 patients with high pretreatment CONUT scores, 17 received active nutritional intervention. Patients in the high CONUT score group (n = 38) had lower BMI and IMRT rates. PSM analysis was used to minimize the difference on BMI and IMRT rates between the two CONUT score groups. After PSM, 38 patients in the low CONUT score group were matched with 38 patients in the high CONUT score group to form a matched cohort. Details of the PSM cohort are presented in Table 1. The post-radiotherapy CONUT scores were obtained in 38 patients. Among 38 individuals, of whom 25 experienced a decrease in their score by more than 2 points after radiotherapy (65.8%), and 15 patients had a decrease of 3 to 5 points (39.5%). During a mean follow-up of 53.78 mo, 41 deaths were observed. In the total cohort, the one-, three-, and five-year OS rates for the entire study population were 93.9%, 77.6%, and 75.2%, respectively. The one-, three-, and five-year PFS rates in the total cohort were 78.8%, 73.3%, and 70.0%, respectively.

Table 1 The baseline characteristics of patients with FIGO stage IIB–IIIB cervical cancer in the total and PSM cohorts

	Level	Total cohort	PSM cohort	
Low CONUT (n = 127)	High CONUT (n = 38)	P	Low CONUT (n = 38)	High CONUT (n = 38)	P	
Age (median [IQR])		52.0 [48.0, 60.0]	50.5 [47.0, 59.8]	0.541	53.5 [49.5, 60.8]	50.5 [47.0, 59.8]	0.163	
Age (n, (%))	≤ 55	73 (57.5)	24 (63.2)	0.663	21 (55.3)	24 (63.2)	0.641	
	> 55	54 (42.5)	14 (36.8)		17 (44.7)	14 (36.8)		
No. of metastatic lymph nodes (n, (%))	> 2	90 (70.9)	30 (78.9)	0.439	32 (84.2)	30 (78.9)	0.767	
	≤ 2	37 (29.1)	8 (21.1)		6 (15.8)	8 (21.1)	0.163	
Size of metastatic lymph nodes (n, (%))	No metastatic lymph nodes	72 (56.7)	28 (73.7)	0.126	27 (71.1)	28 (73.7)	0.897	
	≤ 1 cm	19 (15.0)	2 (5.3)		3 (7.9)	2 (5.3)		
	> 1 cm	36 (28.3)	8 (21.1)		8 (21.1)	8 (21.1)		
Pathology (n, (%))	Squamous cell carcinoma	117 (92.1)	35 (92.1)	0.999	34 (89.5)	35 (92.1)	0.999	
	Adenocarcinoma	10 (7.9)	3 (7.9)		4 (10.5)	3 (7.9)		
FIGO stage (n, (%))	II	70 (55.1)	17 (44.7)	0.348	19 (50.0)	17 (44.7)	0.818	
	III	57 (44.9)	21 (55.3)		19 (50.0)	21 (55.3)		
SCC antigen (n, (%))	≤ 1.5	37 (29.1)	8 (21.1)	0.439	14 (36.8)	8 (21.1)	0.206	
	> 1.5	90 (70.9)	30 (78.9)		24 (63.2)	30 (78.9)		
Height (median [IQR])		157.0 [155.0, 160.0]	156.5 [155.0, 159.8]	0.783	157.0 [155.3, 159.0]	156.5 [155.0, 159.8]	0.921	
Weight (median [IQR])		57.0 [53.0, 62.0]	54.5 [48.0, 59.8]	0.020	56.5 [52.3, 60.0]	54.5 [48.0, 59.8]	0.279	
CONUT (mean (SD))		1.1 (0.9)	3.8 (1.0)	< 0.001	1.0 (0.8)	3.8 (1.0)	< 0.001	
BMI (median [IQR])		23.1 [22.0, 24.7]	22.3 [19.6, 24.6]	0.045	22.5 [21.7, 24.4]	22.3 [19.6, 24.6]	0.294	
BMI (n, (%))	≤ 23.9	83 (65.4)	25 (65.8)	0.999	26 (68.4)	25 (65.8)	0.999	
	> 23.9	44 (34.6)	13 (34.2)		12 (31.6)	13 (34.2)		
Chemoradiotherapy (n, (%))	No	12 (9.4)	5 (13.2)	0.722	5 (13.2)	5 (13.2)	0.999	
	Yes	115 (90.6)	33 (86.8)		33 (86.8)	33 (86.8)		
Type of Radiotherapy (n, (%))	IMRT	85 (66.9)	18 (47.4)	0.046	14 (36.8)	18 (47.4)	0.486	
	Conventional radiotherapy	42 (33.1)	20 (52.6)		24 (63.2)	20 (52.6)		
PSM, propensity score matching; IQR, interquartile range; BMI, body mass index; IMRT, intensity-modulated radiotherapy; SCC, squamous cell carcinoma. Bold values present statistical significance at the P < 0.05

The effect of the CONUT score on OS

The estimated one-, three-, and five-year OS rates were 96.1%, 82.7%, and 81.1%, respectively, in the low CONUT score group. The estimated one-, three-, and five-year OS rates were 86.8%, 60.5%, and 53.8%, respectively, in the high CONUT score group. Additionally, Kaplan–Meier analysis indicated that patients with a high CONUT score had a shorter OS (log-rank test, P < 0.001, Fig. 1A). In the PSM cohort, the five-year OS rate was 75.7%. Of note, Kaplan–Meier analysis showed that the OS differed depending on the CONUT score. Patients with low CONUT scores had improved OS (low CONUT score: one-, three-, and five-year OS rates, 97.4%, 84.2%, and 84.2%, respectively) (log-rank test, P = 0.004, Fig. 1B). Furthermore, the subgroup analysis stratified by stage revealed that a high CONUT score was predictive of shorter overall survival (OS) in patients classified as FIGO stage III, whereas this association was not observed in patients at FIGO stage II. (Additional file 3) Additionally, to explore the impact of active nutrition on the prognosis in patients with high CONUT scores, we performed the Kaplan–Meier analysis. The results showed that 5-year overall survival rate in the active nutrition intervention group was slightly higher than that in the non-intervened group (57.1% vs. 48.5%, P = 0.93), but the difference was not statistically significant. (Additional file 4) Furthermore, 38 patients were included in the analysis to investigate the relationship between post-radiotherapy CONUT score and prognosis. Kaplan–Meier analysis showed that 5-year overall survival was lower in the high-scoring group than in the low-scoring group (53.8% vs. 58.3%, P = 0.69), but the difference was not statistically significant. (Additional file 5) In addition, we found no significant difference in overall survival rates between the group with severe decrease in CONUT score (≥ 2) and the group with moderate decrease or stable in CONUT score (< 2). (Additional file 6)

Fig. 1 Kaplan–Meier curves of overall survival according to the controlling nutritional status (CONUT) score (low CONUT score, ≤ 2; high CONUT score, > 2) (A) total cohort and (B) propensity score matching (PSM) cohort

The effect of the CONUT score on PFS

The estimated one-, three-, and five-year PFS rates were 84.3%, 78.0%, and 76.4% in the low CONUT score group and 60.5%, 57.9% and 48.2% in the high CONUT score group, respectively (log-rank test, P < 0.001, Fig. 2A). Moreover, similar results were obtained concerning the association between a high CONUT score and short PFS in patients with cervical cancer in the PSM cohort (five-year PFS, low CONUT [76.3%] vs. high CONUT [48.2%]). PFS in the high CONUT score group was significantly lower than that in the low CONUT score group (log-rank test, P = 0.012, Fig. 2B). In addition, the subgroup analysis based on stage showed that a high CONUT score was a significant predictor of reduced PFS for patients at FIGO stage III. (Additional file 3) Similarly, among 38 patients with high CONUT scores, no statistically significant difference was observed in the 5-year survival rate between the active nutrition intervention group and non-intervened group (47.6% vs. 47.1%, P = 0.67). (Additional file 4) Additionally, no significant difference in PFS between the group with severe decrease in CONUT scores (≥ 2) and the group with moderate decrease or stable (< 2) was observed in the Kaplan–Meier analysis. (Additional file 6)

Fig. 2 Kaplan–Meier curves of progression-free survival according to the controlling nutritional status (CONUT) score (low CONUT score, ≤ 2; high CONUT score, > 2) (A) total cohort and (B) propensity score matching (PSM) cohort

Univariate and multivariate analyses for patients with cervical cancer

In the univariate analysis of the total cohort, histological type, FIGO stage, number of metastatic lymph nodes, and the CONUT score were significantly associated with OS and PFS, whereas BMI, age, and type of radiotherapy were not significantly associated with short OS or PFS. Multivariate Cox regression analysis indicated that the CONUT score remained a significant predictor of OS (OS: HR 2.93, 95% CI 1.54–5.56, P = 0.001; PFS: HR 2.77, 95% CI 1.52–5.04; P < 0.001). Additionally, the results indicated that for each one-point increase in the CONUT score, the risk of death increases by 1.31 times (OS: HR 1.31, 95% CI 1.08–1.60, P = 0.006). After PSM, univariate analyses showed that the number of metastatic lymph nodes (OS: HR 3.69, 95% CI 1.51–9.03, P = 0.004; PFS: HR 3.68, 95% CI 1.62–8.40; P = 0.002) and the CONUT score (OS: HR 3.58, 95% CI 1.41–9.10, P = 0.007; PFS: HR 2.66, 95% CI 1.20–5.88; P = 0.016) were associated with the prognosis in patients with cervical cancer. Multivariate Cox regression analysis showed that the CONUT score remained an independent factor for poor OS in patients with cervical cancer (HR 2.97, 95% CI 1.11–7.91; P = 0.030). However, the association between a high CONUT score and poor PFS was not significant (HR 2.23, 95% CI 0.98–5.06; P = 0.055) (Tables 2 and 3).

Table 2 Univariate and multivariate analyses of overall survival in the total and PSM cohorts

Characteristics	Total cohort	PSM cohort	
Univariate analysis	Multivariate Cox
regression analysis	Univariate analysis	Multivariate Cox
regression analysis	
HR (95% CI)	P	HR (95% CI)	P	HR (95% CI)	P	HR (95% CI)	P	
Age									
≤ 55 vs. >55	0.69 (0.36–1.32)	0.263			0.47 (0.18–1.18)	0.109	0.48 (0.18–1.27)	0.138	
BMI									
Continuous	0.91 (0.80–1.02)	0.110	0.94 (0.83–1.05)	0.269	0.93 (0.79–1.08)	0.337			
≤ 23.9 vs. >23.9	0.89 (0.46–1.72)	0.726			1.10 (0.46–2.59)	0.834			
No. of metastatic lymph nodes									
> 2 vs. ≤ 2	3.01 (1.63–5.56)	< 0.001	3.29 (1.74–6.25)	< 0.001	3.69 (1.51–9.03)	0.004	1.47 (0.49–4.39)	0.488	
Type of radiotherapy									
conventional radiotherapy vs. IMRT	1.38 (0.74–2.56)	0.305			0.63 (0.28–1.43)	0.269			
Pathology									
squamous cell carcinoma vs. adenocarcinoma	3.9 (1.86–8.20)	< 0.001	4.17 (1.85–9.40)	< 0.001	2.19 (0.74–6.47)	0.154	3.32 (0.87–12.61)	0.078	
FIGO stage									
III vs. II	3.01 (1.54–5.90)	0.001	1.85 (0.90–3.8)	0.092	2.36 (0.97–5.75)	0.058	1.96(0.75–5.08)	0.168	
SCC antigen									
> 1.5 vs. ≤ 1.5	1.22 (0.60–2.49)	0.585			2.15 (0.73–6.31)	0.165	2.53 (0.68–9.42)	0.167	
Chemoradiotherapy									
Yes vs. NO	0.62 (0.26–1.48)	0.280			0.92 (0.27–3.08)	0.887			
CONUT score									
Continuous	1.33 (1.12–1.58)	0.001	1.31 (1.08–1.60)	0.006	1.34 (1.09–1.66)	0.007	1.22 (0.95–1.57)	0.116	
High vs. Low	3.01 (1.61–5.61)	0.001	2.93 (1.54–5.56)	0.001	3.58 (1.41–9.10)	0.007	2.97 (1.11–7.91)	0.030	
PSM, propensity score matching; CI, confidence interval; HR, hazard ratio; BMI, body mass index; IMRT, intensity-modulated radiotherapy; SCC, squamous cell carcinoma. Bold values present statistical significance at the P < 0.05

Table 3 Univariate and multivariate analyses of progression-free survival in the total and PSM cohorts

Characteristics	Total cohort	PSM cohort	
Univariate analysis	Multivariate Cox
regression analysis	Univariate analysis	Multivariate Cox
regression analysis	
HR (95% CI)	P	HR (95% CI)	P	HR (95% CI)	P	HR (95% CI)	P	
Age									
≤ 55 vs. >55	0.86 (0.48–1.53)	0.611			0.64 (0.29–1.41)	0.266			
BMI									
Continuous	0.91 (0.82–1.02)	0.094	0.94 (0.84–1.04)	0.215	0.94 (0.82–1.08)	0.371			
≤ 23.9 vs. >23.9	0.92 (0.51–1.68)	0.794			0.86 (0.39–1.85)	0.693			
No. of metastatic lymph nodes									
> 2 vs. ≤ 2	2.50 (1.42–4.40)	0.001	2.94 (1.62–5.33)	< 0.001	3.68 (1.62–8.40)	0.002	2.36 (0.96–5.81)	0.061	
Type of radiotherapy									
conventional radiotherapy vs. IMRT	1.17 (0.66–2.07)	0.584			0.55 (0.26–1.16)	0.116	0.85 (0.38–1.88)	0.682	
Pathology									
squamous cell carcinoma vs. adenocarcinoma	4.09 (1.97–8.47)	< 0.001	4.87 (2.19–10.84)	< 0.001	2.22 (0.77–6.42)	0.142	4.41 (1.07–18.14)	0.040	
FIGO stage									
III vs. II	2.42 (1.34–4.35)	0.003	1.55 (0.82–2.90)	0.176	1.58 (0.74–3.39)	0.235			
SCC antigen									
> 1.5 vs. ≤ 1.5	1.31 (0.67–2.56)	0.435			2.03 (0.77–5.35)	0.151	2.63 (0.73–9.48)	0.139	
Chemoradiotherapy									
Yes vs. NO	0.60 (0.27–1.33)	0.208			1.11 (0.34–3.68)	0.862			
CONUT score									
Continuous	1.28 (1.08–1.50)	0.004	1.28 (1.06–1.54)	0.010	1.24 (1.02–1.51)	0.034	1.19 (0.95–1.48)	0.113	
High vs. Low	2.68 (1.51–4.77)	0.001	2.77 (1.52–5.04)	< 0.001	2.66 (1.20–5.88)	0.016	2.23 (0.98–5.06)	0.055	
PSM, propensity score matching; CI, confidence interval; HR, hazard ratio; BMI, body mass index; IMRT, intensity-modulated radiotherapy; SCC, squamous cell carcinoma. Bold values present statistical significance at the P < 0.05

The effect of the mCONUT score on OS/PFS

In total, 112 subjects were included in the analysis to explore the relationship between mCONUT score and prognosis. Kaplan–Meier analysis indicated that patients with a high mCONUT score had a shorter OS and PFS (log-rank test, OS, P = 0.034, PFS, P = 0.027). Multivariate Cox regression analysis showed that the a high mCONUT score was not significantly associated with short OS or PFS. (Additional file 7 and Additional file 8)

Prognostic nomograms of the CONUT score

Nomograms based on multivariate Cox regression analysis were created to predict one-, three-, and five-year OS (Fig. 3A) and PFS (Fig. 3B) for each patient. The nomograms for estimating cervical cancer’s OS and PFS outcomes include key prognostic indicators: pathology, stage, and the CONUT score. In the nomograms, each factor in the nomogram is assigned a score, found by aligning with the top scale. The total points of all the included factors were used to predict the survival rate by the bottom points axis. The C-index was the primary measure for assessing the predictive accuracy of the nomograms. The C-index was 0.71 (95% CI 0.63–0.79) for OS and 0.70 (95% CI 0.62–0.77) for PFS, indicating high accuracy in predicting OS and PFS.

Fig. 3 Prognostic nomograms for survival time prediction according to the controlling nutritional status (CONUT) score (A) overall survival (OS) and (B) progression-free survival (PFS)

Discussion

Our study findings indicated that the CONUT score is an independent predictor of prognosis in patients with FIGO IIB–IIIB cervical cancer treated with radiotherapy. Among 165 patients, the five-year OS rate was 53.8% in the high CONUT score group, which was considerably lower than that in the low CONUT score group. In the multivariate analysis, the risk of death in the high CONUT score group was 2.93-fold higher than that in the low CONUT score group. Moreover, with every increase of 1 point, there was a 1.31-fold increased risk of death. One study reported an association between the CONUT score and para-aortic lymph node recurrence in patients with cervical cancer treated with prophylactic extended-field irradiation. However, the results suggested that CONUT scores did not predict OS [23]. Two studies reported that a high CONUT score indicated a poor prognosis in patients with early stage cervical cancer. The results reported that patients with low CONUT scores who received concurrent chemotherapy and surgery had longer five-year cancer-specific survival (CSS), disease-free survival (DFS), and OS time [25, 26]. A meta-analysis also explored the prognostic value of the CONUT score in gynecological cancer. The results indicated that CONUT score was a promising biomarker to predict survival in gynecological cancer. In addition, a high CONUT score predicted decreased OS and PFS in cervical cancer in the subgroup analysis with two included studies [18].

These studies focused on patients treated with surgery or prophylactic extended-field irradiation, and it is difficult to generalize those results to patients receiving IMRT or conventional radiotherapy. Our study provides further information concerning the association between pretreatment nutrition status, as determined using the CONUT score, and survival time in patients with FIGO stage IIB–IIIB cervical cancer treated with radiotherapy. A high CONUT score predicting survival in patients with cervical cancer may be explained as follows. The CONUT score is a nutritional status assessment tool. Patients with high CONUT scores have poor nutritional status. Several studies have highlighted the negative effects of malnutrition on cancer treatment and outcomes. Malnutrition has been shown to influence the efficacy of anticancer therapy, increase the side-effects of treatment, reduce quality of life, and shorten survival time. Malnutrition contributes to the onset of cancer-related cachexia, which ultimately directly affects cancer mortality [27].

Three readily available parameters were used to calculate the CONUT scores. The serum albumin level is considered a marker of nutritional status. With a half-life of nearly 20 days, albumin helps maintain oncotic pressure in the vasculature and transfers various minerals, hormones, and fatty acids [28]. Hypoalbuminemia results from inadequate protein and calorie intake in patients with chronic diseases. For older adults and patients with nonsurgical tumors, the serum albumin concentration is highly sensitive in a diagnosis of malnutrition [29]. In many studies, low albumin (< 3.5 g/dL) levels have been shown to predict high cancer mortality [30].

The lymphocyte count in the CONUT score reflects the inflammatory immune response in patients with cancer. Lymphocytes are recognized as a major factor in tumor progression [31]. Moreover, the total lymphocyte count has previously been proposed as a marker for assessing nutritional status [32]. A total lymphocyte count < 1,200 cell/mm3 is associated with low mid-upper arm circumference, low triceps skinfold thickness, nutritional risk using nutritional risk screening, and malnutrition evaluated using PG-SGA in hospitalized patients [33, 34].

Total cholesterol levels, which represent the combined amount of high- and low-density lipoproteins in blood, were used to calculate the CONUT score. Total cholesterol levels have previously been used to evaluate the nutritional status. The Mini Nutritional Assessment and Elderly Nutritional Indicators for Geriatric Malnutrition Assessment use total cholesterol as a factor for evaluation [35, 36]. A meta-analysis showed that total cholesterol is a useful marker of adult malnutrition, even in the presence of chronic inflammation [37]. Moreover, previously published data show that low HDL-C levels are associated with poor cancer survival [38–40].

Notably, the CONUT score should also be considered as an immune nutritional parameter. The CONUT score can reflect the inflammatory status of the body. Chronic inflammation due to tumors may lead to decreased serum albumin levels and lymphocyte counts. Inflammation plays an important role in the carcinogenesis process [41]. A systemic inflammatory response affects survival in patients with cancer [42]. These factors explain why the CONUT score can be used to predict survival. By introducing CRP, the mCONUT score system can more accurately reflect the level of inflammation in patients with cancer. A recently published study found that the mCONUT scoring system can more comprehensively reflect the nutritional, immune, and inflammatory status of cancer patients and shows a more powerful prognostic value than the original CONUT score in patients with cancer cachexia [24]. However, our research results were inconsistent with this article. The main reasons are, on the one hand, the insufficient sample size may affect the results, and on the other hand, the mCONUT scoring system was more suitable for predicting the prognosis of patients with cancer cachexia, while all subjects in our study were patients with stage IIB–IIIB cervical cancer, who may not be diagnosed with cancer cachexia. In subgroup analysis based on staging, the results showed that the CONUT score system was associated with survival time in patients with FIGO stage III cervical cancer receiving radiotherapy. However, the CONUT score did not predict survival time in patients with FIGO stage II. The main reason for this result may be the insufficient sample size of stage II patients, with only 17 diagnosed with a high CONUT score, accounting for less than 20%, which may potentially affect the predictive efficacy of the CONUT score system. Furthermore, we found that both the post-treatment CONUT score and changes of CONUT score had no significant impact on the prognosis of patients with cervical cancer, and for patients with high CONUT scores, nutritional intervention had no significant effect on prognosis either. Many studies have found that the dynamic changes of indicators during treatment may affect the prognosis of cancer patients [43]. The non positive findings in our trial may be attributable to an insufficient sample size and potential selection bias. Considering only the post-treatment CONUT scores of 38 individuals could be obtained, further rigorous prospective trials are needed to study the impact of CONUT values at various stages on the prognosis of cervical cancer.

This study had some limitations. First, this was a retrospective, single-center study, which may have introduced bias. Second, a ROC curve was used to determine the optimal cut-off value of the CONUT score using data from our cohort. Cut-off values have varied in different studies; however, the optimal CONUT score in patients with cervical cancer remains unclear. Third, antihyperlipidemic drugs may influence total cholesterol levels. Nutritional interventions can also affect clinical outcomes during treatment. However, relevant data were incomplete for analysis in this study. Fourth, for some patients, follow-up examinations were conducted via telephone calls, with a diagnosis of recurrence possibly missed. Finally, other clinical outcomes, such as rates of treatment-related toxicities, were not evaluated.

Conclusions

In summary, we found that the pretreatment CONUT score was associated with survival time in patients with FIGO IIB–IIIB cervical cancer receiving radiotherapy. Clinicians can estimate the prognosis of these patients more precisely by using the CONUT score. Further studies are needed to investigate the optimal cutoff value of the CONUT score and verify its predictive value in patients with cervical cancer. In addition, nutritional therapy based on the CONUT score should be considered.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Additional file 1: Table S1. The calculation of controlling nutritional status score and modified controlling nutritional status score.

Additional file 2: Figure S1. The ROC curves for controlling nutritional status score.

Additional file 3: Figure S2. Kaplan–Meier curves of survival according to the controlling nutritional status (CONUT) score (low CONUT score, ≤ 2; high CONUT score, > 2) (A) overall survival (OS) in patients with FIGO stage II (B) OS in patients with FIGO stage III (C) progression-free survival (PFS) in patients with FIGO stage II (D) PFS in patients with FIGO stage III.

Additional file 4: Figure S3. Kaplan–Meier curves of survival according to the active nutrition intervention in patients with high controlling nutritional status (CONUT) score (A) overall survival (OS) (B) progression-free survival (PFS).

Additional file 5: Figure S4. Kaplan–Meier curves of survival according to the post-radiotherapy controlling nutritional status (CONUT) score (low CONUT score, ≤ 3; high CONUT score, > 3) (A) overall survival (OS) (B) progression-free survival (PFS).

Additional file 6: Figure S5. Kaplan–Meier curves of survival according to changes of the controlling nutritional status (CONUT) score (severe decrease, ≥ 2; moderate decrease or stable, < 2) (A) overall survival (OS) (B) progression-free survival (PFS).

Additional file 7: Figure S6. Kaplan–Meier curves of survival according to the modified controlling nutritional status (mCONUT) score (low mCONUT score, ≤ 2; high mCONUT score, > 2) (A) overall survival (OS) (B) progression-free survival (PFS).

Additional file 8: Table S2. Univariate and multivariate analyses of overall survival and progression-free survival in 112 patients.

Acknowledgements

We thank the patients who participated in the study.

Author contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Juan Fu, Xintian Xu, Hongbing Wang, and Mengxing Tian. The first draft of the manuscript was written by Xin Jin and Xintian Xu, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Funding

This research was funded by Wuhan Municipal Health Commission scientific research project (grant number WG20B01) and Hubei province natural science foundation of China(2024AFB1030).

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of the Hubei Cancer Hospital of Huazhong University of Science and Technology (LLHBCH2021YN-049). The requirement for informed consent was waived owing to the study’s retrospective design by the Ethics Committee of the Hubei Cancer Hospital of Huazhong University of Science and Technology (LLHBCH2021YN-049).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Abbreviations

CONUT Controlling nutritional status

mCONUT Modified controlling nutritional status

PSM Propensity score matching

CI Confidence interval

HR Hazard ratio

IQR Interquartile range

BMI Body mass index

IMRT Intensity-modulated radiotherapy

SCC Squamous cell carcinoma

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Juan Fu and Xintian Xu contributed equally to this work and share the first authorship.
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