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R-CSS: a clinically applicable score to classify cachexia stages in patients with cancer undergoing intensity-modulated radiation therapy

  • Author Footnotes
    # Hanxiao Yi, Yang Wang and Qunying Liang contributed equally to this work.
    Hanxiao Yi
    Correspondence
    Corresponding author.
    Footnotes
    # Hanxiao Yi, Yang Wang and Qunying Liang contributed equally to this work.
    Affiliations
    Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107, YanJiang Road, Yuexiu District, Guangzhou, China
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  • Author Footnotes
    # Hanxiao Yi, Yang Wang and Qunying Liang contributed equally to this work.
    Yang Wang
    Footnotes
    # Hanxiao Yi, Yang Wang and Qunying Liang contributed equally to this work.
    Affiliations
    The Second Affiliated Hospital of Guangzhou Medical University, Institutional Address: 250 Changgang East Road, Haizhu District, Guangzhou
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  • Author Footnotes
    # Hanxiao Yi, Yang Wang and Qunying Liang contributed equally to this work.
    Qunying Liang
    Footnotes
    # Hanxiao Yi, Yang Wang and Qunying Liang contributed equally to this work.
    Affiliations
    Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107, YanJiang Road, Yuexiu District, Guangzhou, China
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  • Xiaolan Li
    Affiliations
    Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107, YanJiang Road, Yuexiu District, Guangzhou, China
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  • Changlong Cheng
    Affiliations
    Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107, YanJiang Road, Yuexiu District, Guangzhou, China
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  • Xiaoqun Mao
    Correspondence
    Corresponding author.
    Affiliations
    Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107, YanJiang Road, Yuexiu District, Guangzhou, China
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  • Author Footnotes
    # Hanxiao Yi, Yang Wang and Qunying Liang contributed equally to this work.
Open AccessPublished:November 08, 2022DOI:https://doi.org/10.1016/j.apjon.2022.100164

      Abstract

      Background

      Accurate cachexia staging is the key to its management. However, there is currently a lack of tools to distinguish the staging of cachexia in cancer patients undergoing radiotherapy.

      Objective

      The Radiotherapy Cachexia Staging Scale (R-CSS) was developed for the stratification of cachexia in patients undergoing cancer radiotherapy.

      Methods

      Cancer patients undergoing radiotherapy were divided into four stages – noncachexia, precachexia, cachexia and refractory cachexia – by the R-CSS scale, and the clinical outcomes of the four groups were compared.

      Results

      A total of 270 cancer patients undergoing radiation therapy were included in the study. All participants were classified into 4 stages of cachexia: stage 0, I, II and III. Patients with a higher cachexia stage had a higher prevalence of sarcopenia (p=0.015). Scores on the 16-item MDASI were higher in patients with higher cachexia stages (p<0.05), but levels of forgetfulness, numbness, and shortness of breath were not higher in these patients (p>0.05). Patients with higher cachexia stages exhibited better scores on the QLQ-C30 scale (p<0.05), except for in the domains of cognitive functioning, diarrhoea, and dyspnoea (p>0.05). The incidence of treatment-related events (any grade III or higher grade of (non-)haematologic adverse events, the need for hospitalization, emergency room admission) was higher in patients with higher cachexia stages.

      Conclusions

      The R-CSS scale is a screening tool that can simultaneously distinguish different stages of cachexia.

      Keywords

      Introduction

      Cancer cachexia is a syndrome associated with reduced food intake and impaired metabolism and is characterized by catabolism and inflammatory changes[
      • Naito T.
      Nursing Management of Cancer Cachexia: A New Frontier.
      ]. Clinical outcomes of cachexia include weight loss (WL), altered body composition, reduced food intake, poor functional status, limited quality of life, and reduced overall survival (OS)
      • Deng J.
      • He Y.
      • Sun X.S.
      • Li J.M.
      • Xin M.Z.
      • Li W.Q.
      • Mai H.Q.
      Construction of a comprehensive nutritional index and its correlation with quality of life and survival in patients with nasopharyngeal carcinoma undergoing IMRT: A prospective study.
      ,
      • Ganju R.G.
      • Morse R.
      • Hoover A.
      • TenNapel M.
      • Lominska C.E.
      The impact of sarcopenia on tolerance of radiation and outcome in patients with head and neck cancer receiving chemoradiation.
      . Considering that cachexia affects 60%-80% of all cancer patients
      • Blum D.S.G.S.T.
      • Euro-Impact
      Validation of the Consensus-Definition for Cancer Cachexia and evaluation of a classification model—a study based on data from an international multicentre project (EPCRC-CSA).
      ,
      • Powrózek T.D.J.M.T.
      Nutritional Deficiencies in Radiotherapy-Treated Head and Neck Cancer Patients.
      , different cachexia stages differentially impact the prognosis of those undergoing radiotherapy (RT), and cachexia should be diagnosed and classified promptly.
      In the international consensus[
      • Fearon K.S.F.A.S.
      Definition and classification of cancer cachexia: an international consensus.
      ], cancer cachexia is divided into three stages: precachexia, cachexia and refractory cachexia. However, due to its complex physiopathology, the diagnosis and classification of cancer cachexia in clinical practice remains challenging. Cachexia stages play an important role in individual management. Therefore, a new tool for staging cachexia cancer patients was designed by Anotonio et al.[
      • Vigano A.A.L.
      • Morais J.A.
      • Ciutto L.
      • Rosenthall L.
      • di Tomasso J.
      • Khan S.
      • Kilgour R.D.
      Use of routinely available clinical, nutritional, and functional criteria to classify cachexia in advanced cancer patients.
      ], but it could not effectively classify the precachexia and cachexia stages. Geisiane et al.[
      • Silva G.A.D.W.E.C.L.
      Clinical utility of the modified Glasgow Prognostic Score to classify cachexia in patients with advanced cancer in palliative care.
      ] used the Glasgow prognostic score to classify cachexia in patients undergoing palliative treatment for advanced cancer, with good results; however, this study only involved predicting the 90-day mortality of patients and did not assess the disease burden and quality of life of patients, which deviated from the definition of cachexia proposed by the international consensus to some extent. Zhou et al.[
      • Zhou T.
      • Wang B.
      • Liu H.
      • Yang K.
      • Thapa S.
      • Zhang H.
      • Yu S.
      Development and validation of a clinically applicable score to classify cachexia stages in advanced cancer patients.
      ] successfully performed cachexia staging among cancer patients; however, the relationship between cachexia stage and treatment-related events could not be analysed.
      Therefore, we aimed to develop a tool for classifying cancer cachexia and validating it to distinguish clinical outcomes, such as the incidence of sarcopenia, symptom burden, quality of life, and treatment-related events, in radiotherapy patients.

      Methods

      Patient selection

      This study presents results from a prospective study conducted at Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University. We calculated the study sample size required to validate the clinical prediction rule based on the requirement of 100 patients with the outcome of interest, i.e., the development of cachexia. This approach is supported by previously described statistical estimates for external validation of the clinical prediction rule. Based on previous studies[
      • Baba M.R.
      • Buch S.A.
      Revisiting Cancer Cachexia: Pathogenesis, Diagnosis, and Current Treatment Approaches.
      ] we estimated the incidence of cachexia in the enrolled sample to be 40%, and thus, the total required sample size was calculated as 250 patients.
      Patients who were at least 18 years old with a diagnosis of cancer (inpatients or outpatients received intensity-modulated radiation therapy at doses of 50 to 66 Gy) were included in this study between May 2021 and October 2021. The following patients were excluded from the study: mental illness, intellectual disability, unwillingness or inability to complete the questionnaires. The reporting of the study adheres to the TRIPOD guidelines (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis)[
      • Collins G.S.
      • Reitsma J.B.
      • Altman D.G.
      • Moons K.G.
      Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement.
      ], The TRIPOD checklist is included in Additional file 1: Table S1. The study was approved by the Sun Yat-Sen Memorial Hospital Ethics Committee (SYSEC-KY-KS-20021-245).
      Tumour staging was performed according to the American Joint Committee on Cancer tumour-node-metastasis (TNM) staging system (AJCC 7th ed, 2010)[
      • Edge S.B.
      • Compton C.C.
      The American Joint Committee on Cancer: the 7th Edition of the AJCC Cancer Staging Manual and the Future of TNM.
      ].

      Characteristics of cancer patients

      Demographics (age, sex, and body mass index (BMI)), clinical characteristics (diagnosis, stage, and treatment type of tumour), and routine blood test data (white blood cell count, haemoglobin, and albumin levels) were collected from the computerized hospital records. The clinician assessed the patient's Eastern Cooperative Oncology Group (ECOG) score.

      R-CSS scale

      To simplify the criteria of cachexia stages, Zhou et al[
      • Zhou T.
      • Wang B.
      • Liu H.
      • Yang K.
      • Thapa S.
      • Zhang H.
      • Yu S.
      Development and validation of a clinically applicable score to classify cachexia stages in advanced cancer patients.
      ]. developed a cachexia staging score (CSS) for clinical use in advanced cancer patients. Based on some radiotherapy studies and international consensus
      • Ganju R.G.
      • Morse R.
      • Hoover A.
      • TenNapel M.
      • Lominska C.E.
      The impact of sarcopenia on tolerance of radiation and outcome in patients with head and neck cancer receiving chemoradiation.
      ,
      • Fearon K.S.F.A.S.
      Definition and classification of cancer cachexia: an international consensus.
      ,
      • Cederholm T.
      • Jensen G.L.
      • Correia M.I.T.D.
      • Gonzalez M.C.
      • Fukushima R.
      • Higashiguchi T.
      GLIM Core Leadership CommitteeGLIM Working Group
      GLIM criteria for the diagnosis of malnutrition - A consensus report from the global clinical nutrition community.
      , we added three items, including items that assess age, BMI, and decreased food intake, to form the radiotherapy cachexia stage scale (R-CSS) for cancer patients undergoing radiation therapy.
      After classifying patients into different stages, we compared the results of the eight components of the R-CSS scale between stages. In addition, we validated the effectiveness of R-CSS in discriminating cachexia by comparing differences in sarcopenia, symptom burden, quality of life, and treatment-related toxicities among the four groups.
      Participants were also asked to complete the SARC-F questionnaire to assess muscle function. The SARC-F questionnaire is a simple tool that is designed to quickly assess a patient's muscle function and screen for sarcopenia[
      • Malmstrom T.K.
      • Miller K.
      • Simonsick E.M.
      • Ferrucci L.
      • Morley J.E.
      SARC-F: a symptom score to predict persons with sarcopenia at risk for poor functional outcomes.
      ]. The SARC-F questionnaire assesses five dimensions: strength, assistance in walking, rising from a chair, climbing stairs, and falls. Each item is scored on a scale of 0 to 2, and higher total scores indicate worse muscle function
      • Fu X.
      • Tian Z.
      • Thapa S.
      • Sun H.
      • Wen S.
      • Xiong H.
      • Yu S.
      Comparing SARC-F with SARC-CalF for screening sarcopenia in advanced cancer patients.
      ,
      • Ida S.
      • Kaneko R.
      • Murata K.
      SARC-F for Screening of Sarcopenia Among Older Adults: A Meta-analysis of Screening Test Accuracy.
      ,
      • Yang M.
      • Hu X.
      • Xie L.
      • Zhang L.
      • Zhou J.
      • Lin J.
      • Wu L.
      Screening Sarcopenia in Community-Dwelling Older Adults: SARC-F vs SARC-F Combined With Calf Circumference (SARC-CalF).
      .

      MDASI scale

      The Chinese version of the M. D. Anderson Symptom Inventory (MDASI-C) [
      • Wang X.S.
      • Wang Y.
      • Guo H.
      • Mendoza T.R.
      • Hao X.S.
      • Cleeland C.S.
      Chinese version of the M. D. Anderson Symptom Inventory: validation and application of symptom measurement in cancer patients.
      ] is a simple, patient-reported outcome measure used to assess the impact and severity of 19 cancer-related symptoms common across all cancer types. We used the MDASI to evaluate the symptom burdens (pain, fatigue, nausea, uneasy sleep, distress, shortness of breath, forgetfulness, poor appetite, drowsiness, dry mouth, sense of sadness, vomiting, numbness, general activity, mood, work, relationships with others, walking, life fun) of our patients. The score for each symptom ranged from 0 to 10, and higher scores indicated worse symptoms.

      QoL scale

      Quality of life was measured using QLQ-C30 version 3.0 (Chinese version 3.0) [
      • Zhao H.
      • Kanda K.
      Testing psychometric properties of the standard Chinese version of the European Organization for Research and Treatment of Cancer Quality of Life Core Questionnaire 30 (EORTC QLQ-C30).
      ]. The QLQ-C30 consists of 30 items, including one global health status scale, five functional scales (physical, role, emotional, cognitive, and social functioning), three symptom scales (fatigue, nausea, pain, and vomiting), and single-item symptom scales (dyspnoea, appetite loss, insomnia, diarrhoea, constipation, and financial difficulties). Twenty-five items were extracted from the QLQ-C30 questionnaire; questions about physical performance or food intake were withdrawn.

      Outcome definition

      Treatment-related events were graded according to the National Cancer Institute Common Terminology Criteria for Adverse Events, version 5.0 (CTCAE v5.0)[
      • Ghilardi G.
      • Chong E.A.
      • Svoboda J.
      • Wohlfarth P.
      • Nasta S.D.
      • Williamson S.
      Bendamustine is safe and effective for lymphodepletion before tisagenlecleucel in patients with refractory or relapsed large B-cell lymphomas.
      ]. Treatment-related events were defined as any grade III or higher haematologic adverse events (such as Hgb <8.0 g/dL, <4.9 mmol/L, <80 g/L, leukocytosis>100000/mm3, transfusion indicated, life-threatening consequences, urgent intervention indicated, death), any grade III or higher nonhaematologic adverse events (such as gastrointestinal disorders, general disorder, hepatobiliary disorders, immune system disorders, infections and infestations severe discomfort or limiting self-care ADL), the need for hospitalization or emergency room visits, and incomplete radiotherapy. All adverse events and complications were recorded from RT initiation until 1 month after the completion of RT.
      Body composition analysis was performed in patients with abdominal computed tomography (CT) images within 1 month. The outer circumference of the sternocleidomastoid muscle and paravertebral muscle was separated manually. Skeletal muscle was defined as -29 to +150 Hounsfield units (HUs)[
      • Barbalho E.R.
      • Rocha I.
      • Medeiros G.
      • Friedman R.
      • Fayh A.
      Agreement between software programmes of body composition analyses on abdominal computed tomography scans of obese adults.
      ], and the total cross-sectional area (CSA) was automatically calculated within the perimeter of the contour. Skeletal muscle CSA conversion at C3 was performed using the equation described by Swartz et al[
      • Swartz J.E.
      • Pothen A.J.
      • Wegner I.
      • Smid E.J.
      • Swart K.M.
      • de Bree R.
      • Grolman W.
      Feasibility of using head and neck CT imaging to assess skeletal muscle mass in head and neck cancer patients.
      ] to estimate skeletal muscle at L3. The SMI was then calculated based on the following equation: SMI (cm2/m2) = SMA (cm2)/height2 (m2)[
      • Prado C.M.
      • Lieffers J.R.
      • McCargar L.J.
      • Reiman T.
      • Sawyer M.B.
      • Martin L.
      • Baracos V.E.
      Prevalence and clinical implications of sarcopenic obesity in patients with solid tumours of the respiratory and gastrointestinal tracts: a population-based study.
      ]. The lumbar SMI (cm2/m2) value was obtained to define sarcopenia. Sarcopenia was defined as an SMI <39 cm2/m2 in female patients or <55 cm2/m2 in male patients[
      • Meza-Valderrama D.
      • Marco E.
      • Dávalos-Yerovi V.
      • Muns M.D.
      • Tejero-Sánchez M.
      • Duarte E.
      • Sarcopenia Sánchez-Rodríguez D.
      • Malnutrition
      • Cachexia
      Adapting Definitions and Terminology of Nutritional Disorders in Older People with Cancer.
      ].
      According to some radiotherapy studies and international consensus
      • Ganju R.G.
      • Morse R.
      • Hoover A.
      • TenNapel M.
      • Lominska C.E.
      The impact of sarcopenia on tolerance of radiation and outcome in patients with head and neck cancer receiving chemoradiation.
      ,
      • Fearon K.S.F.A.S.
      Definition and classification of cancer cachexia: an international consensus.
      ,
      • Cederholm T.
      • Jensen G.L.
      • Correia M.I.T.D.
      • Gonzalez M.C.
      • Fukushima R.
      • Higashiguchi T.
      GLIM Core Leadership CommitteeGLIM Working Group
      GLIM criteria for the diagnosis of malnutrition - A consensus report from the global clinical nutrition community.
      , the cut-off point for determining advanced age was > 70 years old, the cut-off point for BMI was ≥20, < 20, < 18.5, the point for weight loss in 6 months was stable or weight gain, ≤5%, ≤10%, >10% and <20%, ≥20%. and the decomposition point for food intake was reduced.

      Data collection

      Several nurses were trained to ensure that questionnaires were administered correctly and accurately. The first author trained the nurses on the purpose of the study and matters needing attention during the questionnaire distribution. To help patients better understand the questionnaire items, uniform language was used throughout the questionnaire delivery process. The primary outcomes (treatment-related affairs, body composition analysis, QoL scale, MDASI scale) were recorded by investigators who were unaware of the predictor variables.

      Follow-up

      All participants were followed through the follow-up system at the centre where the study was conducted until October 2021, and the final event was either the end of radiotherapy or loss to follow-up. The main outcome of the study was treatment-related events. For patients with dyslexia or difficulty writing, the study nurse asked the questions and completed the questionnaires instead.

      Statistical analysis

      Categorical variables are represented as percentages, and variables with homogeneity of variance are presented as the mean ± standard deviation; for variables without homogeneity of variance, Kruskal‒Wallis tests were used. Variables that were significant in univariate analysis were obtained to a logistic regression model after confirming there was no multicollinearity. Firth's method was implemented where complete or quasi separation was present. Factors in the univariate logistic regression analysis with p value < 0.100 were subsequently entered into the multivariate model to determine independent risk factors for cachexia. Exploratory analyses were performed to determine appropriate weights for the added variables to more accurately evaluate the correlations of age, BMI, and food intake with the R-CSS questionnaire. For this purpose, the following variables were treated as categorical variables using the previously mentioned cut-offs: age > 70 years; BMI≥20, < 20, and < 18.5; and weight stability or gain within 6 months, ≤5%, ≤10%, > 10%, and < 20%, ≥20%. The reduction in food intake was used as a cut-off. Then, the values of these three variables were assigned differently (ranging from 0 to 12), and each variable was tested individually to find the best match [as assessed by the area under the curve (AUC)]. The best choices were combined into a composite score, which already included 12 possible scores from the CSS questionnaire[
      • Zhou T.
      • Wang B.
      • Liu H.
      • Yang K.
      • Thapa S.
      • Zhang H.
      • Yu S.
      Development and validation of a clinically applicable score to classify cachexia stages in advanced cancer patients.
      ]. The cut-off point for the R-CSS was calculated by determining the area under the receiver operating characteristics curve. The receiver operating characteristic (ROC) was used to assess the discriminatory power of the model.
      All statistical analyses were completed using R software, MedCalc software (MedCalc 19.2.1; MedCalc, Mariakerke, Belgium) and SPSS software version 22.0 (SPSS Inc., Chicago, IL, USA). The chi-square test was used to compare categorical variables, but when more than one-fifth of the expected frequencies were <1, Fisher’s exact tests were performed. Pairwise comparisons using nonparametric tests were performed. P values <0.05 (two-sided) were considered statistically significant.

      Results

      A total of 305 patients were included in this study. Among them, 18 patients did not complete the MDASI or QLQ-C30, 8 patients did not complete the SARC-F scale, and 9 patients did not have treatment-related event data. Therefore, these patients were excluded from the study. Finally, data from 270 patients were collected for analysis (Additional file 1: Fig. S1). This study enrolled 270 patients who underwent RT. The ratio of male is 0.42(n=114), the ratio of female is 0.58(n=156), and the mean age of our patients was 50.0±12.48 years. The mean BMI (kg/m2) was calculated using weight (kg) and height (m) and was 21.1±3.34 in our study. Most of the patients had the following tumour types: head and neck cancer (48.1%), breast cancer (23.7%), and gynaecology cancer (8.1%). Other characteristics are summarized in Table 1.
      Table 1Clinical characteristics of patients (n=270).
      VariablesTotal(n=270)
      Age (years)
      Mean/standard deviation.
      50.0(±12.48)
      BMI (kg/m2)
      Mean/standard deviation.
      21.1(±3.34)
      Gender

      Male
      114(42.22)
      Tumor Type

      HN
      Palate, tongue, oral and nasal cavity, tonsil, pharynx, larynx, buccal, zygomatic, salivary glands, gingival.


      GI
      GI, gastrointestinal, esophageal.


      Breast

      Lung

      Gynecology

      Others
      Skin, central nervous system, liposarcoma, extranodal NK/T cell lymphoma, lymphoepitheliomatoid. rhabdomyosarcoma, cholangiocarcinoma, liver cancer.
      130(48.1)

      11(4.1)

      64(23.7)

      8(3.0)

      22(8.1)

      35(13.0)
      Tumor Stages

      I

      II

      III

      IV
      28(10.4)

      47(17.4)

      79(29.2)

      116(43.0)
      Treatment

      RT alone

      CRT postoperative (adjuvant) RT
      4(1.5)

      88(32.6)

      178(65.9)
      N, number of observations, %, frequency; BMI, body mass index; HN, head and neck; Gynecology, cervix uterus endometrium. CRT, concurrent chemoradiotherapy.
      a Mean/standard deviation.
      b Palate, tongue, oral and nasal cavity, tonsil, pharynx, larynx, buccal, zygomatic, salivary glands, gingival.
      c GI, gastrointestinal, esophageal.
      d Skin, central nervous system, liposarcoma, extranodal NK/T cell lymphoma, lymphoepitheliomatoid. rhabdomyosarcoma, cholangiocarcinoma, liver cancer.

      Development of R-CSS

      In univariate analysis, 11 factors were significantly associated with cachexia, as shown in (Additional file 1: Table S2) These potential factors were entered into the multivariate analysis. Subsequently, age (p= 0.004), BMI (p=0.060), weight loss at 6 months (p=0.002), SARC-F (p=0.028), ECOG-PS (p = 0.053), appetite loss (p =0.002), reduced food intake (p=0.012), and abnormal biochemistry (p=0.008) were identified as independent risk factors for cachexia.
      The variance inflation factor (VIF) between variables ranged from 1.041 to 2.336. No VIF was more than 10. Tolerance ranged from 0.04 to 0.960, indicating that multicollinearity was not a problem (Additional file 1: Table S3).
      The R-CSS comprised eight components (Table 2): age (score range: 0-1); BMI (score range: 0-2); weight loss at 6 months (score range: 0-4); the strength, assistance with walking, rising from a chair, climbing stairs, and falls (SARC-F) questionnaire (score range: 0-3); ECOG performance status (score range: 0-2); appetite loss (score range: 0-1); reduced food intake (score range: 0-1); and abnormal biochemistry (score range: 0-2).
      Table 2Criteria and scores for the clinical application of the cachexia stages.
      CriteriaValuesScore
      Age<70

      ≥70
      0

      1
      BMI≥20

      <20

      <18.5
      0

      1

      2
      Weight loss at 6 monthsWeight stable or weight gain

      Weight loss ≤5%

      Weight loss ≤10%

      Weight loss >10% and<20%

      Weight loss ≥20%
      0

      1

      2

      3

      4
      SARC-F0

      1-3

      4-6

      7-10
      0

      1

      2

      3
      ECOG PS0

      1-2

      3-4
      0

      1

      2
      Reduced food intakeNo reduction or more

      Reduce
      0

      1
      Appetite loss0-3

      4-6

      7-10
      0

      1

      2
      Abnormal biochemistry

      Alb<35 g/L

      WBC>10*109/L

      Hb<120/110 g/L (male/female)
      All normal

      One of the three abnormal

      More than one abnormal
      0

      1

      2
      BMI, body mass index; ECOG PS, Eastern cooperative oncology group performance status; Alb, albumin; WBC, white blood cell; Hb, haemoglobin.
      Using the previously mentioned method, the maximum screening power of R-CSS was obtained by adopting different weights. Thus, final scores ranged from 0 to 17, and the optimal cut-off point for cachexia screening was found to be 6 (Youden index: 0.77) (Additional file 1: Fig. S2). The calculated total score classified the noncachexia stage (0-3), precachexia stage (4-6), cachexia stage (7-12), and refractory cachexia stage (13-17). It is therefore clear that the higher the score, the more severe the symptoms (Table 3).
      Table 3Radiotherapy cachexia staging score.
      Table thumbnail fx1
      AG, age; BMI, body mass index; WL, weight loss; ECOG PS, eastern cooperative oncology group performance status; RFT, reduced food intake; AL, appetite loss; AB, abnormal biochemistry.

      Cancer cachexia staging

      Based on the scale scoring criteria, a total of 270 patients were classified into 4 stages of cachexia (NCa, PCa, Ca and RCa). Most patients (48.9%) were classified into the Ca stage, with 32.6% in the NCa stage and 16.3% in the PCa stage. Only 2.2% of patients were classified into the RCa stage (Table 4).
      Table 4Associations to characteristics studied according to cachexia stages (n= 270).
      VariablesNCa (n=89)PCa (n= 41)Ca (n= 135)RCa (n= 5)p- value
      Age (year)(mean) (SD)47.64 (11.24)49.60 (12.89)50.90 (13.02)
      Statistically different from NCa.
      49.84 (12.53)
      Statistically different from NCa.
      0.012
      BMI (kg/m2) (mean)(SD)22.62(3.46)22.23(3.38)20.88(10.28)
      Statistically different from NCa.
      ,
      Statistically different from PCa.
      21.07(2.93)<0.001
      WL 6 month (%) (mean)(SD)0.72(1.30)4.97(6.22)
      Statistically different from NCa.
      11.49(5.58)
      Statistically different from NCa.
      ,
      Statistically different from PCa.
      17.25(6.69)
      Statistically different from NCa.
      ,
      Statistically different from PCa.
      <0.001
      SARC-F

      0

      1-3

      4-6

      7-10
      41(46.6%)

      44(50.0%)

      2(2.3%)

      1(1.1%)
      17(38.6%)

      20(45.4%)

      6(13.7%)
      Statistically different from NCa.


      1(2.3%)
      Statistically different from NCa.
      31(23.5%)

      61(46.2%)

      31(23.5%)
      Statistically different from PCa.


      9(6.8%)
      Statistically different from NCa.
      1(16.7%)

      1(16.7%)

      1(16.7%)
      Statistically different from NCa.


      3(50.0%)
      Statistically different from NCa.
      ,
      Statistically different from PCa.
      <0.001
      ECOG PS

      0

      1-2

      3-4
      39(44.3%)

      45(52.3%)

      3(3.4%)
      8(18.2%)

      32(72.7%) 4(9.1%)
      Statistically different from NCa.
      10(7.6%)
      Statistically different from PCa.


      91(68.9%)
      Statistically different from PCa.


      31(23.5%)
      Statistically different from PCa.
      1(16.7%)

      4(66.7%)
      Statistically different from NCa.
      ,
      Statistically different from Ca.


      1(16.7%)
      Statistically different from NCa.
      ,
      Statistically different from Ca.
      <0.001
      Appetite loss (mean)(SD)3.03(1.99)5.55(2.52)
      Statistically different from NCa.
      6.06(2.51)
      Statistically different from NCa.
      6.50(2.42)
      Statistically different from NCa.
      <0.001
      Reduced food intake (mean)(SD)0.72(1.13)2.05(0.85)
      Statistically different from NCa.
      2.20(1.05)
      Statistically different from NCa.
      2.67(0.51)
      Statistically different from NCa.
      <0.001
      Abnormal biochemistry

      All normal

      One abnormal

      More than one abnormal
      57(64.8%)

      26(29.5%)

      5(5.7%)
      12(27.3%)

      19(43.2%)
      Statistically different from NCa.


      13(29.5%)
      Statistically different from NCa.
      21(15.9%)

      48(36.4%)
      Statistically different from PCa.


      63(47.7%)
      Statistically different from PCa.
      1(16.7%)

      0(0.0%)
      Statistically different from NCa.
      ,
      Statistically different from Ca.


      5(83.3%)
      Statistically different from NCa.
      ,
      Statistically different from Ca.
      <0.001
      ECOG PS, Eastern cooperative oncology group performance status; NCa, noncachexia; PCa, pre-cachexia; Ca, cachexia; RCa, refractory cachexia; SD, standard deviation; BMI, body mass index; WL, weight loss; N-M.
      a Statistically different from NCa.
      b Statistically different from PCa.
      c Statistically different from Ca.
      A significant difference was observed in all analysed covariables (BMI, weight loss, SARC-F, ECOG score, appetite loss, reduced food intake, and abnormal biochemical indicators) among different stages of cachexia, but no difference was identified for age. The BMI, weight loss, SARC-F, ECOG score, appetite loss, reduced food intake, and abnormal biochemical indicators of the NCa group were significantly better than those of the other groups (p<0.001). (The results of the comparison between groups are shown in Additional file 1: Table S4).

      Analysis of sarcopenia in different cachexia stages

      We also compared the prevalence of sarcopenia between different stages of cachexia (Figure 1). The incidence of sarcopenia in the refractory cachexia groups (male, 50%; female, 60%) was significantly higher than that in the noncachexia (male, 5.6%, p=0.016; female, 4%, p=0.009) and precachexia groups (male, 7.7%, p=0.057; female, 5.9%, p=0.024) but not in the cachexia group (male, 27.1%, p=0.056; female, 34%, p=0.342).
      Figure 1
      Figure 1Prevalence of sarcopenia in men and women at different stages of cachexia.
      NCa, noncachexia; PCa, precachexia; Ca, cachexia; RCa, refractory cachexia.

      Symptom burden and quality of life in patients with different cachexia stages

      Symptom burden

      All patients completed the MDASI questionnaires. The symptoms (pain, fatigue, uneasy sleep, distress, shortness of breath, forgetfulness, poor appetite, drowsiness, dry mouth, sense of sadness, vomiting, numbness, general activity, mood, work, relationships with others, walking, life fun) of patients in various stages of cachexia were more serious than those in the noncachexia group (p<0.05), except numbness (p=0.094) and shortness of breath (p=0.068). Among the symptoms that were significantly different among different stages of cachexia (p<0.05) (Additional file 1: Table S5), the most common symptoms in patients receiving RT were pain (73.3%), fatigue (87%), and dry mouth (85%) (noncachexia group [pain, 3.02±2.2; fatigue, 3.94±2.3; dry mouth, 3.68±2.38], precachexia group [pain, 4.21±2.5; fatigue, 4.46±2.16; dry mouth, 5.13±2.36], cachexia group [pain, 4.72±2.8; fatigue, 5.34±2.28; dry mouth, 5.75±2.75], and refractory cachexia group [pain, 4.75±2.9; fatigue, 6.25±3.09; dry mouth, 5.82±2.65]) (Figure 2).
      Figure 2
      Figure 2Symptom burden scores of patients at different stages of cachexia.
      NCa, noncachexia; PCa, precachexia; Ca, cachexia; RCa, refractory cachexia.

      Quality of life

      All patients (n=270) completed the QLQ-C30 scale. Scores on the QLQ-C30 were evaluated in groups according to stages of cachexia (Figure 3). Except for cognitive functioning [noncachexia, 77.58±21.98; precachexia, 72.08±21.14; cachexia, 74.73±22.15; refractory cachexia, 63.33±47.72; p=0.195], diarrhoea [noncachexia, 16.47±22.66; precachexia, 20.83±24.67; cachexia, 18.93±22.25; refractory cachexia, 20.00±29.81; p=0.680], and dyspnoea [noncachexia, 22.98±23.46; precachexia, 26.66±21.61; cachexia, 27.27±23.95; refractory cachexia, 26.66±36.51; p=0.591], patients in the noncachexia group scored higher on functional items and significantly lower on symptom-related items on the QLQ-C30 scale (p<0.05) (Figure 3). Among the significant items, fatigue showed the largest difference among the different cachexia stages.
      Figure 3
      Figure 3Quality of life scores of patients at different stages of cachexia.
      NCa, noncachexia; PCa, precachexia; Ca, cachexia; RCa, refractory cachexia.

      Treatment-related events among patients in different cachexia stages

      Figure 4 shows the ability of the R-CSS scale to predict treatment-related events among patients in the 4 stages of cachexia (Figure 4).
      Figure 4
      Figure 4Incidence of treatment-related events in patients with different stages of cachexia.
      NCa, noncachexia; PCa, precachexia; Ca, cachexia; RCa, refractory cachexia.
      The R-CSS performed well in predicting treatment-related events. Compared to the noncachexia group [grade III or higher grade of haematologic adverse events (G-III-HGHAE), 4%, p=0.000; grade III or higher grade of nonhaematologic adverse events (G-III-NHGHAE), 3.4%, p=0.000, need for hospitalization, 4%, p=0.000; emergency room admission, 0%], the precachexia group (G-III-HGHAE, 5%, p=0.000; G-III-NHGHAE, 8.1%, p=0.000, need for hospitalization, 5%, p=0.000; emergency room admission, 0%), and the cachexia group (G-III-HGHAE, 25%, p=0.002; G-III-NHGHAE, 26.5%, p=0.003, need for hospitalization, 27%, p=0.003; emergency room admission, 3.1%), the refractory cachexia group (G-III-HGHAE, 85.7%; G-III-NHGHAE, 85.7%, need for hospitalization, 85.7%; emergency room admission, 28.5%) had the highest incidence of G-III-HGHAE.

      Discussion

      This study provides a staging system for cachexia that can be used to identify, diagnose, and monitor cachexia at an early stage and stratify patient management so that a more standardized treatment and care plan can be designed for patients diagnosed with cachexia. First, based on the classification system proposed by Fearson[
      • Fearon K.S.F.A.S.
      Definition and classification of cancer cachexia: an international consensus.
      ] et al., the R-CSS scale was developed combining the characteristics of radiotherapy patients. Second, we used this scale to distinguish patients at different cachexia stages.
      The literature shows that different cancer types have different prevalences of cachexia, among which the highest incidence of cancer cachexia is gastric cancer and pancreatic cancer (up to 80%), and the lowest incidence is leukaemia and breast cancer (up to 40%)[
      • Baba M.R.
      • Buch S.A.
      Revisiting Cancer Cachexia: Pathogenesis, Diagnosis, and Current Treatment Approaches.
      ]. In the present study, we found a high cachexia rate in patients with head and neck cancer (67.7%), and the lowest incidence was in breast tumours (26.5%). This could be because certain tumours, such as lung cancer, present different cachexia-inducing gene expression profiles[
      • Freire P.P.
      • Fernandez G.J.
      • de Moraes D.
      • Cury S.S.
      • Dal Pai-Silva M.
      • Dos Reis P.P.
      • Rogatto S.R.
      • Carvalho R.F.
      The expression landscape of cachexia-inducing factors in human cancers.
      ]. In addition to increasing the morbidity and mortality of patients, aggravating the side effects of chemotherapy, and reducing the quality of life of patients, cachexia is associated with the incidence of treatment-related events. In our study, different stages of cachexia were significantly associated with treatment-related events[
      • Kapała A.
      • Surwiłło-Snarska A.
      • Jodkiewicz M.
      • Kawecki A.
      Nutritional Care in Patients with Head and Neck Cancer during Chemoradiotherapy (CRT) and Bioradiotherapy (BRT) Provides Better Compliance with the Treatment Plan.
      ]. The exact mechanism by which higher cachexia stages lead to an increase in the occurrence of treatment-related events is unknown, but certain factors may be involved. For example, radiation-induced fatigue is known to be associated with elevated levels of proinflammatory cytokines, including TNF-α and IL-6, both of which are elevated in cachexia patients[
      • Muthanandam S.
      • Muthu J.
      Understanding Cachexia in Head and Neck Cancer.
      ]. These factors have also been associated with oral mucositis in animal models[
      • Sonis S.T.
      • Peterson R.L.
      • Edwards L.J.
      • Lucey C.A.
      • Wang L.
      • Mason L.
      Defining mechanisms of action of interleukin-11 on the progression of radiation-induced oral mucositis in hamsters.
      ]. TGF-βis another factor that is elevated in cachexia patients[
      • Burks T.N.
      • Cohn R.D.
      Role of TGF-β signaling in inherited and acquired myopathies.
      ] and has been shown to mediate radiation-induced damage. Thus, the potentially proinflammatory state of cachexia patients may be worsened by radiotherapy. Alternatively, cachexia may be a marker of a clinically evident "frailty syndrome" characterized by decreased physiological reserves leading to an inability to cope with acute stressors[
      • Xue Q.L.
      The frailty syndrome: definition and natural history.
      ]. These patients may be less suitable candidates for tolerating treatment-related events. Therefore, cachexia evaluation in cancer patients undergoing radiotherapy is necessary.
      Low BMI and weight loss are important criteria for the assessment of cachexia, and age-adjusted BMI is related to treatment-related events
      • Liu A.
      • Tran E.
      • Berthelet E.
      • Wu J.
      • Olson R.A.
      • Hamilton S.N.
      Association between nutritional risk index and outcomes for head and neck cancer patients receiving concurrent chemo-radiotherapy.
      ,
      • Raphael M.J.
      • Ko G.
      • Booth C.M.
      • Brogly S.B.
      • Li W.
      • Kalyvas M.
      • Patel S.V.
      Factors Associated with Chemoradiation Therapy Interruption and Noncompletion Among Patients With Squamous Cell Anal Carcinoma.
      ,
      • Rim C.H.
      • Yoon W.S.
      • Lee J.A.
      • Yang D.S.
      • Lee N.K.
      • Park Y.J.
      • Kim C.Y.
      Factors predicting intolerance to definitive conventional radiotherapy in geriatric patients.
      . According to our results, NCa patients showed significantly higher BMI and lower weight loss than RCa patients (p<0.001). In addition, previous studies showed inflammation as the major cause of weight loss in cancer patients[
      • Webster J.M.
      • Kempen L.
      • Hardy R.S.
      • Langen R.
      Inflammation and Skeletal Muscle Wasting During Cachexia.
      ] and presented the concentration of albumin and C-reactive protein (CRP) as the best predictors of weight loss. Because white blood cell count (WBC) is more widely used in clinical practice than C-reactive protein (CRP), it has been used as an indicator of cachexia stage in previous studies
      • Morey V.M.
      • Song Y.D.
      • Whang J.S.
      • Kang Y.G.
      • Kim T.K.
      Can Serum Albumin Level and Total Lymphocyte Count be Surrogates for Malnutrition to Predict Wound Complications After Total Knee Arthroplasty?.
      ,
      • Vigano A.A.L.
      • Morais J.A.
      • Ciutto L.
      • Rosenthall L.
      • di Tomasso J.
      • Khan S.
      • Kilgour R.D.
      Use of routinely available clinical, nutritional, and functional criteria to classify cachexia in advanced cancer patients.
      [
      • Bye A.
      • Wesseltoft-Rao N.
      • Iversen P.O.
      • Skjegstad G.
      • Holven K.B.
      • Ulven S.
      • Hjermstad M.J.
      Alterations in inflammatory biomarkers and energy intake in cancer cachexia: a prospective study in patients with inoperable pancreatic cancer.
      ]. Moreover, previous studies included haemoglobin as a biomarker
      • Vigano A.A.L.
      • Morais J.A.
      • Ciutto L.
      • Rosenthall L.
      • di Tomasso J.
      • Khan S.
      • Kilgour R.D.
      Use of routinely available clinical, nutritional, and functional criteria to classify cachexia in advanced cancer patients.
      ,
      • Zhou T.
      • Wang B.
      • Liu H.
      • Yang K.
      • Thapa S.
      • Zhang H.
      • Yu S.
      Development and validation of a clinically applicable score to classify cachexia stages in advanced cancer patients.
      .
      Reduced food intake and appetite loss are also necessary to diagnose cachexia in cancer patients[
      • Cederholm T.
      • Jensen G.L.
      • Correia M.I.T.D.
      • Gonzalez M.C.
      • Fukushima R.
      • Higashiguchi T.
      GLIM Core Leadership CommitteeGLIM Working Group
      GLIM criteria for the diagnosis of malnutrition - A consensus report from the global clinical nutrition community.
      ]. Many nutritional screening scales are widely used to assess patients' dietary intake reduction and appetite loss, such as the PG-SGA[
      • Bauer J.
      • Capra S.
      • Ferguson M.
      Use of the scored Patient-Generated Subjective Global Assessment (PG-SGA) as a nutrition assessment tool in patients with cancer.
      ], nutritional risk screening 2002[
      • Hsueh S.
      • Lai C.
      • Hung C.
      • Lin Y.
      • Lu C.
      • Yeh K.
      • Chou W.
      A comparison of the MNA-SF, MUST, and NRS-2002 nutritional tools in predicting treatment incompletion of concurrent chemoradiotherapy in patients with head and neck cancer.
      ] (NRS2002) and the mini nutrition assessment[
      • Reber E.
      • Schönenberger K.A.
      • Vasiloglou M.F.
      • Stanga Z.
      Nutritional Risk Screening in Cancer Patients: The First Step Toward Better Clinical Outcome.
      ] (MNA). Due to the complexity of these scales, patients' self-reported digital analogue score (NRS: 0-10 points) was used in this study to assess the degree of appetite loss. Dietary intake was divided into two grades: no reduction, increased (0 points), and decreased (1 point).
      Decreased functions are prevalent in cancer patients and are related to cachexia[
      • Reber E.
      • Schönenberger K.A.
      • Vasiloglou M.F.
      • Stanga Z.
      Nutritional Risk Screening in Cancer Patients: The First Step Toward Better Clinical Outcome.
      ] [
      • Meza-Valderrama D.
      • Marco E.
      • Dávalos-Yerovi V.
      • Muns M.D.
      • Tejero-Sánchez M.
      • Duarte E.
      • Sarcopenia Sánchez-Rodríguez D.
      • Malnutrition
      • Cachexia
      Adapting Definitions and Terminology of Nutritional Disorders in Older People with Cancer.
      ]. Function was assessed by using the ECOG scale and SARC-F questionnaire. The SARC-F questionnaire[
      • Malmstrom T.K.
      • Miller K.
      • Simonsick E.M.
      • Ferrucci L.
      • Morley J.E.
      SARC-F: a symptom score to predict persons with sarcopenia at risk for poor functional outcomes.
      ] is a short, easy-to-use tool that has been validated in cancer patients, and scores on this questionnaire have been shown to be associated with the main adverse outcomes of malnutrition and cachexia. The cut-off (score >4) is associated with sarcopenia. Decreased function appears to be the critical transition point between stages of cachexia, and in our study, each stage was statistically significant (p<0.001).
      After designing the R-CSS rating scale, we evaluated the staging efficiency of the scale. In the sarcopenia assessment, the later the stage of cachexia in both male and female patients was, the higher the incidence of sarcopenia, and the difference between groups was statistically significant (p<0.05). There were significant differences in sarcopenia across all cachexia stages except for Ca compared to RCa patients (all p<0.05), which was similar to the study by Zhou[
      • Zhou T.
      • Wang B.
      • Liu H.
      • Yang K.
      • Thapa S.
      • Zhang H.
      • Yu S.
      Development and validation of a clinically applicable score to classify cachexia stages in advanced cancer patients.
      ] et al. However, the cachexia staging scale (CSS) designed by Vigano et al.[
      • Vigano A.A.L.
      • Morais J.A.
      • Ciutto L.
      • Rosenthall L.
      • di Tomasso J.
      • Khan S.
      • Kilgour R.D.
      Use of routinely available clinical, nutritional, and functional criteria to classify cachexia in advanced cancer patients.
      ] did not clearly distinguish between patients in the precachexia stage and patients in the cachexia stage during body composition verification. This finding could have different explanations. For example, the small number of patients in the RCa group (five patients) may have made the results less accurate.
      Symptom burden and quality of life were also important measures of cachexia. Overall, the severity of cachexia was effectively reflected by the subgroups according to the scale score, and the grade was negatively correlated with the quality of life and disease burden of patients, which was consistent with previous research results
      • Silva G.A.D.
      • Wiegert E.V.M.
      • Calixto-Lima L.
      • Oliveira L.C.
      Clinical utility of the modified Glasgow Prognostic Score to classify cachexia in patients with advanced cancer in palliative care.
      ,
      • Yin L.
      • Song C.
      • Cui J.
      • Lin X.
      • Li N.
      • Fan Y.
      • Xu H.
      A fusion decision system to identify and grade malnutrition in cancer patients: Machine learning reveals feasible workflow from representative real-world data.
      . The higher the degree of cachexia, the heavier the disease burden and the worse the quality of life of patients. This finding supports the feasibility of using our score to assess the severity of cachexia in patients.
      Cachexia is frequently associated with higher treatment-related toxicities in patients undergoing RT[
      • Ganju R.G.
      • Morse R.
      • Hoover A.
      • TenNapel M.
      • Lominska C.E.
      The impact of sarcopenia on tolerance of radiation and outcome in patients with head and neck cancer receiving chemoradiation.
      • Hsueh S.
      • Lai C.
      • Hung C.
      • Lin Y.
      • Lu C.
      • Yeh K.
      • Chou W.
      A comparison of the MNA-SF, MUST, and NRS-2002 nutritional tools in predicting treatment incompletion of concurrent chemoradiotherapy in patients with head and neck cancer.
      • Raphael M.J.
      • Ko G.
      • Booth C.M.
      • Brogly S.B.
      • Li W.
      • Kalyvas M.
      • Patel S.V.
      Factors Associated with Chemoradiation Therapy Interruption and Noncompletion Among Patients With Squamous Cell Anal Carcinoma.
      ]. Our data showed significant differences among all groups. Compared to patients in the cachexia stage, patients in the noncachexia stage had the lowest incidence of emergency visits, hospitalization, grade III or higher haematological adverse events, and grade III or higher nonhaematological adverse events. This is similar to previous studies
      • Hsueh S.
      • Lai C.
      • Hung C.
      • Lin Y.
      • Lu C.
      • Yeh K.
      • Chou W.
      A comparison of the MNA-SF, MUST, and NRS-2002 nutritional tools in predicting treatment incompletion of concurrent chemoradiotherapy in patients with head and neck cancer.
      ,
      • Hsueh S.
      • Lai C.
      • Hung C.
      • Lin Y.
      • Lu C.
      • Yeh K.
      • Chou W.
      A comparison of the MNA-SF, MUST, and NRS-2002 nutritional tools in predicting treatment incompletion of concurrent chemoradiotherapy in patients with head and neck cancer.
      . While these treatment-related toxicities are not fatal, they inevitably worsen the physical and mental functioning of patients. This observation confirms that the importance of nutritional screening for patients with cachexia is universal, and the R-CSS scale designed in this study can effectively determine the prognosis of patients.
      Zhou[
      • Zhou T.
      • Wang B.
      • Liu H.
      • Yang K.
      • Thapa S.
      • Zhang H.
      • Yu S.
      Development and validation of a clinically applicable score to classify cachexia stages in advanced cancer patients.
      ] et al. recently developed and validated a clinically applicable scoring system; however, the cachexia staging score is a clinically applicable tool with excellent discrimination for classifying cachexia stages. This scoring system is for patients with advanced cancer. Cong[
      • Cong M.
      • Song C.
      • Xu H.
      • Song C.
      • Wang C.
      • Fu Z.
      Investigation on Nutrition Status and Clinical Outcome of Common Cancers (INSCOC) Group. The patient-generated subjective global assessment is a promising screening tool for cancer cachexia.
      ] et al. found that the PG-SGA scoring system could rapidly screen patients with tumour cachexia; however, the PG-SGA could not be effectively used to define the degree of cachexia. R-CSS is a simple and easy-to-use tool. Our results show that the sensitivity, specificity and stratification effect of R-CSS are good, and the higher the cachexia stage, the more likely it is that treatment-related adverse events. Therefore, R-CSS is suitable as a cachexia stratification tool for patients undergoing RT.

      Limitations

      There are some limitations to our study. First, our study was conducted in patients with many different cancers. Since the incidence of cancer cachexia varies by cancer type, it may not be practical to use the R-CSS in some cancer types. Second, oncologic treatments were disparate with regard to type, administration, and time interval from examination/interview of the patients, and we cannot exclude the possibility that some particularly aggressive therapies may adversely affect nutritional risk. Third, The R-CSS model only predicts patients 1 month after the completion of RT, and lacks long-term prediction. Therefore, if more accurate long-term prediction is needed, new data and further update of the model are needed. Fourth, our study was a small-sample-size study that was conducted at a single centre. Moreover, the number of patients in the RCa stage was small; therefore, multicentre studies with larger sample sizes are needed to further validate the R-CSS. Although this study was prospective, cachexia status changes were not followed up during follow-up; therefore, longitudinal data were not obtained.
      To allow for the quick screening and grading of patients, muscle function assessments, such as grip strength and walking speed, and dual-energy X-ray or CT/MRI measurements of the muscle areas of patients were not included in this evaluation scale, which could have led to reduced accuracy. However, the simple SARC-F questionnaire was used to for screen for sarcopenia and evaluate the muscle function of patients.
      A simple digital analogue scoring method was used to evaluate patients' appetite loss and food intake, while conventional nutritional screening tools, such as PG-SGA and NRS2002, were not used, which may have led to imprecise results. In addition, there were few patients in the refractory cachexia stage, so the results still need to be further verified.

      Conclusion

      Our study developed a new type of cachexia staging scale that is simple and feasible for clinical use. This scale can be used to evaluate the stages of cachexia at the same time and has good distinguishing ability. Multicentre studies with larger sample sizes are needed to further validate the R-CSS.

      Availability of data and materials

      Not applicable.

      Competing interests

      We are grateful for Yang Wang’s assistance in extracting and analysing the data.

      Funding

      This work was supported by nurturing funds for nursing young talents of Sun Yat-sen University (No. N2020Y06) and Yat-Sen Scholarship for Young Nursing Scientists. All authors approved this submission and this statement.

      Declarations of conflicting interests

      There are no conflicts of interest declared by any authors. All authors approved this submission and this statement.

      Authors' contributions

      Hanxiao Yi first presented the idea and designed the outline of this article. LQY and YHX were responsible for all data extraction and analysis with the assistance of Wang Yang and Chen Changlong. The final version was revised by MXQ and YHX. LQY, WY and YHX were all responsible for the final submission.

      Authors' information (optional)

      Malnutrition and cachexia are areas of study of LQY and YHX, who are researchers at the Sun Yat-Sen Memorial Hospital focusing on new treatments for patients undergoing intensity-modulated radiation therapy.

      Uncited References

      • Shodo R.
      • Yamazaki K.
      • Ueki Y.
      • Takahashi T.
      • Horii A.
      Sarcopenia predicts a poor treatment outcome in patients with head and neck squamous cell carcinoma receiving concurrent chemoradiotherapy.
      .

      Acknowledgements

      We thank all those who participated in the questionnaire collection and data entry. Thanks to Dr. Cheng and Clinical Research Devision, Sun Yat-sen Memorial Hospital for statistical guidance.

      Appendix A. Supplementary data

      The following is the Supplementary data to this article:

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