Prognostic impact of cachexia in patients undergoing radical resection for colorectal cancer: a retrospective study

Prognostic impact of cachexia in patients undergoing radical resection for colorectal cancer: a retrospective study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prognostic impact of cachexia in patients undergoing radical resection for colorectal cancer: a retrospective study Hideki Tanda, Masatsune Shibutani, Yuki Seki, Tsuyoshi Nishiyama, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5412890/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Host and tumor factors influence tumor progression. Cachexia has attracted considerable attention as a potential host disease, and is a multifactorial syndrome characterized by skeletal muscle loss; however, it is difficult to objectively assess. The cachexia index (CXI) has been reported as a novel marker for assessing cachexia. This study investigated the relationship between cachexia and long-term prognosis after colorectal cancer surgery using the CXI. Methods : We included 299 patients who underwent radical surgery for colorectal cancer at Osaka City University Hospital between January 2017 and December 2019. CXI was originally calculated using the skeletal muscle index, serum albumin level, and neutrophil-to-lymphocyte ratio. This study also evaluated the P-CXI, which has a component of the psoas muscle index instead of the skeletal muscle index, and was calculated as follows: psoas muscle index (cm 2 /m 2 ) × serum albumin level (g/dL) / neutrophil-to-lymphocyte ratio. The prognostic value of P-CXI was investigated using univariate and multivariate Cox hazard regression models after adjusting for potential confounders. Results : The low P-CXI group included 185 patients with significantly shorter relapse-free survival (RFS) and overall survival (OS) than the high P-CXI group (p=0.002 and p=0.005, respectively). The multivariate analysis showed a significant reduction in RFS and OS, wherein the following were independent poor prognostic factors: age >70 years (hazard ratio [HR]: 2.051, 95% confidence interval [CI]: 1.104–3.807, p=0.022 and HR: 2.649, 95% CI: 1.172–5.990, p=0.019, respectively), T4 tumors (HR: 4.153, 95% CI: 1.869–9.233, p<0.001 and HR: 8.797, 95% CI: 3.185–24.29, p37 U/ml (HR: 2.827, 95% CI: 1.224–6.532, p=0.014 and HR: 5.578, 95% CI: 2.043–15.23, p<0.001, respectively), and low P-CXI (HR: 2.629, 95% CI: 1.312–5.266, p=0.006 and HR: 2.716, 95% CI: 1.064–6.933, p=0.036, respectively). Conclusion : Cachexia was shown to have a prognostic impact in patients with colorectal cancer who underwent radical resection, where P-CXI may be a useful prognostic marker. colorectal cancer cachexia psoas muscle index cachexia index prognosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Background Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer-related mortality [ 1 ]. Surgical resection is the only established curative treatment for patients with stage I–III CRC; however, it has been reported that there may be differences in prognosis even after curative surgery in patients with the same tumor-node-metastasis (TNM) stage [ 2 , 3 ]. Such differences in prognosis may be related not only to tumor factors, but also to host factors, and cancer cachexia has attracted attention as a host factor. According to a review by Dunne et al., the prevalence of cancer cachexia ranges from 12.6–42.7% [ 4 ], suggesting that cachexia is frequent in CRC. It has also been reported that there is no association between cancer cachexia and tumor size or TNM stage [ 5 ], and that cachexia is present even in patients with stage I–III CRC [ 6 ]. Cancer cachexia is a multifactorial syndrome characterized by loss of skeletal muscle mass. According to the criteria of Fearon et al., a combination of weight loss, body mass index (BMI), and skeletal muscle mass is recommended for the diagnosis of cancer cachexia, and an accurate estimation of weight loss is essential [ 7 ]. However, accurately recording weight loss is difficult because of memory bias. The objective parameters for evaluating cachexia have not yet been established. The cachexia index (CXI) is a new index composed of the skeletal muscle index (SMI), serum albumin levels (Alb), and the neutrophil-lymphocyte ratio (NLR). Jafri et al. demonstrated the relationship between the CXI and prognosis in advanced lung cancer and non-Hodgkin lymphoma [ 8 ]. This study aimed to investigate whether the CXI is a useful prognostic indicator in patients undergoing curative surgery for CRC. Methods Patients This study included 394 patients who underwent curative surgery for CRC at Osaka City University Hospital between January 2017 and December 2019. Patients with stage 0 or IV CRC (n = 72), those lacking blood test data (n = 10), and those without preoperative computed tomography (CT) scans (n = 13) were excluded. A total of 299 patients were enrolled in this study (Fig. 1 ). The patient data were retrospectively analyzed, and relapse-free survival (RFS) and overall survival (OS) were examined as primary endpoints. This study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Ethics Committee of Osaka City University (approval number: 4182). Written informed consent was obtained from all the patients. Treatment and patient management The indications for surgery, surgical treatment, chemotherapy options, and postoperative surveillance for CRC were determined using the Japanese Guidelines for the Treatment of Colorectal Cancer [ 9 ]. TNM classification was determined using the 9th Edition of the Guidelines for the Treatment of Colorectal Cancer [ 10 ]. Patients underwent tumor marker measurements and chest and abdominal contrast CT every 3–6 months and colonoscopy was performed every 1 or 2 years. Date collection Preoperative CT scans were collected within 3 months of surgery. Blood data was collected and recorded within 1 month of surgery. Measurement of muscle parameters The cross-sectional areas of the skeletal muscles and psoas muscle were measured using preoperative CT images, semi-automatically, at the umbilicus level using image analysis software SYNAPSE VINCENT® (Fuji-Film Corporation, Tokyo, Japan). The total psoas muscle volume was measured and recorded simultaneously using SYNAPSE VINCENT (Fig. 2 ). The SMI was calculated by dividing the skeletal muscle cross-sectional area (cm 2 ) by the height squared (m 2 ), and the psoas muscle index (PMI) was calculated by dividing the psoas muscle cross-sectional area (cm 2 ) by the height squared (m 2 ). For the PMI, a receiver operating characteristic (ROC) curve for the 5-year RFS was created, and different cutoffs were applied to males and females because of the differences in muscle volume. Patients were stratified into high and low PMI groups. Calculation of the CXI Two evaluation methods were used to calculate for the CXI: the S-CXI, which was based on the cross-sectional area of the skeletal muscle, and the P-CXI, which was based on the cross-sectional area of ​​the psoas muscle. The S-CXI was calculated as follows: SMI (cm 2 /m 2 ) × albumin (g/dL) / NLR. The P-CXI was calculated as follows: PMI (cm 2 /m 2 ) × Alb (g/dL) / NLR. The NLR was calculated as peripheral blood neutrophil count (/mm 3 )/peripheral blood lymphocyte count (/mm 3 ). The CXI cutoff values were defined as those that maximized the Youden index for predicting the 5-year RFS for each sex on the ROC curve. Considering the differences in muscle volume between male and female, different cut-offs were applied for both the S-CXI and P-CXI. Patients were stratified into two groups (CXI-high and CXI-low groups) for the S-CXI and P-CXI using these cutoff values. Statistical analyses Statistical analyses were performed using the EZR statistical software version 1.55 (Saitama Medical Center, Jichi Medical University, Saitama, Japan). Continuous and categorical variables were compared using the Mann–Whitney U -test, chi-square test, or Fisher’s exact test, as appropriate. Kaplan–Meier survival curves were used to analyze survival data, and differences in survival curves were analyzed using log-rank tests. The univariate Cox proportional hazards model was used to analyze RFS and OS. Variables with a p < 0.1 in the univariate analysis were further analyzed in the multivariate analysis. Statistical significance was set at p < 0.05. Results Characteristics of the patients The patient characteristics are shown in Table 1 . A total of 178 men and 121 women with a median age of 71 (27–100) years were included in the study. The median follow-up period for OS was 44.3 months. Based on the cutoff values​, patients were stratified into the high (n = 219) and low S-CXI groups (n = 80), and into the high (n = 114) and low P-CXI groups (n = 185). The S-CXI was significantly correlated with sex (p < 0.001), BMI (p < 0.001), tumor depth (p = 0.032), and preoperative carcinoembryonic antigen (CEA) level (p = 0.007), and tended to correlate with age (p = 0.081) and preoperative carbohydrate antigen 19 − 9 (CA 19 − 9) level (p = 0.093). The P-CXI significantly correlated with age (p < 0.001), BMI (p < 0.001), and preoperative CEA level (p = 0.001). Table 1 Univariate analysis of the clinicopathological variables in relation to CXI. S-CXI P-CXI High (n = 219) Low (n = 80) p-value High (n = 114) Low (n = 185) p-value Age (years) 70 (31–100) 74 (27–91) 0.081 68.5 (31–85) 74.0 (27–100) < 0.001 * Sex Male 105 73 < 0.001 * 49 72 0.544 Female 114 7 65 113 BMI (kg/m 2 ) 23.14 (15.26–50.68) 21.43 (15.18–30.74) < 0.001 * 24.02 (15.39–50.68) 22.08 (15.18–31.81) < 0.001 * Tumor location Right 70 32 0.216 33 69 0.167 Left 149 48 81 116 Depth of tumor invasion T1, 2, 3 209 70 0.032 * 109 170 0.242 T4 10 10 5 15 Lymph node metastasis Negative 163 59 0.883 86 136 0.786 Positive 56 21 28 49 Lymphatic vessel invasion Negative 158 55 0.567 83 130 0.694 Positive 61 25 31 55 Venous invasion Negative 135 47 0.689 68 114 0.807 Positive 84 33 46 71 Preoperative CEA (ng/ml) 2.9 (0.5–163.4) 4.2 (0.9–122.5) 0.007 * 2.7 (0.8–27.8) 3.7 (0.5–163.4) 0.001 * Preoperative CA 19 − 9 (U/ml) 4.0 (2.0–192.4) 6.0 (2.0–251.0) 0.093 4.0 (2.0–136.0) 5.0 (2.0–1924.0) 0.229 * Statistically significant (p < 0.05). CXI, cachexia index; BMI, body mass index; CEA, carcinoembryonic antigen; CA 19 − 9, carbohydrate antigen 19 − 9. ROC curves for the PMI and CXI The ROC curves for the PMI and CXI (S-CXI and P-CXI) according to sex are shown in Figs. 3 and 4 , respectively. The cutoff values ​​for males and females were the following: PMI, 7.82 and 5.30, respectively; S-CXI, 66.8 and 21.2, respectively; and P-CXI, 14.8 and 9.0, respectively. Survival curves stratified by the PMI, S-CXI, and P-CXI The Kaplan–Meier curve for the RFS showed that low PMI was significantly associated with worse RFS (p = 0.033) and tended to be associated with worse OS (p = 0.061; Fig. 5 ). Stratified results for the S-CXI and P-CXI showed that both RFS and OS were significantly lower in the low group than in the high group (Fig. 6 ). Correlation between the area of the psoas muscle at the umbilical level and other muscle mass indices The PMI based on the cross-sectional area of the psoas muscle measured at the umbilical level showed a strong correlation with SMI based on the cross-sectional area of the skeletal muscle measured at the same level (r s =0.683, p < 0.001; Fig. 7 ). The cross-sectional area of the psoas muscle at the umbilical level demonstrated a strong correlation with the three-dimensional total psoas muscle volume (r s =0.944, p < 0.001; Fig. 8 ). Univariate and multivariate analyses for RFS Correlations between the RFS and clinicopathological factors are shown in Table 2 . The univariate analysis revealed significant correlations between RFS and tumor depth (p < 0.001), lymph node metastasis (p < 0.001), lymphatic invasion (p < 0.001), vascular invasion (p = 0.019), preoperative CEA levels (p = 0.004), preoperative CA 19 − 9 levels (p < 0.001), and P-CXI (p = 0.003). Age ≥ 70 years (p = 0.084) tended to correlate with RFS. The multivariate analysis revealed that age ≥ 70 years (hazard ratio [HR]: 2.051, 95% confidence interval [CI]: 1.104–3.807, p = 0.022), T4 tumor (HR: 4.153, 95% CI: 1.869–9.233, p 37 U/ml (HR: 2.827, 95% CI: 1.224–6.532, p = 0.014), and low P-CXI (HR: 2.629, 95% CI: 1.312–5.266, p = 0.006) were identified as independent poor prognostic factors for RFS (Table 2 ). Table 2 Univariate and multivariate analyses of factors associated with the RFS rates in patients with colorectal cancer. Variables RFS univariate analysis RFS multivariate analysis HR 95% CI p-value HR 95% CI p-value Age (≥ 70 years) 1.651 0.934–2.916 0.084 2.051 1.104–3.807 0.022 * Sex (male) 1.062 0.612–1.842 0.830 BMI (≥ 20 kg/m 2 ) 0.922 0.475–1.792 0.812 Right-sided cancer 0.875 0.491–1.559 0.651 Depth of tumor invasion (T4) 6.676 3.421–13.03 < 0.001 * 4.153 1.869–9.233 < 0.001 * Lymph node metastasis (positive) 3.068 1.788–5.264 < 0.001 * 1.699 0.889–3.245 0.108 Lymphatic vessel invasion (positive) 2.728 1.529–4.676 5 ng/ml) 2.200 1.281–3.780 0.004 * 1.159 0.616–2.181 0.646 Preoperative CA 19 − 9 (> 37 U/ml) 4.412 2.078–9.366 < 0.001 * 2.827 1.224–6.532 0.014 * Low P-CXI 2.694 1.386–5.234 0.003 * 2.629 1.312–5.266 0.006 * * Statistically significant (p < 0.05). RFS, relapse-free survival; HR, hazard ratio; CI, confidence interval; BMI, body mass index; CEA, carcinoembryonic antigen; CA 19 − 9, carbohydrate antigen 19 − 9; CXI, cachexia index Univariate and multivariate analyses for OS Correlations between the OS and clinicopathological factors are shown in Table 3 . The univariate analysis showed that age (p = 0.006), BMI (p = 0.043), tumor depth (p < 0.001), lymph node metastasis (p = 0.042), lymphatic invasion (p = 0.025), preoperative CA 19 − 9 levels (p < 0.001), and P-CXI (p = 0.009) were significantly correlated with OS. The preoperative CEA levels (p = 0.073) tended to correlate with OS. The multivariate analysis revealed that age ≥ 70 years (HR: 2.649, 95% CI: 1.172–5.990, p = 0.019), T4 tumor (HR: 8.797, 95% CI: 3.185–24.29, p 37 U/ml (HR: 5.578, 95% CI: 2.043–15.23, p < 0.001), and low P-CXI (HR: 2.716, 95% CI: 1.064–6.933, p = 0.036) were independent poor prognostic factors for OS (Table 3 ). Table 3 Univariate and multivariate analyses of factors associated with the OS rates in patients with colorectal cancer. Variables OS univariate analysis OS Multivariate analysis HR 95% CI p-value HR 95% CI p-value Age (≥ 70 years) 2.028 0.964–4.266 0.006 * 2.649 1.172–5.990 0.019 * Sex (male) 1.664 0.791–3.490 0.179 BMI (≥ 20 kg/m 2 ) 0.474 0.230–0.979 0.043 * 0.869 0.377–2.007 0.743 Right-sided cancer 0.834 0.396–1.752 0.631 Depth of tumor invasion (T4) 7.856 3.639–16.96 < 0.001 * 8.797 3.185–24.29 < 0.001 * Lymph node metastasis (positive) 2.065 1.027–4.155 0.042 * 0.904 0.373–2.190 0.823 Lymphatic vessel invasion (positive) 2.186 1.101–4.337 0.025 * 1.695 0.752–3.817 0.203 Venous invasion (positive) 1.564 0.790–3.096 0.199 Preoperative CEA (> 5 ng/ml) 1.879 0.942–3.748 0.073 0.675 0.278–1.648 0.386 Preoperative CA 19 − 9 (> 37 U/ml) 6.836 2.955–15.82 < 0.001 * 5.578 2.043–15.23 < 0.001 * Low P-CXI 3.242 1.338–7.857 0.009 * 2.716 1.064–6.933 0.036 * * Statistically significant (p < 0.05). OS, overall survival; HR, hazard ratio; CI, confidence interval; BMI, body mass index; CEA, carcinoembryonic antigen; CA 19 − 9, carbohydrate antigen 19 − 9; CXI, cachexia index. Discussion Loss of skeletal muscle, malnutrition, and increased inflammatory response are the three key features of cancer cachexia. Inflammatory cytokines, such as tumor necrosis factor-α and interleukin-6, produced by the tumor are responsible for muscle wasting and atrophy, causing increased energy consumption by the tumor [ 11 , 12 ]. The skeletal muscle also functions as an endocrine organ [ 13 ], and cytokines released from the muscles are called myokines, which play an important role in the interaction between skeletal muscle and tumors and are believed to regulate tumor promotion [ 14 , 15 ]. Although the complex mechanisms of the interaction between cancer and cachexia are still not fully understood, one aspect of the mechanism may be the process by which the progression of cachexia leads to skeletal muscle loss, which leads to a decrease in myokines, leading to tumor growth. Multiple mechanisms are involved in cachexia development, including anorexia, decreased physical activity, and systemic inflammation [ 11 ]. Although our understanding of cachexia has advanced and various assessment items, such as walking speed [ 16 ] and grip strength [ 17 ], have been investigated, objectively evaluating cachexia remains challenging, and the development of universally applicable and useful indicators has not yet been achieved. Previous reports have shown that a high preoperative NLR is an independent factor for poor prognosis after CRC surgery [ 18 ]. Research has also shown that Alb alone correlates with prognosis [ 19 ], and that a combination of various nutritional and inflammatory markers reflects the prognosis of patients with CRC who underwent radical resection [ 20 ]. However, none of these studies included muscle mass in their assessments. The CXI is a new index that combines SMI, a measure of skeletal muscle mass, Alb, a measure of nutritional status, and NLR, which reflects the inflammatory response [ 8 ]. The CXI was initially proposed based on SMI; however, a previous study examined the prognostic value of the CXI calculated using the PMI instead of the SMI [ 21 ]. It has been reported that SMI and PMI are highly correlated in CRC, and that SMI and PMI are indicators of prognosis on their own [ 22 ]. In our study, the SMI and PMI were correlated, and the PMI was closely associated with prognosis after CRC resection, which is consistent with a previous report [ 22 ]. Measurement of the SMI using CT images requires the evaluation of multiple muscles; therefore, we investigated the value of CXI based on the PMI as a prognostic index, which is a more easily usable index. The S-CXI and P-CXI were both associated with prognosis. In previous reports, the SMI and PMI have often been measured at the level of the third lumbar vertebra [ 21 – 25 ]. However, in this study, we measured the SMI and PMI using the cross-sectional area at the umbilical level because of the functionality of the software. Nevertheless, since there is a very strong correlation between the total psoas muscle volume and the cross-sectional area of ​​the psoas muscle at the umbilicus level, we considered that the cross-sectional area of the psoas muscle at the umbilical level reflects the total psoas muscle volume, and that the measurement of PMI at the umbilical level is clinically useful. Therefore, the P-CXI calculated using the PMI based on the area of the psoas muscle at the umbilical level could be a potential substitute for the original S-CXI calculated using the SMI based on the skeletal muscle area at the third lumbar vertebra. This study had some limitations. First, this was a single-center retrospective cohort study, and there were some limitations associated with this design. Second, the cutoff values for the SMI, PMI, and CXI may not be generalizable. Therefore, further large-scale studies are needed to confirm our findings and to determine the optimal cut-off values for the CXI. Conclusion Preoperative cachexia status has been shown to have a prognostic impact in patients with CRC who undergo radical resection. P-CXI may be a useful prognostic marker for patients with CRC in clinical practice. Abbreviations Alb Serum albumin level BMI Body mass index CA 19 − 9 Carbohydrate antigen 19 − 9 CEA Carcinoembryonic antigen CI Confidence interval CRC Colorectal cancer CT Computed tomography CXI Cachexia index HR Hazard ratio NLR Neutrophil-lymphocyte ratio OS Overall survival PMI Psoas muscle index RFS Relapse-free survival ROC Receiver operating characteristic SMI Skeletal muscle index TNM Tumor-node-metastasis Declarations Ethics approval and consent to participate This study was conducted in accordance with the principles of the Declaration of Helsinki. The research protocol and procedures were reviewed and approved by the Ethics Committee of Osaka City University (approval no. 4182). Written informed consent was obtained from all the participants. Consent for publication Not applicable. This manuscript does not contain any individual person’s data. Competing interests The authors declare that they have no competing interests. Funding No funding was received for the study. Author Contribution HT acquired, analyzed, and interpreted the data and drafted the manuscript. MS contributed substantially to the study conception and design, interpreted the data, and critically revised the manuscript. YS, TN, HK, and TF acquired and analyzed the data and critically revised the manuscript. KM contributed to the study conception and design and critically revised the manuscript. All authors read and approved the final manuscript. Acknowledgement We would like to thank Editage (www.editage.jp) for medical writing services. Data Availability The datasets used and analyzed in the current study are available from the corresponding author upon reasonable request. References Siegel RL, Wagle NS, Cercek A, Smith RA, Jemal A. Colorectal cancer statistics, 2023. CA Cancer J Clin. 2023;73:233–54. van Gestel YR, de Hingh IH, van Herk-Sukel MP, van Erning FN, Beerepoot LV, Wijsman JH, et al. Patterns of metachronous metastases after curative treatment of colorectal cancer. 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Usefulness of the cachexia index as a prognostic indicator for patients with gastric cancer. Ann Gastroenterol Surg. 2023;7:733–40. Wan Q, Yuan Q, Zhao R, Shen X, Chen Y, Li T, et al. Prognostic value of cachexia index in patients with colorectal cancer: A retrospective study. Front Oncol. 2022;12:984459. Tanji Y, Furukawa K, Haruki K, Taniai T, Onda S, Tsunematsu M, et al. Significant impact of cachexia index on the outcomes after hepatic resection for colorectal liver metastases. Ann Gastroenterol Surg. 2022;6:804–12. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5412890","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":380951749,"identity":"12a5186e-d92d-4d6c-a53a-91148c5456f5","order_by":0,"name":"Hideki Tanda","email":"","orcid":"","institution":"Osaka Metropolitan University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hideki","middleName":"","lastName":"Tanda","suffix":""},{"id":380951751,"identity":"2567695c-e685-46d8-ad19-92d0e7f52f7a","order_by":1,"name":"Masatsune Shibutani","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIie2QQQqCQBSG3yDY5oEtn1RGN1CEaCF1lUTQTXWGVrbxAEIdQgiipRC48gAug/ZRF8hmxHVju6D5GN5i4ON/7wdQKH6QXgo6EHqWAag3P2wrUbASyjB0ze1XCngXP8tbRQoOkul1ttL8Y7UuruzsgbaXxOCwiGwqdfdUbSKblSGwQ/5ZWVBQkJng6FStpsTiC7B0KUkhPybzReyYNkrdReEphPYko0bJOyjNLbh0qbxHth8HKL1FNHYjrC1jxxt7xnPLkTUm0EjMPt+HP3RSuQHsIabR7jOmDopCoVD8FW9GzkAEvjb4MgAAAABJRU5ErkJggg==","orcid":"","institution":"Osaka Metropolitan University Graduate School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Masatsune","middleName":"","lastName":"Shibutani","suffix":""},{"id":380951753,"identity":"e1a2e350-5172-4d10-9b63-45b92b1274ba","order_by":2,"name":"Yuki Seki","email":"","orcid":"","institution":"Osaka Metropolitan University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yuki","middleName":"","lastName":"Seki","suffix":""},{"id":380951755,"identity":"a388439f-6e94-490b-8e88-e3a15a4c712f","order_by":3,"name":"Tsuyoshi Nishiyama","email":"","orcid":"","institution":"Osaka Metropolitan University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Tsuyoshi","middleName":"","lastName":"Nishiyama","suffix":""},{"id":380951759,"identity":"c4b68b36-fd84-491b-9d80-91f36a655656","order_by":4,"name":"Hiroaki Kasashima","email":"","orcid":"","institution":"Osaka Metropolitan University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hiroaki","middleName":"","lastName":"Kasashima","suffix":""},{"id":380951760,"identity":"15d51b7c-237e-4b1a-b32a-a2da04a77e83","order_by":5,"name":"Tatsunari Fukuoka","email":"","orcid":"","institution":"Osaka Metropolitan University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Tatsunari","middleName":"","lastName":"Fukuoka","suffix":""},{"id":380951761,"identity":"ce2486a3-36ba-4e9e-a93f-5a2abd7b8809","order_by":6,"name":"Kiyoshi Maeda","email":"","orcid":"","institution":"Osaka Metropolitan University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Kiyoshi","middleName":"","lastName":"Maeda","suffix":""}],"badges":[],"createdAt":"2024-11-08 02:08:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5412890/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5412890/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":71053463,"identity":"5a3c1d87-4e3b-42c7-a205-fdb2006ad462","added_by":"auto","created_at":"2024-12-10 15:55:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":209805,"visible":true,"origin":"","legend":"\u003cp\u003ePatient flow. CT, computed tomography.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-5412890/v1/de0137e3fbc6da3ddfe472f4.png"},{"id":71053457,"identity":"2cf6615c-f0a4-484b-9128-63a3e2719761","added_by":"auto","created_at":"2024-12-10 15:55:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":352433,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative images of body composition of muscle and fat reconstructed using SYNAPSE VINCENT®. (a) Computed tomography image of the umbilical level cross section. The orange and yellow color-coded regions indicate the skeletal muscle. The green area indicates the psoas muscle. These color codes were applied semiautomatically. (b) Three-dimensional image construction. The green areas indicate the total psoas muscle volume.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-5412890/v1/20c847b1ac1359cd6262ebcb.png"},{"id":71054297,"identity":"770014ed-b69c-43f5-8161-405c02663c2a","added_by":"auto","created_at":"2024-12-10 16:03:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":231880,"visible":true,"origin":"","legend":"\u003cp\u003eSex-specific ROC curves for PMI. (a) Male and (b) female. ROC, receiver operating characteristic; PMI, psoas muscle index.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-5412890/v1/4a5df46002e9fa6f016c6196.png"},{"id":71053456,"identity":"f3ba30e6-8136-4de8-8388-ab81c73f71ce","added_by":"auto","created_at":"2024-12-10 15:55:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":467633,"visible":true,"origin":"","legend":"\u003cp\u003eSex-specific ROC curves for the S-CXI and P-CXI. (a) male S-CXI; (b) female S-CXI; (c) male P-CXI; and (d) female P-CXI. ROC, receiver operating characteristic; CXI, cachexia index.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-5412890/v1/b19abc67034383b53f534c86.png"},{"id":71053459,"identity":"0f2e3d5f-0af6-4aab-95f2-d96c4d292bc3","added_by":"auto","created_at":"2024-12-10 15:55:15","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":191079,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier survival curves for the associations between PMI. (a) Relapse-free survival and (b) overall survival. PMI, psoas muscle index.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-5412890/v1/e372db5008d7bb97ac5f4f33.png"},{"id":71054295,"identity":"3417a255-8773-4bd4-b9d7-7971e9492a85","added_by":"auto","created_at":"2024-12-10 16:03:15","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":374838,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier survival curves for the associations between the S-CXI and P-CXI. (a) S-CXI, relapse-free survival; (b) S-CXI, overall survival; (c) P-CXI, relapse-free survival; and (d) P-CXI, overall survival. CXI, cachexia index.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-5412890/v1/3118fe77ead8ec0cd342a8cb.png"},{"id":71054296,"identity":"d8229717-7186-4540-b0c1-4424fc178e52","added_by":"auto","created_at":"2024-12-10 16:03:15","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":258856,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between the SMI and PMI calculated using the psoas muscle cross-sectional area and skeletal muscle cross-sectional area measured at the umbilicus level by computed tomography. SMI, skeletal muscle index; PMI, psoas muscle index.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-5412890/v1/47f1e8180fc0d8b9d6eb42c8.png"},{"id":71053461,"identity":"51f05cea-be54-4039-9acd-b849b985af8a","added_by":"auto","created_at":"2024-12-10 15:55:15","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":269264,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between the psoas muscle cross-sectional area measured at the umbilicus level and total psoas muscle volume.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-5412890/v1/0c9d801b45457988398455e6.png"},{"id":78107292,"identity":"c6f72d6f-6625-4919-9284-9474a6e3e734","added_by":"auto","created_at":"2025-03-10 04:01:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3315198,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5412890/v1/0b53e13b-074f-44cc-b2f4-00211a293567.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prognostic impact of cachexia in patients undergoing radical resection for colorectal cancer: a retrospective study","fulltext":[{"header":"Background","content":"\u003cp\u003eColorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer-related mortality [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Surgical resection is the only established curative treatment for patients with stage I\u0026ndash;III CRC; however, it has been reported that there may be differences in prognosis even after curative surgery in patients with the same tumor-node-metastasis (TNM) stage [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Such differences in prognosis may be related not only to tumor factors, but also to host factors, and cancer cachexia has attracted attention as a host factor. According to a review by Dunne et al., the prevalence of cancer cachexia ranges from 12.6\u0026ndash;42.7% [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], suggesting that cachexia is frequent in CRC. It has also been reported that there is no association between cancer cachexia and tumor size or TNM stage [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], and that cachexia is present even in patients with stage I\u0026ndash;III CRC [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCancer cachexia is a multifactorial syndrome characterized by loss of skeletal muscle mass. According to the criteria of Fearon et al., a combination of weight loss, body mass index (BMI), and skeletal muscle mass is recommended for the diagnosis of cancer cachexia, and an accurate estimation of weight loss is essential [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, accurately recording weight loss is difficult because of memory bias. The objective parameters for evaluating cachexia have not yet been established.\u003c/p\u003e \u003cp\u003eThe cachexia index (CXI) is a new index composed of the skeletal muscle index (SMI), serum albumin levels (Alb), and the neutrophil-lymphocyte ratio (NLR). Jafri et al. demonstrated the relationship between the CXI and prognosis in advanced lung cancer and non-Hodgkin lymphoma [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This study aimed to investigate whether the CXI is a useful prognostic indicator in patients undergoing curative surgery for CRC.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eThis study included 394 patients who underwent curative surgery for CRC at Osaka City University Hospital between January 2017 and December 2019. Patients with stage 0 or IV CRC (n\u0026thinsp;=\u0026thinsp;72), those lacking blood test data (n\u0026thinsp;=\u0026thinsp;10), and those without preoperative computed tomography (CT) scans (n\u0026thinsp;=\u0026thinsp;13) were excluded. A total of 299 patients were enrolled in this study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The patient data were retrospectively analyzed, and relapse-free survival (RFS) and overall survival (OS) were examined as primary endpoints. This study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Ethics Committee of Osaka City University (approval number: 4182). Written informed consent was obtained from all the patients.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTreatment and patient management\u003c/h3\u003e\n\u003cp\u003eThe indications for surgery, surgical treatment, chemotherapy options, and postoperative surveillance for CRC were determined using the Japanese Guidelines for the Treatment of Colorectal Cancer [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. TNM classification was determined using the 9th Edition of the Guidelines for the Treatment of Colorectal Cancer [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Patients underwent tumor marker measurements and chest and abdominal contrast CT every 3\u0026ndash;6 months and colonoscopy was performed every 1 or 2 years.\u003c/p\u003e\n\u003ch3\u003eDate collection\u003c/h3\u003e\n\u003cp\u003ePreoperative CT scans were collected within 3 months of surgery. Blood data was collected and recorded within 1 month of surgery.\u003c/p\u003e\n\u003ch3\u003eMeasurement of muscle parameters\u003c/h3\u003e\n\u003cp\u003eThe cross-sectional areas of the skeletal muscles and psoas muscle were measured using preoperative CT images, semi-automatically, at the umbilicus level using image analysis software SYNAPSE VINCENT\u0026reg; (Fuji-Film Corporation, Tokyo, Japan). The total psoas muscle volume was measured and recorded simultaneously using SYNAPSE VINCENT (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The SMI was calculated by dividing the skeletal muscle cross-sectional area (cm\u003csup\u003e2\u003c/sup\u003e) by the height squared (m\u003csup\u003e2\u003c/sup\u003e), and the psoas muscle index (PMI) was calculated by dividing the psoas muscle cross-sectional area (cm\u003csup\u003e2\u003c/sup\u003e) by the height squared (m\u003csup\u003e2\u003c/sup\u003e). For the PMI, a receiver operating characteristic (ROC) curve for the 5-year RFS was created, and different cutoffs were applied to males and females because of the differences in muscle volume. Patients were stratified into high and low PMI groups.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eCalculation of the CXI\u003c/h3\u003e\n\u003cp\u003eTwo evaluation methods were used to calculate for the CXI: the S-CXI, which was based on the cross-sectional area of the skeletal muscle, and the P-CXI, which was based on the cross-sectional area of ​​the psoas muscle. The S-CXI was calculated as follows: SMI (cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e) \u0026times; albumin (g/dL) / NLR. The P-CXI was calculated as follows: PMI (cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e) \u0026times; Alb (g/dL) / NLR. The NLR was calculated as peripheral blood neutrophil count (/mm\u003csup\u003e3\u003c/sup\u003e)/peripheral blood lymphocyte count (/mm\u003csup\u003e3\u003c/sup\u003e). The CXI cutoff values were defined as those that maximized the Youden index for predicting the 5-year RFS for each sex on the ROC curve. Considering the differences in muscle volume between male and female, different cut-offs were applied for both the S-CXI and P-CXI. Patients were stratified into two groups (CXI-high and CXI-low groups) for the S-CXI and P-CXI using these cutoff values.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using the EZR statistical software version 1.55 (Saitama Medical Center, Jichi Medical University, Saitama, Japan). Continuous and categorical variables were compared using the Mann\u0026ndash;Whitney \u003cem\u003eU\u003c/em\u003e-test, chi-square test, or Fisher\u0026rsquo;s exact test, as appropriate. Kaplan\u0026ndash;Meier survival curves were used to analyze survival data, and differences in survival curves were analyzed using log-rank tests. The univariate Cox proportional hazards model was used to analyze RFS and OS. Variables with a p\u0026thinsp;\u0026lt;\u0026thinsp;0.1 in the univariate analysis were further analyzed in the multivariate analysis. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics of the patients\u003c/h2\u003e \u003cp\u003eThe patient characteristics are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A total of 178 men and 121 women with a median age of 71 (27\u0026ndash;100) years were included in the study. The median follow-up period for OS was 44.3 months. Based on the cutoff values​, patients were stratified into the high (n\u0026thinsp;=\u0026thinsp;219) and low S-CXI groups (n\u0026thinsp;=\u0026thinsp;80), and into the high (n\u0026thinsp;=\u0026thinsp;114) and low P-CXI groups (n\u0026thinsp;=\u0026thinsp;185). The S-CXI was significantly correlated with sex (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), BMI (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), tumor depth (p\u0026thinsp;=\u0026thinsp;0.032), and preoperative carcinoembryonic antigen (CEA) level (p\u0026thinsp;=\u0026thinsp;0.007), and tended to correlate with age (p\u0026thinsp;=\u0026thinsp;0.081) and preoperative carbohydrate antigen 19\u0026thinsp;\u0026minus;\u0026thinsp;9 (CA 19\u0026thinsp;\u0026minus;\u0026thinsp;9) level (p\u0026thinsp;=\u0026thinsp;0.093). The P-CXI significantly correlated with age (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), BMI (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and preoperative CEA level (p\u0026thinsp;=\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate analysis of the clinicopathological variables in relation to CXI.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eS-CXI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eP-CXI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh (n\u0026thinsp;=\u0026thinsp;219)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow (n\u0026thinsp;=\u0026thinsp;80)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHigh (n\u0026thinsp;=\u0026thinsp;114)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLow (n\u0026thinsp;=\u0026thinsp;185)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (31\u0026ndash;100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74 (27\u0026ndash;91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68.5 (31\u0026ndash;85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e74.0 (27\u0026ndash;100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.544\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.14\u003c/p\u003e \u003cp\u003e(15.26\u0026ndash;50.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.43\u003c/p\u003e \u003cp\u003e(15.18\u0026ndash;30.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.02\u003c/p\u003e \u003cp\u003e(15.39\u0026ndash;50.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.08\u003c/p\u003e \u003cp\u003e(15.18\u0026ndash;31.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTumor location\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDepth of tumor invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1, 2, 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.032\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLymph node metastasis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.786\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLymphatic vessel invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.694\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVenous invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.807\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative CEA\u003c/p\u003e \u003cp\u003e(ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003cp\u003e(0.5\u0026ndash;163.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003cp\u003e(0.9\u0026ndash;122.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003cp\u003e(0.8\u0026ndash;27.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003cp\u003e(0.5\u0026ndash;163.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative CA 19\u0026thinsp;\u0026minus;\u0026thinsp;9\u003c/p\u003e \u003cp\u003e(U/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003cp\u003e(2.0\u0026ndash;192.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003cp\u003e(2.0\u0026ndash;251.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003cp\u003e(2.0\u0026ndash;136.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003cp\u003e(2.0\u0026ndash;1924.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e*\u003c/sup\u003eStatistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). CXI, cachexia index; BMI, body mass index; CEA, carcinoembryonic antigen; CA 19\u0026thinsp;\u0026minus;\u0026thinsp;9, carbohydrate antigen 19\u0026thinsp;\u0026minus;\u0026thinsp;9.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eROC curves for the PMI and CXI\u003c/h2\u003e \u003cp\u003eThe ROC curves for the PMI and CXI (S-CXI and P-CXI) according to sex are shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, respectively. The cutoff values ​​for males and females were the following: PMI, 7.82 and 5.30, respectively; S-CXI, 66.8 and 21.2, respectively; and P-CXI, 14.8 and 9.0, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSurvival curves stratified by the PMI, S-CXI, and P-CXI\u003c/h2\u003e \u003cp\u003eThe Kaplan\u0026ndash;Meier curve for the RFS showed that low PMI was significantly associated with worse RFS (p\u0026thinsp;=\u0026thinsp;0.033) and tended to be associated with worse OS (p\u0026thinsp;=\u0026thinsp;0.061; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Stratified results for the S-CXI and P-CXI showed that both RFS and OS were significantly lower in the low group than in the high group (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eCorrelation between the area of the psoas muscle at the umbilical level and other muscle mass indices\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe PMI based on the cross-sectional area of the psoas muscle measured at the umbilical level showed a strong correlation with SMI based on the cross-sectional area of the skeletal muscle measured at the same level (r\u003csub\u003es\u003c/sub\u003e=0.683, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The cross-sectional area of the psoas muscle at the umbilical level demonstrated a strong correlation with the three-dimensional total psoas muscle volume (r\u003csub\u003es\u003c/sub\u003e=0.944, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eUnivariate and multivariate analyses for RFS\u003c/h2\u003e \u003cp\u003eCorrelations between the RFS and clinicopathological factors are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The univariate analysis revealed significant correlations between RFS and tumor depth (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), lymph node metastasis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), lymphatic invasion (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), vascular invasion (p\u0026thinsp;=\u0026thinsp;0.019), preoperative CEA levels (p\u0026thinsp;=\u0026thinsp;0.004), preoperative CA 19\u0026thinsp;\u0026minus;\u0026thinsp;9 levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and P-CXI (p\u0026thinsp;=\u0026thinsp;0.003). Age\u0026thinsp;\u0026ge;\u0026thinsp;70 years (p\u0026thinsp;=\u0026thinsp;0.084) tended to correlate with RFS. The multivariate analysis revealed that age\u0026thinsp;\u0026ge;\u0026thinsp;70 years (hazard ratio [HR]: 2.051, 95% confidence interval [CI]: 1.104\u0026ndash;3.807, p\u0026thinsp;=\u0026thinsp;0.022), T4 tumor (HR: 4.153, 95% CI: 1.869\u0026ndash;9.233, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), preoperative CA 19\u0026thinsp;\u0026minus;\u0026thinsp;9\u0026thinsp;\u0026gt;\u0026thinsp;37 U/ml (HR: 2.827, 95% CI: 1.224\u0026ndash;6.532, p\u0026thinsp;=\u0026thinsp;0.014), and low P-CXI (HR: 2.629, 95% CI: 1.312\u0026ndash;5.266, p\u0026thinsp;=\u0026thinsp;0.006) were identified as independent poor prognostic factors for RFS (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate analyses of factors associated with the RFS rates in patients with colorectal cancer.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eRFS univariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eRFS multivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (\u0026ge;\u0026thinsp;70 years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.934\u0026ndash;2.916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.104\u0026ndash;3.807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.022\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.612\u0026ndash;1.842\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (\u0026ge;\u0026thinsp;20 kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.475\u0026ndash;1.792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight-sided cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.491\u0026ndash;1.559\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepth of tumor invasion (T4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.676\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.421\u0026ndash;13.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.869\u0026ndash;9.233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymph node metastasis (positive)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.788\u0026ndash;5.264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.889\u0026ndash;3.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphatic vessel invasion (positive)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.529\u0026ndash;4.676\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.828\u0026ndash;2.990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVenous invasion (positive)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.902\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.109\u0026ndash;3.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.019\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.925\u0026ndash;2.888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative CEA (\u0026gt;\u0026thinsp;5 ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.281\u0026ndash;3.780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.616\u0026ndash;2.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.646\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative CA 19\u0026thinsp;\u0026minus;\u0026thinsp;9 (\u0026gt;\u0026thinsp;37 U/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.078\u0026ndash;9.366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.224\u0026ndash;6.532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.014\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow P-CXI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.386\u0026ndash;5.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.629\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.312\u0026ndash;5.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.006\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003e*\u003c/sup\u003eStatistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). RFS, relapse-free survival; HR, hazard ratio; CI, confidence interval; BMI, body mass index; CEA, carcinoembryonic antigen; CA 19\u0026thinsp;\u0026minus;\u0026thinsp;9, carbohydrate antigen 19\u0026thinsp;\u0026minus;\u0026thinsp;9; CXI, cachexia index\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eUnivariate and multivariate analyses for OS\u003c/h2\u003e \u003cp\u003eCorrelations between the OS and clinicopathological factors are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The univariate analysis showed that age (p\u0026thinsp;=\u0026thinsp;0.006), BMI (p\u0026thinsp;=\u0026thinsp;0.043), tumor depth (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), lymph node metastasis (p\u0026thinsp;=\u0026thinsp;0.042), lymphatic invasion (p\u0026thinsp;=\u0026thinsp;0.025), preoperative CA 19\u0026thinsp;\u0026minus;\u0026thinsp;9 levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and P-CXI (p\u0026thinsp;=\u0026thinsp;0.009) were significantly correlated with OS. The preoperative CEA levels (p\u0026thinsp;=\u0026thinsp;0.073) tended to correlate with OS. The multivariate analysis revealed that age\u0026thinsp;\u0026ge;\u0026thinsp;70 years (HR: 2.649, 95% CI: 1.172\u0026ndash;5.990, p\u0026thinsp;=\u0026thinsp;0.019), T4 tumor (HR: 8.797, 95% CI: 3.185\u0026ndash;24.29, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), preoperative CA 19\u0026thinsp;\u0026minus;\u0026thinsp;9\u0026thinsp;\u0026gt;\u0026thinsp;37 U/ml (HR: 5.578, 95% CI: 2.043\u0026ndash;15.23, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and low P-CXI (HR: 2.716, 95% CI: 1.064\u0026ndash;6.933, p\u0026thinsp;=\u0026thinsp;0.036) were independent poor prognostic factors for OS (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate analyses of factors associated with the OS rates in patients with colorectal cancer.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eOS univariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eOS Multivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (\u0026ge;\u0026thinsp;70 years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.964\u0026ndash;4.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.172\u0026ndash;5.990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.019\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.664\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.791\u0026ndash;3.490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (\u0026ge;\u0026thinsp;20 kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.230\u0026ndash;0.979\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.043\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.377\u0026ndash;2.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.743\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight-sided cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.396\u0026ndash;1.752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepth of tumor invasion (T4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.639\u0026ndash;16.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.185\u0026ndash;24.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymph node metastasis (positive)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.027\u0026ndash;4.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.042\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.373\u0026ndash;2.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.823\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphatic vessel invasion (positive)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.101\u0026ndash;4.337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.025\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.752\u0026ndash;3.817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVenous invasion (positive)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.790\u0026ndash;3.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative CEA (\u0026gt;\u0026thinsp;5 ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.942\u0026ndash;3.748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.675\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.278\u0026ndash;1.648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative CA 19\u0026thinsp;\u0026minus;\u0026thinsp;9 (\u0026gt;\u0026thinsp;37 U/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.955\u0026ndash;15.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.043\u0026ndash;15.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow P-CXI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.338\u0026ndash;7.857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.009\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.064\u0026ndash;6.933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.036\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003e*\u003c/sup\u003eStatistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). OS, overall survival; HR, hazard ratio; CI, confidence interval; BMI, body mass index; CEA, carcinoembryonic antigen; CA 19\u0026thinsp;\u0026minus;\u0026thinsp;9, carbohydrate antigen 19\u0026thinsp;\u0026minus;\u0026thinsp;9; CXI, cachexia index.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eLoss of skeletal muscle, malnutrition, and increased inflammatory response are the three key features of cancer cachexia. Inflammatory cytokines, such as tumor necrosis factor-α and interleukin-6, produced by the tumor are responsible for muscle wasting and atrophy, causing increased energy consumption by the tumor [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The skeletal muscle also functions as an endocrine organ [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], and cytokines released from the muscles are called myokines, which play an important role in the interaction between skeletal muscle and tumors and are believed to regulate tumor promotion [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Although the complex mechanisms of the interaction between cancer and cachexia are still not fully understood, one aspect of the mechanism may be the process by which the progression of cachexia leads to skeletal muscle loss, which leads to a decrease in myokines, leading to tumor growth. Multiple mechanisms are involved in cachexia development, including anorexia, decreased physical activity, and systemic inflammation [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Although our understanding of cachexia has advanced and various assessment items, such as walking speed [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and grip strength [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], have been investigated, objectively evaluating cachexia remains challenging, and the development of universally applicable and useful indicators has not yet been achieved. Previous reports have shown that a high preoperative NLR is an independent factor for poor prognosis after CRC surgery [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eResearch has also shown that Alb alone correlates with prognosis\u003c/span\u003e [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eand that a combination of various nutritional and inflammatory markers reflects the prognosis of patients with CRC who underwent radical resection\u003c/span\u003e [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, none of these studies included muscle mass in their assessments.\u003c/p\u003e \u003cp\u003eThe CXI is a new index that combines SMI, a measure of skeletal muscle mass, Alb, a measure of nutritional status, and NLR, which reflects the inflammatory response [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The CXI was initially proposed based on SMI; however, a previous study examined the prognostic value of the CXI calculated using the PMI instead of the SMI [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. It has been reported that SMI and PMI are highly correlated in CRC, and that SMI and PMI are indicators of prognosis on their own [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In our study, the SMI and PMI were correlated, and the PMI was closely associated with prognosis after CRC resection, which is consistent with a previous report [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Measurement of the SMI using CT images requires the evaluation of multiple muscles; therefore, we investigated the value of CXI based on the PMI as a prognostic index, which is a more easily usable index. The S-CXI and P-CXI were both associated with prognosis.\u003c/p\u003e \u003cp\u003eIn previous reports, the SMI and PMI have often been measured at the level of the third lumbar vertebra [\u003cspan additionalcitationids=\"CR22 CR23 CR24\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, in this study, we measured the SMI and PMI using the cross-sectional area at the umbilical level because of the functionality of the software. Nevertheless, since there is a very strong correlation between the total psoas muscle volume and the cross-sectional area of ​​the psoas muscle at the umbilicus level, we considered that the cross-sectional area of the psoas muscle at the umbilical level reflects the total psoas muscle volume, and that the measurement of PMI at the umbilical level is clinically useful.\u003c/p\u003e \u003cp\u003eTherefore, the P-CXI calculated using the PMI based on the area of the psoas muscle at the umbilical level could be a potential substitute for the original S-CXI calculated using the SMI based on the skeletal muscle area at the third lumbar vertebra.\u003c/p\u003e \u003cp\u003eThis study had some limitations. First, this was a single-center retrospective cohort study, and there were some limitations associated with this design. Second, the cutoff values for the SMI, PMI, and CXI may not be generalizable. Therefore, further large-scale studies are needed to confirm our findings and to determine the optimal cut-off values for the CXI.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePreoperative cachexia status has been shown to have a prognostic impact in patients with CRC who undergo radical resection. P-CXI may be a useful prognostic marker for patients with CRC in clinical practice.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAlb Serum albumin level\u003c/p\u003e\u003cp\u003eBMI Body mass index\u003c/p\u003e\u003cp\u003eCA 19 − 9 Carbohydrate antigen 19 − 9\u003c/p\u003e\u003cp\u003eCEA Carcinoembryonic antigen\u003c/p\u003e\u003cp\u003eCI Confidence interval\u003c/p\u003e\u003cp\u003eCRC Colorectal cancer\u003c/p\u003e\u003cp\u003eCT Computed tomography\u003c/p\u003e\u003cp\u003eCXI Cachexia index\u003c/p\u003e\u003cp\u003eHR Hazard ratio\u003c/p\u003e\u003cp\u003eNLR Neutrophil-lymphocyte ratio\u003c/p\u003e\u003cp\u003eOS Overall survival\u003c/p\u003e\u003cp\u003ePMI Psoas muscle index\u003c/p\u003e\u003cp\u003eRFS Relapse-free survival\u003c/p\u003e\u003cp\u003eROC Receiver operating characteristic\u003c/p\u003e\u003cp\u003eSMI Skeletal muscle index\u003c/p\u003e\u003cp\u003eTNM Tumor-node-metastasis\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003c/p\u003e\u003cp\u003e This study was conducted in accordance with the principles of the Declaration of Helsinki. The research protocol and procedures were reviewed and approved by the Ethics Committee of Osaka City University (approval no. 4182). Written informed consent was obtained from all the participants.\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eNot applicable. This manuscript does not contain any individual person’s data.\u003c/p\u003e \u003cp\u003e\u003c/p\u003e\u003cp\u003e \u003c/p\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003cp\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eNo funding was received for the study.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eHT acquired, analyzed, and interpreted the data and drafted the manuscript. MS contributed substantially to the study conception and design, interpreted the data, and critically revised the manuscript. YS, TN, HK, and TF acquired and analyzed the data and critically revised the manuscript. KM contributed to the study conception and design and critically revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to thank Editage (www.editage.jp) for medical writing services.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and analyzed in the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSiegel RL, Wagle NS, Cercek A, Smith RA, Jemal A. Colorectal cancer statistics, 2023. CA Cancer J Clin. 2023;73:233\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Gestel YR, de Hingh IH, van Herk-Sukel MP, van Erning FN, Beerepoot LV, Wijsman JH, et al. Patterns of metachronous metastases after curative treatment of colorectal cancer. Cancer Epidemiol. 2014;38:448\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNeki K, Eto K, Kosuge M, Ohkuma M, Ito D, Takeda Y, et al. Identification of the risk factors for recurrence of Stage III colorectal cancer. Anticancer Res. 2019;39:5721\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDunne RF, Crawford J, Smoyer KE, McRae TD, Rossulek MI, Revkin JH, et al. The mortality burden of cachexia or weight loss in patients with colorectal or pancreatic cancer: A systematic literature review. J Cachexia Sarcopenia Muscle. 2024;15:1628\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetruzzelli M, Wagner EF. Mechanisms of metabolic dysfunction in cancer-associated cachexia. Genes Dev. 2016;30:489\u0026ndash;501.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDolin TG, Mikkelsen MK, Jakobsen HL, Vinther A, Zerahn B, Nielsen DL, et al. The prevalence of sarcopenia and cachexia in older patients with localized colorectal cancer. J Geriatr Oncol. 2023;14:101402.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFearon K, Strasser F, Anker SD, Bosaeus I, Bruera E, Fainsinger RL, et al. Definition and classification of cancer cachexia: an international consensus. Lancet Oncol. 2011;12:489\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJafri SH, Previgliano C, Khandelwal K, Shi R. Cachexia index in advanced non-small-cell lung cancer patients. Clin Med Insights Oncol. 2015;9:87\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHashiguchi Y, Muro K, Saito Y, Ito Y, Ajioka Y, Hamaguchi T, et al. Japanese Society for Cancer of the Colon and Rectum (JSCCR) guidelines 2019 for the treatment of colorectal cancer. Int J Clin Oncol. 2020;25:1\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJapanese Society for Cancer of the Colon and Rectum. Japanese classification of colorectal, appendiceal, and anal carcinoma: the 3rd. English. J Anus Rectum Colon. 2019;3:175\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAoyagi T, Terracina KP, Raza A, Matsubara H, Takabe K. Cancer cachexia, mechanism and treatment. World J Gastrointest Oncol. 2015;7:17\u0026ndash;29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFearon KC, Glass DJ, Guttridge DC. Cancer cachexia: mediators, signaling, and metabolic pathways. Cell Metab. 2012;16:153\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIizuka K, Machida T, Hirafuji M. Skeletal muscle is an endocrine organ. J Pharmacol Sci. 2014;125:125\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHojman P, Dethlefsen C, Brandt C, Hansen J, Pedersen L, Pedersen BK. Exercise-induced muscle-derived cytokines inhibit mammary cancer cell growth. Am J Physiol Endocrinol Metab. 2011;301:E504\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark SY, Hwang BO, Song NY. The role of myokines in cancer: crosstalk between skeletal muscle and tumor. BMB Rep. 2023;56:365\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGale N, Wasley D, Roberts S, Backx K, Nelson A, van Deursen R, et al. A longitudinal study of muscle strength and function in patients with cancer cachexia. Support Care Cancer. 2019;27:131\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSong M, Zhang Q, Tang M, Zhang X, Ruan G, Zhang X, et al. Associations of low hand grip strength with 1 year mortality of cancer cachexia: a multicentre observational study. J Cachexia Sarcopenia Muscle. 2021;12:1489\u0026ndash;500.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShibutani M, Maeda K, Nagahara H, Noda E, Ohtani H, Nishiguchi Y, et al. A high preoperative neutrophil-to-lymphocyte ratio is associated with poor survival in patients with colorectal cancer. Anticancer Res. 2013;33:3291\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIseki Y, Shibutani M, Maeda K, Nagahara H, Ohtani H, Sugano K, et al. Impact of the preoperative controlling nutritional status (CONUT) score on the survival after curative surgery for colorectal cancer. PLoS ONE. 2015;10:e0132488.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShibutani M, Kashiwagi S, Fukuoka T, Iseki Y, Kasashima H, Maeda K. Significance of the prognostic immune and nutritional index in patients with Stage I-III colorectal cancer. Cancer Diagn Progn. 2023;3:354\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKamada T, Haruki K, Nakashima K, Takahashi J, Nakaseko Y, Suzuki N, et al. Prognostic significance of the cachexia index in patients with stage I-III colorectal cancer who underwent laparoscopic surgery. Surg Today. 2023;53:1064\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbbass T, Tsz Ho YT, Horgan PG, Dolan RD, McMillan DC. The relationship between computed tomography derived skeletal muscle index, psoas muscle index and clinical outcomes in patients with operable colorectal cancer. Clin Nutr ESPEN. 2020;39:104\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNakashima K, Haruki K, Kamada T, Takahashi J, Nakaseko Y, Ohdaira H, et al. Usefulness of the cachexia index as a prognostic indicator for patients with gastric cancer. Ann Gastroenterol Surg. 2023;7:733\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWan Q, Yuan Q, Zhao R, Shen X, Chen Y, Li T, et al. Prognostic value of cachexia index in patients with colorectal cancer: A retrospective study. Front Oncol. 2022;12:984459.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTanji Y, Furukawa K, Haruki K, Taniai T, Onda S, Tsunematsu M, et al. Significant impact of cachexia index on the outcomes after hepatic resection for colorectal liver metastases. Ann Gastroenterol Surg. 2022;6:804\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"colorectal cancer, cachexia, psoas muscle index, cachexia index, prognosis","lastPublishedDoi":"10.21203/rs.3.rs-5412890/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5412890/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eHost and tumor factors influence tumor progression. Cachexia has attracted considerable attention as a potential host disease, and is a multifactorial syndrome characterized by skeletal muscle loss; however, it is difficult to objectively assess. The cachexia index (CXI) has been reported as a novel marker for assessing cachexia. This study investigated the relationship between cachexia and long-term prognosis after colorectal cancer surgery using the CXI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: We included 299 patients who underwent radical surgery for colorectal cancer at Osaka City University Hospital between January 2017 and December 2019. CXI was originally calculated using the skeletal muscle index, serum albumin level, and neutrophil-to-lymphocyte ratio. This study also evaluated the P-CXI, which has a component of the psoas muscle index instead of the skeletal muscle index, and was calculated as follows: psoas muscle index (cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e) × serum albumin level (g/dL) / neutrophil-to-lymphocyte ratio. The prognostic value of P-CXI was investigated using univariate and multivariate Cox hazard regression models after adjusting for potential confounders.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The low P-CXI group included 185 patients with significantly shorter relapse-free survival (RFS) and overall survival (OS) than the high P-CXI group (p=0.002 and p=0.005, respectively). The multivariate analysis showed a significant reduction in RFS and OS, wherein the following were independent poor prognostic factors: age \u0026gt;70 years (hazard ratio [HR]: 2.051, 95% confidence interval [CI]: 1.104–3.807, p=0.022 and HR: 2.649, 95% CI: 1.172–5.990, p=0.019, respectively), T4 tumors (HR: 4.153, 95% CI: 1.869–9.233, p\u0026lt;0.001 and HR: 8.797, 95% CI: 3.185–24.29, p\u0026lt;0.001, respectively), preoperative carbohydrate antigen 19-9 \u0026gt;37 U/ml (HR: 2.827, 95% CI: 1.224–6.532, p=0.014 and HR: 5.578, 95% CI: 2.043–15.23, p\u0026lt;0.001, respectively), and low P-CXI (HR: 2.629, 95% CI: 1.312–5.266, p=0.006 and HR: 2.716, 95% CI: 1.064–6.933, p=0.036, respectively).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: Cachexia was shown to have a prognostic impact in patients with colorectal cancer who underwent radical resection, where P-CXI may be a useful prognostic marker. \u003c/p\u003e","manuscriptTitle":"Prognostic impact of cachexia in patients undergoing radical resection for colorectal cancer: a retrospective study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-10 15:55:10","doi":"10.21203/rs.3.rs-5412890/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fadf4673-479d-4f28-9c59-0c8d2e83d337","owner":[],"postedDate":"December 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-15T14:53:24+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-10 15:55:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5412890","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5412890","identity":"rs-5412890","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}